135 resultados para Problem solving

em Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho"


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This paper shows a comparative study between the Artificial Intelligence Problem Solving and the Human Problem Solving. The study is based on the solution by many ways of problems proposed via multiple-choice questions. General techniques used by humans to solve this kind of problems are grouped in blocks and each block is divided in steps. A new architecture for ITS - Intelligent Tutoring System is proposed to support experts' knowledge representation and novices' activities. Problems are represented by a text and feasible answers with particular meaning and form, to be rigorously analyzed by the solver to find the right one. Paths through a conceptual space of states represent each right solution.

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A fourth-order numerical method for solving the Navier-Stokes equations in streamfunction/vorticity formulation on a two-dimensional non-uniform orthogonal grid has been tested on the fluid flow in a constricted symmetric channel. The family of grids is generated algebraically using a conformal transformation followed by a non-uniform stretching of the mesh cells in which the shape of the channel boundary can vary from a smooth constriction to one which one possesses a very sharp but smooth corner. The generality of the grids allows the use of long channels upstream and downstream as well as having a refined grid near the sharp corner. Derivatives in the governing equations are replaced by fourth-order central differences and the vorticity is eliminated, either before or after the discretization, to form a wide difference molecule for the streamfunction. Extra boundary conditions, necessary for wide-molecule methods, are supplied by a procedure proposed by Henshaw et al. The ensuing set of non-linear equations is solved using Newton iteration. Results have been obtained for Reynolds numbers up to 250 for three constrictions, the first being smooth, the second having a moderately sharp corner and the third with a very sharp corner. Estimates of the error incurred show that the results are very accurate and substantially better than those of the corresponding second-order method. The observed order of the method has been shown to be close to four, demonstrating that the method is genuinely fourth-order. © 1977 John Wiley & Sons, Ltd.

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In this paper, the concept of Matching Parallelepiped (MP) is presented. It is shown that the volume of the MP can be used as an additional measure of `distance' between a pair of candidate points in a matching algorithm by Relaxation Labeling (RL). The volume of the MP is related with the Epipolar Geometry and the use of this measure works as an epipolar constraint in a RL process, decreasing the efforts in the matching algorithm since it is not necessary to explicitly determine the equations of the epipolar lines and to compute the distance of a candidate point to each epipolar line. As at the beginning of the process the Relative Orientation (RO) parameters are unknown, a initial matching based on gradient, intensities and correlation is obtained. Based on this set of labeled points the RO is determined and the epipolar constraint included in the algorithm. The obtained results shown that the proposed approach is suitable to determine feature-point matching with simultaneous estimation of camera orientation parameters even for the cases where the pair of optical axes are not parallel.

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The regular-geometric-figure solution to the N-body problem is presented in a very simple way. The Newtonian formalism is used without resorting to a more involved rotating coordinate system. Those configurations occur for other kinds of interactions beyond the gravitational ones for some special values of the parameters of the forces. For the harmonic oscillator, in particular, it is shown that the N-body problem is reduced to N one-body problems.

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A branch and bound algorithm is proposed to solve the [image omitted]-norm model reduction problem for continuous and discrete-time linear systems, with convergence to the global optimum in a finite time. The lower and upper bounds in the optimization procedure are described by linear matrix inequalities (LMI). Also proposed are two methods with which to reduce the convergence time of the branch and bound algorithm: the first one uses the Hankel singular values as a sufficient condition to stop the algorithm, providing to the method a fast convergence to the global optimum. The second one assumes that the reduced model is in the controllable or observable canonical form. The [image omitted]-norm of the error between the original model and the reduced model is considered. Examples illustrate the application of the proposed method.

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The present paper evaluates meta-heuristic approaches to solve a soft drink industry problem. This problem is motivated by a real situation found in soft drink companies, where the lot sizing and scheduling of raw materials in tanks and products in lines must be simultaneously determined. Tabu search, threshold accepting and genetic algorithms are used as procedures to solve the problem at hand. The methods are evaluated with a set of instance already available for this problem. This paper also proposes a new set of complex instances. The computational results comparing these approaches are reported. © 2008 IEEE.

