909 resultados para Lead-time and set-up optimization
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In recent decades, there has been an increasing interest in systems comprised of several autonomous mobile robots, and as a result, there has been a substantial amount of development in the eld of Articial Intelligence, especially in Robotics. There are several studies in the literature by some researchers from the scientic community that focus on the creation of intelligent machines and devices capable to imitate the functions and movements of living beings. Multi-Robot Systems (MRS) can often deal with tasks that are dicult, if not impossible, to be accomplished by a single robot. In the context of MRS, one of the main challenges is the need to control, coordinate and synchronize the operation of multiple robots to perform a specic task. This requires the development of new strategies and methods which allow us to obtain the desired system behavior in a formal and concise way. This PhD thesis aims to study the coordination of multi-robot systems, in particular, addresses the problem of the distribution of heterogeneous multi-tasks. The main interest in these systems is to understand how from simple rules inspired by the division of labor in social insects, a group of robots can perform tasks in an organized and coordinated way. We are mainly interested on truly distributed or decentralized solutions in which the robots themselves, autonomously and in an individual manner, select a particular task so that all tasks are optimally distributed. In general, to perform the multi-tasks distribution among a team of robots, they have to synchronize their actions and exchange information. Under this approach we can speak of multi-tasks selection instead of multi-tasks assignment, which means, that the agents or robots select the tasks instead of being assigned a task by a central controller. The key element in these algorithms is the estimation ix of the stimuli and the adaptive update of the thresholds. This means that each robot performs this estimate locally depending on the load or the number of pending tasks to be performed. In addition, it is very interesting the evaluation of the results in function in each approach, comparing the results obtained by the introducing noise in the number of pending loads, with the purpose of simulate the robot's error in estimating the real number of pending tasks. The main contribution of this thesis can be found in the approach based on self-organization and division of labor in social insects. An experimental scenario for the coordination problem among multiple robots, the robustness of the approaches and the generation of dynamic tasks have been presented and discussed. The particular issues studied are: Threshold models: It presents the experiments conducted to test the response threshold model with the objective to analyze the system performance index, for the problem of the distribution of heterogeneous multitasks in multi-robot systems; also has been introduced additive noise in the number of pending loads and has been generated dynamic tasks over time. Learning automata methods: It describes the experiments to test the learning automata-based probabilistic algorithms. The approach was tested to evaluate the system performance index with additive noise and with dynamic tasks generation for the same problem of the distribution of heterogeneous multi-tasks in multi-robot systems. Ant colony optimization: The goal of the experiments presented is to test the ant colony optimization-based deterministic algorithms, to achieve the distribution of heterogeneous multi-tasks in multi-robot systems. In the experiments performed, the system performance index is evaluated by introducing additive noise and dynamic tasks generation over time.
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Probabilistic modeling is the de�ning characteristic of estimation of distribution algorithms (EDAs) which determines their behavior and performance in optimization. Regularization is a well-known statistical technique used for obtaining an improved model by reducing the generalization error of estimation, especially in high-dimensional problems. `1-regularization is a type of this technique with the appealing variable selection property which results in sparse model estimations. In this thesis, we study the use of regularization techniques for model learning in EDAs. Several methods for regularized model estimation in continuous domains based on a Gaussian distribution assumption are presented, and analyzed from di�erent aspects when used for optimization in a high-dimensional setting, where the population size of EDA has a logarithmic scale with respect to the number of variables. The optimization results obtained for a number of continuous problems with an increasing number of variables show that the proposed EDA based on regularized model estimation performs a more robust optimization, and is able to achieve signi�cantly better results for larger dimensions than other Gaussian-based EDAs. We also propose a method for learning a marginally factorized Gaussian Markov random �eld model using regularization techniques and a clustering algorithm. The experimental results show notable optimization performance on continuous additively decomposable problems when using