977 resultados para Efficient Solutions
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O presente trabalho aborda a temática da eficiência energética em sistemas de iluminação pública. A principal motivação prende-se com o peso significativo que a parcela energética destes sistemas ocupa na economia mundial. O uso eficiente de energia é uma crescente preocupação devido à diminuição de recursos, às consequências climáticas cada vez mais marcadas e ao elevado custo da energia, representando ainda um papel fundamental ao nível económico e de competitividade. A Iluminação Pública (IP) representa um peso importante nas despesas correntes dos municípios. É assim importante encontrar uma solução que permita manter níveis de segurança e conforto necessários às populações e que proporcione uma redução substancial do peso da IP nas despesas municipais. Neste sentido, este trabalho propõe-se estudar esta problemática, apresentando uma sistematização de soluções eficientes, quer a nível de lâmpadas e luminárias como também ao nível de tecnologias que auxiliem e complementem a eficiência de uma instalação de iluminação pública. A dissertação está dividida em duas partes. A primeira parte sistematiza os consumos verificados em Portugal, a vários níveis (consumo de energia elétrica, evolução do consumo energético de iluminação pública, etc.) abordando as políticas de eficiência energética, e são descritos alguns procedimentos que possibilitam a poupança energética na iluminação pública, aliada a instalações eficientes. A segunda parte da dissertação contempla o estudo de um caso prático cujo objetivo é propor soluções técnicas que permitam melhorar a eficiência energética na iluminação pública de Esposende, face à situação atual do concelho. Serão propostas várias soluções, tais como luminárias LED, balastros electrónicos reguláveis, lâmpadas de menor consumo e até mesmo o uso da telegestão.
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Value chain collaboration has been a prevailing topic for research, and there is a constantly growing interest in developing collaborative models for improved efficiency in logistics. One area of collaboration is demand information management, which enables improved visibility and decrease of inventories in the value chain. Outsourcing of non-core competencies has changed the nature of collaboration from intra-enterprise to cross-enterprise activity, and this together with increasing competition in the globalizing markets have created a need for methods and tools for collaborative work. The retailer part in the value chain of consumer packaged goods (CPG) has been studied relatively widely, proven models have been defined, and there exist several best practice collaboration cases. The information and communications technology has developed rapidly, offering efficient solutions and applications to exchange information between value chain partners. However, the majority of CPG industry still works with traditional business models and practices. This concerns especially companies operating in the upstream of the CPG value chain. Demand information for consumer packaged goods originates at retailers' counters, based on consumers' buying decisions. As this information does not get transferred along the value chain towards the upstream parties, each player needs to optimize their part, causing safety margins for inventories and speculation in purchasing decisions. The safety margins increase with each player, resulting in a phenomenon known as the bullwhip effect. The further the company is from the original demand information source, the more distorted the information is. This thesis concentrates on the upstream parts of the value chain of consumer packaged goods, and more precisely the packaging value chain. Packaging is becoming a part of the product with informative and interactive features, and therefore is not just a cost item needed to protect the product. The upstream part of the CPG value chain is distinctive, as the product changes after each involved party, and therefore the original demand information from the retailers cannot be utilized as such – even if it were transferred seamlessly. The objective of this thesis is to examine the main drivers for collaboration, and barriers causing the moderate adaptation level of collaborative models. Another objective is to define a collaborative demand information management model and test it in a pilot business situation in order to see if the barriers can be eliminated. The empirical part of this thesis contains three parts, all related to the research objective, but involving different target groups, viewpoints and research approaches. The study shows evidence that the main barriers for collaboration are very similar to the barriers in the lower part of the same value chain; lack of trust, lack of business case and lack of senior management commitment. Eliminating one of them – the lack of business case – is not enough to eliminate the two other barriers, as the operational model in this thesis shows. The uncertainty of the future, fear of losing an independent position in purchasing decision making and lack of commitment remain strong enough barriers to prevent the implementation of the proposed collaborative business model. The study proposes a new way of defining the value chain processes: it divides the contracting and planning process into two processes, one managing the commercial parts and the other managing the quantity and specification related issues. This model can reduce the resistance to collaboration, as the commercial part of the contracting process would remain the same as in the traditional model. The quantity/specification-related issues would be managed by the parties with the best capabilities and resources, as well as access to the original demand information. The parties in between would be involved in the planning process as well, as their impact for the next party upstream is significant. The study also highlights the future challenges for companies operating in the CPG value chain. The markets are becoming global, with toughening competition. Also, the technology development will most likely continue with a speed exceeding the adaptation capabilities of the industry. Value chains are also becoming increasingly dynamic, which means shorter and more agile business relationships, and at the same time the predictability of consumer demand is getting more difficult due to shorter product life cycles and trends. These changes will certainly have an effect on companies' operational models, but it is very difficult to estimate when and how the proven methods will gain wide enough adaptation to become standards.
