911 resultados para Redes definidas por software


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The microstrip antennas are in constant evidence in current researches due to several advantages that it presents. Fractal geometry coupled with good performance and convenience of the planar structures are an excellent combination for design and analysis of structures with ever smaller features and multi-resonant and broadband. This geometry has been applied in such patch microstrip antennas to reduce its size and highlight its multi-band behavior. Compared with the conventional microstrip antennas, the quasifractal patch antennas have lower frequencies of resonance, enabling the manufacture of more compact antennas. The aim of this work is the design of quasi-fractal patch antennas through the use of Koch and Minkowski fractal curves applied to radiating and nonradiating antenna s edges of conventional rectangular patch fed by microstrip inset-fed line, initially designed for the frequency of 2.45 GHz. The inset-fed technique is investigated for the impedance matching of fractal antennas, which are fed through lines of microstrip. The efficiency of this technique is investigated experimentally and compared with simulations carried out by commercial software Ansoft Designer used for precise analysis of the electromagnetic behavior of antennas by the method of moments and the neural model proposed. In this dissertation a study of literature on theory of microstrip antennas is done, the same study is performed on the fractal geometry, giving more emphasis to its various forms, techniques for generation of fractals and its applicability. This work also presents a study on artificial neural networks, showing the types/architecture of networks used and their characteristics as well as the training algorithms that were used for their implementation. The equations of settings of the parameters for networks used in this study were derived from the gradient method. It will also be carried out research with emphasis on miniaturization of the proposed new structures, showing how an antenna designed with contours fractals is capable of a miniaturized antenna conventional rectangular patch. The study also consists of a modeling through artificial neural networks of the various parameters of the electromagnetic near-fractal antennas. The presented results demonstrate the excellent capacity of modeling techniques for neural microstrip antennas and all algorithms used in this work in achieving the proposed models were implemented in commercial software simulation of Matlab 7. In order to validate the results, several prototypes of antennas were built, measured on a vector network analyzer and simulated in software for comparison

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This dissertation aims to develop a software applied to a communication system for a wireless sensor network (WSN) for tracking analog and digital variables and control valve of the gas flow in artificial oil s elevation units, Plunger Lift type. The reason for this implementation is due to the fact that, in the studied plant configuration, the sensors communicate with the PLC (Programmable and Logic Controller) by the cables and pipelines, making any changes in that system, such as changing the layout of it, as well as inconveniences that arise from the nature of the site, such as the vicinity s animals presence that tend to destroy the cables for interconnection of sensors to the PLC. For software development, was used communication polling method via SMAC protocol (Simple Medium Access ControlIEEE 802.15.4 standard) in the CodeWarrior environment to which generated a firmware, loaded into the WSN s transceivers, present in the kit MC13193-EVK, (all items described above are owners of Freescale Semiconductors Inc.). The network monitoring and parameterization used in its application, was developed in LabVIEW software from National Instruments. The results were obtained through the observation of the network s behavior of sensors proposal, focusing on aspects such as: indoor and outdoor quantity of packages received and lost, general aspects of reliability in data transmission, coexistence with other types of wireless networks and power consumption under different operating conditions. The results were considered satisfactory, which showed the software efficiency in this communication system

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Nowadays, where the market competition requires products with better quality and a constant search for cost savings and a better use of raw materials, the research for more efficient control strategies becomes vital. In Natural Gas Processin Units (NGPUs), as in the most chemical processes, the quality control is accomplished through their products composition. However, the chemical composition analysis has a long measurement time, even when performed by instruments such as gas chromatographs. This fact hinders the development of control strategies to provide a better process yield. The natural gas processing is one of the most important activities in the petroleum industry. The main economic product of a NGPU is the liquefied petroleum gas (LPG). The LPG is ideally composed by propane and butane, however, in practice, its composition has some contaminants, such as ethane and pentane. In this work is proposed an inferential system using neural networks to estimate the ethane and pentane mole fractions in LPG and the propane mole fraction in residual gas. The goal is to provide the values of these estimated variables in every minute using a single multilayer neural network, making it possibly to apply inferential control techniques in order to monitor the LPG quality and to reduce the propane loss in the process. To develop this work a NGPU was simulated in HYSYS R software, composed by two distillation collumns: deethanizer and debutanizer. The inference is performed through the process variables of the PID controllers present in the instrumentation of these columns. To reduce the complexity of the inferential neural network is used the statistical technique of principal component analysis to decrease the number of network inputs, thus forming a hybrid inferential system. It is also proposed in this work a simple strategy to correct the inferential system in real-time, based on measurements of the chromatographs which may exist in process under study

