880 resultados para Weak Greedy Algorithms


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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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We investigate the effects induced by excited leptons, at the one-loop level, in the anomalous magnetic and weak-magnetic form factors of the leptons. In particular, we compute their contributions to the weak-magnetic moment of the tau lepton, which can be measured on the Z peak, and we compare it with the contributions to g(mu) - 2, measured at low energies.

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Ferromagnetic behaviour at 300 K has been observed from SQUID experiments in ClO4- doped PMTh, the samples were prepared electrochemically at 25 degreesC in acetonitrile with 0.1M LiClO4 and then partially reduced. Atomic absorption analysis discards magnetic particles contamination. Hysteresis curves were observed for pressed pellets in ail range of temperatures (300K-2K). The remanence at 300 K and pressed at 250 bar was around 8.06x10(-4) emu/g with coercitivity of 130 Oe. The influence of water content in the solvent during the sample synthesis and the pressure is shown. We discuss a model that explains our data in terms of the anisotropic superexchange Dziatoshinski-Moriya interaction giving rise to weak ferromagnetism.

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The helicity flip of a spin-1/2 Dirac particle interacting gravitationally with a scalar field is analyzed in the context of linearized quantum gravity. It is shown that massive fermions may have their helicity flipped by gravity, in opposition to massless fermions which preserve their helicity.

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We propose a method for accelerating iterative algorithms for solving symmetric linear complementarity problems. The method consists in performing a one-dimensional optimization in the direction generated by a splitting method even for non-descent directions. We give strong convergence proofs and present numerical experiments that justify using this acceleration.

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The recipe used to compute the symmetric energy-momentum tensor in the framework of ordinary field theory bears little resemblance to that used in the context of general relativity, if any. We show that if one stal ts fi om the field equations instead of the Lagrangian density, one obtains a unified algorithm for computing the symmetric energy-momentum tensor in the sense that it can be used for both usual field theory and general relativity.

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We investigate the sensitivity of some weak processes to a Cabibbo-Kobayashi-Maskawa in the leptonic sector. Values for mixing angles and masses compatible with several experimental accelerator data were found. We discuss in this context neutrino oscillations and cosmological and astrophysical consequences as well.

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The usefulness of the application of heuristic algorithms in the transportation model, first proposed by Garver, is analysed in relation to planning for the expansion of transmission systems. The formulation of the mathematical model and the solution techniques proposed in the specialised literature are analysed in detail. Starting with the constructive heuristic algorithm proposed by Garver, an extension is made to the problem of multistage planning for transmission systems. The quality of the solutions found by heuristic algorithms for the transportation model is analysed, as are applications in problems of planning transmission systems.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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

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This paper analyses the impact of choosing good initial populations for genetic algorithms regarding convergence speed and final solution quality. Test problems were taken from complex electricity distribution network expansion planning. Constructive heuristic algorithms were used to generate good initial populations, particularly those used in resolving transmission network expansion planning. The results were compared to those found by a genetic algorithm with random initial populations. The results showed that an efficiently generated initial population led to better solutions being found in less time when applied to low complexity electricity distribution networks and better quality solutions for highly complex networks when compared to a genetic algorithm using random initial populations.