continuous dependence on initial time and spatial geometry in generalized heat conduction abstract in this paper we consider two different initial boundary value problems in generalized heat conduction we first establish continuous dependence on the initial time geometry in an exterior region for solutions of one well studied model system we then derive inequalities which imply continuous dependence on the spatial geometry in a bounded region for the same problem with an added dissipation term

symmetry aware graph matching visual symmetry encodes middle to high level geometric information and plays an important role in many computer vision applications not much effort however has been devoted to utilize symmetry information for graph matching in this paper we propose a new framework for symmetry aware graph matching in the context of image matching in the framework we first define symmetry matrices to characterize the geometric symmetry relation among image features and then develop two methods to discover such symmetry after that we design general strategies to boost graph matching algorithms with symmetry constraints and apply these strategies to several state of the art algorithms for evaluation the proposed symmetry aware graph matching algorithms are first applied to two datasets involving clear symmetry patterns a recently proposed architecture image set and a dental panoramic radiograph collection the results clearly demonstrate the benefits of using symmetry information an experiment is also conducted on a dataset where symmetry is less obvious the results show that our strategies still achieve better of similar performance compared with state of the arts highlightsit is the first time symmetry constraints that are introduced into graph matching the symmetry aware graph matching improves the matching performance a new dataset with annotation for evaluating graph matching is constructed

global attractors for the extensible thermoelastic beam system abstract this work is focused on the dissipative system t t u x x x x u x x x u l 2 0 1 2 x x u f t x x x x t u g describing the dynamics of an extensible thermoelastic beam where the dissipation is entirely contributed by the second equation ruling the evolution of under natural boundary conditions we prove the existence of bounded absorbing sets when the external sources f and g are time independent the related semigroup of solutions is shown to possess the global attractor of optimal regularity for all parameters r the same result holds true when the first equation is replaced by t t u x x t t u x x x x u x x x u l 2 0 1 2 x x u f with 0 in both cases the solutions on the attractor are strong solutions

partial regularity of a generalized solution to the navier stokes equations in exterior domain in this note we prove two regularity theorems for solutions to the navier stokes equations of an i b v p in exterior domains namely we prove that the sets of the singular points of a solution if not empty has at most 1 hausdorff measureh1 s 0 moreover the sets is enclosed in a sphere of rayr for anyt 0 these results are obtained as corollaries to the partial regularity results furnished in 2

a graduated assignment algorithm for graph matching a graduated assignment algorithm for graph matching is presented which is fast and accurate even in the presence of high noise by combining graduated nonconvexity two way assignment constraints and sparsity large improvements in accuracy and speed are achieved its low order computational complexity o lm where l and m are the number of links in the two graphs and robustness in the presence of noise offer advantages over traditional combinatorial approaches the algorithm not restricted to any special class of graph is applied to subgraph isomorphism weighted graph matching and attributed relational graph matching to illustrate the performance of the algorithm attributed relational graphs derived from objects are matched then results from twenty five thousand experiments conducted on 100 mode random graphs of varying types graphs with only zero one links weighted graphs and graphs with node attributes and multiple link types are reported no comparable results have been reported by any other graph matching algorithm before in the research literature twenty five hundred control experiments are conducted using a relaxation labeling algorithm and large improvements in accuracy are demonstrated

monotonic decreasing and asymptotic behavior of the kinetic energy for weak solutions of the navier stokes equations in exterior domains existence of weak solutions of the three dimensional navier stokes problem was first proved by j leray in the case of the cauchy problem cf leray 1934 as is well known these solutions are important in that they are the only solutions which so far are known to exist for all times without restriction on the data unfortunately however the question of whether they are classical in an ordinary sense is still open even though partial conclusions regarding regularity are avilable leray 1934 scheffer 1976 1980 caffarelli kohn nirenberg 1982 subsequently e hopf 1951 using a different technique constructed weak solutions for a general initial boundary value problem however hopf s solution even for the cauchy problem has weaker properties than leray s solution among others we refer to the energy inequality for the velocity field u x t i e ntimits mega u 2 x t dx ntimits mega u 2 x s sx eqq 2ntimits s t ntimits mega abla u abla udxdau i for s 0 for almost all s 0 and for all t s

