920 resultados para Uncertainty Avoidance
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Includes bibliography
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In this paper, a novel methodology to price the reactive power support ancillary service of Distributed Generators (DGs) with primary energy source uncertainty is shown. The proposed methodology provides the service pricing based on the Loss of Opportunity Costs (LOC) calculation. An algorithm is proposed to reduce the uncertainty present in these generators using Multiobjective Power Flows (MOPFs) implemented in multiple probabilistic scenarios through Monte Carlo Simulations (MCS), and modeling the time series associated with the generation of active power from DGs through Markov Chains (MC). © 2011 IEEE.
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Due to the renewed interest in distributed generation (DG), the number of DG units incorporated in distribution systems has been rapidly increasing in the past few years. This situation requires new analysis tools for understanding system performance, and taking advantage of the potential benefits of DG. This paper presents an evolutionary multi-objective programming approach to determine the optimal operation of DG in distribution systems. The objectives are the minimization of the system power losses and operation cost of the DG units. The proposed approach also considers the inherent stochasticity of DG technologies powered by renewable resources. Some tests were carried out on the IEEE 34 bus distribution test system showing the robustness and applicability of the proposed methodology. © 2011 IEEE.
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A foreground is formed through the possibilities, tendencies, propensities, obstructions, barriers, hindrances, et cetera, which his or her context provides for a person. Simultaneously, a foreground is formed through the person's interpretations of these possibilities, tendencies, propensities, obstructions, barriers, hindrances. A foreground is a fragmented, partial, and inconsistent constellation of bits and pieces of aspirations, hopes, and frustrations. It might be both promising and frightening; it is always being rebuilt and restructured. Foregrounds are multiple as one person might see very different possibilities; at the same time they are collective and established through processes of communication. In this article educational meaning is discussed in terms of relationships between the students' foregrounds and activities in the classroom. I illustrate how students' dreams might be kept in cages, and how this has implications for how they engage or do not engage in learning processes. I investigate how a foreground might be ruined, and in what sense a ruined foreground might turn into a learning obstacle. Finally, I discuss processes of inclusion and exclusion with reference to the notion of foreground. © 2012. The Authors.
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Software transaction memory (STM) systems have been used as an approach to improve performance, by allowing the concurrent execution of atomic blocks. However, under high-contention workloads, STM-based systems can considerably degrade performance, as transaction conflict rate increases. Contention management policies have been used as a way to select which transaction to abort when a conflict occurs. In general, contention managers are not capable of avoiding conflicts, as they can only select which transaction to abort and the moment it should restart. Since contention managers act only after a conflict is detected, it becomes harder to effectively increase transaction throughput. More proactive approaches have emerged, aiming at predicting when a transaction is likely to abort, postponing its execution. Nevertheless, most of the proposed proactive techniques are limited, as they do not replace the doomed transaction by another or, when they do, they rely on the operating system for that, having little or no control on which transaction to run. This article proposes LUTS, a lightweight user-level transaction scheduler. Unlike other techniques, LUTS provides the means for selecting another transaction to run in parallel, thus improving system throughput. We discuss LUTS design and propose a dynamic conflict-avoidance heuristic built around its scheduling capabilities. Experimental results, conducted with the STAMP and STMBench7 benchmark suites, running on TinySTM and SwissTM, show how our conflict-avoidance heuristic can effectively improve STM performance on high contention applications. © 2012 Springer Science+Business Media, LLC.
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Increasing human demands on soil-derived ecosystem services requires reliable data on global soil resources for sustainable development. The soil organic carbon (SOC) pool is a key indicator of soil quality as it affects essential biological, chemical and physical soil functions such as nutrient cycling, pesticide and water retention, and soil structure maintenance. However, information on the SOC pool, and its temporal and spatial dynamics is unbalanced. Even in well-studied regions with a pronounced interest in environmental issues information on soil carbon (C) is inconsistent. Several activities for the compilation of global soil C data are under way. However, different approaches for soil sampling and chemical analyses make even regional comparisons highly uncertain. Often, the procedures used so far have not allowed the reliable estimation of the total SOC pool, partly because the available knowledge is focused on not clearly defined upper soil horizons and the contribution of subsoil to SOC stocks has been less considered. Even more difficult is quantifying SOC pool changes over time. SOC consists of variable amounts of labile and recalcitrant molecules of plant, and microbial and animal origin that are often operationally defined. A comprehensively active soil expert community needs to agree on protocols of soil surveying and lab procedures towards reliable SOC pool estimates. Already established long-term ecological research sites, where SOC changes are quantified and the underlying mechanisms are investigated, are potentially the backbones for regional, national, and international SOC monitoring programs. © 2013 Elsevier B.V.
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Includes bibliography
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Includes bibliography
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Despite the recovery in intraregional trade over the past three years, intra-group trade, that is trade within the Southern Common Market (MERCOSUR), the Andean Community (CAN) and the Central American Common Market (CACM), remains much weaker than that observed within similar groups in other regions of the world. This weakness is due essentially to the serious lack of complementarity in the process of eliminating tariff barriers (see chapter 3 of Latin America and the Caribbean in the World Economy 2004: Trends 2005, and the study on regional integration entitled: "América Latina y El Caribe: La integración regional en la hora de las definiciones", which is due to be published shortly and which updates basic information for the year 2005). The reasons include (a) weak institutional capacities; (b) the lack of macroeconomic coordination; (c) inadequate infrastructure and d) the lack of depth in integration-related trade disciplines. This edition of the Bulletin reviews the mechanisms for dispute settlement within Mercosur, the Andean Community and CACM with a view to drawing conclusions on the extent to which they are used. In order to reform such mechanisms, consideration should be given to the creation of a single dispute settlement mechanism which would replicate the procedures and regulations of the World Trade Organization (WTO).
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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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This paper proposes a Fuzzy Goal Programming model (FGP) for a real aggregate production-planning problem. To do so, an application was made in a Brazilian Sugar and Ethanol Milling Company. The FGP Model depicts the comprehensive production process of sugar, ethanol, molasses and derivatives, and considers the uncertainties involved in ethanol and sugar production. Decision-makings, related to the agricultural and logistics phases, were considered on a weekly-basis planning horizon to include the whole harvesting season and the periods between harvests. The research has provided interesting results about decisions in the agricultural stages of cutting, loading and transportation to sugarcane suppliers and, especially, in milling decisions, whose choice of production process includes storage and logistics distribution. (C)2014 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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We consider model selection uncertainty in linear regression. We study theoretically and by simulation the approach of Buckland and co-workers, who proposed estimating a parameter common to all models under study by taking a weighted average over the models, using weights obtained from information criteria or the bootstrap. This approach is compared with the usual approach in which the 'best' model is used, and with Bayesian model averaging. The weighted predictor behaves similarly to model averaging, with generally more realistic mean-squared errors than the usual model-selection-based estimator.