924 resultados para Control Network


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Esse trabalho tem por objetivo o desenvolvimento de um sistema inteligente para detecção da queima no processo de retificação tangencial plana através da utilização de uma rede neural perceptron multi camadas, treinada para generalizar o processo e, conseqüentemente, obter o limiar de queima. em geral, a ocorrência da queima no processo de retificação pode ser detectada pelos parâmetros DPO e FKS. Porém esses parâmetros não são eficientes nas condições de usinagem usadas nesse trabalho. Os sinais de emissão acústica e potência elétrica do motor de acionamento do rebolo são variáveis de entrada e a variável de saída é a ocorrência da queima. No trabalho experimental, foram empregados um tipo de aço (ABNT 1045 temperado) e um tipo de rebolo denominado TARGA, modelo ART 3TG80.3 NVHB.

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Optimised placement of control and protective devices in distribution networks allows for a better operation and improvement of the reliability indices of the system. Control devices (used to reconfigure the feeders) are placed in distribution networks to obtain an optimal operation strategy to facilitate power supply restoration in the case of a contingency. Protective devices (used to isolate faults) are placed in distribution systems to improve the reliability and continuity of the power supply, significantly reducing the impacts that a fault can have in terms of customer outages, and the time needed for fault location and system restoration. This paper presents a novel technique to optimally place both control and protective devices in the same optimisation process on radial distribution feeders. The problem is modelled through mixed integer non-linear programming (MINLP) with real and binary variables. The reactive tabu search algorithm (RTS) is proposed to solve this problem. Results and optimised strategies for placing control and protective devices considering a practical feeder are presented. (c) 2007 Elsevier B.V. All rights reserved.

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A Internet atual vem sofrendo vários problemas em termos de escalabilidade, desempenho, mobilidade, etc., devido ao vertiginoso incremento no número de usuários e o surgimento de novos serviços com novas demandas, propiciando assim o nascimento da Internet do Futuro. Novas propostas sobre redes orientadas a conteúdo, como a arquitetura Entidade Titulo (ETArch), proveem novos serviços para este tipo de cenários, implementados sobre o paradigma de redes definidas por software. Contudo, o modelo de transporte do ETArch é equivalente ao modelo best-effort da Internet atual, e vem limitando a confiabilidade das suas comunicações. Neste trabalho, ETArch é redesenhado seguindo o paradigma do sobreaprovisionamento de recursos para conseguir uma alocação de recursos avançada integrada com OpenFlow. Como resultado, o framework SMART (Suporte de Sessões Móveis com Alta Demanda de Recursos de Transporte), permite que a rede defina semanticamente os requisitos qualitativos das sessões para assim gerenciar o controle de Qualidade de Serviço visando manter a melhor Qualidade de Experiência possível. A avaliação do planos de dados e de controle teve lugar na plataforma de testes na ilha do projeto OFELIA, mostrando o suporte de aplicações móveis multimídia com alta demanda de recursos de transporte com QoS e QoE garantidos através de um esquema de sinalização restrito em comparação com o ETArch legado

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

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The accurate determination of thermophysical properties of milk is very important for design, simulation, optimization, and control of food processing such as evaporation, heat exchanging, spray drying, and so forth. Generally, polynomial methods are used for prediction of these properties based on empirical correlation to experimental data. Artificial neural networks are better Suited for processing noisy and extensive knowledge indexing. This article proposed the application of neural networks for prediction of specific heat, thermal conductivity, and density of milk with temperature ranged from 2.0 to 71.0degreesC, 72.0 to 92.0% of water content (w/w), and 1.350 to 7.822% of fat content (w/w). Artificial neural networks presented a better prediction capability of specific heat, thermal conductivity, and density of milk than polynomial modeling. It showed a reasonable alternative to empirical modeling for thermophysical properties of foods.

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An algorithm is presented that finds the optimal plan long-term transmission for till cases studied, including relatively large and complex networks. The knowledge of optimal plans is becoming more important in the emerging competitive environment, to which the correct economic signals have to be sent to all participants. The paper presents a new specialised branch-and-bound algorithm for transmission network expansion planning. Optimality is obtained at a cost, however: that is the use of a transportation model for representing the transmission network, in this model only the Kirchhoff current law is taken into account (the second law being relaxed). The expansion problem then becomes an integer linear program (ILP) which is solved by the proposed branch-and-bound method without any further approximations. To control combinatorial explosion the branch- and bound algorithm is specialised using specific knowledge about the problem for both the selection of candidate problems and the selection of the next variable to be used for branching. Special constraints are also used to reduce the gap between the optimal integer solution (ILP program) and the solution obtained by relaxing the integrality constraints (LP program). Tests have been performed with small, medium and large networks available in the literature.

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Nowadays, networks must support applications such as: distance learning, electronic commerce, access to Internet, Intranets and Extranets, voice over IP (Internet Protocol) and many others. These new applications, employing data, voice, and video traffic, require high bandwidth and Quality of Service (QoS). The ATM (Asynchronous Transfer Mode) technology, together with dynamic resource allocation methods, offers network connections that guarantee QoS parameters, such as minimum losses and delays. This paper presents a system that uses Network Management Functions together with dynamic resource allocation for provision of the end-to-end QoS parameters for rt-VBR connections.

