approximation of the levy feller advection dispersion process by random walk and finite difference method in this paper we present a random walk model for approximating a levy feller advection dispersion process governed by the levy feller advection dispersion differential equation lfade we show that the random walk model converges to lfade by use of a properly scaled transition to vanishing space and time steps we propose an explicit finite difference approximation efda for lfade resulting from the grunwald letnikov discretization of fractional derivatives as a result of the interpretation of the random walk model the stability and convergence of efda for lfade in a bounded domain are discussed finally some numerical examples are presented to show the application of the present technique

computing positive stable numerical solutions of moving boundary problems for concrete carbonation abstract this paper deals with the construction and computation of numerical solutions of a coupled mixed partial differential equation system arising in concrete carbonation problems the moving boundary problem under study is firstly transformed in a fixed boundary one allowing the computation of the propagation front as a new unknown that can be computed together with the mass concentrations of co 2 in air and water apart from the stability and the consistency of the numerical solution constructed by a finite difference scheme qualitative properties of the numerical solution are established in fact positivity of the concentrations increasing properties of the propagation front and monotone behavior of the solution are proved we also confirm numerically the t law of propagation results are illustrated with numerical examples

stationary distribution of a stochastic delayed sveir epidemic model with vaccination and saturation incidence abstract in this paper we develop and analyze a stochastic delayed sveir epidemic model with vaccination and saturation incidence by constructing a suitable stochastic lyapunov function we establish sufficient conditions for the existence and uniqueness of an ergodic stationary distribution of the positive solutions to the model the existence of a stationary distribution implies stochastic weak stability numerical simulations are introduced to illustrate the analytical result

tracking deformable objects in the plane using an active contour model the problems of segmenting a noisy intensity image and tracking a nonrigid object in the plane are discussed in evaluating these problems a technique based on an active contour model commonly called a snake is examined the technique is applied to cell locomotion and tracking studies the snake permits both the segmentation and tracking problems to be simultaneously solved in constrained cases a detailed analysis of the snake model emphasizing its limitations and shortcomings is presented and improvements to the original description of the model are proposed problems of convergence of the optimization scheme are considered in particular an improved terminating criterion for the optimization scheme that is based on topographic features of the graph of the intensity image is proposed hierarchical filtering methods as well as a continuation method based on a discrete sale space representation are discussed results for both segmentation and tracking are presented possible failures of the method are discussed

composite scheme lr th for decoding with erasures and its effective equivalence to forney s rule for decoding with erasures forney s scheme is known to be optimal in the sense that no other scheme can make the erasure probability p sub ers and undetected error probability p sub uer simultaneously smaller we propose a scheme for erasure decision which tests the likelihood ratio as well as the likelihood itself and show that the attainable upper bounds on p sub ers and p sub uer are the same as those proved for the optimal scheme up to a constant factor we also show that the scheme gives when applied to convolutional codes a bound which is related to the block coding bound via forney s inverse concatenation construction we show that this bound is the same as the one which naturally arises when we apply raghavan and baum s 1998 optimal scheme to convolutional code

fast open world person re identification existing person re identification re id methods typically assume that 1 any probe person is guaranteed to appear in the gallery target population during deployment i e closed world and 2 the probe set contains only a limited number of people i e small search scale both assumptions are artificial and breached in real world applications since the probe population in target people search can be extremely vast in practice due to the ambiguity of probe search space boundary therefore it is unrealistic that any probe person is assumed as one target people and a large scale search in person images is inherently demanded in this paper we introduce a new person re id search setting called large scale open world lsow re id characterized by huge size probe images and open person population in search thus more close to practical deployments under lsow the under studied problem of person re id efficiency is essential in addition to that of commonly studied re id accuracy we therefore develop a novel fast person re id method called cross view identity correlation and verification x ice hashing for joint learning of cross view identity representation binarisation and discrimination in a unified manner extensive comparative experiments on three large scale benchmarks have been conducted to validate the superiority and advantages of the proposed x ice method over a wide range of the state of the art hashing models person re id methods and their combinations

