The multistart clustering global optimization method called GLOBAL has been introduced in the 1980s for bound constrained global optimization problems with black-box type objective function. Since then the technological environment has been changed much. The present paper describes shortly the revisions and updates made on the involved algorithms to utilize the novel technologies, and to improv...

Abstract Notwithstanding the political origins of constitutionalism in west and leading role played by United States creation new global order after WWII, this origin constitutional project does not undermine claims to universality underlying it. After laying out a basic account some core theoretical premises guiding constitutionalism, article presents series genealogical reflections, which is ...

Previously, researchers have used circular contours with sinusoidal deformations of the radius (radial frequency [RF] patterns) to investigate the underlying processing involved in simple shape perception. On finding that the rapid improvement in sensitivity to deformation as more cycles of modulation were added was greater than expected from probability summation across sets of local independe...

Communication constraints dictated by hardware often require a multi-robot system to make decisions and take actions locally. Unfortunately, local knowledge may impose limits that ultimately impede global optimality in a decentralized optimization problem. This paper enhances a recent anytime optimal assignment method based on a task-swap mechanism, redesigning the algorithm to address task all...

Graphical Models bring together two different mathematical areas: graph theory and probability theory. Recent years have witnessed an increase in the significance of the role played by Graphical Models in solving several machine learning problems. Graphical Models can be either directed or undirected. Undirected Graphical Models are also called Bayesian networks. The manual construction of Baye...