969 resultados para Data Flow Algorithm


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Pós-graduação em Engenharia Elétrica - FEIS

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Pós-graduação em Engenharia Elétrica - FEIS

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The growing demand for electricity in Brazil has stimulated the implementation of Small Hydro Power (PCH) in various regions of the country. However, the silting of reservoirs is a major problem faced by power plants and power plants. In this context, this study aimed to evaluate the data hydrosedimentological strategic points of the watershed of the Alto Rio Sucuriú (MS) to identify the possible causes siltation of the reservoir PCH Costa Rica and suggest mitigation measures. Hydrosedimentological surveys were conducted during the rainy season (February / March 2012) and drought (August 2012), and obtained data flow, discharge liquid, suspended solids and bottom and organic matter content. Based on these results it was determined that the points 2, 4, 7 and 9 are the largest contributors to sedimentation, and point 4 got most liquid discharge (38,20 m3s-1), point 7 largest discharge of solid suspension (906,3 mg L-1), points 2 and 4 major discharges solid totals (231,59 t dia-1 and 238,185 t dia-1 respectively) and point 9 higher organic matter content (22,18%) . Found greater fraction of fine sand and very fine suspended solids and solid medium sand in the background. As mitigation measures for the process of silting of the reservoir PCH Costa Rica (MS) highlights the orientation of landowners in adopting conservation measures and planting of leguminous species native to the region in symbiosis with nitrogen-fixing bacteria

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Pós-graduação em Engenharia Elétrica - FEIS

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Pós-graduação em Engenharia Elétrica - FEIS

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Spreadsheets are widely used but often contain faults. Thus, in prior work we presented a data-flow testing methodology for use with spreadsheets, which studies have shown can be used cost-effectively by end-user programmers. To date, however, the methodology has been investigated across a limited set of spreadsheet language features. Commercial spreadsheet environments are multiparadigm languages, utilizing features not accommodated by our prior approaches. In addition, most spreadsheets contain large numbers of replicated formulas that severely limit the efficiency of data-flow testing approaches. We show how to handle these two issues with a new data-flow adequacy criterion and automated detection of areas of replicated formulas, and report results of a controlled experiment investigating the feasibility of our approach.

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In this paper, we carry out robust modeling and influence diagnostics in Birnbaum-Saunders (BS) regression models. Specifically, we present some aspects related to BS and log-BS distributions and their generalizations from the Student-t distribution, and develop BS-t regression models, including maximum likelihood estimation based on the EM algorithm and diagnostic tools. In addition, we apply the obtained results to real data from insurance, which shows the uses of the proposed model. Copyright (c) 2011 John Wiley & Sons, Ltd.

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Máster Universitario en Sistemas Inteligentes y Aplicaciones Numéricas en Ingeniería (SIANI)

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Computer aided design of Monolithic Microwave Integrated Circuits (MMICs) depends critically on active device models that are accurate, computationally efficient, and easily extracted from measurements or device simulators. Empirical models of active electron devices, which are based on actual device measurements, do not provide a detailed description of the electron device physics. However they are numerically efficient and quite accurate. These characteristics make them very suitable for MMIC design in the framework of commercially available CAD tools. In the empirical model formulation it is very important to separate linear memory effects (parasitic effects) from the nonlinear effects (intrinsic effects). Thus an empirical active device model is generally described by an extrinsic linear part which accounts for the parasitic passive structures connecting the nonlinear intrinsic electron device to the external world. An important task circuit designers deal with is evaluating the ultimate potential of a device for specific applications. In fact once the technology has been selected, the designer would choose the best device for the particular application and the best device for the different blocks composing the overall MMIC. Thus in order to accurately reproducing the behaviour of different-in-size devices, good scalability properties of the model are necessarily required. Another important aspect of empirical modelling of electron devices is the mathematical (or equivalent circuit) description of the nonlinearities inherently associated with the intrinsic device. Once the model has been defined, the proper measurements for the characterization of the device are performed in order to identify the model. Hence, the correct measurement of the device nonlinear characteristics (in the device characterization phase) and their reconstruction (in the identification or even simulation phase) are two of the more important aspects of empirical modelling. This thesis presents an original contribution to nonlinear electron device empirical modelling treating the issues of model scalability and reconstruction of the device nonlinear characteristics. The scalability of an empirical model strictly depends on the scalability of the linear extrinsic parasitic network, which should possibly maintain the link between technological process parameters and the corresponding device electrical response. Since lumped parasitic networks, together with simple linear scaling rules, cannot provide accurate scalable models, either complicate technology-dependent scaling rules or computationally inefficient distributed models are available in literature. This thesis shows how the above mentioned problems can be avoided through the use of commercially available electromagnetic (EM) simulators. They enable the actual device geometry and material stratification, as well as losses in the dielectrics and electrodes, to be taken into account for any given device structure and size, providing an accurate description of the parasitic effects which occur in the device passive structure. It is shown how the electron device behaviour can be described as an equivalent two-port intrinsic nonlinear block connected to a linear distributed four-port passive parasitic network, which is identified by means of the EM simulation of the device layout, allowing for better frequency extrapolation and scalability properties than conventional empirical models. Concerning the issue of the reconstruction of the nonlinear electron device characteristics, a data approximation algorithm has been developed for the exploitation in the framework of empirical table look-up nonlinear models. Such an approach is based on the strong analogy between timedomain signal reconstruction from a set of samples and the continuous approximation of device nonlinear characteristics on the basis of a finite grid of measurements. According to this criterion, nonlinear empirical device modelling can be carried out by using, in the sampled voltage domain, typical methods of the time-domain sampling theory.

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[EN]We present a new strategy, based on the idea of the meccano method and a novel T-mesh optimization procedure, to construct a T-spline parameterization of 2D geometries for the application of isogeometric analysis. The proposed method only demands a boundary representation of the geometry as input data. The algorithm obtains, as a result, high quality parametric transformation between 2D objects and the parametric domain, the unit square. First, we define a parametric mapping between the input boundary of the object and the boundary of the parametric domain. Then, we build a T-mesh adapted to the geometric singularities of the domain in order to preserve the features of the object boundary with a desired tolerance...

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[EN]We present a new strategy, based on the meccano method [1, 2, 3], to construct a T-spline parameterization of 2D geometries for the application of isogeometric analysis. The proposed method only demands a boundary representation of the geometry as input data. The algorithm obtains, as a result, high quality parametric transformation between 2D objects and the parametric domain, the unit square. The key of the method lies in defining an isomorphic transformation between the parametric and physical T-mesh finding the optimal position of the interior nodes by applying a new T-mesh untangling and smoothing procedure. Bivariate T-spline representation is calculated by imposing the interpolation conditions on points sited both on the interior and on the boundary of the geometry…

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[EN]We have recently introduced a new strategy, based on the meccano method [1, 2], to construct a T-spline parameterization of 2D and 3D geometries for the application of iso geometric analysis [3, 4]. The proposed method only demands a boundary representation of the geometry as input data. The algorithm obtains, as a result, high quality parametric transformation between the objects and the parametric domain, i.e. the meccano. The key of the method lies in de_ning an isomorphic transformation between the parametric and physical T-mesh _nding the optimal position of the interior nodes, once the meccano boundary nodes are mapped to the boundary of the physical domain…