elicitation strategies for soft constraint problems with missing preferences properties algorithms and experimental studies we consider soft constraint problems where some of the preferences may be unspecified this models for example settings where agents are distributed and have privacy issues or where there is an ongoing preference elicitation process in this context we study how to find an optimal solution without having to wait for all the preferences in particular we define algorithms that interleave search and preference elicitation to find a solution which is necessarily optimal that is optimal no matter what the missing data will be with the aim to ask the user to reveal as few preferences as possible we define a combined solving and preference elicitation scheme with a large number of different instantiations each corresponding to a concrete algorithm which we compare experimentally we compute both the number of elicited preferences and the user effort which may be larger as it contains all the preference values the user has to compute to be able to respond to the elicitation requests while the number of elicited preferences is important when the concern is to communicate as little information as possible the user effort measures also the hidden work the user has to do to be able to communicate the elicited preferences our experimental results on classical fuzzy weighted and temporal incomplete csps show that some of our algorithms are very good at finding a necessarily optimal solution while asking the user for only a very small fraction of the missing preferences the user effort is also very small for the best algorithms

a higher order compact lod method and its extrapolations for nonhomogeneous parabolic differential equations abstract a higher order compact locally one dimensional lod finite difference method for two dimensional nonhomogeneous parabolic differential equations is proposed the resulting scheme consists of two one dimensional tridiagonal systems and all computations are implemented completely in one spatial direction as for one dimensional problems the solvability and the stability of the scheme are proved almost unconditionally the error estimates are obtained in the discrete h 1 l 2 and l norms and show that the proposed compact lod method has the accuracy of the second order in time and the fourth order in space two richardson extrapolation algorithms are presented to increase the accuracy to the fourth order and the sixth order in both time and space when the time step is proportional to the spatial mesh size numerical results demonstrate the accuracy of the compact lod method and the high efficiency of its extrapolation algorithms

a bayesian spatiotemporal model for very large data sets functional mri provides a unique perspective of neuronal organization however these data include many complex sources of spatiotemporal variability which require spatial preprocessing and statistical analysis for the latter bayesian models provide a promising alternative to classical inference which uses results from gaussian random field theory to assess the significance of spatially correlated statistic images a bayesian approach generalizes the application of these ideas in that 1 random fields are used to model all spatial parameters not solely observation error 2 their smoothness is optimized and 3 a broader class of models can be compared the main problem however is computational due to the large number of voxels in a brain volume sampling methods are time consuming however approximate inference using variational bayes vb offers a principled and transparent way to specify assumptions necessary for computational tractability penny et al 2005b described such a scheme using a joint spatial prior and approximated the joint posterior density with one that factorized over voxels however a further computational bottleneck is encountered when evaluating the log model evidence used to compare models this has lead to dividing a brain volume into slices and treating each independently this amounts to approximating the spatial prior over a full volume with stacked 2d priors that is smoothness along the z axis is not included in the model here we describe a vb scheme that approximates the zero mean joint spatial prior with a non zero mean empirical prior that factors over voxels thereby overcoming this problem we do this by modifying the original vb algorithm of penny et al using the conditional form of a so called conditional autoregressive car prior to update a marginal prior over voxels we refer to this as a spatially informed voxel wise prior svp and use them to spatially regularise general linear model glm and autoregressive ar coefficients over time to model serial correlations this algorithm scales more favourably with the number of voxels providing a truly 3d spatiotemporal model over volumes containing tens of thousands of voxels we compare the scaling of compute times with the number of voxels and performance with a joint prior applied to synthetic and single subject data

recovering the history of a groundwater contaminant plume method of quasi reversibility the method of quasi reversibility qr lattes and lions 1969 has been used previously to solve the diffusion equation with reversed time we develop a quasi reversible solution to a convection dispersion equation by solving the qr diffusion operator in a moving coordinate system the solution procedure is applied to the problem of recovering the history of a groundwater contaminant plume from observations of its present conditions this approach to the plume history problem is potentially superior to the tikhonov regularization approach used by skaggs and kabala 1994 because it is easier to implement and readily allows for space and time dependent transport parameters however our results for a few example problems suggest that the qr procedure is less accurate than the regularization technique thus the easy implementation and improved generality of the qr procedure come at the expense of accuracy this trade off will have to be weighed if the qr technique is to be used

