a method of finite element tearing and interconnecting and its parallel solution algorithm a novel domain decomposition approach for the parallel finite element solution of equilibrium equations is presented the spatial domain is partitioned into a set of totally disconnected subdomains each assigned to an individual processor lagrange multipliers are introduced to enforce compatibility at the interface nodes in the static case each floating subdomain induces a local singularity that is resolved in two phases first the rigid body modes are eliminated in parallel from each local problem and a direct scheme is applied concurrently to all subdomains in order to recover each partial local solution next the contributions of these modes are related to the lagrange multipliers through an orthogonality condition a parallel conjugate projected gradient algorithm is developed for the solution of the coupled system of local rigid modes components and lagrange multipliers which completes the solution of the problem when implemented on local memory multiprocessors this proposed method of tearing and interconnecting requires less interprocessor communications than the classical method of substructuring it is also suitable for parallel vector computers with shared memory moreover unlike parallel direct solvers it exhibits a degree of parallelism that is not limited by the bandwidth of the finite element system of equations

dynamic programming alignment of sequences representing cyclic patterns string alignment by dynamic programming is generalized to include cyclic shift and corresponding optimal alignment cost for strings representing cyclic patterns a guided search algorithm uses bounds on alignment costs to find all optimal cyclic shifts the bounds are derived from submatrices of an initial dynamic programming matrix algorithmic complexity is analyzed for major stages in the search the applicability of the method is illustrated with satellite dna sequences and circularly permuted protein sequences

a numerical scheme to couple subdomains with different time steps for predominantly linear transient analysis abstract this paper generalizes the explicit implicit time integration algorithms pioneered by belytschko hughes and their respective co workers and the feti domain decomposition methods introduced by farhat and his co workers to the case where the same newmark scheme but different and coefficients and different time steps are specified in each subdomain building upon the work of farhat crivelli and geradin it considers various interface boundary constraints and performs a stability analysis of the proposed time integration algorithms

representing images using points on image surfaces this paper presents a new approach to represent an image by verge points which are defined as high curvature points on the image surface this representation offers a compact and reversible way to preserve the essence of the original image various applications such as compression edge detection image enhancement and image editing can be achieved based on this representation in this paper the whole procedure for verge point representation is presented based on these verge points image reconstruction can be easily achieved via iterative linear interpolation these extracted verge points with compatible properties are further linked into verge curves to offer more compact representation progressive representation is also developed based on a multiscale extraction scheme some potential applications are then presented to demonstrate the versatility of this representation

algebraic description of curve structure the authors propose a compact and concise method of describing curves in terms of the quasi topological features and the structure of each singular point the quasi topological features are the convexity loop and connectivity the quasi topological structure is analyzed in a hierarchical way and algebraic structure is presented explicitly for each representation level the lower level representations are integrated into the higher level one in a systematic way when a curve has singular points branch points the curve is decomposed into components where each is a simple arc or a simple closed curve by decomposing each singular point the description scheme is applied to character recognition

a potential based approach for shape matching and recognition this paper presents a novel potential based approach for recognizing the shape of a two dimensional 2d region by identifying the best match from a selected group of shape templates the proposed model assumes that the border of every 2d region is uniformly charged an initially small shape template placed inside a shape sample will experience the repulsive force and torque arising from the potential field a better match in the shape between the template and the sample can be obtained if the template translates and reorients itself to reduce the potential while growing in size the shape template with the largest final size corresponds to the best match and represents the shape of the given sample the potential and the associated repulsive force and torque between the polygonal contours are analytically tractable hence resulting in high computational efficiency of the matching process the proposed approach is intrinsically invariant under translation rotation and size changes of the shape sample moreover not only can the matching be carried out directly for shape contours at different viewscales but the contours can also be unconnected provided that the template is confined within the shape sample throughout the matching process

classification with nonmetric distances image retrieval and class representation a key problem in appearance based vision is understanding how to use a set of labeled images to classify new images systems that model human performance or that use robust image matching methods often use nonmetric similarity judgments but when the triangle inequality is not obeyed most pattern recognition techniques are not applicable exemplar based nearest neighbor methods can be applied to a wide class of nonmetric similarity functions the key issue however is to find methods for choosing good representatives of a class that accurately characterize it we show that existing condensing techniques are ill suited to deal with nonmetric dataspaces we develop techniques for solving this problem emphasizing two points first we show that the distance between images is not a good measure of how well one image can represent another in nonmetric spaces instead we use the vector correlation between the distances from each image to other previously seen images second we show that in nonmetric spaces boundary points are less significant for capturing the structure of a class than in euclidean spaces we suggest that atypical points may be more important in describing classes we demonstrate the importance of these ideas to learning that generalizes from experience by improving performance we also suggest ways of applying parametric techniques to supervised learning problems that involve a specific nonmetric distance functions showing how to generalize the idea of linear discriminant functions in a way that may be more useful in nonmetric spaces

