886 resultados para Search-based technique


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Phasor Measurement Units (PMUs) optimized allocation allows control, monitoring and accurate operation of electric power distribution systems, improving reliability and service quality. Good quality and considerable results are obtained for transmission systems using fault location techniques based on voltage measurements. Based on these techniques and performing PMUs optimized allocation it is possible to develop an electric power distribution system fault locator, which provides accurate results. The PMUs allocation problem presents combinatorial features related to devices number that can be allocated, and also probably places for allocation. Tabu search algorithm is the proposed technique to carry out PMUs allocation. This technique applied in a 141 buses real-life distribution urban feeder improved significantly the fault location results. © 2004 IEEE.

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This report describes a search for associated production of W and Higgs bosons based on data corresponding to an integrated luminosity of L≈5.3fb -1 collected with the D0 detector at the Fermilab Tevatron pp̄ Collider. Events containing a W→ν candidate (with corresponding to e or μ) are selected in association with two or three reconstructed jets. One or two of the jets are required to be consistent with having evolved from a b quark. A multivariate discriminant technique is used to improve the separation of signal and backgrounds. Expected and observed upper limits are obtained for the product of the WH production cross section and branching ratios and reported in terms of ratios relative to the prediction of the standard model as a function of the mass of the Higgs boson (M H). The observed and expected 95% C.L. upper limits obtained for an assumed M H=115GeV are, respectively, factors of 4.5 and 4.8 larger than the value predicted by the standard model. © 2012 American Physical Society.

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Wireless Sensor Networks (WSN) are a special kind of ad-hoc networks that is usually deployed in a monitoring field in order to detect some physical phenomenon. Due to the low dependability of individual nodes, small radio coverage and large areas to be monitored, the organization of nodes in small clusters is generally used. Moreover, a large number of WSN nodes is usually deployed in the monitoring area to increase WSN dependability. Therefore, the best cluster head positioning is a desirable characteristic in a WSN. In this paper, we propose a hybrid clustering algorithm based on community detection in complex networks and traditional K-means clustering technique: the QK-Means algorithm. Simulation results show that QK-Means detect communities and sub-communities thus lost message rate is decreased and WSN coverage is increased. © 2012 IEEE.

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Background: Because of ethical and medico-legal aspects involved in the training of cutaneous surgical skills on living patients, human cadavers and living animals, it is necessary the search for alternative and effective forms of training simulation. Aims: To propose and describe an alternative methodology for teaching and learning the principles of cutaneous surgery in a medical undergraduate program by using a chicken-skin bench model. Materials and Methods: One instructor for every four students, teaching materials on cutaneous surgical skills, chicken trunks, wings, or thighs, a rigid platform support, needled threads, needle holders, surgical blades with scalpel handles, rat-tooth tweezers, scissors, and marking pens were necessary for training simulation. Results: A proposal for simulation-based training on incision, suture, biopsy, and on reconstruction techniques using a chicken-skin bench model distributed in several sessions and with increasing levels of difficultywas structured. Both feedback and objective evaluations always directed to individual students were also outlined. Conclusion: The teaching of a methodology for the principles of cutaneous surgery using a chicken-skin bench model versatile, portable, easy to assemble, and inexpensive is an alternative and complementary option to the armamentarium of methods based on other bench models described. © Indian Journal of Dermatology 2013.

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The non-technical loss is not a problem with trivial solution or regional character and its minimization represents the guarantee of investments in product quality and maintenance of power systems, introduced by a competitive environment after the period of privatization in the national scene. In this paper, we show how to improve the training phase of a neural network-based classifier using a recently proposed meta-heuristic technique called Charged System Search, which is based on the interactions between electrically charged particles. The experiments were carried out in the context of non-technical loss in power distribution systems in a dataset obtained from a Brazilian electrical power company, and have demonstrated the robustness of the proposed technique against with several others nature-inspired optimization techniques for training neural networks. Thus, it is possible to improve some applications on Smart Grids. © 2013 IEEE.

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Feature selection has been actively pursued in the last years, since to find the most discriminative set of features can enhance the recognition rates and also to make feature extraction faster. In this paper, the propose a new feature selection called Binary Cuckoo Search, which is based on the behavior of cuckoo birds. The experiments were carried out in the context of theft detection in power distribution systems in two datasets obtained from a Brazilian electrical power company, and have demonstrated the robustness of the proposed technique against with several others nature-inspired optimization techniques. © 2013 IEEE.

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Image restoration is a research field that attempts to recover a blurred and noisy image. Since it can be modeled as a linear system, we propose in this paper to use the meta-heuristics optimization algorithm Harmony Search (HS) to find out near-optimal solutions in a Projections Onto Convex Sets-based formulation to solve this problem. The experiments using HS and four of its variants have shown that we can obtain near-optimal and faster restored images than other evolutionary optimization approach. © 2013 IEEE.

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Feature selection aims to find the most important information from a given set of features. As this task can be seen as an optimization problem, the combinatorial growth of the possible solutions may be inviable for a exhaustive search. In this paper we propose a new nature-inspired feature selection technique based on the Charged System Search (CSS), which has never been applied to this context so far. The wrapper approach combines the power of exploration of CSS together with the speed of the Optimum-Path Forest classifier to find the set of features that maximizes the accuracy in a validating set. Experiments conducted in four public datasets have demonstrated the validity of the proposed approach can outperform some well-known swarm-based techniques. © 2013 Springer-Verlag.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Optical flow methods are accurate algorithms for estimating the displacement and velocity fields of objects in a wide variety of applications, being their performance dependent on the configuration of a set of parameters. Since there is a lack of research that aims to automatically tune such parameters, in this work we have proposed an evolutionary-based framework for such task, thus introducing three techniques for such purpose: Particle Swarm Optimization, Harmony Search and Social-Spider Optimization. The proposed framework has been compared against with the well-known Large Displacement Optical Flow approach, obtaining the best results in three out eight image sequences provided by a public dataset. Additionally, the proposed framework can be used with any other optimization technique.