University of Maribor

About: University of Maribor is a education organization based out in Maribor, Slovenia. It is known for research contribution in the topics: Population & KEKB. The organization has 3987 authors who have published 13077 publications receiving 258339 citations. The organization is also known as: Univerza v Mariboru.

High internal phase emulsion templating--a path to hierarchically porous functional polymers.

Abstract: Recently, a series of new monomers and polymerization mechanisms has been applied to the templating of high internal phase emulsions (HIPEs) providing a route to hierarchically porous materials with a range of functionalities and applications The high degree of control over the pore size is another attractive feature of these materials Usually, the continuous phase contains monomers, the droplet phase is used to template the large, primary pores, which are interconnected by secondary pores The addition of nonpolymerizable components to the continuous phase can result in phase separation during polymerization and tertiary pores Applications include polymer supports for catalysis and synthesis, separation and filtration, cell culture media, enzyme supports, and structural and isolation applications

Optimization of cutting process by GA approach

Abstract: The paper proposes a new optimization technique based on genetic algorithms (GA) for the determination of the cutting parameters in machining operations. In metal cutting processes, cutting conditions have an influence on reducing the production cost and time and deciding the quality of a final product. This paper presents a new methodology for continual improvement of cutting conditions with GA. It performs the following: the modification of recommended cutting conditions obtained from a machining data, learning of obtained cutting conditions using neural networks and the substitution of better cutting conditions for those learned previously by a proposed GA. Experimental results show that the proposed genetic algorithm-based procedure for solving the optimization problem is both effective and efficient, and can be integrated into an intelligent manufacturing system for solving complex machining optimization problems.

Teaching–learning-based optimization algorithm for unconstrained and constrained real-parameter optimization problems

Abstract: An efficient optimization algorithm called teaching–learning-based optimization (TLBO) is proposed in this article to solve continuous unconstrained and constrained optimization problems. The proposed method is based on the effect of the influence of a teacher on the output of learners in a class. The basic philosophy of the method is explained in detail. The algorithm is tested on 25 different unconstrained benchmark functions and 35 constrained benchmark functions with different characteristics. For the constrained benchmark functions, TLBO is tested with different constraint handling techniques such as superiority of feasible solutions, self-adaptive penalty, ϵ-constraint, stochastic ranking and ensemble of constraints. The performance of the TLBO algorithm is compared with that of other optimization algorithms and the results show the better performance of the proposed algorithm.