efficient parallel algorithms for string editing and related problems the string editing problem for input strings x and y consists of transforming x into y by performing a series of weighted edit operations on x of overall minimum cost an edit operation on x can be the deletion of a symbol from x the insertion of a symbol in x or the substitution of a symbol of x with another symbol this problem has a well known o x y time sequential solution efficient pram parallel algorithms for the string editing problem are given if m min x y and n max x y then the crew bound is o log m log n time with o mn log m processors the crow bound is o log n log log m 2 time with o mn log log m processors in all algorithms space is o mn

object detection by global contour shape we present a method for object class detection in images based on global shape a distance measure for elastic shape matching is derived which is invariant to scale and rotation and robust against non parametric deformations starting from an over segmentation of the image the space of potential object boundaries is explored to find boundaries which have high similarity with the shape template of the object class to be detected an extensive experimental evaluation is presented the approach achieves a remarkable detection rate of 83 91 at 0 2 false positives per image on three challenging data sets

estimation of nonlinearities in parabolic models for growth predation and dispersal of populations a convergence theory is given for approximation techniques to treat inverse problems involving systems of nonlinear parabolic partial differential equations these techniques can be used to estimate density dependent dispersal coefficients in population models as well as nonlinear growth and predation terms numerical experiences with the resulting algorithms on both conventional scalar and vector computers are reported along with an indication of performance of the methods with field data from prey predator experiments

on the solutions to 1 laplacian equation with l1 data in the present paper we study the behaviour as p goes to 1 of the renormalized solutions to the problems 0 1 div up p 2 up fin up 0on where p 1 is a bounded open set of rn n 2 with lipschitz boundary and f belongs to l1 we prove that these renormalized solutions pointwise converge up to subsequences to a function u with a suitable definition of solution we also prove that u is a solution to a limit problem moreover we analyze the situation occurring when more regular data f are considered

the best constant for the sobolev trace embedding from w1 1 ω into l1 ω abstract in this paper we study the best constant 1 for the trace map from w 1 1 into l 1 we show that this constant is attained in bv when 1 1 moreover we prove that this constant can be obtained as limit when p 1 of the best constant of w 1 p l p to perform the proofs we will look at neumann problems involving the 1 laplacian 1 u div du du

estimation of variable coefficients in parabolic distributed systems we present techniques based on cubic spline approximations for estimating coefficients e g diffusion convector velocity etc depending on time and the spatial variable in parabolic distributed systems such as those that arise in transport models convergence results and a summary of numerical performance of the resulting algorithms are given

variational method based on finite dimensional approximation in a generalized prescribed mean curvature problem abstract an elementary existence proof based on variational and finite dimensional approximation methods is proposed for nontrivial solutions of the generalized prescribed mean curvature boundary value problem div x u 1 1 u 2 u f x u in u 0 on which has been studied otherwise by elaborated abstract theories

nonparametric algorithm for identification of weakly nonlinear static distributed parameter systems an algorithm for identification of a nonlinear characteristic in a static distributed parameter system is proposed the algorithm is nonparametric in the sense that only smooth requirements are imposed on the unknown characteristic and that the number of terms in its orthogonal series expansion is not fixed in advance depending on the number of measurements the idea borrowed from statistics computational simplicity of the algorithm is obtained by restricting its applications to the identification of only weakly nonlinear static systems which allows applying perturbation theory it is shown that if the unknown characteristic in the system equation is replaced by its estimator then the resulting state converges to the true system state in the mean square sense

mesh independence of kleinman newton iterations for riccati equations in hilbert space in this paper we consider the convergence of the infinite dimensional version of the kleinman newton algorithm for solving the algebraic riccati operator equation associated with the linear quadratic regulator problem in a hilbert space we establish mesh independence for this algorithm and apply the result to systems governed by delay equations numerical examples are presented to illustrate the results