a numerical scheme for the solution of the space charge problem on a multiply connected region in this paper we extend the work of budd and wheeler proc r soc london a 417 389 1988 who described a new numerical scheme for the solution of the space charge equation on a simple connected domain to multiply connected regions the space charge equation 0 is a third order nonlinear partial differential equation for the electric potential which models the electric field in the vicinity of a coronating conductor budd and wheeler described a new way of analysing this equation by constructing an orthogonal coordinate system and recasting the equation in terms of x y and as functions of this transformation is singular on multiply connected regions and in this paper we show how this may be overcome to provide an efficient numerical scheme for the solution of the space charge equation this scheme also provides a new method for the solution of laplaces equation and the calculation of orthogonal meshes on multiply connected regions

on the equivalence of soft wavelet shrinkage total variation diffusion total variation regularization and sides soft wavelet shrinkage total variation tv diffusion tv regularization and a dynamical system called sides are four useful techniques for discontinuity preserving denoising of signals and images in this paper we investigate under which circumstances these methods are equivalent in the one dimensional case first we prove that haar wavelet shrinkage on a single scale is equivalent to a single step of space discrete tv diffusion or regularization of two pixel pairs in the translationally invariant case we show that applying cycle spinning to haar wavelet shrinkage on a single scale can be regarded as an absolutely stable explicit discretization of tv diffusion we prove that space discrete tv diffusion and tv regularization are identical and that they are also equivalent to the sides system when a specific force function is chosen afterwards we show that wavelet shrinkage on multiple scales can be regarded as a single step diffusion filtering or regularization of the laplacian pyramid of the signal we analyze possibilities to avoid gibbs like artifacts for multiscale haar wavelet shrinkage by scaling the thresholds finally we present experiments where hybrid methods are designed that combine the advantages of wavelets and pde variational approaches these methods are based on iterated shift invariant wavelet shrinkage at multiple scales with scaled thresholds

stability analysis of six point finite difference schemes for the constant coefficient convective diffusion equation abstract a comprehensive and systematic study is presented to derive stability properties of various two level six point finite difference schemes in particular difference schemes of pade type for the approximation to the constant coefficient convective diffusion equation first the modified equivalent partial differential equation mepde for a general six point difference scheme is derive the mepde provides direct information on the order of accuracy of a difference scheme the von neumann and matrix methods are then employed to deduce the necessary and sufficient conditions for the numerical stability for the six point difference schemes an unified technique is developed to find the stability regions for the difference schemes some new second and third order six point difference schemes for the approximation of the constant coefficient convective diffusion equation are presented

dynamics and optimal control of a non linear epidemic model with relapse and cure abstract in this work we introduce the basic reproduction number r 0 for a general epidemic model with graded cure relapse and nonlinear incidence rate in a non constant population size we established that the disease free equilibrium state e f is globally asymptotically exponentially stable if r 0 1 and globally asymptotically stable if r 0 1 if r 0 1 we proved that the system model has at least one endemic state e e then by means of an appropriate lyapunov function we showed that e e is unique and globally asymptotically stable under some acceptable biological conditions on the other hand we use two types of control to reduce the number of infectious individuals the optimality system is formulated and solved numerically using a gauss seidel like implicit finite difference method

efficient orthogonal matrix polynomial based method for computing matrix exponential the matrix exponential plays a fundamental role in the solution of differential systems which appear in different science fields this paper presents an efficient method for computing matrix exponentials based on hermite matrix polynomial expansions hermite series truncation together with scaling and squaring and the application of floating point arithmetic bounds to the intermediate results provide excellent accuracy results compared with the best acknowledged computational methods a backward error analysis of the approximation in exact arithmetic is given this analysis is used to provide a theoretical estimate for the optimal scaling of matrices two algorithms based on this method have been implemented as matlab functions they have been compared with matlab functions funm and expm obtaining greater accuracy in the majority of tests a careful cost comparison analysis with expm is provided showing that the proposed algorithms have lower maximum cost for some matrix norm intervals numerical tests show that the application of floating point arithmetic bounds to the intermediate results may reduce considerably computational costs reaching in numerical tests relative higher average costs than expm of only 4 43 for the final hermite selected order and obtaining better accuracy results in the 77 36 of the test matrices the matlab implementation of the best hermite matrix polynomial based algorithm has been made available online