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The goal of this study is to investigate about the existence or absence of environmental dumping in the production of fuel ethanol in Brazil, as well as identifying the reasons why the figure of ecological dumping is pernicious to the principles enumerated in constitutional economic order, in particular the principle of free competition. In the twenty-first century environmental issues gained momentum and importance in these terms, which was seen as a mere fallacy given the concern of governments of various countries, after all, environmental protection shows up as the only means of bringing about the maintenance of life at planet. Indeed, it is essential to halt the drastic effects of climate change, and think fast and efficient solutions. Undoubtedly, the contemporary requirements that resulted in the transition to a new economy brings with it the duty of enterprise search for sustainability, and this behavior can not be passive, otherwise it is imperative to work hard and incessant economic agents, even if initially costs are high, this step will ensure a production accountable, transparent and free from accusations of environmental degradation. It is also intended to study the importance of the sector not only as a source of economic growth, but mainly, its contribution to national development, without forgetting that this is devoted in the Constitution of 1988 as one of the objectives of the Federative Republic of Brazil. In fact, the criticism most common perceptions about the production of biofuels, said the interests of the countries producing them in large scale, will eventually generate a exhaustion of soil and a significant increase in food prices. However, the ethanol produced in Brazil is unique in that it is produced from cane sugar, a product is not intended for human or animal, not to mention that the recovery of land just to the rotation with the planting other cultures. It is expected that environmental certifications are useful to demonstrate the quality of ethanol for export and to refute unfounded criticism. Finally, this study will be analyzed further solutions for the plants to develop an economic activity without damaging the environment and in compliance with Brazilian law
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The greater part of monitoring onshore Oil and Gas environment currently are based on wireless solutions. However, these solutions have a technological configuration that are out-of-date, mainly because analog radios and inefficient communication topologies are used. On the other hand, solutions based in digital radios can provide more efficient solutions related to energy consumption, security and fault tolerance. Thus, this paper evaluated if the Wireless Sensor Network, communication technology based on digital radios, are adequate to monitoring Oil and Gas onshore wells. Percent of packets transmitted with successful, energy consumption, communication delay and routing techniques applied to a mesh topology will be used as metrics to validate the proposal in the different routing techniques through network simulation tool NS-2
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Function approximation is a very important task in environments where computation has to be based on extracting information from data samples in real world processes. Neural networks and wavenets have been recently seen as attractive tools for developing efficient solutions for many real world problems in function approximation. In this paper, it is shown how feedforward neural networks can be built using a different type of activation function referred to as the PPS-wavelet. An algorithm is presented to generate a family of PPS-wavelets that can be used to efficiently construct feedforward networks for function approximation.
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Cogeneration system design deals with several parameters in the synthesis phase, where not only a thermal cycle must be indicated but the general arrangement, type, capacity and number of machines need to be defined. This problem is not trivial because many parameters are considered as goals in the project. An optimization technique that considers costs and revenues, reliability, pollutant emissions and exergetic efficiency as goals to be reached in the synthesis phase of a cogeneration system design process is presented. A discussion of appropriated values and the results for a pulp and paper plant integration to a cogeneration system are shown in order to illustrate the proposed methodology.
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The automatic characterization of particles in metallographic images has been paramount, mainly because of the importance of quantifying such microstructures in order to assess the mechanical properties of materials common used in industry. This automated characterization may avoid problems related with fatigue and possible measurement errors. In this paper, computer techniques are used and assessed towards the accomplishment of this crucial industrial goal in an efficient and robust manner. Hence, the use of the most actively pursued machine learning classification techniques. In particularity, Support Vector Machine, Bayesian and Optimum-Path Forest based classifiers, and also the Otsu's method, which is commonly used in computer imaging to binarize automatically simply images and used here to demonstrated the need for more complex methods, are evaluated in the characterization of graphite particles in metallographic images. The statistical based analysis performed confirmed that these computer techniques are efficient solutions to accomplish the aimed characterization. Additionally, the Optimum-Path Forest based classifier demonstrated an overall superior performance, both in terms of accuracy and speed. © 2012 Elsevier Ltd. All rights reserved.