sensors and controllers location in distributed systems a survey a survey of the field of optimal sensors and or controllers location for dynamical distributed parameter systems modelled by partial differential equations is presented the recent contributions in this field are grouped according to the main goal for which the location problem is developed namely system identification state estimation and optimal control in order to pose the sensors and controllers location problem the semigroup approach for modelling distributed linear systems is briefly reviewed together with its equivalent infinite dimensional and approximate finite dimensional fourier expansion representations after presenting a concise general review of the several methods considered in the current literature a classification of methods is also proposed the main classifying factor concerns the use of n modal approximation schemes and the different stages of the optimization procedure in which they are required

relaxing the triangle inequality in pattern matching any notion of closeness in pattern matching should have the property that if a is close to b and b is close to c then a is close to c traditionally this property is attained because of the triangle inequality d a c d a b d b c where d represents a notion of distance however the full power of the triangle inequality is not needed for this property to hold instead a relaxed triangle inequality suffices of the form d a c c d a b d b c where c is a constant that is not too large in this paper we show that one of the measures used for distances between shapes in an experimental version of ibm s qbic1 query by image content system niblack et al 1993 satisfies a relaxed triangle inequality although it does not satisfy the triangle inequality

on detecting dominant points abstract detecting dominant points is a crucial preprocessing step for shape recognition and point based motion estimation polygonal approximation has been a commonly used approach in detecting dominant points this paper presents two alternatives which detect stable dominant points in the first method we find a set of positive maximum and negative minimum curvature points along the gaussian smoothed boundary followed by a split and merge polygonal approximation algorithm the resulting break points vertices of the approximated polygon are the dominant points experimental results show that dominant points obtained by this method are less sensitive to the orientation of the boundary than other polygonal approximation algorithms in the sense that the number and the location of the dominant points along the contour remain relatively unchanged in the second method we smooth a boundary by a gaussian filter using various widths until the extreme curvature points remain relatively unchanged for a range of filter widths the resulting extreme curvature points which are stable to orientation and a reasonable range of scaling are the dominant points

cubic spline approximation techniques for parameter estimation in distributed systems approximation schemes employing cubic splines in the context of a linear semigroup framework are developed for both parabolic and and hyperbolic second order partial differential equation parameter estimation problems convergence results are established for problems with linear and nonlinear systems and a summary of numerical experiments with the techniques proposed is given

estimation of discontinuous coefficients in parabolic systems applications to reservoir simulation we present spline based techniques for estimating spatially varying parameters that appear in parabolic distributed systems typical of those found in reservoir simulation problems in particular we discuss the problem of determining discontinuous coefficients estimating both the functional shape and points of discontinuity for such parameters in addition our ideas may also be applied to problems with unknown initial conditions and unknown parameters appearing in terms representing external forces convergence results and a summary of numerical performance of the resulting algorithms are given

galerkin approximation of optimal linear filtering of infinite dimensional linear systems in this paper an implementable approximation of the infinite dimensional kalman filter is proposed for linear distributed systems corrupted by white noise it relies on a galerkin type treatment of both the riccati and the filter equations and it is shown to converge to the best linear estimate of the state for each sample path of the noise a basic tool is the study of the riccati equation on the hilbert space of hilbert schmidt operators on the state space numerical results are given for a case concerning delay differential equation

estimates of the best sobolev constant of the embedding of bv ω into l1 ω and related shape optimization problems abstract in this paper we find estimates for the optimal constant in the critical sobolev trace inequality 1 u l 1 u w 1 1 that are independent of these estimates generalize those of j fernandez bonder n saintier estimates for the sobolev trace constant with critical exponent and applications ann mat pura aplicata in press concerning the p laplacian to the case p 1 we apply our results to prove the existence of an extremal for this embedding we then study an optimal design problem related to 1 and eventually compute the shape derivative of the functional 1

