961 resultados para Operation Overlord
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Includes bibliography
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Incluye Bibliografía
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Incluye Bibliografía
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Contiene antecedentes y lineamientos para formular e impulsar un programa regional de cooperacion entre redes y sistemas nacionales de informacion existentes en America Latina y el Caribe.
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Dispute settlement mechanisms help to create a fairly predictable and accurate environment in which economic agents can pursue their activities in the international arena. The World Trade Organization (WTO) Dispute Settlement Body (DSB) has now been in operation for 10 years and it is fitting, at this point to assess the progress achieved by Latin America and the Caribbean, the region that made most use of this mechanism during the period, and whose countries have made significant gains against protectionism in key export sectors. These successes constitute important precedents which will influence upcoming multilateral negotiations and future trade disputes.This article reviews the work carried out by the DSB, the role of the leading stakeholders in the system (the United States and the European Union) and progress made by countries of the region in a global context marked by the complexity of trade issues and the legal framework that regulates them. The findings presented in this article are based on the study "Una década de funcionamiento del Sistema de Solución de Diferencias de la OMC: avances y desafíos".
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This paper proposes an approach to load characterization and revenue metering, which accounts for the influence of supply deterioration and line impedance. It makes use of the Conservative Power Theory and aims at characterizing the load from the measurements done at the point of common coupling. Despite the inherent limitations of a single-point measurement, the proposed methodology enables evaluation of power terms, which clarify the effects of reactivity, asymmetry and distortion, and attempts to depurate the power consumption accounted to the load from those terms deriving from supply nonidealities.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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The grinding operation gives workpieces their final finish, minimizing surface roughness through the interaction between the abrasive grains of a tool (grinding wheel) and the workpiece. However, excessive grinding wheel wear due to friction renders the tool unsuitable for further use, thus requiring the dressing operation to remove and/or sharpen the cutting edges of the worn grains to render them reusable. The purpose of this study was to monitor the dressing operation using the acoustic emission (AE) signal and statistics derived from this signal, classifying the grinding wheel as sharp or dull by means of artificial neural networks. An aluminum oxide wheel installed on a surface grinding machine, a signal acquisition system, and a single-point dresser were used in the experiments. Tests were performed varying overlap ratios and dressing depths. The root mean square values and two additional statistics were calculated based on the raw AE data. A multilayer perceptron neural network was used with the Levenberg-Marquardt learning algorithm, whose inputs were the aforementioned statistics. The results indicate that this method was successful in classifying the conditions of the grinding wheel in the dressing process, identifying the tool as "sharp''(with cutting capacity) or "dull''(with loss of cutting capacity), thus reducing the time and cost of the operation and minimizing excessive removal of abrasive material from the grinding wheel.