some global dynamical properties of the kuramoto sivashinsky equations nonlinear stability and attractors abstract the kuramoto sivashinsky equations model pattern formations on unstable flame fronts and thin hydrodynamic films they are characterized by the coexistence of coherent spatial structures with temporal chaos we investigate some global dynamical properties including nonlinear stability we demonstrate their low modal behavior in terms of determining modes and that the fractal dimension of all attractors is bounded by a universal constant times l 13 8 where l is a dimensionless pattern cell size in the one dimensional case such equations are indeed a paradigm of low dimensional behavior for infinite dimensional systems

globally consistent correspondence of multiple feature sets using proximal gauss seidel relaxation feature correspondence between two or more images is a fundamental problem towards many computer vision applications the case of correspondence between two images has been intensively studied however few works so far have been concerned with multi image correspondence in this paper we address the problem of establishing a globally consistent correspondence among multiple more than two feature sets given the pairwise feature affinity information our main contribution is to propose a novel optimization framework for solving this problem based on the so called proximal gauss seidel relaxation pgsr the proposed method is distinguished from previous works mainly in three aspects 1 it is more robust to noise and outliers 2 its solution is based on convex relaxation and the principled pgsr method which in general has convergence guarantee 3 the scale of the problem in our method is linear with respect to the number of feature sets making it computationally practical to be used in real world applications experimental results both synthetic and real image datasets have demonstrated the effectiveness and superiority of the proposed method highlightswe study finding globally consistent correspondence from multiple feature sets a novel method is proposed based on proximal gauss seidel relaxation pgsr pgsr is more robust to noise outliers and deformation than competitors the optimization has general convergence guarantee the scale of our formulation is linear w r t the number of feature sets

convex and semi nonnegative matrix factorizations we present several new variations on the theme of nonnegative matrix factorization nmf considering factorizations of the form x fgt we focus on algorithms in which g is restricted to containing nonnegative entries but allowing the data matrix x to have mixed signs thus extending the applicable range of nmf methods we also consider algorithms in which the basis vectors of f are constrained to be convex combinations of the data points this is used for a kernel extension of nmf we provide algorithms for computing these new factorizations and we provide supporting theoretical analysis we also analyze the relationships between our algorithms and clustering algorithms and consider the implications for sparseness of solutions finally we present experimental results that explore the properties of these new methods

exact solution approaches for bilevel lot sizing abstract in this paper we propose exact solution methods for a bilevel uncapacitated lot sizing problem with backlogs this is an extension of the classical uncapacitated lot sizing problem with backlogs in which two autonomous and self interested decision makers constitute a two echelon supply chain the leader buys items from the follower in order to meet external demand at lowest cost the follower also tries to minimize its costs both parties may backlog we study the leader s problem i e how to determine supply requests over time to minimize its costs in view of the possible actions of the follower we develop two mixed integer linear programming reformulations as well as cutting planes to cut off feasible but suboptimal solutions we compare the reformulations on a series of benchmark instances

fuzzy programming approach to multi objective stochastic programming problems when b i s follow joint normal distribution abstract in this paper a multi objective chance constrained programming problem has been considered when bi s are normal random variables and the constraints have a joint probability distribution the probabilistic problem is converted into an equivalent deterministic non linear programming problem then the fuzzy programming technique has been applied to obtain a compromise solution a numerical example is also presented to illustrate the methodology

a uniqueness theorem for viscous fluid motions in exterior domains as is known one of the most interesting still open questions in the dynamics of viscous incompressible flows governed by the navier stokes equations is that of the uniqueness of three dimensional motions an early answer to this problem is found in the paper 5 of e fo subsequently the uniqueness question acquired new importance when it was recognized by j leray 18 that when formulated in a suitable class it is tightly linked with that of the existence of global in time and regular solutions to the navier stokes equations el also 17 22 23 the above class is called the hopf class which consists of those weak solutions satisfying suitable summability conditions along with the energy inequality in particular they and their first spatial derivatives belong to the lebesgue space l2 2 q is the domain of motion however it was also recognized by j kamp de f riet that in general an existence and uniqueness theory in l2 classes is not well suited to studying homogeneous turbulence 16 when q is unbounded motivated by these and other considerations d graffi in a remarkable paper of 1960 13 proved uniqueness for classical solutions in an arbitrary smooth unbounded domain without assuming that the velocity field v tends to a limit at infinity rather he required v and vv only bounded in space and time however he needed suitable assumptions on the behavior of the pressure p at infinity this type of problem has been reconsidered by several authors who improved graffi s theorem by reducing the assumptions on both v and p but who still required that the pressure tends to a limit po suitably at great distances 2 4 6 12 21 26 actually it is worth remarking that one of the main goals of papers 3 4 8 21 was just to avoid or at least to weaken as far as possible the hypothesis about p po for such an assumption is always an undesired feature for flows of incompressible fluids this kind of results which hold for