open constraint programming traditionally constraint satisfaction problems csp have assumed closed world scenarios where all domains and constraints are fixed from the beginning with the internet many of the traditional csp applications in resource allocation scheduling and planning pose themselves in open world settings where domains and constraints must be discovered from different sources in a network to model this scenario we define open constraint satisfaction problems ocsp as csp where domains and constraints are incrementally discovered through a network we then extend the concept to open constraint optimization ocop ocsp can be solved without complete knowledge of the variable domains and we give sound and complete algorithms we show that ocop require the additional assumption that variable domains and relations are revealed in non decreasing order of preference we present a variety of algorithms for solving ocop in the possibilistic and weighted model we compare the algorithms through experiments on randomly generated problems we show that in certain cases open constraint programming can require significantly less information than traditional methods where gathering information and solving the csp are separated this leads to a reduction in network traffic and server load and improves privacy in distributed problem solving

invariant surface segmentation through energy minimization with discontinuities the computational problems in segmenting range data into surface patches based on the invariant surface properties i e mean curvature h and gaussian curvature k are investigated the goal is to obtain reliable hk surface maps two commonly encountered problems are firstly the noise effect in computing derivative estimates and secondly the smoothing across discontinuities here the segmentation is formulated as finding minimization solutions of energy functionals involving discontinuities a two stage approach to the goal is presented stage 1 from a range image to curvature images and stage 2 from the curvature images to the hk maps in both stages solutions are found through minimizing energy functionals that measure the degree of bias of a solution from two constraints the closeness of the solution to the data and the smoothness of the solution controlled by predetermined discontinuities propagation across discontinuities is prevented during minimization which preserves the original surface shapes experimental results are given for a variety of test images

analytical solutions for heat diffusion beyond fourier law we obtain solutions for differential equations describing a broad range of physical problems by the operational method with recourse to inverse differential operators integral transforms and operational exponent generalized families of orthogonal polynomials and special functions are also employed with recourse to their operational definitions the evolutional type problems for heat transfer in various heat conduction models are studied exact analytical solutions for guyer krumhansl hyperbolic heat equation are obtained and compared with those of fourier and cattaneo equations modelling heat pulse propagation from a laser source is performed in the framework of fourier cattaneo and guyer krumhansl heat transfer models compliance of obtained solutions with the maximum principle is studied

a mathematical study of a model for childhood diseases with non permanent immunity protecting children from diseases that can be prevented by vaccination is a primary goal of health administrators since vaccination is considered to be the most effective strategy against childhood diseases the development of a framework that would predict the optimal vaccine coverage level needed to prevent the spread of these diseases is crucial this paper provides this framework via qualitative and quantitative analysis of a deterministic mathematical model for the transmission dynamics of a childhood disease in the presence of a preventive vaccine that may wane over time using global stability analysis of the model based on constructing a lyapunov function it is shown that the disease can be eradicated from the population if the vaccination coverage level exceeds a certain threshold value it is also shown that the disease will persist within the population if the coverage level is below this threshold these results are verified numerically by constructing and then simulating a robust semi explicit second order finite difference method

the maximum number of infected individuals in sis epidemic models computational techniques and quasi stationary distributions we study the maximum number of infected individuals observed during an epidemic for a susceptible infected susceptible sis model which corresponds to a birth death process with an absorbing state we develop computational schemes for the corresponding distributions in a transient regime and till absorption moreover we study the distribution of the current number of infected individuals given that the maximum number during the epidemic has not exceeded a given threshold in this sense some quasi stationary distributions of a related process are also discussed

