We propose a novel tree-like curvilinear structure reconstruction algorithm based on supervised learning and graph theory. In this work we analyze image patches to obtain the local major orientations and the rankings that correspond to the curvilinear structure. To extract local curvilinear features, we compute oriented gradient information using steerable filters. We then employ Structured Sup...

In this paper, we present an approach for recovering a topological map of the environment using only detection events from a deployed sensor network. Unlike other solutions to this problem, our technique operates on timestamp free observational data; i.e. no timing information is exploited by our algorithm except the ordering. We first give a theoretical analysis of this version of the problem,...

The purpose of this paper is to present a polynomial time algorithm which determines the lot sizes for purchase component in Material Requirement Planning (MRP) environments with deterministic time-phased demand with zero lead time. In this model, backlog is not permitted, the unit purchasing price is based on the all-units discount system and resale of the excess units is possible at the order...

The ordering dynamics of the Higgs field is studied, using techniques inspired by the study of phase ordering in condensed matter physics, as a first step to understanding the evolution of cosmic structure through the formation of topological defects in the early universe. The common feature of these different physical processes is scaling. A fully analytical approximate scheme − the linear-gau...

Topological optimization is a type of structural that provides conceptual design for lighter structures. The aim this method to maximize system performance given set loads, boundary conditions, and constraints. This based on element analysis finished assembly. lightweight robot key point since the weight directly proportional load capacity its motor power. iterated in loop until function conver...