local higher integrability for unsteady motion equations of generalized newtonian fluids abstract in this paper we show local higher integrability of the gradient of weak solutions for unsteady motions of generalized newtonian fluids including electrorheological fluids under the restriction p z 3 n 2 n 2 moreover this is a new result even for corresponding stokes setting or a system with p structure depending on the symmetric gradient under the restriction p z 2 n n 2

high regularity of the solution to the singular elliptic p laplacian system abstract we study the regularity properties of solutions to the non homogeneous singular p x laplacian system in a bounded domain of r n under suitable restrictions on the range of p x we construct a w 2 r solution with r n that implies the holder continuity of the gradient moreover assuming just p x 1 2 we prove that the second derivatives belong to l 2

some backward uniqueness results soit 7b u un operateur non borne lineaire ou non lineaire sur un espace de hilbert h tel que 7b u 0 0 soit une fonction solution de l equation d evolution d dt 7b u 0 et telle que t 0 pour un t 0 on etudie la propriete d unicite retrograde sur 0 t pour des inegalites d t dt a t t h n t t d a 1 2 t ou a t t 0 est une famille d operateurs lineaires non bornes autoadjoint sur h et u l 2 0 t

exponential decay of solutions of damped nonlinear hyperbolic equations on considere le comportement asymptotique des solutions de certaines equations hyperboliques non lineaires a amortissement lineaire

lagrangian relaxation graph matching abstract graph matching is a fundamental problem in computer vision area graph matching problem that incorporates pair wise constraints can be formulated as an integer quadratic programming iqp problem with affine mapping constraint since it is known to be np hard approximate relaxation methods are usually required to find approximate solutions in this paper we present a new effective graph matching relaxation method called lagrangian relaxation graph matching lrgm which aims to generate a relaxation model by incorporating the affine mapping constraint into the matching objective optimization there are three main benefits of the proposed lrgm method 1 the nonnegative affine mapping constraint encoding one to one mapping is naturally incorporated in lrgm relaxation via lagrangian regularization 2 by further adding a l 1 norm constraint lrgm can generate a sparse solution empirically and thus returns a desired discrete solution for original iqp matching problem 3 an effective update algorithm is derived to solve the proposed lrgm model theoretically the converged solution can be proven to be karush kuhn tucker kkt optimal experimental results on both synthetic data and real world image datasets show the effectiveness and benefits of the proposed lrgm method

on the linear problem of swelling porous elastic soils in this paper we consider the linear theory of swelling porous elastic soils the formulation belongs to the theory of mixtures for porous elastic solids filled with fluid and gas it proposes some new mathematical difficulties logarithmic convexity and or the lagrange identity method is used in the case of fluid and gas saturation continuous results dependent on initial conditions and supply terms are obtained in the general case spatial decay estimates are also obtained by means of comparison arguments this last result is only valid when suitable conditions on the viscosity coefficients are satisfied

extinction and positivity for the evolution p laplacian equation in rn abstract the aim of this paper is to discuss extinction and positivity for the solution of the initial boundary value problem of evolution p laplacian equation it is proved that the weak solution will be extincted for 1 p 2 and will be positive for p 2 for large t

fast matching of large point sets under occlusions the problem of isometric point pattern matching can be modeled as inference in small tree width graphical models whose embeddings in the plane are said to be globally rigid although such graphical models lead to efficient and exact solutions they cannot generally handle occlusions as even a single missing point may break the rigidity of the graph in question in addition such models can efficiently handle point sets of only moderate size in this paper we propose a new graphical model that is not only adapted to handle occlusions but is much faster than previous approaches for solving the isometric point pattern matching problem we can match point patterns with thousands of points in a few seconds

