Interface gráfica no contexto de teoria dos jogos sob a forma de Java Apples

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Sistema inteligente baseado nas redes neurais artificiais para dosagem do concreto

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Capacidade de Uso das Terras da Bacia do Ribeirão Água Fria – Bofete (SP)

A determinação da capacidade de uso das terras numa bacia é muito importante para o planejamento e uso do solo, pois o uso inadequado e sem planejamento dessas terras provocam a baixa produtividade das culturas. Este trabalho visou definir as classes homogêneas de capacidade de uso da terra da bacia do Ribeirão Água Fria - Bofete (SP) para atender ao planejamento de práticas de conservação do solo desta área. A bacia situa-se entre as coordenadas geográficas 22o 58' 30`` a 23o 04' 30`` de latitude S e 48o 09' 30`` a 48o 18' 30`` de longitude W Gr., apresentando uma área de 9.180,12 hectares. A carta de capacidade de uso da terra da bacia foi elaborada a partir da carta clinográfica obtida por Santos et al. (1999), mapa pedológico do Estado de São Paulo (Oliveira et al., 1999), da tabela de julgamento de classes de capacidade de uso do solo (França, 1963) e das recomendações constantes no manual para levantamento utilitário do meio físico e classificação das terras no sistema de capacidade de uso (Lepsch et al., 1983). A discriminação, o mapeamento e a quantificação das áreas das classes e subclasses de capacidade de uso pelo Sistema de Informação Geográfica - IDRISI apresentaram os seguintes valores: IIIe,s - 517,020 ha (5,63%); IIIs - 863,150 ha (9,40%); IVe - 846,730 ha (9,23%); VIe - 871,110 ha (9,49%) e VIIe - 6082,115 ha (66,25%). Os resultados permitiram concluir que a bacia essencialmente constituída por 2/3 pela subclasse VIIe, ou seja, são terras que podem ser utilizadas por pastagens com uso moderado ou florestas, pois apresentam problemas complexos de erosão por causa de sua declividade. O Sistema de Informação Geográfica IDRISI permitiu através de seus módulos discriminar, mapear e quantificar as áreas das classes e subclasses de capacidade de uso das terras da bacia com rapidez e confiabilidade.

Desenvolvimento de uma metodologia para elaboração de modelos de predição dos níveis de ruído do campo acústico de usinas hidrelétricas

Pós-graduação em Engenharia Mecânica - FEIS

Análise de Tópicos Relevantes em Programação Linear e Aplicações no Ensino de Engenharia

Pós-graduação em Engenharia Elétrica - FEIS

Sobre o uso de sistemas de computação algébrica na solução de problemas de mecânica das estruturas

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

The use of artificial neural networks in analysing the nutritional ecology of Chrysomya megacephala (F.) (Diptera: Calliphoridae), compared with a statistical model

Artificial neural networks (ANNs) have been widely applied to the resolution of complex biological problems. An important feature of neural models is that their implementation is not precluded by the theoretical distribution shape of the data used. Frequently, the performance of ANNs over linear or non-linear regression-based statistical methods is deemed to be significantly superior if suitable sample sizes are provided, especially in multidimensional and non-linear processes. The current work was aimed at utilising three well-known neural network methods in order to evaluate whether these models would be able to provide more accurate outcomes in relation to a conventional regression method in pupal weight predictions of Chrysomya megacephala, a species of blowfly (Diptera: Calliphoridae), using larval density (i.e. the initial number of larvae), amount of available food and pupal size as input data. It was possible to notice that the neural networks yielded more accurate performances in comparison with the statistical model (multiple regression). Assessing the three types of networks utilised (Multi-layer Perceptron, Radial Basis Function and Generalised Regression Neural Network), no considerable differences between these models were detected. The superiority of these neural models over a classical statistical method represents an important fact, because more accurate models may clarify several intricate aspects concerning the nutritional ecology of blowflies.

