957 resultados para novel algorithm


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No literature data above atmospheric pressure could be found for the viscosity of TOTIVI. As a consequence, the present viscosity results could only be compared upon extrapolation of the vibrating wire data to 0.1 MPa. Independent viscosity measurements were performed, at atmospheric pressure, using an Ubbelohde capillary in order to compare with the vibrating wire results, extrapolated by means of the above mentioned correlation. The two data sets agree within +/- 1%, which is commensurate with the mutual uncertainty of the experimental methods. Comparisons of the literature data obtained at atmospheric pressure with the present extrapolated vibrating-wire viscosity measurements have shown an agreement within +/- 2% for temperatures up to 339 K and within +/- 3.3% for temperatures up to 368 K. (C) 2014 Elsevier B.V. All rights reserved.

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This paper presents a biased random-key genetic algorithm for the resource constrained project scheduling problem. The chromosome representation of the problem is based on random keys. Active schedules are constructed using a priority-rule heuristic in which the priorities of the activities are defined by the genetic algorithm. A forward-backward improvement procedure is applied to all solutions. The chromosomes supplied by the genetic algorithm are adjusted to reflect the solutions obtained by the improvement procedure. The heuristic is tested on a set of standard problems taken from the literature and compared with other approaches. The computational results validate the effectiveness of the proposed algorithm.

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This paper proposes a novel method for controlling the convergence rate of a particle swarm optimization algorithm using fractional calculus (FC) concepts. The optimization is tested for several well-known functions and the relationship between the fractional order velocity and the convergence of the algorithm is observed. The FC demonstrates a potential for interpreting evolution of the algorithm and to control its convergence.

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This paper presents a methodology for applying scheduling algorithms using Monte Carlo simulation. The methodology is based on a decision support system (DSS). The proposed methodology combines a genetic algorithm with a new local search using Monte Carlo Method. The methodology is applied to the job shop scheduling problem (JSSP). The JSSP is a difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms. The methodology is tested on a set of standard instances taken from the literature and compared with others. The computation results validate the effectiveness of the proposed methodology. The DSS developed can be utilized in a common industrial or construction environment.

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This paper presents a genetic algorithm for the multimode resource-constrained project scheduling problem (MRCPSP), in which multiple execution modes are available for each of the activities of the project. The objective function is the minimization of the construction project completion time. To solve the problem, is applied a two-level genetic algorithm, which makes use of two separate levels and extend the parameterized schedule generation scheme by introducing an improvement procedure. It is evaluated the quality of the schedule and present detailed comparative computational results for the MRCPSP, which reveal that this approach is a competitive algorithm.

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Several phenomena present in electrical systems motivated the development of comprehensive models based on the theory of fractional calculus (FC). Bearing these ideas in mind, in this work are applied the FC concepts to define, and to evaluate, the electrical potential of fractional order, based in a genetic algorithm optimization scheme. The feasibility and the convergence of the proposed method are evaluated.

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This paper analyses the performance of a genetic algorithm (GA) in the synthesis of digital circuits using two novel approaches. The first concept consists in improving the static fitness function by including a discontinuity evaluation. The measure of variability in the error of the Boolean table has similarities with the function continuity issue in classical calculus. The second concept extends the static fitness by introducing a fractional-order dynamical evaluation.

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Dissertação apresentada para obtenção do Grau de Doutor em Engenharia Electrotécnica e de Computadores pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

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This paper presents a genetic algorithm for the Resource Constrained Project Scheduling Problem (RCPSP). The chromosome representation of the problem is based on random keys. The schedule is constructed using a heuristic priority rule in which the priorities of the activities are defined by the genetic algorithm. The heuristic generates parameterized active schedules. The approach was tested on a set of standard problems taken from the literature and compared with other approaches. The computational results validate the effectiveness of the proposed algorithm.

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This work addresses the signal propagation and the fractional-order dynamics during the evolution of a genetic algorithm (GA). In order to investigate the phenomena involved in the GA population evolution, the mutation is exposed to excitation perturbations during some generations and the corresponding fitness variations are evaluated. Three distinct fitness functions are used to study their influence in the GA dynamics. The input and output signals are studied revealing a fractional-order dynamic evolution, characteristic of a long-term system memory.

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A novel two-component enzyme system from Escherichia coli involving a flavorubredoxin (FlRd) and its reductase was studied in terms of spectroscopic, redox, and biochemical properties of its constituents. FlRd contains one FMN and one rubredoxin (Rd) center per monomer. To assess the role of the Rd domain, FlRd and a truncated form lacking the Rd domain (FlRd¢Rd), were characterized. FlRd contains 2.9 ( 0.5 iron atoms/subunit, whereas FlRd¢Rd contains 2.1 ( 0.6 iron atoms/subunit. While for FlRd one iron atom corresponds to the Rd center, the other two irons, also present in FlRd¢Rd, are most probably due to a di-iron site. Redox titrations of FlRd using EPR and visible spectroscopies allowed us to determine that the Rd site has a reduction potential of -140 ( 15 mV, whereas the FMN undergoes reduction via a red-semiquinone, at -140 ( 15 mV (Flox/Flsq) and -180 ( 15 mV (Flsq/Flred), at pH 7.6. The Rd site has the lowest potential ever reported for a Rd center, which may be correlated with specific amino acid substitutions close to both cysteine clusters. The gene adjacent to that encoding FlRd was found to code for an FAD-containing protein, (flavo)rubredoxin reductase (FlRd-reductase), which is capable of mediating electron transfer from NADH to DesulfoVibrio gigas Rd as well as to E. coli FlRd. Furthermore, electron donation was found to proceed through the Rd domain of FlRd as the Rd-truncated protein does not react with FlRd-reductase. In vitro, this pathway links NADH oxidation with dioxygen reduction. The possible function of this chain is discussed considering the presence of FlRd homologues in all known genomes of anaerobes and facultative aerobes.

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Extracting the semantic relatedness of terms is an important topic in several areas, including data mining, information retrieval and web recommendation. This paper presents an approach for computing the semantic relatedness of terms using the knowledge base of DBpedia — a community effort to extract structured information from Wikipedia. Several approaches to extract semantic relatedness from Wikipedia using bag-of-words vector models are already available in the literature. The research presented in this paper explores a novel approach using paths on an ontological graph extracted from DBpedia. It is based on an algorithm for finding and weighting a collection of paths connecting concept nodes. This algorithm was implemented on a tool called Shakti that extract relevant ontological data for a given domain from DBpedia using its SPARQL endpoint. To validate the proposed approach Shakti was used to recommend web pages on a Portuguese social site related to alternative music and the results of that experiment are reported in this paper.

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IEEE International Symposium on Circuits and Systems, pp. 724 – 727, Seattle, EUA

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Desulfovibrio desulfuricans was the first species of a sulphatereducing bacterium to be isolated, in 1895. Since that time, many questions were raised in the scientific community regarding the metabolic and ecological aspects of these bacteria. At present, there is still a myriad of open questions remaining to be answered to enlarge our knowledge of the metabolic pathways operative in these bacteria that have implications in the sulfur cycle, in biocorrosion, namely in sewers and in oil and gas systems, and in bioremediation of several toxic metals. The work presented in this dissertation aimed at contributing with new insights of enzymes involved in two different metabolic systems on Desulfovibrio species, namely enzymes that play a role in the response to oxidative stress and that are involved in the haem biosynthetic pathway.(...)