constraint based optimization and utility elicitation using the minimax decision criterion in many situations a set of hard constraints encodes the feasible configurations of some system or product over which multiple users have distinct preferences however making suitable decisions requires that the preferences of a specific user for different configurations be articulated or elicited something generally acknowledged to be onerous we address two problems associated with preference elicitation computing a best feasible solution when the user s utilities are imprecisely specified and developing useful elicitation procedures that reduce utility uncertainty with minimal user interaction to a point where approximately optimal decisions can be made our main contributions are threefold first we propose the use of minimax regret as a suitable decision criterion for decision making in the presence of such utility function uncertainty second we devise several different procedures all relying on mixed integer linear programs that can be used to compute minimax regret and regret optimizing solutions effectively in particular our methods exploit generalized additive structure in a user s utility function to ensure tractable computation third we propose various elicitation methods that can be used to refine utility uncertainty in such a way as to quickly i e with as few questions as possible reduce minimax regret empirical study suggests that several of these methods are quite successful in minimizing the number of user queries while remaining computationally practical so as to admit real time user interaction

performance of viterbi decoding with and without arq on rician fading channels in this paper we investigate the performance of the viterbi decoding algorithm with without automatic repeat request arq over a rician flat fading channel with unlimited interleaving we show that the decay rate of the average bit error probability with respect to the bit energy to noise ratio is at least equal to d f at high bit energy to noise ratio for both cases with arq and without arq where d f is the free distance of the convolutional code the yamamoto itoh flag helps to reduce the average bit error probability by a factor of 4 d f with a negligible retransmission rate we also prove an interesting result that the average bit error probability decays exponentially fast with respect to the rician factor for any fixed bit energy per noise ratio in addition the average bit error exponent with respect to the rician factor is shown to be d f

numerical analysis and computing of a non arbitrage liquidity model with observable parameters for derivatives abstract this paper deals with the numerical analysis and computing of a nonlinear model of option pricing appearing in illiquid markets with observable parameters for derivatives a consistent monotone finite difference scheme is proposed and a stability condition on the stepsize discretizations is given

stability analysis of an hiv aids epidemic model with treatment an hiv aids epidemic model with treatment is investigated the model allows for some infected individuals to move from the symptomatic phase to the asymptomatic phase by all sorts of treatment methods we first establish the ode treatment model with two infective stages mathematical analyses establish that the global dynamics of the spread of the hiv infectious disease are completely determined by the basic reproduction number 0 if email protected 1 the disease free equilibrium is globally stable whereas the unique infected equilibrium is globally asymptotically stable if 0 1 then we introduce a discrete time delay to the model to describe the time from the start of treatment in the symptomatic stage until treatment effects become visible the effect of the time delay on the stability of the endemically infected equilibrium is investigated moreover the delay model exhibits hopf bifurcations by using the delay as a bifurcation parameter finally numerical simulations are presented to illustrate the results

examination clarification and simplification of stability and dispersion analysis for adi fdtd and cnss fdtd schemes we describe a rigorous analysis of unconditional stability for the alternating direction implicit finite difference time domain adi fdtd and crank nicholson split step cnss fdtd schemes avoiding use of the von neumann spectral criterion the proof is performed in the spectral domain and uses skew hermitivity of matrix terms in the adi and cnss total amplification matrices a bound for the total adi amplification matrix is provided while the cn and cnss fdtd amplification matrices are unitary the bound on the adi fdtd depends on the courant number importantly we have found that the adi fdtd amplification matrix is not normal i e the unit spectral radius alone cannot be used to prove the adi fdtd unconditional stability the paper also shows that the adi fdtd and cnss fdtd schemes share the same dispersion equation by a similarity of their total amplification matrices and the two schemes have identical numerical dispersion in the frame of plane waves