feti and neumann neumann iterative substructuring methods connections and new results the feti and neumann neumann families of algorithms are among the best know and most severely tested domain decomposition methods for elliptic partial differential equations they are iterative substructuring methods and have many algorithmic components in common but there are also differences the purpose of this paper is to further unify the theory for these two families of methods and to introduce a new family of feti algorithms bounds on the rate of convergence which are uniform with respect to the coefficients of a family of elliptic problems with heterogeneous coefficients are established for these new algorithms the theory for a variant of the neumann neumann algorithm is also redeveloped stressing similarities to that for the feti methods

recognition of occluded objects with heuristic search abstract this paper presents a new heuristic search based approach for recognition of partially obscured planar shapes based on a general scheme for representing the planar shapes in terms of their contour segments a state space formulation is obtained for the recognition problem the search in the state space is guided by an admissible heuristic function which is not dependent upon the features actually used for representing the shapes some schemes for toning up the efficiency of the method are also discussed a study of the method was carried out by experimenting with some typical objects and results of experimentation are presented

attributed string matching with merging for shape recognition a new structural approach to shape recognition using attributed string matching with merging is proposed after illustrating the disadvantages of conventional symbolic string matching using changes deletions and insertions attributed strings are suggested for matching each attributed string is an ordered sequence of shape boundary primitives each representing a basic boundary structural unit line segment with two types of numerical attributes length and direction a new type of primitive edit operation called merge is then introduced which can be used to combine and then match any number of consecutive boundary primitives in one shape with those in another the resulting attributed string matching with merging approach is shown useful for recognizing distorted shapes experimental results prove the feasibility of the proposed approach for general shape recognition some possible extensions of the approach are also included

two dimensional object recognition through two stage string matching a two stage string matching method for the recognition of two dimensional 2 d objects is proposed in this work the first stage is a global cyclic string matching the second stage is a local matching with local dissimilarity measure computing the dissimilarity measure function of the input shape and the reference shape are obtained by combining the global matching cost and the local dissimilarity measure the proposed method has the advantage that there is no need to set any parameter in the recognition process experimental results indicate that the hostage string matching approach significantly improves the recognition rates compared to the one stage string matching method

the mosaic of high performance domain decomposition methods for structural mechanics formulation interrelation and numerical efficiency of primal and dual methods a multitude of domain decomposition methods ddm for structural mechanics is available in the literature today a unified framework for formulating primal and dual ddm is thus presented in this paper aiming at providing a mathematical platform for a uniform treatment of high performance ddm in structural mechanics a novel approach for developing new ddm from existing methods is also proposed and is applied to dual and primal methods in the field of the feti methods this approach leads to a new category of methods derived from existing feti variants furthermore two alternative formulations of the balancing domain decomposition method are described while interrelations between the introduced and existing methods are established finally comparative numerical tests demonstrate the differences in the computational performance of the methods in question

robust symbolic representation for shape recognition and retrieval a new method for shape recognition and retrieval is proposed here the suggested algorithm is based on several steps the algorithm analyzes the contour of pairs of shapes their contours are recovered and represented by a pair of n points obtained by linear interpolation given two points p i and q j from the two shapes the cost of their matching is evaluated by using the shape context and by using dynamic programming the best matching between the point sets is obtained dynamic programming not only recovers the best matching but also identifies occlusions i e points in the two shapes which cannot be properly matched given the correspondence between the two point sets the two contours are aligned using procrustes analysis after alignment each contour is transformed into a string of symbols and a modified version of edit distance is used to compute the similarity between strings of symbols finally recognition and retrieval are obtained by a simple nearest neighbor procedure the algorithm has been tested on a large set of shape databases kimia mpeg 7 natural silhouette database gesture database marine database swedish leaf database diatom database eth 80 3d object database providing performances for both in recognition and in retrieval superior to most of previously proposed approaches

syntax and semantics of multi adjoint normal logic programming abstract multi adjoint logic programming is a general framework with interesting features which involves other positive logic programming frameworks such as monotonic and residuated logic programming generalized annotated logic programs fuzzy logic programming and possibilistic logic programming one of the most interesting extensions of this framework is the possibility of considering a negation operator in the logic programs which will improve its flexibility and the range of real applications this paper introduces multi adjoint normal logic programming which is an extension of multi adjoint logic programming including a negation operator in the underlying lattice beside the introduction of the syntax and semantics of this paradigm we will provide sufficient conditions for the existence of stable models defined on a convex compact set of an euclidean space finally we will consider a particular algebraic structure in which sufficient conditions can be given in order to ensure the unicity of stable models of multi adjoint normal logic programs

