919 resultados para Network-on-Chip (NoC)
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O presente trabalho explora as causas pelas quais o campo da moda plus size carece de legitimidade com as consumidoras plus size. Eu explorei o assunto em três artigos. No primeiro, eu estudo o processo de legitimação de um novo mercado emergente, o mercado da moda plus size brasileira e os desafios para sua a institucionalização. Eu conduzi dezessete entrevistas com consumidoras plus size, uma netnografia em quatro blogs de moda plus size brasileiros e analisei de maneira semiótica um site que vende roupas de moda plus size. Meus resultados indicam que, apesar de ter atores legítimos que promovem essas marcas de moda plus size, o campo da moda plus size ainda é percebido como uma versão vergonhosa do campo da moda. Defendo aqui que o fato de uma das lógicas de campo da moda plus size ser estigma, acaba afetando os projetos identitários das consumidoras de maneira depreciativa, de forma elas não se envolvem em práticas de capital cultural que ocorrem dentro do campo da moda plus size. No segundo artigo, eu conduzi uma introspecção genealógica em que eu pesquisei questões de identidade. Como uma mulher (que se assume ) plus size, eu imaginei que seria relevante para olhar para dentro de mim mesma, a fim de explorar a forma como a minha identidade liga-se com a rede semiótica-material que me rodeia em termos de moda, alimentos e outros elementos. Meus dados vieram tanto de técnicas de introspecção simultâneas, quanto retrospectivas. Em termos teóricos, eu usei a ideia de ―assemblages‖ e eu foquei minha análise tanto nos aspectos materiais da minha rede de consumo, quanto na estabilidade da rede. As consequências da minha assemblage estão ligadas a uma gestão de qualidade total da minha identidade, tanto online como off-line, refletidas em práticas de consumo que se conectam à ideia de uma lógica de consumo bulímica em que o consumo de alimentos e gestão corpo estão interligadas. Por fim, no meu terceiro artigo, eu explorei o conceito de identidade a partir do consumo da moda feminina plus size. Foram feitas catorze entrevistas fenomenológicas, cujos dados foram analisados a partir de uma perspectiva hermenêutica. Três categorias temáticas emergiram da análise de dados: a construção da identidade por meio da moda, elementos de identidade plus size e estratégias criativas para lidar com a falta de produtos para mulheres plus size no varejo. Entre os principais resultados, destacam-se a forma como o termo plus size atua como estigma, influenciando projetos de identidade das consumidoras, o papel do varejo no processo de estigmatização e a saga épica de compras, que envolve um "mercado negro", com a participação de vendedores. Eu concluo discutindo o papel da identidade na instabilidade do campo da moda plus size.
5th BRICS Trade and Economic Research Network (TERN) meeting: the impact of mega agreements on BRICS
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The BRICS TERN – BRICS Trade and Economics Research Network is a group of independent research institutes established four years ago by five think tanks from Brazil, Russia, India, China and South Africa. The main objective of the network is to study different aspects of trade and economic relations amongst these five countries. The purpose of the V BRICS TERN Meeting was to analyze and debate the effects of the negotiations of the Mega Agreements, mainly those initiated by the US and the EU, already in negotiation, to each of the BRICS Trade Policies. Both Mega Agreements were examined – the Trans Pacific Partnership (TPP) and the Transatlantic Trade and Investment Partnership (TTIP). The studies included the main impacts on trade flows and on the international trade rules system, respecting the perspective of each of the countries concerned. This workshop was an initiative of the Center for Global Trade and Investments (CGTI), a think-tank on International Trade held by FGV Sao Paulo School of Economics. Its main objective is the research on trade regulation, preferential trade agreements, trade and currency, trade and global value chains, through legal analysis and economic modelling. One of its main researches, now, is on the potential economic and legal impacts of the Mega Agreements on Brazil and WTO rules. This meeting was organized in March14, 2014, in Rio de Janeiro, in a perfect timing for introducing such issues in the international agenda, in advance of the 6th BRICS Summit scheduled to be held in Brazil in July 2014.
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This paper describes a method of identifying morphological attributes that classify wear particles in relation to the wear process from which they originate and permit the automatic identification without human expertise. The method is based on the use of Multi Layer Perceptron (MLP) for analysis of specific types of microscopic wear particles. The classification of the wear particles was performed according to their morphological attributes of size and aspect ratio, among others. (C) 2010 Journal of Mechanical Engineering. All rights reserved.