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This work proposes hardware architecture, VHDL described, developed to embedded Artificial Neural Network (ANN), Multilayer Perceptron (MLP). The present work idealizes that, in this architecture, ANN applications could easily embed several different topologies of MLP network industrial field. The MLP topology in which the architecture can be configured is defined by a simple and specifically data input (instructions) that determines the layers and Perceptron quantity of the network. In order to set several MLP topologies, many components (datapath) and a controller were developed to execute these instructions. Thus, an user defines a group of previously known instructions which determine ANN characteristics. The system will guarantee the MLP execution through the neural processors (Perceptrons), the components of datapath and the controller that were developed. In other way, the biases and the weights must be static, the ANN that will be embedded must had been trained previously, in off-line way. The knowledge of system internal characteristics and the VHDL language by the user are not needed. The reconfigurable FPGA device was used to implement, simulate and test all the system, allowing application in several real daily problems

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In a real process, all used resources, whether physical or developed in software, are subject to interruptions or operational commitments. However, in situations in which operate critical systems, any kind of problem may bring big consequences. Knowing this, this paper aims to develop a system capable to detect the presence and indicate the types of failures that may occur in a process. For implementing and testing the proposed methodology, a coupled tank system was used as a study model case. The system should be developed to generate a set of signals that notify the process operator and that may be post-processed, enabling changes in control strategy or control parameters. Due to the damage risks involved with sensors, actuators and amplifiers of the real plant, the data set of the faults will be computationally generated and the results collected from numerical simulations of the process model. The system will be composed by structures with Artificial Neural Networks, trained in offline mode using Matlab®

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This work develops a methodology for defining the maximum active power being injected into predefined nodes in the studied distribution networks, considering the possibility of multiple accesses of generating units. The definition of these maximum values is obtained from an optimization study, in which further losses should not exceed those of the base case, i.e., without the presence of distributed generation. The restrictions on the loading of the branches and voltages of the system are respected. To face the problem it is proposed an algorithm, which is based on the numerical method called particle swarm optimization, applied to the study of AC conventional load flow and optimal load flow for maximizing the penetration of distributed generation. Alternatively, the Newton-Raphson method was incorporated to resolution of the load flow. The computer program is performed with the SCILAB software. The proposed algorithm is tested with the data from the IEEE network with 14 nodes and from another network, this one from the Rio Grande do Norte State, at a high voltage (69 kV), with 25 nodes. The algorithm defines allowed values of nominal active power of distributed generation, in percentage terms relative to the demand of the network, from reference values

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Industrial automation networks is in focus and is gradually replacing older architectures of systems used in automation world. Among existing automation networks, most prominent standard is the Foundation Fieldbus (FF). This particular standard was chosen for the development of this work thanks to its complete application layer specification and its user interface, organized as function blocks and that allows interoperability among different vendors' devices. Nowadays, one of most seeked solutions on industrial automation are the indirect measurements, that consist in infering a value from measures of other sensors. This can be made through implementation of the so-called software sensors. One of the most used tools in this project and in sensor implementation are artificial neural networks. The absence of a standard solution to implement neural networks in FF environment makes impossible the development of a field-indirect-measurement project, besides other projects involving neural networks, unless a closed proprietary solution is used, which dos not guarantee interoperability among network devices, specially if those are from different vendors. In order to keep the interoperability, this work's goal is develop a solution that implements artificial neural networks in Foundation Fieldbus industrial network environment, based on standard function blocks. Along the work, some results of the solution's implementation are also presented