efficient implicit scheme with positivity preserving and smoothing properties using classical finite difference schemes often generates numerical drawbacks such as spurious oscillations in the solution of the famous black scholes partial differential equation we analyze the fully implicit scheme frequently used numerical method in finance that in the presence of discontinuous payoff and low volatility arises spurious oscillations we propose a modification of this scheme so that we guarantee a smooth numerical solution free of spurious oscillations and satisfies the positivity requirement as is demanded for the financial solution of the black scholes equation the method is used within the strategy suggested by rannacher only in few initial time steps in the presence of discontinuous initial conditions as a consequence although the method is low order accurate it returns a spurious oscillations free solution next starting from the smooth initial condition obtained any other family of arbitrary higher order schemes may be used

stereo correspondence by surface reconstruction an algorithm that solves the computational stereo correspondence and the surface reconstruction is presented the algorithm integrates the reconstruction process in the correspondence analysis by means of multipass attribute matching and disparity refinement in the matching process the requirement of attribute similarity is relaxed with the pass number while the requirement for agreement between the predicted and the measured disparity is tightened disparity discontinuities and occluded areas are detected by analyzing the partial derivatives of the reconstructed disparity surface results on synthetic and on real stereo image pairs are reported

constructing positive reliable numerical solution for american call options a new front fixing transformation is applied to the black scholes equation for the american call option pricing problem the transformed non linear problem involves homogeneous boundary conditions independent of the free boundary the numerical solution by an explicit finite difference method is positive and monotone stability and consistency of the scheme are studied the explicit proposed method is compared with other competitive implicit ones from the points of view accuracy and computational cost

analysis of a nonautonomous dynamical model of diseases through droplet infection and direct contact in this paper we have considered a nonautonomous dynamical model of diseases that spread by droplet infection and also through direct contact with a lower risk with varying total population size and distributed time delay to become infectious it is assumed that there is a time lag due to incubation period of pathogens i e the development of an infection from the time the pathogen enters the body until signs or symptoms first appear here we have established some sufficient conditions on the permanence and extinction of the disease by using inequality analytical technique we have obtained the explicit formula of the eventual lower bounds of infected persons we have introduced some new threshold values by lyapunov functional method we have also obtained some sufficient conditions for global asymptotic stability of this model computer simulations are carried out to explain the analytical findings the aim of the analysis of this model is to trace the parameters of interest for further study with a view to informing and assisting policy maker in targeting prevention and treatment resources for maximum effectiveness

an accurate computation of the global solution curve for the gelfand problem through a two point approximation when one solves numerically the gelfand boundary value problem in two dimensions with u u x y r x 2 y 2 and l a positive parameter email protected u 0forr 1 u 0whenr r with 10 mesh points two spurious turns appear on the solution curve when one increases the number of mesh points the spurious turns persist occurring at smaller values of l it turns out that spurious turns are avoided in the other direction by using two to six mesh points we prove this in case of two mesh points this gives us the correct form of the solution curve and the accuracy can then be improved by using a linear search on u 0 combined with shooting

on gaussian macs with variable length feedback and non vanishing error probabilities we characterize the fundamental limits of transmission of information over a gaussian multiple access channel mac with the use of variable length feedback codes and under a non vanishing error probability formalism we develop new achievability and converse techniques to handle the continuous nature of the channel and the presence of expected power constraints we establish the varepsilon capacity regions and bounds on the second order asymptotics of the gaussian mac with variable length feedback with termination codes and stop feedback codes we show that the former outperforms the latter significantly due to the multi terminal nature of the channel model we leverage tools from renewal theory developed by lai and siegmund to bound the asymptotic behavior of the maximum of a finite number of stopping times

exponentially fitted imex methods for advection diffusion problems the paper is devoted to the numerical solution of advection diffusion problems of boussinesq type by means of adapted numerical methods the adaptation occurs at two levels along space by suitably semidiscretizing the spatial derivatives through finite differences based on exponential fitting along time integration through an adapted imex method based on exponential fitting itself stability analysis is provided and numerical examples showing the effectiveness of the approach also in comparison with the classical one are given

