74 resultados para Parameter robustness


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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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This paper introduces the Optimum-Path Forest (OPF) classifier for static video summarization, being its results comparable to the ones obtained by some state-of-the-art video summarization techniques. The experimental section has been conducted using several image descriptors in two public datasets, followed by an analysis of OPF robustness regarding one ad-hoc parameter. Future works are guided to improve OPF effectiveness on each distinct video category.

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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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Since the beginning, some pattern recognition techniques have faced the problem of high computational burden for dataset learning. Among the most widely used techniques, we may highlight Support Vector Machines (SVM), which have obtained very promising results for data classification. However, this classifier requires an expensive training phase, which is dominated by a parameter optimization that aims to make SVM less prone to errors over the training set. In this paper, we model the problem of finding such parameters as a metaheuristic-based optimization task, which is performed through Harmony Search (HS) and some of its variants. The experimental results have showen the robustness of HS-based approaches for such task in comparison against with an exhaustive (grid) search, and also a Particle Swarm Optimization-based implementation.

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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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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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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.

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We examine, from both the experimental and theoretical point of view, the behavior of the maximum splitting ΔE, of the 7F1 manifold of the Eu3+ ion as a function of the so-called crystal field strength parameter, Nv, in a series of oxides. In connection with the original theory that describes the relation between ΔE and Nv, a more consistent procedure to describe this relation is presented for the cases of small total angular momentum J. Good agreement is found between theory and experiment. © 1995.

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Priestley and Taylor provided a practical formulation of the partitioning of net radiation between heat flux and evaporation contained within a parameter α. Their model (PTM) needs verification under a range of environmental conditions. Micrometeorological data sets collected over the Amazon forest at the Ducke Reserve site (2°57′S; 59°57′W) gave an opportunity to evaluate α. Evidence presented here and by others shows that there is pronounced diurnal variation in α, with minimum values around midday and maximum values in the morning and evening hours. During unstable and stable conditions in the daylight hours, the Bowen ratio (B) varied from 0.10 to 0.57 and -0.71 to -0.08, respectively, whereas α varied from 0.67 to 1.16 and 1.28 to 3.12, respectively. A mean value of α = 1.16±0.56 was obtained from daytime hourly values for two days. The daily data sets from three expeditions gave a mean of α = 1.03±0.13. This work confirms that α is a function of atmospheric stability over the Amazon forest. Thus the PTM should be applied with caution over time-intervals of one day or less because of the sensitivity to variation in α. The calculated values of α are in general agreement with those reported in literature. © 1991.

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A low-energy shape-independent expansion is suggested for the function tan(2εBB)/(2k2), where εBB is the Blatt-Biedenharn mixing parameter for the 3S1 - 3D1 channel. This expansion allows an evaluation of the mixing parameter εBB from a knowledge of the deuteron asymptotic D to S ratio, pion mass and other low-energy observables, such as the scattering lengths, deuteron binding etc., of the nucleon-nucleon system. We demonstrate that the correct long range behavior of the tensor potential is essential for a realistic reproduction of εBB.

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The new result presented here is a theorem involving series in the three-parameter Mittag-Le er function. As a by-product, we recover some known results and discuss corollaries. As an application, we obtain the solution of a fractional di erential equation associated with a RLC electrical circuit in a closed form, in terms of the two-parameter Mittag-Le er function.

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In this paper the dynamical interactions of a double pendulum arm and an electromechanical shaker is investigated. The double pendulum is a three degree of freedom system coupled to an RLC circuit based nonlinear shaker through a magnetic field, and the capacitor voltage is a nonlinear function of the instantaneous electric charge. Numerical simulations show the existence of chaotic behavior for some regions in the parameter space and this behaviour is characterized by power spectral density and Lyapunov exponents. The bifurcation diagram is constructed to explore the qualitative behaviour of the system. This kind of electromechanical system is frequently found in robotic systems, and in order to suppress the chaotic motion, the State-Dependent Riccati Equation (SDRE) control and the Nonlinear Saturation control (NSC) techniques are analyzed. The robustness of these two controllers is tested by a sensitivity analysis to parametric uncertainties.