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The problem of assigning cells to switches in a cellular mobile network is an NP-hard optimization problem. So, real size mobile networks could not be solved by using exact methods. The alternative is the use of the heuristic methods, because they allow us to find a good quality solution in a quite satisfactory computational time. This paper proposes a Beam Search method to solve the problem of assignment cell in cellular mobile networks. Some modifications in this algorithm are also presented, which allows its parallel application. Computational results obtained from several tests confirm the effectiveness of this approach to provide good solutions for medium- and large-sized cellular mobile network.

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In this paper a framework based on the decomposition of the first-order optimality conditions is described and applied to solve the Probabilistic Power Flow (PPF) problem in a coordinated but decentralized way in the context of multi-area power systems. The purpose of the decomposition framework is to solve the problem through a process of solving smaller subproblems, associated with each area of the power system, iteratively. This strategy allows the probabilistic analysis of the variables of interest, in a particular area, without explicit knowledge of network data of the other interconnected areas, being only necessary to exchange border information related to the tie-lines between areas. An efficient method for probabilistic analysis, considering uncertainty in n system loads, is applied. The proposal is to use a particular case of the point estimate method, known as Two-Point Estimate Method (TPM), rather than the traditional approach based on Monte Carlo simulation. The main feature of the TPM is that it only requires resolve 2n power flows for to obtain the behavior of any random variable. An iterative coordination algorithm between areas is also presented. This algorithm solves the Multi-Area PPF problem in a decentralized way, ensures the independent operation of each area and integrates the decomposition framework and the TPM appropriately. The IEEE RTS-96 system is used in order to show the operation and effectiveness of the proposed approach and the Monte Carlo simulations are used to validation of the results. © 2011 IEEE.

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This paper proposes a new strategy to reduce the combinatorial search space of a mixed integer linear programming (MILP) problem. The construction phase of greedy randomized adaptive search procedure (GRASP-CP) is employed to reduce the domain of the integer variables of the transportation model of the transmission expansion planning (TM-TEP) problem. This problem is a MILP and very difficult to solve specially for large scale systems. The branch and bound (BB) algorithm is used to solve the problem in both full and the reduced search space. The proposed method might be useful to reduce the search space of those kinds of MILP problems that a fast heuristic algorithm is available for finding local optimal solutions. The obtained results using some real test systems show the efficiency of the proposed method. © 2012 Springer-Verlag.

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A first order analytical model for optimal small amplitude attitude maneuvers of spacecraft with cylindrical symmetry in an elliptical orbits is presented. The optimization problem is formulated as a Mayer problem with the control torques provided by a power limited propulsion system. The state is defined by Seffet-Andoyer's variables and the control by the components of the propulsive torques. The Pontryagin Maximum Principle is applied to the problem and the optimal torques are given explicitly in Serret-Andoyer's variables and their adjoints. For small amplitude attitude maneuvers, the optimal Hamiltonian function is linearized around a reference attitude. A complete first order analytical solution is obtained by simple quadrature and is expressed through a linear algebraic system involving the initial values of the adjoint variables. A numerical solution is obtained by taking the Euler angles formulation of the problem, solving the two-point boundary problem through the shooting method, and, then, determining the Serret-Andoyer variables through Serret-Andoyer transformation. Numerical results show that the first order solution provides a good approximation to the optimal control law and also that is possible to establish an optimal control law for the artificial satellite's attitude. (C) 2003 COSPAR. Published by Elsevier B.V. Ltd. All rights reserved.

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Este artigo é uma tentativa de delinear as principais características da pesquisa numa nova área de estudos a chamada Inteligência Artificial (AI). Os itens 1 e 2 constituem um rápido histórico da AI e seus pressupostos básicos. O item 3 trata da teoria de resolução de problemas, desenvolvida por A. Newell e H. Simon. O item 4 procura mostrar a relevância da AI para a Filosofia, em especial para a filosofia da Mente e para a Teoria do Conhecimento.

