Solving large 0–1 multidimensional knapsack problems by a new simplified binary artificial fish swarm algorithm

The artificial fish swarm algorithm has recently been emerged in continuous global optimization. It uses points of a population in space to identify the position of fish in the school. Many real-world optimization problems are described by 0-1 multidimensional knapsack problems that are NP-hard. In the last decades several exact as well as heuristic methods have been proposed for solving these problems. In this paper, a new simpli ed binary version of the artificial fish swarm algorithm is presented, where a point/ fish is represented by a binary string of 0/1 bits. Trial points are created by using crossover and mutation in the different fi sh behavior that are randomly selected by using two user de ned probability values. In order to make the points feasible the presented algorithm uses a random heuristic drop item procedure followed by an add item procedure aiming to increase the profit throughout the adding of more items in the knapsack. A cyclic reinitialization of 50% of the population, and a simple local search that allows the progress of a small percentage of points towards optimality and after that refines the best point in the population greatly improve the quality of the solutions. The presented method is tested on a set of benchmark instances and a comparison with other methods available in literature is shown. The comparison shows that the proposed method can be an alternative method for solving these problems.

A firefly dynamic penalty approach for solving engineering design problems

Firefly Algorithm is a recent swarm intelligence method, inspired by the social behavior of fireflies, based on their flashing and attraction characteristics [1, 2]. In this paper, we analyze the implementation of a dynamic penalty approach combined with the Firefly algorithm for solving constrained global optimization problems. In order to assess the applicability and performance of the proposed method, some benchmark problems from engineering design optimization are considered.

Sistema de visão robótico baseado no sensor kinect para orientação no espaço e contorno de obstáculos

Dissertação de mestrado em Engenharia Eletrónica Industrial e Computadores (área de especialização em Robótica)

Localization of MCT2 at peroxisomes is associated with malignant transformation in prostate cancer

Previous studies on monocarboxylate transporters expression in prostate cancer (PCa) have shown that monocarboxylate transporter 2 (MCT2) was clearly overexpressed in prostate malignant glands, pointing it out as a putative biomarker for PCa. However, its localization and possible role in PCa cells remained unclear. In this study, we demonstrate that MCT2 localizes mainly at peroxisomes in PCa cells and is able to take advantage of the peroxisomal transport machinery by interacting with Pex19. We have also shown an increase in MCT2 expression from non-malignant to malignant cells that was directly correlated with its peroxisomal localization. Upon analysis of the expression of several peroxisomal ß-oxidation proteins in PIN lesions and PCa cells from a large variety of human prostate samples, we suggest that MCT2 presence at peroxisomes is related to an increase in ß -oxidation levels which may be crucial for malignant transformation. Our results present novel evidence that may not only contribute to the study of PCa development mechanisms but also pinpoint novel targets for cancer therapy.

Nanotechnological approaches using curcumin and Withania somnifera: neuroprotection and antimicrobial activities

Tese de Doutoramento em Biologia de Plantas

Emotional and behavioral problems in preschoolers: risk factors and assessment Issues

Tese de Doutoramento em Psicologia Aplicada.

Localização de conteúdos: experiência de estágio na Bloomidea

Relatório de estágio de mestrado em Tradução e Comunicação Multilingue

A civic biology : presented in problems / by George William Hunter.

1914

On boundary value problems for Willmore surfaces and Hartree-Fock theory of pseudo-relativistic atoms

Magdeburg, Univ., Fak. für Mathematik, kumulative Habil.-Schr., 2011

Robust learning in safety-related domains : machine learning methods for solving safety-related application problems

Magdeburg, Univ., Fak. für Informatik, Diss., 2009