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This work aims to investigate the behavior of fractal elements in planar microstrip structures. In particular, microstrip antennas and frequency selective surfaces (FSSs) had changed its conventional elements to fractal shapes. For microstrip antennas, was used as the radiating element of Minkowski fractal. The feeding method used was microstrip line. Some prototypes were built and the analysis revealed the possibility of miniaturization of structures, besides the multiband behavior, provided by the fractal element. In particular, the Minkowski fractal antenna level 3 was used to exploit the multiband feature, enabling simultaneous operation of two commercial tracks (Wi-Fi and WiMAX) regulated by ANATEL. After, we investigated the effect of switches that have been placed on the at the pre-fractal edges of radiating element. For the FSSs, the fractal used to elements of FSSs was Dürer s pentagon. Some prototypes were built and measured. The results showed a multiband behavior of the structure provided by fractal geometry. Then, a parametric analysis allowed the analysis of the variation of periodicity on the electromagnetic behavior of FSS, and its bandwidth and quality factor. For numerical and experimental characterization of the structures discussed was used, respectively, the commercial software Ansoft DesignerTM and a vector network analyzer, Agilent N5230A model

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

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A serious problem that affects an oil refinery s processing units is the deposition of solid particles or the fouling on the equipments. These residues are naturally present on the oil or are by-products of chemical reactions during its transport. A fouled heat exchanger loses its capacity to adequately heat the oil, needing to be shut down periodically for cleaning. Previous knowledge of the best period to shut down the exchanger may improve the energetic and production efficiency of the plant. In this work we develop a system to predict the fouling on a heat exchanger from the Potiguar Clara Camarão Refinery, based on data collected in a partnership with Petrobras. Recurrent Neural Networks are used to predict the heat exchanger s flow in future time. This variable is the main indicator of fouling, because its value decreases gradually as the deposits on the tubes reduce their diameter. The prediction could be used to tell when the flow will have decreased under an acceptable value, indicating when the exchanger shutdown for cleaning will be needed

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One of the current major concerns in engineering is the development of aircrafts that have low power consumption and high performance. So, airfoils that have a high value of Lift Coefficient and a low value for the Drag Coefficient, generating a High-Efficiency airfoil are studied and designed. When the value of the Efficiency increases, the aircraft s fuel consumption decreases, thus improving its performance. Therefore, this work aims to develop a tool for designing of airfoils from desired characteristics, as Lift and Drag coefficients and the maximum Efficiency, using an algorithm based on an Artificial Neural Network (ANN). For this, it was initially collected an aerodynamic characteristics database, with a total of 300 airfoils, from the software XFoil. Then, through the software MATLAB, several network architectures were trained, between modular and hierarchical, using the Back-propagation algorithm and the Momentum rule. For data analysis, was used the technique of cross- validation, evaluating the network that has the lowest value of Root Mean Square (RMS). In this case, the best result was obtained for a hierarchical architecture with two modules and one layer of hidden neurons. The airfoils developed for that network, in the regions of lower RMS, were compared with the same airfoils imported into the software XFoil

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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In Brazil, there have been several GPS applications and with the introduction of the Law 10.267/2001 that among other dispositions, deals with georeferencing of the rural parcels. However, most commercial softwares of processing and adjustment of GPS data don't let users to evaluate their results in a reliable way. For example, the constraints are normally used as absolute, which provides results with very optimists precisions. The adoption of additional analyses and the implementation of softwares can reduce these kinds of problems. Thus, a software for adjustment of GPS networks was developed, aiming at assisting the requirements of the Law 10.267/2001 in a reliable way. In this context, in this work it is analyzed the adjustments of GPS networks, by using absolute and relative constraints. In the latter, the adjustments were accomplished considering and not considering the correlations among the coordinate positions.