electrorheological fluids ill posedness of uniqueness backward in time abstract it is well known that the uniqueness backward in time for smooth solutions to a linear parabolic equation is an improperly posed problem on the other hand for the p laplacian parabolic problem p 1 2 the extinction of the solution in a finite interval of time is one of the major property in this note we investigate on the extinction property in the case of an electrorheological fluid in the l 2 setting of weak solutions we are able to prove the following characterization there is extinction of a solution to p x stokes ibvp iff p x 2 n n 2 2

a multi level non linear multi objective decision making under fuzziness this paper studies a three level non linear multi objective decision making tln modm problem with linear or non linear constraints and in which the objective function at every level are non linear functions which are to be maximized this paper makes an extension work of abo sinna j operat res soc india opsearch 38 5 2001 484 495 which deal with a bi level non linear multi objective decision making problem under fuzziness the three level programming tlp problem whether from the stand point of the three planner stackelberg behavior or from the interactive organizational behavior is a very practical problem and encountered frequently in actual practice this paper proposes a three planner multi objective decision making model and solution method for solving this problem this method uses the concepts of tolerance membership function and multi objective optimization at each level to develop a fuzzy max min decision model for generating pareto optimal satisfactory solution for tln modm problem the first level decision maker fldm specifies his her objective functions and decisions with possible tolerances which are described by membership functions of fuzzy set theory then the second level decision maker sldm specifies his her objective functions and decisions in the view of the fldm with possible tolerances which are described by membership functions of fuzzy set theory finally the third level decision maker tldm uses the preference information for the fldm and sldm to solves his her problem subject to the two upper level decision makers restrictions an illustrative numerical example is given to demonstrate the obtained results

stackelberg solutions for fuzzy random two level linear programming through probability maximization with possibility this paper considers stackelberg solutions for decision making problems in hierarchical organizations under fuzzy random environments taking into account vagueness of judgments of decision makers fuzzy goals are introduced into the formulated fuzzy random two level linear programming problems on the basis of the possibility and necessity measures that each objective function fulfills the corresponding fuzzy goal together with the introduction of probability maximization criterion in stochastic programming we propose new two level fuzzy random decision making models which maximize the probabilities that the degrees of possibility and necessity are greater than or equal to certain values through the proposed models it is shown that the original two level linear programming problems with fuzzy random variables can be transformed into deterministic two level linear fractional programming problems for the transformed problems extended concepts of stackelberg solutions are defined and computational methods are also presented a numerical example is provided to illustrate the proposed methods

a fuzzy approach for bi level integer non linear programming problem abstract bi level programming a tool for modeling decentralized decisions consists of the objective of the leader at its first level and that is of the follower at the second level integer programming deals with the mathematical programming problems in which some or all the variables are to be integer this paper studies a bi level integer non linear programming problem with linear or non linear constraints and in which the non linear objective function at each level are to maximized the bi level integer non linear programming bli nlp problem can be thought as a static version of the stackelberg strategy which is used leader follower game in which a stackelberg strategy is used by the leader or the higher level decision maker hldm given the rational reaction of the follower or the lower level decision maker lldm this paper proposes a two planner integer model and a solution method for solving this problem this method uses the concept of tolerance membership function and the branch and bound technique to develop a fuzzy max min decision model for generating pareto optimal solution for this problem an illustrative numerical example is given to demonstrate the obtained results

a pocs based graph matching algorithm a novel projections onto convex sets pocs graph matching algorithm is presented two way assignment constraints are enforced without using elaborate penalty terms graduated nonconvexity or sophisticated annealing mechanisms to escape from poor local minima results indicate that the presented algorithm is robust and compares favorably to other well known algorithms

on finding compromise solutions in multicriteria problems using the fuzzy min operator abstract this paper presents an application of fuzzy approaches to the linear vectormaximum problem it shows that using the fuzzy min operator together with linear as well as special nonlinear membership functions the obtained solutions are always compromise solutions of the original multicriteria problem

