variable neighborhood tabu search and its application to the median cycle problem abstract the variable neighborhood tabu search consists of a constructive phase and a series of local searches that use tabu tools when the local search stops at a nontabu local minimum a shake procedure starts a new local search the local searches and the shake procedure are based on a series of standard moves the local search consists of applying the best possible move until no such move exists the shake procedure consists of applying a number of random moves since the shake could provide an infeasible solution the local search considers as possible moves those providing a feasible solution or reducing the infeasibility a location allocation problem consists of selecting the location for some facilities and the allocation of the users to them two functions to be minimized are considered the length of the solution as a measure of the set of locations and the total cost of the allocations the standard moves for these problems are the add drop and add drop moves the heuristic procedure is tested on the median cycle problem

group gradings on associative algebras abstract let r g g rg be a g graded ring we describe all types of gradings on r if g is torsion free and r is artinian semisimple if r is a matrix algebra over an algebraically closed field f then we give a description of all g gradings on r provided that g is an abelian group in the case of an abelian group g we also classify all finite dimensional graded simple algebras and finite dimensional graded division algebras over an algebraically closed field of characteristic zero

color texture classification by integrative co occurrence matrices abstract integrative co occurrence matrices are introduced as novel features for color texture classification the extended co occurrence notation allows the comparison between integrative and parallel color texture concepts the information profit of the new matrices is shown quantitatively using the kolmogorov distance and by extensive classification experiments on two datasets applying them to the rgb and the luv color space the combined color and intensity textures are studied and the existence of intensity independent pure color patterns is demonstrated the results are compared with two baselines gray scale texture analysis and color histogram analysis the novel features improve the classification results up to 20 and 32 for the first and second baseline respectively

a new feature extractor invariant to intensity rotation and scaling of color images this paper proposes a new method for extracting the invariant features of an image based on the concept of principal component analysis and a competitive learning algorithm the proposed algorithm can be applied to binary gray level or colored texture images with a size greater than 256x256 pixels in addition to translation scaling and rotation invariant extraction the extraction of a feature invariant to color intensity can be implemented by using this method in our experiment the proposed method shows the capability to differentiate images having the same shape but different colored textures the experimental results report the effectiveness of this technique and its performance as measured by recognition accuracy rate and computational time these results are also compared with those obtained by classical techniques

quasialgebra structure of the octonions abstract we show that the octonions are a twisting of the group algebra of z 2 z 2 z 2 in the quasitensor category of representations of a quasi hopf algebra associated to a group 3 cocycle in particular we show that they are quasialgebras associative up to a 3 cocycle isomorphism we show that one may make general constructions for quasialgebras exactly along the lines of the associative theory including quasilinear algebra representation theory and an automorphism quasi hopf algebra we study the algebraic properties of quasialgebras of the type which includes the octonions further examples include the higher 2n onion cayley algebras and examples associated to hadamard matrices

on the structure of graded commutative algebras abstract consider a a commutative algebra graded by means of an abelian group g we show that under the hypothesis a 0 g a g a g where g g a g 0 the algebra a is of the form a j i j with any i j a well described graded ideal of a satisfying i j i k 0 if j k under certain conditions the simplicity of a is characterized and it is shown that a is the direct sum of the family of its minimal graded ideals each one being a simple graded commutative algebra

meals a multiobjective evolutionary algorithm with local search for solving the bi objective ring star problem abstract in this paper we develop a hybrid metaheuristic for approaching the pareto front of the bi objective ring star problem this problem consists of finding a simple cycle ring through a subset of nodes of a network the aim is to minimize both the cost of connecting the nodes in the ring and the cost of allocating the nodes not in the ring to nodes in the ring the algorithm preserves the general characteristics of a multiobjective evolutionary algorithm and embeds a local search procedure which deals with multiple objectives the encoding scheme utilized leads to solving a traveling salesman problem in order to compute the ring associated with the chromosome this allows the algorithm to implicitly discard feasible solutions which are not efficient the algorithm also includes an ad hoc initial population construction which contributes to diversification extensive computational experiments using benchmark problems show the performance of the algorithm and reveal the noteworthy contribution of the local search procedure