dynamically consistent nonstandard finite difference schemes for epidemiological models this work is the numerical analysis and computational companion of the paper by kamgang and sallet j c kamgang g sallet computation of threshold conditions for epidemiological models and global stability of the disease free equilibrium dfe mathematical biosciences 213 2008 1 12 where threshold conditions for epidemiological models and the global stability of the disease free equilibrium dfe are studied we establish a discrete counterpart of the main continuous result that guarantees the global asymptotic stability gas of the dfe for general epidemiological models then we design nonstandard finite difference nsfd schemes in which the metzler matrix structure of the continuous model is carefully incorporated and both mickens rules world scientific singapore 1994 on the denominator of the discrete derivative and the nonlocal approximation of nonlinear terms are used in an innovative way as a result of these strategies our nsfd schemes are proved to be dynamically consistent with the continuous model i e they replicate their basic features including the gas of the dfe the linear stability of the endemic equilibrium ee the positivity of the solutions the dissipativity of the system and its inherent conservation law the general analysis is made detailed for the mseir model for which the nsfd theta method is implemented with emphasis on the computational aspects such as its convergence or local truncation error numerical simulations that illustrate the theory are provided

the dynamics of a one dimensional parabolic problem versus the dynamics of its discretization abstract in this paper we prove that the spatial discretization of a one dimensional system of parabolic equations with suitably small step size contains exactly the same asymptotic dynamics as the continuous problem

semiring based constraint satisfaction and optimization we introduce a general framework for constraint satisfaction and optimization where classical csps fuzzy csps weighted csps partial constraint satisfaction and others can be easily cast the framework is based on a semiring structure where the set of the semiring specifies the values to be associated with each tuple of values of the variable domain and the two semiring operations and x model constraint projection and combination respectively local consistency algorithms as usually used for classical csps can be exploited in this general framework as well provided that certain conditions on the semiring operations are satisfied we then show how this framework can be used to model both old and new constraint solving and optimization schemes thus allowing one to both formally justify many informally taken choices in existing schemes and to prove that local consistency techniques can be used also in newly defined schemes

evaluating the performance of convolutional codes over block fading channels this correspondence considers union upper bound techniques for error control codes with limited interleaving over block fading rician channels a modified bounding technique is presented that relies on limiting the conditional union bound before averaging over the fading process this technique although analytically not very attractive provides tight and hence useful numerical results

on the error exponent of convolutionally coded arq forney s 1968 exponent is effectively the best one for the block coded automatic repeat request systems arq and it has been conjectured that a counterpart of forney s exponent is attainable by convolutional codes with reasonable decoder complexity in the paper it is show that the scheme of yamamoto and itoh 1980 which is known to be one of the simplest convolutionally coded arq schemes actually gives a better performance than ever expected and that it has an error exponent quite close to the conjectured counterpart of forney s exponent at relatively low rates it is further shown that the likelihood ratio test used by yamamoto and itoh gives forney s exponent in the case of block coded arq

a linearized numerical scheme for burgers like equations a linearized implicit finite difference method is presented to find numerical solutions of the one dimensional burgers like equations the method has been used successfully to obtain accurate numerical solutions even for small values of viscosity term n results obtained by the present method using a direct technique for some values of n have been compared with the exact values and are found to be in good agreement with each other

on the spectrum of stiffness matrices arising from isogeometric analysis we study the spectral properties of stiffness matrices that arise in the context of isogeometric analysis for the numerical solution of classical second order elliptic problems motivated by the applicative interest in the fast solution of the related linear systems we are looking for a spectral characterization of the involved matrices in particular we investigate non singularity conditioning extremal behavior spectral distribution in the weyl sense as well as clustering of the eigenvalues to a certain compact subset of mathbb c c all the analysis is related to the notion of symbol in the toeplitz setting and is carried out both for the cases of 1d and 2d problems

stability analysis and numerical simulation of 1 d and 2 d radial flow towards an oil well abstract the radial flow of oil towards a well in one and two dimensions is modeled by a family of finite difference schemes this family depends on one parameter 0 1 the stability of the proposed schemes is analyzed applying the matrix method which takes into account boundary conditions particularly in the 2 d case an almost pentadiagonal matrix is obtained choosing an appropriate order of equations and unknowns we prove that this matrix may be symmetrized by a similarity transformation therefore studying bounds for the corresponding eigenvalues unconditional stability is found for 1 2 and stability restrictions are established for 1 2 numerical simulations are presented using the bsor block successive over relaxation method to solve the resulting system of linear equations the finite difference solution has perfectly reproduced the analytical solution of a simplified 1 d model

