758 resultados para Problem-solving Support


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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.

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No presente artigo, além de lançar mão de informações da literatura, como comumente se faz, peço licença e me autorizo a emitir sobre avaliação escolar, minhas próprias idéias e opiniões, fruto de muitos anos de investigação, vivência em salas de aula, problemas e reflexão.

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O estudo avaliou a formação em enfermagem ancorada na problematização e na aprendizagem baseada em problemas a partir da percepção dos egressos. Trata-se de estudo transversal de natureza ex-post-facto. Os resultados foram analisados na triangulação das abordagens quantitativa e qualitativa e na perspectiva hermenêutica dialética. Na abordagem quantitativa 180 egressos responderam um questionário. Na qualitativa, 14 participaram das entrevistas, que buscaram sentidos relacionados ao cuidado ideal, para construção dos indicadores que revelassem a lógica da avaliação. Esses indicadores nortearam a escolha das questões para triangulação. Os resultados apontaram que 85,1% dos egressos estão inseridos no mercado de trabalho, 92,1% cursaram pós-graduação e 99,1% acreditam apresentar formação necessária ao cuidado ético, humanizado e fundamentado. A análise dos dados aponta para formação comprometida com a construção da autonomia e do conhecimento, bem como articulada aos princípios do Sistema Único de Saúde e do mundo do trabalho em enfermagem.

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We address the different "personalities" of the rational number and the concept of proportionality, analyzing the possibilities for using the Mathematics Teaching and Learning through Problem-solving Method. This method is based on the principle that knowledge can be constructed through the use of problems that generate new concepts and new contents. The different meanings of rational number - rational point, quotient, fraction, ratio, and operator - are constructs that depend on mathematical theories in which they are imbedded and the situations that evoke them in problem-solving. Some data will be presented from continuing education courses for teachers, aiming to contribute to understanding regarding the different "personalities" of the rational number. In general, these "personalities" are not easily identified by teachers and students, which is the reason for the many difficulties encountered during problem-solving involving rational numbers. One of these "personalities", the ratio, provides the basis for the concept of proportionality, which is relevant because it is a unifying idea in mathematics.

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The objective of this study is to present the trajectory of a research project (ALLEVATO, 2005) whose phenomenon of interest is the teaching of mathematics using problem solving with computers. The text is an attempt to portray this trajectory, from the point of view of the methodological route followed by the researcher, which was based on two main axes: the guidance of the educator Thomas A. Romberg (1992), and the guidelines provided by the foundations of qualitative research. The study was developed during a doctoral course offered by the Graduate Program in Mathematics Education at the State University of São Paulo (UNESP), Rio Claro campus.

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Analog networks for solving convex nonlinear unconstrained programming problems without using gradient information of the objective function are proposed. The one-dimensional net can be used as a building block in multi-dimensional networks for optimizing objective functions of several variables.

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Piecewise-Linear Programming (PLP) is an important area of Mathematical Programming and concerns the minimisation of a convex separable piecewise-linear objective function, subject to linear constraints. In this paper a subarea of PLP called Network Piecewise-Linear Programming (NPLP) is explored. The paper presents four specialised algorithms for NPLP: (Strongly Feasible) Primal Simplex, Dual Method, Out-of-Kilter and (Strongly Polynomial) Cost-Scaling and their relative efficiency is studied. A statistically designed experiment is used to perform a computational comparison of the algorithms. The response variable observed in the experiment is the CPU time to solve randomly generated network piecewise-linear problems classified according to problem class (Transportation, Transshipment and Circulation), problem size, extent of capacitation, and number of breakpoints per arc. Results and conclusions on performance of the algorithms are reported.

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This article describes a methodological approach to conditional reasoning in online asynchronous learning environments such as Virtual-U VGroups, developed by SFU, BC, Canada, consistent with the notion of meaning implication: If part of a meaning C is embedded in B and a part of a meaning B is embedded in A, then A implies C in terms of meaning [Piaget 91]. A new transcript analysis technique was developed to assess the flows of conditional meaning implications and to identify the occurrence of hypotheses and connections among them in two human science graduate mixed-mode online courses offered in the summer/spring session of 1997 by SFU. Flows of conditional meaning implications were confronted with Virtual-U VGroups threads and results of the two courses were compared. Findings suggest that Virtual-U VGroups is a knowledge-building environment although the tree-like Virtual-U VGroups threads should be transformed into neuronal-like threads. Findings also suggest that formulating hypotheses together triggers a collaboratively problem-solving process that scaffolds knowledge-building in asynchronous learning environments: A pedagogical technique and an built-in tool for formulating hypotheses together are proposed. © Springer Pub. Co.