genetic local search for multi objective combinatorial optimization abstract the paper presents a new genetic local search gls algorithm for multi objective combinatorial optimization moco the goal of the algorithm is to generate in a short time a set of approximately efficient solutions that will allow the decision maker to choose a good compromise solution in each iteration the algorithm draws at random a utility function and constructs a temporary population composed of a number of best solutions among the prior generated solutions then a pair of solutions selected at random from the temporary population is recombined local search procedure is applied to each offspring results of the presented experiment indicate that the algorithm outperforms other multi objective methods based on gls and a pareto ranking based multi objective genetic algorithm ga on travelling salesperson problem tsp

gradings on symmetric composition algebras abstract the group gradings on the symmetric composition algebras over arbitrary fields are classified applications of this result to gradings on the exceptional simple lie algebras are considered too

a series of algebras generalizing the octonions and hurwitz radon identity we study non associative twisted group algebras over mathbb z 2 n with cubic twisting functions we construct a series of algebras that extend the classical algebra of octonions in the same way as the clifford algebras extend the algebra of quaternions we study their properties give several equivalent definitions and prove their uniqueness within some natural assumptions we then prove a simplicity criterion

simple graded commutative algebras we study the notion of graded commutative algebra for an arbitrary abelian group the main examples are the clifford algebras already treated in h albuquerque and s majid 2002 2 we prove that the clifford algebras are the only simple finite dimensional associative graded commutative algebras over r or c our approach also leads to non associative graded commutative algebras extending the clifford algebras

fast and accurate global motion estimation algorithm using pixel subsampling global motion generally describes the motion of a camera although it may comprise motions of large objects global motions are often modeled by parametric transformations of two dimensional images the process of estimating the motions parameters is called global motion estimation gme gme is widely employed in many applications such as video coding image stabilization and super resolution to estimate global motion parameters the levenburg marquardt algorithm lma is typically used to minimize an objective function iteratively since the region of support for the global motion representation consists of the entire image frame the minimization process tends to be very expensive computationally by involving all the pixels within an image frame in order to significantly reduce the computational complexity of the lma we proposed to select only a small subset of the pixels for estimating the motion parameters based on several subsampling patterns and their combinations simulation results demonstrated that the proposed method could speed up the conventional gme approach by over ten times with only a very slight loss less than 0 1db in estimation accuracy the proposed method was also found to outperform several state of the art fast gme methods in terms of the speed accuracy tradeoffs

the category of z2n supermanifolds in physics and in mathematics z2n gradings n 2 appear in various fields the corresponding sign rule is determined by the scalar product of the involved z2n degrees the z2n supergeometry exhibits challenging differences with the classical one nonzero degree even coordinates are not nilpotent and even respectively odd coordinates do not necessarily commute respectively anticommute pairwise in this article we develop the foundations of the theory we define z2n supermanifolds and provide examples in the ringed space and coordinate settings we thus show that formal series are the appropriate substitute for nilpotency moreover the class of z2 supermanifolds is closed with respect to the tangent and cotangent functors we explain that any n fold vector bundle has a canonical superization to a z2n supermanifold and prove that the fundamental theorem describing supermorphisms in terms of coordinates can be extended to the z2n context

gradings on octonions abstract all the different ways of grading any cayley dickson or octonion algebra as well as the associated central simple malcev algebras will be obtained

translation invariants of zernike moments moment functions defined using a polar coordinate representation of the image space such as radial moments and zernike moments are used in several recognition tasks requiring rotation invariance however this coordinate representation does not easily yield translation invariant functions which are also widely sought after in pattern recognition applications this paper presents a mathematical framework for the derivation of translation invariants of radial moments defined in polar form using a direct application of this framework translation invariant functions of zernike moments are derived algebraically from the corresponding central moments both derived functions are developed for non symmetrical as well as symmetrical images they mitigate the zero value obtained for odd order moments of the symmetrical images vision applications generally resort to image normalization to achieve translation invariance the proposed method eliminates this requirement by providing a translation invariance property in a zernike feature set the performance of the derived invariant sets is experimentally confirmed using a set of binary latin and english characters