coded diversity on block fading channels this paper considers coded diversity schemes over block fading rician channels using random coding techniques two random coding upper bounds on the error probability of block codes are derived a new bound and a simpler but looser bound assuming binary input distribution also a new lower bound for any block code is derived using the strong converse to channel coding theorem the lower bound shows that the new random coding upper bound is quite tight furthermore it is shown that the maximum achievable diversity order in a block fading channel with finite interleaving depends not only on the number of subchannels l but also on the code rate r and that the performance can only marginally be improved by increasing the block length of the code the random coding upper bound and the lower bound are shown to converge to the capacity outage for large channel block lengths n demonstrating that the capacity outage can be used for estimating the error probability of coded diversity schemes

an adaptive multigrid scheme for bose einstein condensates in a periodic potential we present a novel multigrid continuation method for treating parameter dependent problems the proposed algorithm which can be flexibly implemented is a generalization of the two grid discretization schemes c s chien b w jeng a two grid discretization scheme for semilinear elliptic eigenvalue problems siam j sci comput 27 2006 1287 1304 that is approximating points on a solution curve do not necessarily lie on the same fine grid we apply the algorithm to compute energy levels and superfluid densities of bose einstein condensates bec in a periodic potential both positive and negative scattering lengths are considered in our numerical experiments for positive scattering length if the chemical potential is large enough and the domain is properly chosen the results show that the number of peaks of the first few energy states of the 2d bec in a periodic potential depends on the wave number of the periodic potential moreover for bright solitons the number of peaks of the ground state solutions is 1d 1 2 and 1d 2 where the periodic potential is expressed in terms of the sine or the cosine functions respectively however these formulae do not hold if the scattering length is negative the numerical study is extended to the two component 1d and 2d bec in a periodic potential

global stability of an sveir epidemic model with ages of vaccination and latency the vaccination period i e the time period retaining acquired immunity following vaccination and the latent period are two important factors affecting disease dynamics classical compartmental disease models unrealistically assume that these periods are exponentially distributed in this paper these two ages are assumed to have arbitrary distributions that are represented by age specific rates leaving the vaccinated and the exposed classes resulting in an sveir model with population dynamics we investigate the global behavior of this model and derive its basic reproduction number the basic reproduction number completely determines the global dynamics of the model i e the disease free equilibrium is globally asymptotically stable and the disease always dies out when the basic reproduction number is less than unity whereas when the basic reproduction number is larger than unity there exists a unique endemic equilibrium which is globally asymptotically stable and the disease persists at this endemic equilibrium if it initially exists the contributions of the vaccine wane rate to the basic reproduction number and the level of the endemic equilibrium are displayed

reliability output decoding of tail biting convolutional codes we present extensions to raghavan and baum s reliability output viterbi algorithm rova to accommodate tail biting convolutional codes these tail biting reliability output algorithms compute the exact word error probability of the decoded codeword after first calculating the posterior probability of the decoded tail biting codeword s starting state one approach employs a state estimation algorithm that selects the maximum a posteriori state based on the posterior distribution of the starting states another approach is an approximation to the exact tail biting rova that estimates the word error probability a comparison of the computational complexity of each approach is discussed in detail the presented reliability output algorithms apply to both feedforward and feedback tail biting convolutional encoders these tail biting reliability output algorithms are suitable for use in reliability based retransmission schemes with short blocklengths in which terminated convolutional codes would introduce rate loss

a low computational cost numerical method for solving mixed diffusion problems in this paper a discrete eigenfunctions method for constructing numerical solutions of mixed diffusion problem with space varying properties and source term is developed after discretization instead of solving algebraically the discretized problem we propose a discrete eigenfunctions method which reduces the computational cost of standard finite difference methods