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A study was developed in order to build a function M invariant in time, by means of Hamiltonian's formulation, taking into account the equation associated to the problem, showing that starting from this function the equation of motion of the system with the contour conditions for non-conservative considered problems can be obtained. The Hamiltonian method is extended for these kind of systems in order to validate for non-potential operators through variational approach.

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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. Neural networks with feedback connections provide a computing model capable of solving a large class of optimization problems. This paper presents a novel approach for solving dynamic programming problems using artificial neural networks. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid-subspace technique. These parameters guarantee the convergence of the network to the equilibrium points which represent solutions (not necessarily optimal) for the dynamic programming problem. Simulated examples are presented and compared with other neural networks. The results demonstrate that proposed method gives a significant improvement.

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A branch and bound algorithm is proposed to solve the H2-norm model reduction problem and the H2-norm controller reduction problem, with conditions assuring convergence to the global optimum in finite time. The lower and upper bounds used in the optimization procedure are obtained through linear matrix inequalities formulations. Examples illustrate the results.

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Mathematical programming problems with equilibrium constraints (MPEC) are nonlinear programming problems where the constraints have a form that is analogous to first-order optimality conditions of constrained optimization. We prove that, under reasonable sufficient conditions, stationary points of the sum of squares of the constraints are feasible points of the MPEC. In usual formulations of MPEC all the feasible points are nonregular in the sense that they do not satisfy the Mangasarian-Fromovitz constraint qualification of nonlinear programming. Therefore, all the feasible points satisfy the classical Fritz-John necessary optimality conditions. In principle, this can cause serious difficulties for nonlinear programming algorithms applied to MPEC. However, we show that most feasible points do not satisfy a recently introduced stronger optimality condition for nonlinear programming. This is the reason why, in general, nonlinear programming algorithms are successful when applied to MPEC.

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This article addresses the problem of stability of impulsive control systems whose dynamics are given by measure driven differential inclusions. One important feature concerns the adopted solution which allows the consideration of systems whose singular dynamics do not satisfy the so-called Frobenius condition. After extending the conventional notion of control Lyapounov pair for impulsive systems, some stability conditions of the Lyapounov type are given. Some conclusions follow the outline of the proof of the main result.

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Tuberculosis (TB), an infectious disease readily transmitted between animals and humans, is an great threat to public and animal health a like and has been declared an international emergency. According to the WHO, animal TB is a source of much concern, especially in the poorer countries where there is little awareness of the problem. Thus, improvements in veterinary health are essential, with regard to infection by Mycobacterium bovis, particularly in areas where the public is at risk. The prevalence of infected animals in Brazil is about 1%, whereas, in the dairy cattle region of São Carlos, the average proportion of positive tests was found to be 3. 1% from 1987 to 1996. The current research was carried out to investigate the prevalence, in the region, of dairy cattle reacting positively to the tuberculin test, from 1997 to the first half of 2001. The results were obtained by searching through the data collected by the Federal Inspection Authority, and they indicated an average prevalence of 1.3% over the period, similar to the official national average. It was concluded that bovine TB continues to be present in the region, posing a potential threat of infection to the human population.

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Here the results for CD4+T cells count and the viral load obtained from HIV sero-positive patients are compared with results from numerical simulations by computer. Also, the standard scheme of administration of drugs anti HIV (HAART schemes) which uses constant doses is compared with an alternative sub-optimal teatment scheme which uses variable drug dosage according to the evolution of a quantitative measure of the side effects. The quantitative analysis done here shows that it is possible to obtain, using the alternative scheme, the same performance of actual data but using variable dosage and having fewer side effects. Optimal control theory is used to solve and also to provide a prognosis related to the strategies for control of viraemia.