As very powerful and important tools in the study of nonlinear sciences, variational inequalities and vector optimization have attracted so much attention. Over the last decades, variational inequality and vector optimization techniques have been applied extensively in such diverse fields as biology, chemistry, economics, engineering, game theory, management science, physics, and so on. The tho...

This study examined the probability of (a) being placed in a disciplinary alternative education setting for mandatory versus discretionary reasons and (b) returning within the same year among an ethnically diverse sample (African American, Caucasian, Hispanic) of middle and high school students (N=270). Participants were compared based on ethnicity, gender, grade level, and special education st...

In this paper, we propose a novel subspace learning framework for one-class classification. The proposed presents the problem in form of graph embedding. It includes previously techniques as its special cases and provides further insight on what these actually optimize. allows to incorporate other meaningful optimization goals via preserving criterion reveals spectral solution regression-based ...

We introduce a new system of generalized vector quasiequilibrium problems which includes system of vector quasiequilibrium problems, system of vector equilibrium problems, and vector equilibrium problems, and so forth in literature as special cases.We prove the existence of solutions for this system of generalized vector quasi-equilibrium problems. Consequently, we derive some existence results...

Matching modern to historical images requires a special effort in the sense of dealing with historical photos. While there are many robust matching techniques which are vectoror binary-based that perform effectively on modern images, they are not accurate on historic photos. Photos of different landmarks were gathered for a long timeline taken in different conditions of illuminations, position,...

This paper presents a novel technique for color image compression in the transform domain. For compression of images vector quantization (VQ) technique is used and the codebook in VQ is designed using Kohonen’s Self Organizing Feature Maps (SOFM). This work exploits the special features of SOFM for generic codebook generation that enables to construct the codebook only once. Apart from spatial ...

A technique is presented which is suitable for function optimization in high-dimensional binary domains. The method allows an eecient parallel implementation and is based on the combination of genetic algorithms and reinforcement learning schemes. More speciically, a population of probability vectors is considered, each member corresponding to a reinforcement learning optimizer. Each probabilit...

A technique is presented that is suitable for function optimization in high-dimensional binary domains. The method allows an efficient parallel implementation and is based on the combination of genetic algorithms and reinforcement learning schemes. More specifically, a population of probability vectors is considered, each member corresponding to a reinforcement learning optimizer. Each probabil...