53 resultados para Circular shortest path

em Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho"


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Pós-graduação em Matemática - IBILCE

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Pós-graduação em Matemática - IBILCE

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Pós-graduação em Agronomia (Energia na Agricultura) - FCA

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This paper considers the multi-plant lot sizing problem. Each item can be produced in any plant and it is possible to meet the demand of a particular plant with production from one (or several) other plants, in this case, incurs a transfer cost. The objective is todevelop strong formulations for this problem. Reformulations that based on the shortest path problem and facility location problem are investigated. Finally, some computational results are presented comparing all the proposed formulations.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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The human cyclin-dependent kinase 9 (CDK9) protein was expressed in E coli BL21 using the pET23a vector at 30 degrees C. Several milligrams of protein were purified from soluble fraction using ionic exchange and ATP-affinity chromatography. The structural quality of recombinant CDK9 and the estimation of its secondary structure were obtained by circular dichroism. Structural models of CDK9 presented 26% of helices in agreement with the spectra by circular dichroism analysis. This is the first report on human CDK9 expression in Escherichia coli and structure analysis and provides the first step for the development of CDK9 inhibitors. (c) 2006 Elsevier B.V. All rights reserved.

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Nowadays, fraud detection is important to avoid nontechnical energy losses. Various electric companies around the world have been faced with such losses, mainly from industrial and commercial consumers. This problem has traditionally been dealt with using artificial intelligence techniques, although their use can result in difficulties such as a high computational burden in the training phase and problems with parameter optimization. A recently-developed pattern recognition technique called optimum-path forest (OPF), however, has been shown to be superior to state-of-the-art artificial intelligence techniques. In this paper, we proposed to use OPF for nontechnical losses detection, as well as to apply its learning and pruning algorithms to this purpose. Comparisons against neural networks and other techniques demonstrated the robustness of the OPF with respect to commercial losses automatic identification.

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