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Pós-graduação em Engenharia Elétrica - FEB
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Pós-graduação em Direito - FCHS
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The growing use of e-commerce and the need to generate efficient solutions to problems such as traffic jams and the physical distribution of merchandise have created a new scenario for transport in general, particularly in urban areas. Because of this, the application of new information and telecommunications technologies presents a strategic challenge that enables maximum advantage to be obtained from the deregulation of markets and the opening up of economies, as well as addressing other urgent needs of this sector. This issue of the Bulletin is based on a study of the application of information and telecommunications technologies to fleet management and urban transport, being carried out by the ECLAC Transport Unit. Although the study focuses on the impact of these technologies in these fields, its reflections, analysis and conclusions are also applicable in other areas of the transport sector.
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A automação na gestão e análise de dados tem sido um fator crucial para as empresas que necessitam de soluções eficientes em um mundo corporativo cada vez mais competitivo. A explosão do volume de informações, que vem se mantendo crescente nos últimos anos, tem exigido cada vez mais empenho em buscar estratégias para gerenciar e, principalmente, extrair informações estratégicas valiosas a partir do uso de algoritmos de Mineração de Dados, que comumente necessitam realizar buscas exaustivas na base de dados a fim de obter estatísticas que solucionem ou otimizem os parâmetros do modelo de extração do conhecimento utilizado; processo que requer computação intensiva para a execução de cálculos e acesso frequente à base de dados. Dada a eficiência no tratamento de incerteza, Redes Bayesianas têm sido amplamente utilizadas neste processo, entretanto, à medida que o volume de dados (registros e/ou atributos) aumenta, torna-se ainda mais custoso e demorado extrair informações relevantes em uma base de conhecimento. O foco deste trabalho é propor uma nova abordagem para otimização do aprendizado da estrutura da Rede Bayesiana no contexto de BigData, por meio do uso do processo de MapReduce, com vista na melhora do tempo de processamento. Para tanto, foi gerada uma nova metodologia que inclui a criação de uma Base de Dados Intermediária contendo todas as probabilidades necessárias para a realização dos cálculos da estrutura da rede. Por meio das análises apresentadas neste estudo, mostra-se que a combinação da metodologia proposta com o processo de MapReduce é uma boa alternativa para resolver o problema de escalabilidade nas etapas de busca em frequência do algoritmo K2 e, consequentemente, reduzir o tempo de resposta na geração da rede.
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Pós-graduação em Engenharia Elétrica - FEIS
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This article deals with a vector optimization problem with cone constraints in a Banach space setting. By making use of a real-valued Lagrangian and the concept of generalized subconvex-like functions, weakly efficient solutions are characterized through saddle point type conditions. The results, jointly with the notion of generalized Hessian (introduced in [Cominetti, R., Correa, R.: A generalized second-order derivative in nonsmooth optimization. SIAM J. Control Optim. 28, 789–809 (1990)]), are applied to achieve second order necessary and sufficient optimality conditions (without requiring twice differentiability for the objective and constraining functions) for the particular case when the functionals involved are defined on a general Banach space into finite dimensional ones.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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This paper proposes a technique for solving the multiobjective environmental/economic dispatch problem using the weighted sum and ε-constraint strategies, which transform the problem into a set of single-objective problems. In the first strategy, the objective function is a weighted sum of the environmental and economic objective functions. The second strategy considers one of the objective functions: in this case, the environmental function, as a problem constraint, bounded above by a constant. A specific predictor-corrector primal-dual interior point method which uses the modified log barrier is proposed for solving the set of single-objective problems generated by such strategies. The purpose of the modified barrier approach is to solve the problem with relaxation of its original feasible region, enabling the method to be initialized with unfeasible points. The tests involving the proposed solution technique indicate i) the efficiency of the proposed method with respect to the initialization with unfeasible points, and ii) its ability to find a set of efficient solutions for the multiobjective environmental/economic dispatch problem.