820 resultados para multi-dimensional systems


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Os Sistemas Multi-Robôs proporcionam vantagens sobre um robô individual, quando da realização de uma tarefa com maiores velocidade, precisão e tolerância a falhas. Os estudos dos comportamentos sociais na natureza têm permitido desenvolver algoritmos bio-inspirados úteis na área da robótica de enxame. Seguindo instruções simples e repetitivas, grupos de robôs, fisicamente limitados, conseguem solucionar problemas complexos. Quando existem duas ou mais tarefas a serem realizadas e o conjunto de robôs é heterogêneo, é possível agrupá-los de acordo com as funcionalidades neles disponíveis. No caso em que o conjunto de robôs é homogêneo, o agrupamento pode ser realizado considerando a posição relativa do robô em relação a uma tarefa ou acrescentando alguma característica distintiva. Nesta dissertação, é proposta uma técnica de clusterização espacial baseada simplesmente na comunicação local de robôs. Por meio de troca de mensagens entre os robôs vizinhos, esta técnica permite formar grupos de robôs espacialmente próximos sem precisar movimentar os robôs. Baseando-se nos métodos de clusterização de fichas, a técnica proposta emprega a noção de fichas virtuais, que são chamadas de cargas, sendo que uma carga pode ser estática ou dinâmica. Se uma carga é estática permite determinar a classe à qual um robô pertence. Dependendo da quantidade e do peso das cargas disponíveis no sistema, os robôs intercambiam informações até alcançar uma disposição homogênea de cargas. Quando as cargas se tornam estacionárias, é calculada uma densidade que permite guiar aquelas que estão ainda em movimento. Durante as experiências, foi observado visualmente que as cargas com maior peso acabam se agrupando primeiro enquanto aquelas com menor peso continuam se deslocando no enxame, até que estas cargas formem faixas de densidades diferenciadas para cada classe, alcançando assim o objetivo final que é a clusterização dos robôs.

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A modelagem orientada a agentes surge como paradigma no desenvolvimento de software, haja vista a quantidade de iniciativas e estudos que remetem à utilização de agentes de software como solução para tratar de problemas mais complexos. Apesar da popularidade de utilização de agentes, especialistas esbarram na falta de universalidade de uma metodologia para construção dos Sistemas Multiagentes (MAS), pois estas acabam pecando pelo excesso ou falta de soluções para modelar o problema. Esta dissertação propõe o uso de uma Ontologia sobre Metodologias Multiagentes, seguindo os princípios da Engenharia de Métodos Situacionais que se propõe a usar fragmentos de métodos para construção de metodologias baseados na especificidade do projeto em desenvolvimento. O objetivo do estudo é sedimentar o conhecimento na área de Metodologias Multiagentes, auxiliando o engenheiro de software a escolher a melhor metodologia ou o melhor fragmento de metodologia capaz de modelar um Sistema Multiagentes.

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This study estimated the adoption rate of integrated aquaculture-agriculture (IAA) technologies in Bangladesh and their impact on poverty and fish and food consumption in adopting households. We used a novel, simulation-based approach to impact assessment called Tradeoff Analysis for Multi-Dimensional Impact Assessment (TOA-MD). We used the TOA-MD model to demonstrate how it is possible to use available data to estimate adoption rates in relevant populations, and to quantify impacts on distributional outcomes such as poverty and food security, thus demonstrating ex ante the potential for further investment in technology dissemination. The analysis used baseline and end-of-project survey data from WorldFish-implemented Development of Sustainable Aquaculture Project (DSAP), promoting IAA. This dataset was used to simulate adoption and assess its impacts on poverty and food security in the target population. We found that, if adopted, IAA had a significant positive impact on reducing poverty and improving food security and income.

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There are increasing requirements for impact assessment by development partners in order to increase the accountability and effectiveness of research and development projects. Impact assessment research has been dominated by conventional economic methods. This context challenges agricultural research organizations to develop and apply alternative impact assessment methods incorporating economic, social, and environmental impact components. In this study, we use the Tradeoff Analysis for Multi-Dimensional Impact Assessment (TOA-MD) model to evaluate the impact of integrated aquaculture-agriculture (IAA) adoption in Malawi. The study demonstrated that with a minimal data set, the TOA-MD model can be applied to predict and assess the adoption rates of new technologies and practices as well as their economic and non-economic impacts.

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A tecnologia de agentes tem sido reconhecida como um paradigma promissor em sistemas educacionais da nova geração. Entretanto, o esforço e inflexibilidade de algumas metodologias próprias para agentesacarretam num alto custo, tempo e adaptação de escopo. Este trabalho visaavaliar alternativas de desenvolvimento de um jogo educacional médico orientado a agentes, através da aplicação de um estudo de caso, com o intuito de verificar se metodologias próprias para implementação de sistemas multiagentes trazem benefícios no resultado final da implementação do jogo, e também se os resultados alcançados na comparação de processos de desenvolvimento de cunho tradicional e ágil fazem diferença no resultado final. Desta forma, este trabalho compara três metodologias baseadas nos conceitos da Engenharia de Software através de um estudo de caso, sendo elas: O-MaSE que é uma metodologiatradicional de desenvolvimento de sistemas multiagentes e utiliza um processo de desenvolvimento tradicional; AgilePASSI que é baseada no processo de desenvolvimento ágil e específica para sistemas multiagentes; e, por último, Scrum que é uma metodologia ágil, não sendo específica para implementação de sistemas multiagentes