attributed relational graph matching based on the nested assignment structure in this paper we propose a new arg matching scheme based on the nested assignment structure to assess the similarity between two attributed relational graphs args args are represented by nodes and edges containing unary attributes and binary relations between nodes respectively the nested assignment structure consists of inner and outer steps in the inner step to form a distance matrix combinatorial differences between every pair of nodes in two args are computed by using an assignment algorithm then in the outer step a correspondence between nodes in the two args is established by using an assignment algorithm based on the distance matrix the proposed arg matching scheme consists of three procedures as follows first in the initializing procedure the nested assignment structure is performed to generate an initial correspondence between nodes in two args next the correspondence is refined by iteratively performing the updating procedure which also utilizes the nested assignment structure until the correspondence does not change finally the verifying procedure can be performed in case that some nodes to be matched in the two args are missing from experimental results the proposed arg matching scheme shows superior matching performance and localizes target objects robustly and correctly even in severely noisy and occluded scenes

a probabilistic bi level linear multi objective programming problem to supply chain planning abstract bi level programming a tool for modeling decentralized decisions consists of the objective s of the leader at its first level and that is of the follower at the second level three level programming results when second level is itself a bi level programming by extending this idea it is possible to define multi level programs with any number of levels in most of the real life problems in mathematical programming the parameters are considered as random variables the branch of mathematical programming which deals with the theory and methods for the solution of conditional extremum problems under incomplete information about the random parameters is called stochastic programming supply chain planning problems are concerned with synchronizing and optimizing multiple activities involved in the enterprise from the start of the process such as procurement of the raw materials through a series of process operations to the end such as distribution of the final product to customers enterprise wide supply chain planning problems naturally exhibit a multi level decision network structure where for example one level may correspond to a local plant control scheduling planning problem and another level to a corresponding plant wide planning network problem such a multi level decision network structure can be mathematically represented by using multi level programming principles in this paper we consider a probabilistic bi level linear multi objective programming problem and its application in enterprise wide supply chain planning problem where 1 market demand 2 production capacity of each plant and 3 resource available to all plants for each product are random variables and the constraints may consist of joint probability distributions or not this probabilistic model is first converted into an equivalent deterministic model in each level to which fuzzy programming technique is applied to solve the multi objective nonlinear programming problem to obtain a compromise solution

a priori estimates in terms of the maximum norm for the solutions of the navier stokes equations in this paper we consider the cauchy problem for the incompressible navier stokes equations with bounded initial data and derive a priori estimates of the maximum norm of all derivatives of the solution in terms of the maximum norm of the initial velocity field for illustrative purposes we first derive corresponding a priori estimates for certain parabolic systems because of the pressure term the case of the navier stokes equations is more difficult however

dimension of the attractors associated to the ginzburg landau partial differential equation abstract we study the long time behavior of solutions to the ginzburg landau partial differential equation it is shown that a finite dimensional attractor captures all the solutions an upper bound on this dimension is given in terms of physical quantities by estimating the lyapunov exponents on the trajectories finally using the well known side band instabilities of an exact time dependent solution stokes solution we derive lower bounds on the dimension of the universal attractor moreover the lower and upper bounds agree

structural stability for the darcy equations of flow in porous media a priori bounds are derived for the darcy equations of flow in porous media when the porous body is subject to boundary conditions of newton cooling type with the aid of these a priori bounds we are able to demonstrate continuous dependence on the cooling coefficient when the boundary condition of newton cooling type is employed we further show that the solution depends continuously on a change in the equation of state employed in the body force in the darcy equation the model is allowed to change from one of boussinesq convection type to one more general and structural stability is established

a sparse nonnegative matrix factorization technique for graph matching problems graph matching problem that incorporates pairwise constraints can be cast as an integer quadratic programming iqp since it is np hard approximate methods are required in this paper a new approximate method based on nonnegative matrix factorization with sparse constraints is presented firstly the graph matching is formulated as an optimization problem with nonnegative and sparse constraints followed by an efficient algorithm to solve this constrained problem then we show the strong relationship between the sparsity of the relaxation solution and its effectiveness for graph matching based on our model a key benefit of our method is that the solution is sparse and thus can approximately impose the one to one mapping constraints in the optimization process naturally therefore our method can approximate the original iqp problem more closely than other approximate methods extensive and comparative experimental results on both synthetic and real world data demonstrate the effectiveness of our graph matching method we present a graph matching method based on nmf with sparse constraints our sparse model can incorporate the mapping constraints approximately we show the link between the sparsity of the solution and its effectiveness experimental results show the effectiveness of our graph matching method