Application of a bounded upwinding scheme to complex fluid dynamics problems

This paper is concerned with an overview of upwinding schemes, and further nonlinear applications of a recently introduced high resolution upwind differencing scheme, namely the ADBQUICKEST [V.G. Ferreira, F.A. Kurokawa, R.A.B. Queiroz, M.K. Kaibara, C.M. Oishi, J.A.Cuminato, A.F. Castelo, M.F. Tomé, S. McKee, assessment of a high-order finite difference upwind scheme for the simulation of convection-diffusion problems, International Journal for Numerical Methods in Fluids 60 (2009) 1-26]. The ADBQUICKEST scheme is a new TVD version of the QUICKEST [B.P. Leonard, A stable and accurate convective modeling procedure based on quadratic upstream interpolation, Computer Methods in Applied Mechanics and Engineering 19 (1979) 59-98] for solving nonlinear balance laws. The scheme is based on the concept of NV and TVD formalisms and satisfies a convective boundedness criterion. The accuracy of the scheme is compared with other popularly used convective upwinding schemes (see, for example, Roe (1985) [19], Van Leer (1974) [18] and Arora & Roe (1997) [17]) for solving nonlinear conservation laws (for example, Buckley-Leverett, shallow water and Euler equations). The ADBQUICKEST scheme is then used to solve six types of fluid flow problems of increasing complexity: namely, 2D aerosol filtration by fibrous filters; axisymmetric flow in a tubular membrane; 2D two-phase flow in a fluidized bed; 2D compressible Orszag-Tang MHD vortex; axisymmetric jet onto a flat surface at low Reynolds number and full 3D incompressible flows involving moving free surfaces. The numerical simulations indicate that this convective upwinding scheme is a good generic alternative for solving complex fluid dynamics problems. © 2012.

Bifurcation Analysis of a Van der Pol-Duffing Circuit with Parallel Resistor

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A new approach to the granulation of beta-cyclodextrin inclusion complexes

Cyclodextrins (CDs) are annular oligosaccharides containing 6-12 glucose unities joined together by alpha-1,4 bonds. They have a conical-truncated shape with a lipophilic cavity in which different molecules can be included resulting in a stable inclusion complex. The cyclodextrins have been widely applied in pharmaceutical technology with the objective of increasing the solubility, stability and bioavailability of drugs in different pharmaceutical dosage forms, such as tablets. In order to obtain beta-CD tablets, liquid dispersions of drug/beta-CD are usually submitted to different drying processes, like spray-drying, freeze-drying or slow evaporation, being this dry material added to a number of excipients. However, such drying processes can generate particulate materials showing problems of flow and compressibility, needing their conversion into granulates by means of wetting with granulation liquid followed by additional drying. In this work, the main objective was to evaluate the preparation of tablets without the need of this additional drying step. For this purpose an aqueous dispersion containing acetaminophen/beta-CD complex and cornstarch was dried using a spouted bed and the obtained granules were compressed in tablets. Acetaminophen was used as model drug due to its low water solubility and the inexpensive and widely available cornstarch was chosen as excipient. Acetaminophen powder was added into a beta-cyclodextrin solution prepared in distilled water at 70 degrees C. Stirring was kept until this dispersion cooled to room temperature. Then cornstarch was added and the resulting dispersion was dried in spouted bed equipment. This material was compressed into tablets using an Erweka Korsh EKO tablet machine. This innovative approach allowed the tablets preparation process to be carried out with fewer steps and represents a technological reliable strategy to produce beta-cyclodextrin inclusion complexes tablets. (C) 2010 Elsevier By. All rights reserved.

Mathematical tests about the existence and applications of PPS-wavelets in function approximation problems

Neural networks and wavelet transform have been recently seen as attractive tools for developing eficient solutions for many real world problems in function approximation. Function approximation is a very important task in environments where computation has to be based on extracting information from data samples in real world processes. So, mathematical model is a very important tool to guarantee the development of the neural network area. In this article we will introduce one series of mathematical demonstrations that guarantee the wavelets properties for the PPS functions. As application, we will show the use of PPS-wavelets in pattern recognition problems of handwritten digit through function approximation techniques.

A continuously differentiable upwinding scheme for the simulation of fluid flow problems

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

Predictor-Corrector Primal-Dual Interior Point Method for Solving Economic Dispatch Problems: A Postoptimization Analysis

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

An efficient Hopfield network to solve economic dispatch problems with transmission system representation

Economic dispatch (ED) problems have recently been solved by artificial neural network approaches. Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements and the high degree of connectivity between these elements. The ability of neural networks to realize some complex non-linear function makes them attractive for system optimization. All ED models solved by neural approaches described in the literature fail to represent the transmission system. Therefore, such procedures may calculate dispatch policies, which do not take into account important active power constraints. Another drawback pointed out in the literature is that some of the neural approaches fail to converge efficiently toward feasible equilibrium points. A modified Hopfield approach designed to solve ED problems with transmission system representation is presented in this paper. The transmission system is represented through linear load flow equations and constraints on active power flows. The internal parameters of such modified Hopfield networks are computed using the valid-subspace technique. These parameters guarantee the network convergence to feasible equilibrium points, which represent the solution for the ED problem. Simulation results and a sensitivity analysis involving IEEE 14-bus test system are presented to illustrate efficiency of the proposed approach. (C) 2004 Elsevier Ltd. All rights reserved.

Experimental Active Vibration Control in Truss Structures Considering Uncertainties in System Parameters

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