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O presente estudo discute a formação de Redes Sociais no cotidiano da Estratégia Saúde da Família, a partir de aportes da teoria sociológica sobre redes, interações, dádiva e reconhecimento. O objetivo geral é analisar as redes sociais locais em saúde a partir da interação de usuários e profissionais da Estratégia Saúde da Família na Unidade de Saúde de Ligéia, em Natal, RN. Seus objetivos específicos são: Mapear as redes sociais locais em saúde existentes no território adscrito; Identificar os tipos de interações cotidianas entre os sujeitos; Compreender a percepção dos sujeitos sobre o processo de formação de redes sociais a partir das interações. Caracteriza-se enquanto pesquisa qualitativa exploratória cujos sujeitos foram profissionais e usuários vinculados à referida unidade de saúde. Para a coleta de dados foram utilizadas entrevistas individuais semiestruturadas e debates em grupos focais, estimulados pela Metodologia de Análise de Redes do Cotidiano (MARES), pertinente para abordar a complexidade das relações sociais e mapear os diferentes conteúdos expressos e as formas de mobilização coletiva. A análise dos dados foi realizada através da Técnica de Análise Temática de Conteúdo, proposta por Minayo. Os resultados foram interpretados à luz das Teorias da Dádiva (Mauss) e do Reconhecimento (Honneth). Os sujeitos visualizaram: Rede Virtual (28,20%); Rede de Atenção à Saúde (25,64%); Redes de Usuários (17,95%); Rede Pessoal (10,26%); Conselho Comunitário (10,26%); Escolas (7,69%). Os participantes não perceberam os arranjos familiares enquanto Redes Sociais. Os tipos de interações sociais identificadas foram: Confrontação/Negociação (41.02%); Harmônicas (25,70%); Correlativas (17,90%); Definidas pela Organização (15,38%). A formação de redes sociais ocorre a partir de interações cotidianas entre pessoas, pela articulação inseparável de conteúdos e formas, catalisadas pelo contexto, experiência e cognição, valorizando a liberdade, a expressividade e a diversidade dos parceiros de significação. Foram encontradas duas categorias, na percepção dos sujeitos, sobre a formação de redes sociais do cotidiano: Diálogo e Encontro. Validamos e recomendamos o uso da metodologia MARES: Na formação, para despertar uma visão mais tolerante e humana de si e do outro; Na avaliação qualitativa dos serviços, por facilitar a reflexão sobre a prática e (re)organização do processo de trabalho; Na comunidade, para estimular movimentos sociais existentes ou emergentes. A aposta no circuito da dádiva e do reconhecimento recíproco, durante o trânsito nas redes sociais em saúde, pode ser capaz de tecer uma práxis transformadora, pela busca e alcance de confiança, respeito e estima, nos espaços de encontro entre usuários e profissionais da Estratégia Saúde da Família

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A maioria da soluções apresentadas como candidatas à implementação de serviços de distribuição de áudio e vídeo, têm sido projetadas levando-se em consideração determinadas condições de infra-estrutura, formato dos fluxos de vídeo a serem transmitidos, ou ainda os tipos de clientes que serão atendidos pelo serviço. Aplicações que utilizam serviços de distribuição de vídeo normalmente precisam lidar com grandes oscilações na demanda pelo serviço devido a entrada e saída de usuários do serviço. Com exemplo, basta observar a enorme variação nos níveis de audiência de programas de televisão. Este comportamento coloca um importante requisito para esta classe de sistemas distribuídos: a capacidade de reconfiguração como conseqüência de variações na demanda. Esta dissertação apresenta um estudo que envolveu o uso de agentes móveis para implementar os servidores de um serviço de distribuição de vídeo denominada DynaVideo. Uma das principais características deste serviço é a capacidade de ajustar sua configuração em conseqüência de variações na demanda. Como os servidores DynaVideo podem replicar-se e são implementados como código móvel, seu posicionamento pode ser otimizado para atender uma dada demanda e, como conseqüência, a configuração do serviço pode ser ajustada para minimizar o consumo de recursos necessários para distribuir vídeo para seus usuários. A principal contribuição desta dissertação foi provar a viabilidade do conceito de servidores implementados como agentes móveis Java baseados no ambiente de desenvolvimento de software Aglet.