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The two-point spatial correlation of the rate of change of fluctuating heat release rate is central to the sound emission from open turbulent flames, and a few attempts have been made to address this correlation in recent studies. In this paper, the two-point correlation and its role in combustion noise are studied by analysing direct numerical simulation (DNS) data of statistically multi-dimensional turbulent premixed flames. The results suggest that this correlation function depends on the separation distance and direction but, not on the positions inside the flame brush. This correlation can be modelled using a combination of Hermite-Gaussian functions of zero and second order, i.e. functions of the form (1-Ax2)e-Bx2 for constants A and B, to include its possible negative values. The integral correlation volume obtained using this model is about 0.2δL3 with the length scale obtained from its cube root being about 0.6δ L, where δ L is the laminar flame thermal thickness. Both of the values are slightly larger than the values reported in an earlier study because of the anisotropy observed for the correlation. This model together with the turbulence-dependent parameter K, the ratio of the root-mean-square (RMS) value of the rate of change of reaction rate to the mean reaction rate, derived from the DNS data is applied to predict the far-field sound emitted from open flames. The calculated noise levels agree well with recently reported measurements and show a sensitivity to K values. © 2012 The Combustion Institute.

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Ultrafast lasers play an increasingly important role in many applications. Nanotubes and graphene have emerged as promising novel saturable absorbers for passive mode-locking. Here, we review recent progress on the exploitation of these two carbon nanomaterials in ultrafast photonics. © 2012 Elsevier B.V. All rights reserved.

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Sub-picosecond tunable ultrafast lasers are important tools for many applications. Here we present an ultrafast tunable fiber laser mode-locked by a nanotube based saturable absorber. The laser outputs ∼500fs pulses over a 33 nm range at 1.5μm. This outperforms the current achievable pulse duration from tunable nanotube mode-locked lasers. © 2012 Elsevier B.V. All rights reserved.

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In this work, we present some approaches recently developed for enhancing light emission from Er-based materials and devices. We have investigated the luminescence quenching processes limiting quantum efficiency in light-emitting devices based on Si nanoclusters (Si nc) or Er-doped Si nc. It is found that carrier injection, while needed to excite Si nc or Er ions through electron-hole recombination, at the same time produces an efficient non-radiative Auger de-excitation with trapped carriers. A strong light confinement and enhancement of Er emission at 1.54 μm in planar silicon-on-insulator waveguides containing a thin layer (slot) of SiO2 with Er-doped Si nc at the center of the Si core has been obtained. By measuring the guided photoluminescence from the cleaved edge of the sample, we have observed a more than fivefold enhancement of emission for the transverse magnetic mode over the transverse electric one at room temperature. Slot waveguides have also been integrated with a photonic crystal (PhC), consisting of a triangular lattice of holes. An enhancement by more than two orders of magnitude of the Er near-normal emission is observed when the transition is in resonance with an appropriate mode of the PhC slab. Finally, in order to increase the concentration of excitable Er ions, a completely different approach, based on Er disilicate thin films, has been explored. Under proper annealing conditions crystalline and chemically stable Er2Si2O7 films are obtained; these films exhibit a strong luminescence at 1.54 μm owing to the efficient reduction of the defect density. © 2008 Elsevier B.V. All rights reserved.

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The brain extracts useful features from a maelstrom of sensory information, and a fundamental goal of theoretical neuroscience is to work out how it does so. One proposed feature extraction strategy is motivated by the observation that the meaning of sensory data, such as the identity of a moving visual object, is often more persistent than the activation of any single sensory receptor. This notion is embodied in the slow feature analysis (SFA) algorithm, which uses “slowness” as an heuristic by which to extract semantic information from multi-dimensional time-series. Here, we develop a probabilistic interpretation of this algorithm showing that inference and learning in the limiting case of a suitable probabilistic model yield exactly the results of SFA. Similar equivalences have proved useful in interpreting and extending comparable algorithms such as independent component analysis. For SFA, we use the equivalent probabilistic model as a conceptual spring-board, with which to motivate several novel extensions to the algorithm.

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Innovation policies play an important role throughout the development process of emerging industries in China. Existing policy and industry studies view the emergence process as a black-box, and fail to understand the impacts of policy to the process along which it varies. This paper aims to develop a multi-dimensional roadmapping tool to better analyse the dynamics between policy and industrial growth for new industries in China. Through reviewing the emergence process of Chinese wind turbine industry, this paper elaborates how policy and other factors influence the emergence of this industry along this path. Further, this paper generalises some Chinese specifics for the policy-industry dynamics. As a practical output, this study proposes a roadmapping framework that generalises some patterns of policy-industry interactions for the emergence process of new industries in China. This paper will be of interest to policy makers, strategists, investors and industrial experts. Copyright © 2013 Inderscience Enterprises Ltd.