extinction and positivity for the evolution p laplacian equation abstract the aim of this paper is to discuss the extinction and positivity for the evolution p laplacian equation formula with p 1 in particular the necessary and sufficient condition for extinction is obtained

interactive fuzzy random two level linear programming based on level sets and fractile criterion optimization in this paper assuming cooperative behavior of the decision makers two level linear programming problems under fuzzy random environments are considered by introducing a level sets of fuzzy random variables and defining an a stochastic two level linear programming problem for guaranteeing the degree of realization of the problem through a new decision making model proposed based on the fractile criterion optimization model considering fuzzy goals the a stochastic two level programming problem can be equivalently transformed into a deterministic problem interactive fuzzy programming to derive a satisfactory solution for the decision maker at the upper level in consideration of the cooperative relation between decision makers is presented an illustrative numerical example is provided to demonstrate the feasibility and efficiency of the proposed method

on gradient adaptation with unit norm constraints in this correspondence we describe gradient based adaptive algorithms within parameter spaces that are specified by w 1 where spl middot is any vector norm we provide several algorithm forms and relate them to true gradient procedures via their geometric structures we also give algorithms that mitigate an inherent numerical instability for l sub 2 norm constrained optimization tasks simulations showing the performance of the techniques for independent component analysis are provided

interactive random fuzzy two level programming through possibility based probability model this paper considers interactive decision making methods for random fuzzy two level linear programming problems assuming that the decision makers concern about the probabilities that their own objective function values are smaller than or equal to certain target values fuzzy goals of the decision makers for the probabilities are introduced then the possibility based probability model to maximize the degrees of possibility with respect to the attained probability is considered interactive fuzzy nonlinear programming to obtain a satisfactory solution for the decision maker at the upper level in consideration of the cooperative relation between decision makers is presented an illustrative numerical example demonstrates the feasibility and efficiency of the proposed method

on the existence of weak solutions for the steady baldwin lomax model and generalizations abstract in this paper we consider the steady baldwin lomax model which is a rotational model proposed to describe turbulent flows at statistical equilibrium the baldwin lomax model is specifically designed to address the problem of a turbulent motion taking place in a bounded domain with dirichlet boundary conditions at solid boundaries the main features of this model are the degeneracy of the operator at the boundary and a formulation in velocity vorticity variables the principal part of the operator is non linear and it is degenerate due to the presence as a coefficient of a power of the distance from the boundary this fact makes the existence theory naturally set in the framework of appropriate weighted sobolev spaces

an approximate solution for nonlinear backward parabolic equations we consider the backward parabolic equation ut au f t u t 0 t t u t g where a is a positive unbounded operator and f is a nonlinear function satisfying a lipschitz condition with an approximate datum g the problem is severely ill posed using the truncation method we propose a regularized solution which is the solution of a system of differential equations in finite dimensional subspaces according to some a priori assumptions on the regularity of the exact solution we obtain several explicit error estimates including an error estimate of holder type for all t 0 t an example on heat equations and numerical experiments are given

a path following algorithm for the graph matching problem we propose a convex concave programming approach for the labeled weighted graph matching problem the convex concave programming formulation is obtained by rewriting the weighted graph matching problem as a least square problem on the set of permutation matrices and relaxing it to two different optimization problems a quadratic convex and a quadratic concave optimization problem on the set of doubly stochastic matrices the concave relaxation has the same global minimum as the initial graph matching problem but the search for its global minimum is also a hard combinatorial problem we therefore construct an approximation of the concave problem solution by following a solution path of a convex concave problem obtained by linear interpolation of the convex and concave formulations starting from the convex relaxation this method allows to easily integrate the information on graph label similarities into the optimization problem and therefore perform labeled weighted graph matching the algorithm is compared with some of the best performing graph matching methods on four data sets simulated graphs qaplib retina vessel images and handwritten chinese characters in all cases the results are competitive with the state of the art