noisy logo recognition using line segment hausdorff distance logo recognition is of great interest in the document and shape analysis domain in order to develop a recognition method that is robust to employ under adverse conditions such as different scale orientation broken curves added noise and occlusion a modified line segment hausdorff distance is proposed in this paper the new approach has the advantage to incorporate structural and spatial information to compute dissimilarity between two sets of line segments rather than two sets of points the proposed technique has been applied on line segments generated from logos with encouraging results clear cut distinction between the correct and incorrect matches has been observed this suggests a strong potential for logo and shape recognition system

on the detection of dominant points on digital curves a parallel algorithm is presented for detecting dominant points on a digital closed curve the procedure requires no input parameter and remains reliable even when features of multiple sizes are present on the digital curve the procedure first determines the region of support for each point based on its local properties then computes measures of relative significance e g curvature of each point and finally detects dominant points by a process of nonmaximum suppression this procedure leads to the observation that the performance of dominant points detection depends not only on the accuracy of the measure of significance but also on the precise determination of the region of support this solves the fundamental problem of scale factor selection encountered in various dominant point detection algorithms the inherent nature of scale space filtering in the procedure is addressed and the performance of the procedure is compared to those of several other dominant point detection algorithms using a number of examples

deformed trademark retrieval based on 2d pseudo hidden markov model abstract a new deformed trademark retrieval method based on two dimensional pseudo hidden markov model 2d phmm is proposed in this paper most trademark retrieval systems focus on color features shape silhouettes or the combination of color and shape however these approaches adopted individual silhouettes as shape features leading to the following two crucial problems first most trademarks have various numbers of decomposed components while the silhouette based approaches cannot handle the variety correctly second the infringement cases in which trademarks are changed by non rigid deformation in particular nonlinear deformation may escape detection thus our method focuses on the overall appearance of trademarks and incorporates color and shape features into 2d phmm to tackle the above two problems the reason to involve 2d phmm is that it has high tolerance to noise and distortion moreover contextual information can be incorporated into it in a natural and elegant way however 2d phmm is computation intensive and sensitive to rotation scale and translation variations thus it is the main originality of this paper to include the advantages of 2d phmm but to exclude its disadvantages as a result similar trademarks can be retrieved effectively even those with different numbers of components or non rigid deformation various experiments have been conducted on a trademark database to prove the effectiveness and practicability of the proposed method

fitting numerical solutions of differential equations to experimental data a case study and some general remarks summary a simple and efficient algorithm for least squares estimation of the parameters of a numerically solved diffusion model is presented the algorithm has been specially developed for the analysis of data obtained by vitreous fluorophotometry a method in clinical eye research but it has several straightforward generalizations which are also outlined in the paper it happens that these equations are difficult or impossible to solve explicitly and that numerical methods are employed often it is desired to estimate the parameters of such models from experimental data using the method of least squares or one of its relatives the main body of differential equation models in biometry consists of initial value problems for systems of ordinary differential equations such as occur in compartment models but also partial differential equations appear banks and kareiva 1983 discuss the transport of glucose in the cat brain as well as deterministic population dynamic models for insect dispersal the current study deals with the transport of a fluorescent dye in the vitreous body of the human eye and in general questions of diffusion or heat transfer involve similar equations further applications might include fluid flow problems or equations of elasticity in biomechanics since numerical methods for the solution of partial differential equations are computationally demanding it is important to choose an efficient algorithm for the estimation of model parameters particularly in situations where the algorithm is to be applied many times for instance when several curves are to be fitted for each examination of each patient as part of an interactive routine for coordination of data from different sources the current study deals with vitreous fluorophotometry a method in clinical eye research where the model involves the diffusion equation and the parameters are the diffusion coefficient in the vitreous body of the eye and the permeability of the blood retinal barrier the data are concentration measurements in the vitreous body we have found that for this