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O estudo trata-se de uma pesquisa descritiva, com o objetivo de avaliar as contribuições e dificuldades sentidas pelos alunos, na utilização do Modelo Operacional do Estudo de Caso, proposto pelas autoras como uma das estratégias de ensino utilizada pela disciplina de Enfermagem Médico-Cirúrgica. Para instrumentalizar e operacionalizar a análise de conteúdo das respostas concedidas pelos alunos, utilizamos da análise temática, segundo Bardin. Com a realização desta investigação concluímos que os alunos reconhecem o modelo como estratégia de ensino na formação dos mesmos, principalmente, quanto ao conhecimento teórico-prático da assistência (70%) que este oferece, estimulando-os à autonomia na tomada de decisões e solução de problemas na área, além de incentivá-los na utilização do acervo da biblioteca. A outra contribuição está relacionada ao conhecimento referente à metodologia científica (30%), onde o modelo emerge a eles como uma estratégia de iniciação a esta atividade. As dificuldades sentidas pelos alunos na elaboração do estudo de caso ocorreram nas seguintes etapas: - no levantamento bibliográfico (58%), principalmente, quanto a falta de bibliografia específica e recente na área de enfermagem e ao não acesso dos alunos da graduação aos índices informatizados: - na redação do trabalho(27%), porém ao mesmo tempo revelando que o estudo de caso propiciou conhecimentos básicos de como elaborar e escrever um trabalho científico; dentre outras (15%).

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A degradação ambiental vem modificando nosso cenário de forma acelerada e interferindo negativamente no processo saúde-doença de toda a comunidade. No entanto, o meio ambiente vem sendo concebido como um simples cenário, algo externo ao ser humano, não onde estamos inseridos e no qual acontecem suas interações e inter-relações. A complexidade dos problemas ambientais clama pela adoção de medidas que superem práticas assistencialistas, levando à adoção de práticas transdisciplinares que avancem na promoção da saúde. Neste artigo procura-se discutir, nesta perspectiva, a necessidade de inserção nos cursos de graduação em saúde a temática saúde e meio ambiente, adotando como exemplo um curso de enfermagem do interior paulista que inseriu uma disciplina relacionada ao tema. Analisa também o papel do enfermeiro na relação com o meio ambiente segundo a representação social dos alunos, trabalhada a partir do Discurso do Sujeito Coletivo. Nota-se que é fundamental discutir essa temática ambiental entre os profissionais da saúde, a fim de que eles se empoderem desse conhecimento e consigam identificar problemas relacionados à questão ambiental, propondo ações resolutivas e preventivas, juntamente com a comunidade, procurando amenizar os riscos ambientais a que todos estão expostos. Reforça-se a profundidade do papel dos profissionais de saúde diante dos problemas ambientais, buscando a saúde em uma perspectiva ampliada de promoção da saúde.

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O presente estudo investigou aspectos da representação numérica (processamento numérico e cálculo) e memória operacional de crianças com transtornos de aprendizagem. Participaram 30 crianças de idade entre 9 e 10 anos, ambos os gêneros, divididas em dois grupos: sem dificuldade em aritmética (SDA; N=11) e com dificuldade em aritmética (CDA; N=19), avaliadas pela ZAREKI-R, Matrizes Coloridas de Raven, o Blocos de Corsi e o BCPR. Crianças CDA exibiram escores levemente mais baixos que as SDA quanto ao nível intelectual e nos Blocos de Corsi. Na ZAREKI-R apresentaram prejuízo nos subtestes ditado de números, cálculo mental, problemas aritméticos e total. Crianças CDA apresentaram déficits específicos em memória operacional visuoespacial e comprometimento em processamento numérico e cálculo, compatível com discalculia do desenvolvimento.

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Este artigo apresenta uma breve revisão de alguns dos mais recentes métodos bioinspirados baseados no comportamento de populações para o desenvolvimento de técnicas de solução de problemas. As metaheurísticas tratadas aqui correspondem às estratégias de otimização por colônia de formigas, otimização por enxame de partículas, algoritmo shuffled frog-leaping, coleta de alimentos por bactérias e colônia de abelhas. Os princípios biológicos que motivaram o desenvolvimento de cada uma dessas estratégias, assim como seus respectivos algoritmos computacionais, são introduzidos. Duas aplicações diferentes foram conduzidas para exemplificar o desempenho de tais algoritmos. A finalidade é enfatizar perspectivas de aplicação destas abordagens em diferentes problemas da área de engenharia.