inertial manifolds and finite dimensional reduction for dissipative pdes this paper is devoted to the problem of finite dimensional reduction for parabolic partial differential equations we give a detailed exposition of the classical theory of inertial manifolds as well as various attempts to generalize it based on the so called mane projection theorems the recent counter examples showing that the underlying dynamics may in a sense be infinite dimensional if the spectral gap condition is violated as well as a discussion of the most important open problems are also included

graph matching based on spectral embedding with missing value this paper proposes an efficient algorithm for inexact graph matching based on spectral embedding with missing value we commence by building an association graph model based on initial matching algorithm then by dot product representation of graph with missing value a new embedding method co embedding where the correspondences between unmatched nodes are treated as missing data in an association graph is presented at last a new graph matching algorithm which alternates between the co embedding and point pattern matching is proposed convictive experimental results on both synthetic and real world data demonstrate the effectiveness of the proposed graph matching algorithm

strange an interactive method for multi objective linear programming under uncertainty abstract in the field of investment planning within a time horizon problems typically involve multiple objectives and basic data are uncertain in a large number of cases these decision problems can be written as linear programming problems in which time dependent uncertainties affect the coefficients and the right hand side of constraints given the possibility of defining plausible scenarios on basic data discrete sets of such coefficients are given each with its subjective probability of occurrence the corresponding structure is then characteristic for multi objective stochastic linear programming moslp in the paper an interactive procedure is described to obtain a best compromise for such a moslp problem this algorithm called strange extends the stem method to take the random aspects into account it involves in particular the concepts of stochastic programming with recourse in its interactive steps the efficiency projection techniques are used to provide the decision maker with detailed graphical information on efficient solution families as an illustration of the successive steps a didactic example is solved in some detail and the results of a case study in energy planning are given

stability and newton s law of cooling in double diffusive flow abstract we study the system of equations for flow of a viscous heat conducting fluid which has dissolved in a salt field under the approximation often employed in the fluid dynamical literature that the prandtl number be infinite we developa prioribounds and we show the solution depends continuously on changes in the newton cooling coefficient

structural graph matching using the em algorithm and singular value decomposition this paper describes an efficient algorithm for inexact graph matching the method is purely structural that is it uses only the edge or connectivity structure of the graph and does not draw on node or edge attributes we make two contributions 1 commencing from a probability distribution for matching errors we show how the problem of graph matching can be posed as maximum likelihood estimation using the apparatus of the em algorithm and 2 we cast the recovery of correspondence matches between the graph nodes in a matrix framework this allows one to efficiently recover correspondence matches using the singular value decomposition we experiment with the method on both real world and synthetic data here we demonstrate that the method offers comparable performance to more computationally demanding methods

logic optimality for multi objective optimization pareto dominance is one of the most basic concepts in multi objective optimization however it is inefficient when the number of objectives is large because in this case it leads to an unmanageable number of pareto solutions in order to solve this problem a new concept of logic dominance is defined by considering the number of improved objectives and the quantity of improvement simultaneously where probabilistic logic is applied to measure the quantity of improvement based on logic dominance the corresponding logic nondominated solution is defined as a feasible solution which is not dominated by other ones based on this new relationship and it is proved that each logic nondominated solution is also a pareto solution essentially logic dominance is an extension of pareto dominance since there are already several extensions for pareto dominance some comparisons are given in terms of numerical examples which indicates that logic dominance is more efficient as an application of logic dominance a house choice problem with five objectives is considered

on the lack of null controllability of the heat equation on the half line we consider the linear heat equation on the half line with a dirichlet boundary control we analyze the null controllability problem more precisely we study the class of initial data that may be driven to zero in finite time by means of an appropriate choice of the l2 boundary control we rewrite the system on the similarity variables that are a common tool when analyzing asymptotic problems next the control problem is reduced to a moment problem which turns out to be critical since it concerns the family of real exponentials eit j in which the usual summability condition on the inverses of the eigenvalues does not hold roughly speaking we prove that controllable data have fourier coefficients that grow exponentially for large frequencies this result is in contrast with the existing ones for bounded domains that guarantee that every initial datum belonging to a sobolev space of negative order may be driven to zero in an arbitrarily small time