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This article describes the simulation and analysis of collisionless optical interconnection network, which the objective is to achieve a high performance level based on a single protocol control. The optical coupler has one shared control channel and N communication channels. Each network node two communication modules one for packet transmission/reception and another for control channel access. We show by simulation that system achieves a high performance and ensures high scalability.

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Stroma-epithelium relationships are of great relevance in prostatic morphogenesis and physiology, However, little knowledge exists about either stromal cells or extracellular matrix composition and arrangement in this system, Ultrastructural analysis revealed the existence of a microfibrillar system which occupies large areas of the rat prostatic stroma, In this work, we have applied immunocytochemistry and an ATP treatment for the ultrastructural identification of collagen type VI microfibrils, aiming at examining its participation in the prostatic microfibrillar network. Immunocytochemistry was also extended to a human case of prostatic nodular hyperplasia, Both methods succeeded in identifying collagen type VI in the rat ventral prostate, Collagen type VI is evenly distributed throughout the stroma but mainly associated with the basal lamina, collagen fibrils, and around the stromal cells, the use of ATP treatment allowed for the discrimination between collagen type VI and elastin-associated microfibrils, and demonstrated that these two classes of microfibrils establish an extended, mixed, and open network. The same aspects of association with the basal lamina, with stromal cells (particularly with smooth muscle cells), and with fibrillar components of the stroma were observed in the human tissue, We suggest that the collagen type VI and elastin-associated microfibril system may be involved in the control of some aspects of cellular behavior and may also play a structural role, maintaining the organ integrity after the deformations occurring under smooth muscle contraction.

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This paper proposes an approach of optimal sensitivity applied in the tertiary loop of the automatic generation control. The approach is based on the theorem of non-linear perturbation. From an optimal operation point obtained by an optimal power flow a new optimal operation point is directly determined after a perturbation, i.e., without the necessity of an iterative process. This new optimal operation point satisfies the constraints of the problem for small perturbation in the loads. The participation factors and the voltage set point of the automatic voltage regulators (AVR) of the generators are determined by the technique of optimal sensitivity, considering the effects of the active power losses minimization and the network constraints. The participation factors and voltage set point of the generators are supplied directly to a computational program of dynamic simulation of the automatic generation control, named by power sensitivity mode. Test results are presented to show the good performance of this approach. (C) 2008 Elsevier B.V. All rights reserved.

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One of the major problems facing Blast Furnaces is the occurrence of cracks in taphole mud, as the underlying causes are not easily identifiable. The absence of this knowledge makes it difficult the use of conventional techniques for predictability and mitigation. This paper will address the application of Probabilistic Neural Network using the Matlab software as a means to detect and control such cracks. The most relevant BF operational variables were picked through the statistic tool "Principal Component Analysis - PCA." Based upon the selection of these variables a probabilistic neural network was built. A set of BF operational data, consisting of 30 controlling variables, was divided into 2 groups, one of which for network training, and the other one to validate the neural network. The neural network got 98% of the cases right. The results show the effectiveness of this tool for crack prediction in relation to clay intrinsic properties and as a result of the fluctuation in operational variables.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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The task of controlling urban traffic requires flexibility, adaptability and handling uncertain information spread through the intersection network. The use of fuzzy sets concepts convey these characteristics to improve system performance. This paper reviews a distributed traffic control system built upon a fuzzy distributed architecture previously developed by the authors. The emphasis of the paper is on the application of the system to control part of Campinas downtown area. Simulation experiments considering several traffic scenarios were performed to verify the capabilities of the system in controlling a set of coupled intersections. The performance of the proposed system is compared with conventional traffic control strategies under the same scenarios. The results obtained show that the distributed traffic control system outperforms conventional systems as far as average queues, average delay and maximum delay measures are concerned.

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A model for preventive control in electrical systems is presented, taking into account the dynamic aspects of the network. Among these aspects, the effects provoked by perturbations which cause oscillations in synchronous machine angles (transient stability), such as electric equipment outages and short circuits, are presented. The energy function is used to measure the stability of the system using a procedure defined as the security margin. The control actions employed are load shedding and generation reallocation. An application of the methodology to a system located in southern Brazil, which is composed of 10 synchronous machines, 45 busses, and 72 transmission lines. The results confirm the theoretical studies.

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This work presents a methodology to analyze transient stability for electric energy systems using artificial neural networks based on fuzzy ARTMAP architecture. This architecture seeks exploring similarity with computational concepts on fuzzy set theory and ART (Adaptive Resonance Theory) neural network. The ART architectures show plasticity and stability characteristics, which are essential qualities to provide the training and to execute the analysis. Therefore, it is used a very fast training, when compared to the conventional backpropagation algorithm formulation. Consequently, the analysis becomes more competitive, compared to the principal methods found in the specialized literature. Results considering a system composed of 45 buses, 72 transmission lines and 10 synchronous machines are presented. © 2003 IEEE.