911 resultados para Análise de Sistema


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Nesta dissertação de mestrado é desenvolvido um sistema de replicação de circuitos integrados digitais (combinatórios e sequenciais), por observação do seu normal funcionamento. O sistema desenvolvido carateriza-se pela capacidade de extrair e descrever na linguagem VHDL o comportamento de um circuito integrado digital em funcionamento, utilizando técnicas não invasivas e automatizadas, suportado por um vasto conjunto de algoritmos de aquisição e análise de dados. O sistema desenvolvido assenta em dois módulos principais: um módulo de software que consiste numa plataforma de algoritmos de análise, controlo e gestão do sistema (alojada num computador) e um módulo de aquisição de dados (hardware) que consiste num circuito capaz de realizar as medições necessárias para o funcionamento do sistema, comandado pelo módulo de software. A comunicação entre os dois módulos é efetuada via porta série. Os algoritmos desenvolvidos realizam uma análise da correspondência entre entradas e saídas procurando aplicar uma aproximação a um circuito combinatório se possível, caso contrário são utilizados métodos heurísticos para efetuar uma aproximação a um circuito sequencial através de uma máquina de estados. Entradas ou saídas constantes são previamente identificados e excluídos do processo de análise, para efeitos de simplificação. Os resultados obtidos demonstram que é possível replicar o comportamento observado em circuitos digitais (combinatórios e sequenciais) desde que o número de amostras recolhidas seja adequado. Verifica-se ainda que o método desenvolvido replica a funcionalidade do circuito integrado nas condições onde o circuito está inserido.

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The starting point of the present work consisted of investigating the development of biotechnology in the Northeast region of Brazil from the perspective of a Regional Innovation System (RIS). The theoretical framework adopted relied on the approaches and concepts presented by the Neo-Schumpeterian perspective. This framework was chosen because, by means of the Innovation System concept, this literature allows us to analyze the relationships and configurations of actors, as well as the role of the state and of social, science and technology, and economic policies in the studied region. The analysis considered four selected dimensions: physical infrastructure, human capital, scientific production, and funding. These variables were chosen because they allow us to verify the possibilities and limitations of developing a biotechnology RIS in the Northeast of Brazil, and these elements would help in answering the question behind this dissertation. The location of the physical infrastructure was determined by means of bibliographic and documental research and interviews with heads of institutions that do biotechnology research. Regarding human capital, the analysis focused on resource training in biotechnology, highlighting graduate courses and research groups in the area. To measure knowledge production, we delimited scientific collaboration among researchers in the field of biotechnology as the focus of this category. For the funding dimension, information was gathered from reports available at the websites of national and state funding agencies. The data was analyzed through method triangulation, involving quantitative and qualitative research stages. To back the analyses, we revisited the integration policies in the area of Science, Technology and Innovation. Our analysis has shown that these policies play a crucial role in the development of biotechnology in the region being studied. The data revealed that the physical infrastructure is concentrated in only three states (Bahia, Ceará, and Pernambuco). In this regard, the Northeast Biotechnology Network (Renorbio) stands out as a strategic actor, enabling states with poor infrastructure to develop research through partnerships with institutions located in another state. We have also verified that the practices involving human resource training and knowledge production are factors that enable the emergence of a regional system for biotechnology in the studied region. As limitations, we have verified the low immersion level of regional actors, the heterogeneity of socioeconomic indicators, the lack of financial resources, and a low innovation culture in the business sector. Overall, we have concluded that the development of a Regional Innovation System in Biotechnology, based on the current regional dynamics, depends on an effective change in the behavior of the social agents involved, both in the national and regional dimensions as well as in the public and private spheres

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The cerium oxide has a high potential for use in removing pollutants after combustion, removal of organic matter in waste water and the fuel-cell technology. The nickel oxide is an attractive material due to its excellent chemical stability and their optical properties, electrical and magnetic. In this work, CeO2-NiO- systems on molars reasons 1:1(I), 1:2(II) e 1:3(III) metal-citric acid were synthesized using the Pechini method. We used techniques of TG / DTG and ATD to monitor the degradation process of organic matter to the formation of the oxide. By thermogravimetric analysis and applying the dynamic method proposed by Coats-Redfern, it was possible to study the reactions of thermal decomposition in order to propose the possible mechanism by which the reaction takes place, as well as the determination of kinetic parameters as activation energy, Ea, pre-exponential factor and parameters of activation. It was observed that both variables exert a significant influence on the formation of complex polymeric precursor. The model that best fitted the experimental data in the dynamic mode was R3, which consists of nuclear growth, which formed the nuclei grow to a continuous reaction interface, it proposes a spherical symmetry (order 2 / 3). The values of enthalpy of activation of the system showed that the reaction in the state of transition is exothermic. The variables of composition, together with the variable temperature of calcination were studied by different techniques such as XRD, IV and SEM. Also a study was conducted microstructure by the Rietveld method, the calculation routine was developed to run the package program FullProf Suite, and analyzed by pseudo-Voigt function. It was found that the molar ratio of variable metal-citric acid in the system CeO2-NiO (I), (II), (III) has strong influence on the microstructural properties, size of crystallites and microstrain network, and can be used to control these properties

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The artificial lifting of oil is needed when the pressure of the reservoir is not high enough so that the fluid contained in it can reach the surface spontaneously. Thus the increase in energy supplies artificial or additional fluid integral to the well to come to the surface. The rod pump is the artificial lift method most used in the world and the dynamometer card (surface and down-hole) is the best tool for the analysis of a well equipped with such method. A computational method using Artificial Neural Networks MLP was and developed using pre-established patterns, based on its geometry, the downhole card are used for training the network and then the network provides the knowledge for classification of new cards, allows the fails diagnose in the system and operation conditions of the lifting system. These routines could be integrated to a supervisory system that collects the cards to be analyzed

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This Thesis presents the elaboration of a methodological propose for the development of an intelligent system, able to automatically achieve the effective porosity, in sedimentary layers, from a data bank built with information from the Ground Penetrating Radar GPR. The intelligent system was built to model the relation between the porosity (response variable) and the electromagnetic attribute from the GPR (explicative variables). Using it, the porosity was estimated using the artificial neural network (Multilayer Perceptron MLP) and the multiple linear regression. The data from the response variable and from the explicative variables were achieved in laboratory and in GPR surveys outlined in controlled sites, on site and in laboratory. The proposed intelligent system has the capacity of estimating the porosity from any available data bank, which has the same variables used in this Thesis. The architecture of the neural network used can be modified according to the existing necessity, adapting to the available data bank. The use of the multiple linear regression model allowed the identification and quantification of the influence (level of effect) from each explicative variable in the estimation of the porosity. The proposed methodology can revolutionize the use of the GPR, not only for the imaging of the sedimentary geometry and faces, but mainly for the automatically achievement of the porosity one of the most important parameters for the characterization of reservoir rocks (from petroleum or water)