equilibria with a nontrivial nodal set and the dynamics of parabolic equations on symmetric domains we consider the dirichlet problem for a class of semilinear parabolic equations on a bounded domain which is reflectionally symmetric about a hyperplane h the equations consist of a symmetric time autonomous part and a nonsymmetric perturbation which decays to zero as time approaches infinity in our first theorem we prove the asymptotic symmetry of each bounded positive solution of this asymptotically symmetric problem the novelty of this result is that the solutions considered are not assumed uniformly positive which prevents one from applying common techniques based on the method of moving hyperplanes in our second main theorem we classify the positive entire solutions of the unperturbed time autonomous problems in particular we characterize all entire solutions which are not symmetrically decreasing in the direction orthogonal to h as connecting orbits from an equilibrium with a nontrivial nodal set to another invariant set

global existence of weak solutions to 3d navier stokes ibvp with non decaying initial data in exterior domains abstract we consider the navier stokes initial boundary value problem in 3d exterior domains with non decaying initial data we investigate the existence of weak solutions defined for all t 0 for large non decaying initial data to achieve the result we extend the half space technique developed by maremonti and shimizu 2018 26 to the case of an exterior domain

long time behaviour of solutions of abstract inequalities applications to thermo hydraulic and magnetohydrodynamic equations abstract we study some scalar inequalities of parabolic type and we give the leading term of an asymptotic expansion as t for solutions of thermo hydraulic equations without external excitation a phenomenon of resonance is pointed out we also treat m h d equations and navier stokes equations on a riemannian manifold

some mathematical questions related to the mhd equations some questions relating to the large time behavior of the solutions of mhd equations for a viscous incompressible resistive fluid are investigated the physical system is briefly described and the functional setting of the equations a flow in a bounded domain or in whole space with a space periodicity property in all directions the main existence and uniqueness results for weak and strong solutions of the mhd equations are recalled regularity properties and bounds on the solutions to the equations which are valid for all time are established and the concept of functional invariant sets is introduced which is contained in the space of smooth functions if the data are sufficiently regular the squeezing property of the trajectories are stated and it is shown that any functional invariant set for the mhd equations and in particular any attractor has a finite haussdorf dimension the flow is found to be totally determined for large dimensions by a finite number of parameters 26 references

the uniqueness of nondecaying solutions for the navier stokes equations the uniqueness of solutions of the navier stokes equations in the whole space is established when the velocity field is bounded and the pressure field is a bmo valued locally integrable in time function for bounded initial data here the velocity field may not decay at space infinity although there are a few results concerning uniqueness without the decay assumption our result is new and applicable for solutions constructed by solving the integral equations

an algorithm based on particle swarm optimization for multiobjective bilevel linear problems improved mopso for multiobjective at the upper level bilevel linear problems a hybrid scheme for the selection of the global best particles is proposed an adaptive mutation is also introduced the incorporation of these mechanisms led to significantly better results this paper presents an improved multiple objective particle swarm optimization mopso algorithm to solve bilevel linear programming problems with multiple objective functions at the upper level the algorithm aims to produce a good approximation of the entire pareto front of the problem we have previously designed a mopso algorithm for the same class of problems in which several techniques for the global best selection were tested including a new one the algorithm revealed a good convergence towards the pareto front but the diversity of the solutions was a drawback the algorithm we propose herein uses a hybrid strategy for the global best selection and an adaptive mutation operator the incorporation of these mechanisms led to an improved algorithm which also showed better overall performance than considering alternative options usually employed in mopso algorithms the algorithm and computational results are presented

spatial decay estimates and continuous dependence on modelling for an equation from dynamo theory this paper studies the improperly posed backward in time problem in addition to the well posed forward in time problem for a non symmetric partial differential equation which describes the behaviour of the toroidal part of the magnetic field in a dynamo problem we first show that solutions in an unbounded cylinder decay exponentially in space provided that for the backward in time problem a dirichlet integral is bounded and provided the prescribed velocity field satisfies particular bounds for the forward in time problem several of these constraints are relaxed it is next shown that the solution to the same problem on a bounded spatial domain depends holder continuously on changes in the prescribed velocity field