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One of the most important characteristics of intelligent activity is the ability to change behaviour according to many forms of feedback. Through learning an agent can interact with its environment to improve its performance over time. However, most of the techniques known that involves learning are time expensive, i.e., once the agent is supposed to learn over time by experimentation, the task has to be executed many times. Hence, high fidelity simulators can save a lot of time. In this context, this paper describes the framework designed to allow a team of real RoboNova-I humanoids robots to be simulated under USARSim environment. Details about the complete process of modeling and programming the robot are given, as well as the learning methodology proposed to improve robot's performance. Due to the use of a high fidelity model, the learning algorithms can be widely explored in simulation before adapted to real robots. © 2008 Springer-Verlag Berlin Heidelberg.

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Includes bibliography

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The aim of this paper is to optimize the machining of Ti-6Al-4V alloy, by studying the chip formation, roughness and tool wear for different cooling conditions. The results were compared between cooling methods, minimal quantity of fluid (MQF) and flooding, and also without fluid for the tool H13A. The turning of Ti-6Al-4V has shown good results on roughness (0, 8μm) and tool life, which was 11% lower with MQF than with the flooding method. The tool wear causes variation of the shear angle, which promotes strength hardening of the chip. As a result, the machined surface could be damaged. The use of the cutting fluid helps to save the cutting edge and could reduce the strength hardening. Nevertheless, it could also facilitate the formation of built-up edge. The nucleation of alpha lamellar colonies can occur due to a combination of deformation rates and temperature, mainly when the flooding is used, but it's not conclusive. The lamellar colonies were also found with the MQF in some regions, however, this structure did not show hardness variation compared to equiaxial. For all this reasons, the machining parameters might be carefully chosen.

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Includes bibliography

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Forest dynamics will depend upon the physiological performance of individual tree species under more stressful conditions caused by climate change. In order to compare the idiosyncratic responses of Mediterranean tree species (Quercus faginea, Pinus nigra, Juniperus thurifera) coexisting in forests of central Spain, we evaluated the temporal changes in secondary growth (basal area increment; BAI) and intrinsic water-use efficiency (iWUE) during the last four decades, determined how coexisting species are responding to increases in atmospheric CO2 concentrations (Ca) and drought stress, and assessed the relationship among iWUE and growth during climatically contrasting years. All species increased their iWUE (ca. +15 to +21 %) between the 1970s and the 2000s. This increase was positively related to Ca for J. thurifera and to higher Ca and drought for Q. faginea and P. nigra. During climatically favourable years the study species either increased or maintained their growth at rising iWUE, suggesting a higher CO2 uptake. However, during unfavourable climatic years Q. faginea and especially P. nigra showed sharp declines in growth at enhanced iWUE, likely caused by a reduced stomatal conductance to save water under stressful dry conditions. In contrast, J. thurifera showed enhanced growth also during unfavourable years at increased iWUE, denoting a beneficial effect of Ca even under climatically harsh conditions. Our results reveal significant inter-specific differences in growth driven by alternative physiological responses to increasing drought stress. Thus, forest composition in the Mediterranean region might be altered due to contrasting capacities of coexisting tree species to withstand increasingly stressful conditions. © 2013 Springer-Verlag Berlin Heidelberg.

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Feature selection aims to find the most important information to save computational efforts and data storage. We formulated this task as a combinatorial optimization problem since the exponential growth of possible solutions makes an exhaustive search infeasible. In this work, we propose a new nature-inspired feature selection technique based on bats behavior, namely, binary bat algorithm The wrapper approach combines the power of exploration of the bats together with the speed of the optimum-path forest classifier to find a better data representation. Experiments in public datasets have shown that the proposed technique can indeed improve the effectiveness of the optimum-path forest and outperform some well-known swarm-based techniques. © 2013 Copyright © 2013 Elsevier Inc. All rights reserved.

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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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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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Includes bibliography

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Pós-graduação em Educação - FFC

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Pós-graduação em Física - FEG

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Pós-graduação em Pediatria - FMB

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)