equilateral polygon approximation of closed contours numerous algorithms have been suggested for computing polygonal approximations of closed contours we present an algorithm which as a unique feature creates polygons which are equilateral that is whose edges are all of the same length this allows one dimensional shape descriptions to be derived using the interior polygon angles conceptually the algorithm is an optimization framework for finding the minimum energy configuration of a mechanical system of particles and springs that represent the contour points the polygon vertices and their interaction in practice the dominant points are detected on the gaussian smoothed contour and used to seed an initial polygon nonlinear programming is then used to minimize the system energy subject to the constraint that adjacent vertices must be equidistant the objective function is the sum of a curvature weighted distance between each vertex and a set of contour points associated therewith experimental results are given for closed contours obtained from grey scale images

flexible syntactic matching of curves and its application to automatic hierarchical classification of silhouettes curve matching is one instance of the fundamental correspondence problem our flexible algorithm is designed to match curves under substantial deformations and arbitrary large scaling and rigid transformations a syntactic representation is constructed for both curves and an edit transformation which maps one curve to the other is found using dynamic programming we present extensive experiments where we apply the algorithm to silhouette matching in these experiments we examine partial occlusion viewpoint variation articulation and class matching where silhouettes of similar objects are matched based on the qualitative syntactic matching we define a dissimilarity measure and we compute it for every pair of images in a database of 121 images we use this experiment to objectively evaluate our algorithm first we compare our results to those reported by others second we use the dissimilarity values in order to organize the image database into shape categories the veridical hierarchical organization stands as evidence to the quality of our matching and similarity estimation

efficient shape matching through model based shape recognition abstract an efficient shape matching method for shape recognition is proposed it first uses a polygonal approximation technique to describe a shape then using the proposed matching algorithm based on some polygonal attributes the dissimilarity measure between an input shape and its reference model is obtained the input shape can be classified into the class model which has the minimum dissimilarity measure with it in addition it can provide the best matching orientation information for the input shape and its model so that further applications such as automated inspection and assembly can be effectively performed the proposed shape matching is invariant to translation rotation and scale changes of a shape experiments using noisy shapes and real images are performed and the recognition results demonstrate that the proposed method is very effective

a method for representing shape based on an equivalence relation on polygons abstract it is proved that there is a correspondence between deformations of polygons and a grammar this gives rise to an o n lo g n algorithm to match regions whose connectivity has been changed based on boundary contours this has application to problems in handwriting recognition it is then shown that deformations of polygons can be decomposed into canonical types this gives rise to new types of features to measure symmetry handedness rigidity bending and stretching

on dual schur domain decomposition method for linear first order transient problems this paper addresses some numerical and theoretical aspects of dual schur domain decomposition methods for linear first order transient partial differential equations the spatially discrete system of equations resulting from a dual schur domain decomposition method can be expressed as a system of differential algebraic equations daes in this work we consider the trapezoidal family of schemes for integrating the ordinary differential equations odes for each subdomain and present four different coupling methods corresponding to different algebraic constraints for enforcing kinematic continuity on the interface between the subdomains unlike the continuous formulation the discretized formulation of the transient problem is unable to enforce simultaneously the continuity of both the primary variable and its rate along the subdomain interface except for the backward euler method method 1 d continuity is based on the conventional approach using continuity of the primary variable and we show that this method is unstable for a lot of commonly used time integrators including the mid point rule to alleviate this difficulty we propose a new method 2 modified d continuity and prove its stability for coupling all time integrators in the trapezoidal family except the forward euler method 3 v continuity is based on enforcing the continuity of the time derivative of the primary variable however this constraint introduces a drift in the primary variable on the interface we present method 4 baumgarte stabilized which uses baumgarte stabilization to limit this drift and we derive bounds for the stabilization parameter to ensure stability our stability analysis is based on the energy method and one of the main contributions of this paper is the extension of the energy method which was previously introduced in the context of numerical methods for odes to assess the stability of numerical formulations for index 2 differential algebraic equations daes finally we present numerical examples to corroborate our theoretical predictions

extraction of dominant points by estimation of the contour fluctuations a new method of dominant points dps extraction is presented for each boundary point the method assigns a support region whose length is individually limited two steps are used to detect dps firstly points having higher curvature value than the estimated fluctuations over the support region are extracted as candidates secondly adjacent candidates are merged and a final elimination step is performed on each region additionally a new error measurement scheme is introduced which takes into account the error due to the polygonalisation and the deviation brought by each dp this error is used to compare our algorithm to other methods

polygonal shape recognition using string matching techniques in this paper we study several aspects of the use of string matching techniques as an approach to the problem of recognizing and classifying polygons several authors have already proposed methods for polygon recognition that are based on string matching in many cases however linear strings are used to represent polygons which makes it difficult to handle different orientations of an object efficiently we can however easily extend the linear string matching techniques to cyclic strings at some small computational cost we will propose a method to represent polygons as cyclic strings and we will show how cyclic string matching techniques can be used for rotation translation and scale independent polygonal shape recognition we will however also point out the limitations of such an approach