efficient local transformation estimation using lie operators conventional translation only motion estimation algorithms cannot cope with transformations of objects such as scaling rotations and deformations motion models characterizing non translation motions are thus beneficial as they offer more accurate motion estimation and compensation in this paper we introduce low complexity transformation estimation methods with four motion models based on lie operators which are linear operators that have found applications in optical character recognitions we show that individual lie operators are capable of capturing small degrees of object transformations we propose an efficient local transformation estimation algorithm in order to further improve the accuracy of the translation only estimation by integrating all four motion models simulations with an mpeg 2 video codec on two video sequences show that the proposed transformation estimation approach can noticeably improve the motion compensation performance of the translation only method by achieving higher psnr peak signal to noise ratio values for the predicted frames with only a small fraction of the complexity required by the translation motion search

fuzzy relation equations for coding decoding processes of images and videos we adopt fuzzy relation equations with continuous triangular norms for compression decompression processes of grey images colour images in the rgb space and frames of videos by comparing the results of the reconstructed images with standard methods like jpeg and mpeg 4 any image is subdivided in blocks and each block is coded decoded using arbitrary fuzzy sets as coders in the fuzzy equations we evaluate the peak signal to noise ratio psnr on the decompressed images for several values of the compression rates as measure of the quality of images and frames reconstructed the original frames of a video are classified in intra frames and predictive frames by using a similarity measure based on the well known lukasiewicz t norm

an effective implementation of the lin kernighan traveling salesman heuristic abstract this paper describes an implementation of the lin kernighan heuristic one of the most successful methods for generating optimal or near optimal solutions for the symmetric traveling salesman problem tsp computational tests show that the implementation is highly effective it has found optimal solutions for all solved problem instances we have been able to obtain including a 13 509 city problem the largest non trivial problem instance solved to optimality today

an efficient evolutionary algorithm for the ring star problem abstract this paper addresses the ring star problem rsp the goal is to locate a cycle through a subset of nodes of a network aiming to minimize the sum of the cost of installing facilities on the nodes on the cycle the cost of connecting them and the cost of assigning the nodes not on the cycle to their closest node on the cycle a fast and efficient evolutionary algorithm is developed which is based on a new formulation of the rsp as a bilevel programming problem with one leader and two independent followers the leader decides which nodes to include in the ring one follower decides about the connections of the cycle and the other follower decides about the assignment of the nodes not on the cycle the bilevel approach leads to a new form of chromosome encoding in which genes are associated to values of the upper level variables the quality of each chromosome is evaluated by its fitness by means of the objective function of the rsp hence in order to compute the value of the lower level variables two optimization problems are solved for each chromosome the computational results show the efficiency of the algorithm in terms of the quality of the solutions yielded and the computing time a study to select the best configuration of the algorithm is presented the algorithm is tested on a set of benchmark problems providing very accurate solutions within short computing times moreover for one of the problems a new best solution is found

efficient robust and fast global motion estimation for video coding in this paper we propose an efficient robust and fast method for the estimation of global motion from image sequences the method is generic in that it can accommodate various global motion models from a simple translation to an eight parameter perspective model the algorithm is hierarchical and consists of three stages in the first stage a low pass image pyramid is built then an initial translation is estimated with full pixel precision at the top of the pyramid using a modified n step search matching in the third stage a gradient descent is executed at each level of the pyramid starting from the initial translation at the coarsest level due to the coarse initial estimation and the hierarchical implementation the method is very fast to increase robustness to outliers we replace the usual formulation based on a quadratic error criterion with a truncated quadratic function we have applied the algorithm to various test sequences within an mpeg 4 coding system from the experimental results we conclude that global motion estimation provides significant performance gains for video material with camera zoom and or pan the gains result from a reduced prediction error and a more compact representation of motion we also conclude that the robust error criterion can introduce additional performance gains without increasing computational complexity