discontinuous velocity domain splitting in limit analysis abstract we present a new limit analysis method originated in ionescu and lachand robert 2005 and called discontinuous velocity domain splitting method dvds dvds is a mesh free method which focuses on the strain localization and completely neglect the bulk deformations it considers the kinematic variational principle on a special class of virtual velocity fields to get an upper bound of the limit load to construct this class of virtual velocity fields the rigid plastic body is splinted into simple connected sub domains and on each such sub domain a rigid motion is associated the discontinuous collapse flow velocity field results in localized deformations only located at the boundary of the sub domains in the numerical applications of the dvds method we introduce a numerical technique based on a level set description of the partition of the rigid plastic body and on genetic minimization algorithms for the anti plane flow of a von mises material dvds is exact in solving the limit analysis problem the collapse flow is a rigid motion of a sub domain the associated deformation rate is localized on the smooth boundary of the moving sub domain representing the fracture surface in the case of in plane deformation of pressure insensitive materials the internal boundaries of the sub domains are parts of circles or straight lines tangent to the collapse velocity jumps in this case dvds reduces to the block decomposition method which was intensively used to get analytical upper bounds of the limit loads when applied to the two notched tensile problem of a von mises material dvds gives excellent results with a low computational cost furthermore dvds was applied to model collapse in pressure sensitive plastic materials illustrative examples for homogenous and heterogeneous coulomb and cam clay materials shows that dvds gives excellent prediction of limit loads and on the collapse flow

an approximation theory for nonlinear partial differential equations with applications to identification and control approximation results from linear semigroup theory are used to develop a general framework for convergence of approximation schemes in parameter estimation and optimal control problems for nonlinear partial differential equations these ideas are used to establish theoretical convergence results for parameter identification using modal eigenfunction approximation techniques results from numerical investigations of these schemes for both hyperbolic and parabolic systems are given

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

estimation of coefficients and boundary parameters in hyperbolic systems we consider semi discrete galerkin approximation schemes in connection with inverse problems for the estimation of spatially varying coefficients and boundary condition parameters in second order hyperbolic systems typical of those arising in 1 d surface seismic problems spline based algorithms are proposed for which theoretical convergence results along with a representative sample of numerical findings are glven

elliptic equations involving the 1 laplacian and a subcritical source term abstract in this paper we deal with a dirichlet problem for an elliptic equation involving the 1 laplacian operator and a source term we prove that when the growth of the source is subcritical there exist two bounded nontrivial solutions to our problem moreover a pohozaev type identity is proved which holds even when the growth is supercritical we also show explicit examples of our results

trademark shapes description by string matching techniques abstract this work considers the possibility of measuring the shape similarity distances of two dimensional objects the method proposed is articulated in two stages chain coding the objects contours and applying string distances to the coded contours the distance values obtained by such a procedure are then associated to the general geometrical characteristics of the object comparison of the distance values of two objects gives an indication of their similarity the implementation of a shape similarity distance based on this concept is considered in depth its theoretical and practical implications are examined the effectiveness of the method is tested with trademarks a class of images of considerable practical interest the results are encouraging and point to the feasibility of the task undertaken by using the proposed approach

reduction of distributed system identification complexity using intelligent sensors abstract the identification problems of distributed parameter systems dps is dealt with a special method of data collection by using moving sensors is proposed the sensors are intelligent in the sense that they are able to track the positions of the exiremum values of a system state at each time instant it is shown how to reduce the identification problem for dps to that of identifying a certain system described by ordinary differential equations ode the proposed approach is applicable to the dps described by quasi linear partial differential equations of the hyperbolic type attention is focused on the problem of reduction while the identification of the resulting ode is not considered in detail since it is an easier task

on the shape of the solutions of second order parabolic partial differential equations on etudie certains aspects de la forme des solutions des equations aux derivees partielles paraboliques lineaires on considere le cas u t au x x cu t x 0 u 0 r j u t 0 t 0 j 1 2 ou 0 1 et r j est un operateur limite general on etudie la cardinalite de l ensemble des zeros d une section temporelle u x t t 0 ainsi que l ensemble s des ordonnees ou la section de temps u t d une solution atteint une valeur specifiee