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This work presents a methodology to analyze electric power systems transient stability for first swing using a neural network based on adaptive resonance theory (ART) architecture, called Euclidean ARTMAP neural network. The ART architectures present plasticity and stability characteristics, which are very important for the training and to execute the analysis in a fast way. The Euclidean ARTMAP version provides more accurate and faster solutions, when compared to the fuzzy ARTMAP configuration. Three steps are necessary for the network working, training, analysis and continuous training. The training step requires much effort (processing) while the analysis is effectuated almost without computational effort. The proposed network allows approaching several topologies of the electric system at the same time; therefore it is an alternative for real time transient stability of electric power systems. To illustrate the proposed neural network an application is presented for a multi-machine electric power systems composed of 10 synchronous machines, 45 buses and 73 transmission lines. (C) 2010 Elsevier B.V. All rights reserved.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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This work describes an application of a multilayer perceptron neural network technique to correct dome emission effects on longwave atmospheric radiation measurements carried out using an Eppley Precision Infrared Radiometer (PIR) pyrgeometer. It is shown that approximately 7-month-long measurements of dome and case temperatures and meteorological variables available in regular surface stations (global solar radiation, air temperature, and air relative humidity) are enough to train the neural network algorithm and correct the observed longwave radiation for dome temperature effects in surface stations with climates similar to that of the city of São Paulo, Brazil. The network was trained using data from 15 October 2003 to 7 January 2004 and verified using data, not present during the network-training period, from 8 January to 30 April 2004. The longwave radiation values generated by the neural network technique were very similar to the values obtained by Fairall et al., assumed here as the reference approach to correct dome emission effects in PIR pyrgeometers. Compared to the empirical approach the neural network technique is less limited to sensor type and time of day (allows nighttime corrections).
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The new complex [Cu(NCS)(2)(pn)] (1) (pn = 1,3-propanediamine) has been synthesized and characterized by elemental analysis, infrared and electronic spectroscopy. Single crystal X-ray diffraction studies revealed that complex 1 is made up of neutral [Cu(NCS)(2)(pn)] units which are connected by mu-1,3,3-thiocyanato groups to yield a 2D metal-organic framework with a brick-wall network topology. Intermolecular hydrogen bonds of the type NH...SCN and NH...NCS are also responsible for the stabilization of the crystal structure. (c) 2007 Elsevier B.V. All rights reserved.
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This paper describes a methodology for solving efficiently the sparse network equations on multiprocessor computers. The methodology is based on the matrix inverse factors (W-matrix) approach to the direct solution phase of A(x) = b systems. A partitioning scheme of W-matrix , based on the leaf-nodes of the factorization path tree, is proposed. The methodology allows the performance of all the updating operations on vector b in parallel, within each partition, using a row-oriented processing. The approach takes advantage of the processing power of the individual processors. Performance results are presented and discussed.
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We have investigated and extensively tested three families of non-convex optimization approaches for solving the transmission network expansion planning problem: simulated annealing (SA), genetic algorithms (GA), and tabu search algorithms (TS). The paper compares the main features of the three approaches and presents an integrated view of these methodologies. A hybrid approach is then proposed which presents performances which are far better than the ones obtained with any of these approaches individually. Results obtained in tests performed with large scale real-life networks are summarized.
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Undoped and/or doped with 1 mol% of Co2+ Mg2TiO4 and Mg2SnO4 powders were synthesized by the polymeric precursor method. The influence of the network former (Sn4+ or Ti4+) on the thermal, structural and optical properties was investigated. The recorded mass losses are due to the escape of water and adsorbed gases and to the elimination of the organic matter. Mg2TiO4 crystallizes at lower temperatures and also presents more ordered structure with a smaller unit call and having more intense green color than Mg2SnO4 has.
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This work is devoted to Study and discuss the main methods to solve the network cost allocation problem both for generators and demands. From the presented, compared and discussed methods, the first one is based on power injections, the second deals with proportional sharing factors, the third is based upon Equivalent Bilateral Exchanges, the fourth analyzes the power How sensitivity in relation to the power injected, and the last one is based on Z(bus) network matrix. All the methods are initially illustrated using a 4-bus system. In addition, the IEEE 24-bus RTS system is presented for further comparisons and analysis. Appropriate conclusions are finally drawn. (C) 2008 Elsevier B.V. All rights reserved.
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This paper presents a technique for oriented texture classification which is based on the Hough transform and Kohonen's neural network model. In this technique, oriented texture features are extracted from the Hough space by means of two distinct strategies. While the first operates on a non-uniformly sampled Hough space, the second concentrates on the peaks produced in the Hough space. The described technique gives good results for the classification of oriented textures, a common phenomenon in nature underlying an important class of images. Experimental results are presented to demonstrate the performance of the new technique in comparison, with an implemented technique based on Gabor filters.