this model estimation method. Our study also covers multi-objective optimization and we propose joint probabilistic modeling of variables and objectives in EDAs based on Bayesian networks, speci�cally models inspired from multi-dimensional Bayesian network classi�ers. It is shown that with this approach to modeling, two new types of relationships are encoded in the estimated models in addition to the variable relationships captured in other EDAs: objectivevariable and objective-objective relationships. An extensive experimental study shows the e�ectiveness of this approach for multi- and many-objective optimization. With the proposed joint variable-objective modeling, in addition to the Pareto set approximation, the algorithm is also able to obtain an estimation of the multi-objective problem structure. Finally, the study of multi-objective optimization based on joint probabilistic modeling is extended to noisy domains, where the noise in objective values is represented by intervals. A new version of the Pareto dominance relation for ordering the solutions in these problems, namely �-degree Pareto dominance, is introduced and its properties are analyzed. We show that the ranking methods based on this dominance relation can result in competitive performance of EDAs with respect to the quality of the approximated Pareto sets. This dominance relation is then used together with a method for joint probabilistic modeling based on `1-regularization for multi-objective feature subset selection in classi�cation, where six di�erent measures of accuracy are considered as objectives with interval values. The individual assessment of the proposed joint probabilistic modeling and solution ranking methods on datasets with small-medium dimensionality, when using two di�erent Bayesian classi�ers, shows that comparable or better Pareto sets of feature subsets are approximated in comparison to standard methods.
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Outline: • Motivation, aim • Complement waveguide data on silica • Optical data in quartz • Detailed analysis, i.e. both fluence kinetics and resolution • Efficiency of irradiation and analysis, samples, time... • Experimental set-up description • Reflectance procedure • Options: light source (lasers, white light..), detectors, configurations • Results and discussion • Comparative of amorphous and crystalline phases
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It has been proposed that the use of self-assembled quantum dot (QD) arrays can break the Shockley-Queisser efficiency limit by extending the absorption of solar cells into the low-energy photon range while preserving their output voltage. This would be possible if the infrared photons are absorbed in the two sub-bandgap QD transitions simultaneously and the energy of two photons is added up to produce one single electron-hole pair, as described by the intermediate band model. Here, we present an InAs/Al 0.25Ga 0.75As QD solar cell that exhibits such electrical up-conversion of low-energy photons. When the device is monochromatically illuminated with 1.32 eV photons, open-circuit voltages as high as 1.58 V are measured (for a total gap of 1.8 eV). Moreover, the photocurrent produced by illumination with photons exciting the valence band to intermediate band (VB-IB) and the intermediate band to conduction band (IB-CB) transitions can be both spectrally resolved. The first corresponds to the QD inter-band transition and is observable for photons of energy mayor que 1 eV, and the later corresponds to the QD intra-band transition and peaks around 0.5 eV. The voltage up-conversion process reported here for the first time is the key to the use of the low-energy end of the solar spectrum to increase the conversion efficiency, and not only the photocurrent, of single-junction photovoltaic devices. In spite of the low absorption threshold measured in our devices - 0.25 eV - we report open-circuit voltages at room temperature as high as 1.12 V under concentrated broadband illumination.
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Although most ecologists agree that both top-down and bottom-up forces (predation and resource limitation, respectively) act in concert to influence populations of herbivores, it has proven difficult to estimate the relative contributions of such forces in terrestrial systems. Using a combination of time–series analysis of population counts recorded over 16 years and experimental data, we present the first estimates of the relative roles of top-down and bottom-up forces on the population dynamics of two terrestrial insect herbivores on the English oak (Quercus robur). Data suggest that temporal variation in winter moth, Operophtera brumata, density is dominated by time-lagged effects of pupal predators. By comparison, spatial variation in O. brumata density is dominated by host–plant quality. Overall, top-down forces explain 34.2% of population variance, bottom-up forces explain 17.2% of population variance, and 48.6% remains unexplained. In contrast, populations of the green oak tortrix, Tortrix viridana, appear dominated by bottom-up forces. Resource limitation, expressed as intraspecific competition among larvae for oak leaves, explains 29.4% of population variance. Host quality effects explain an additional 5.7% of population variance. We detected no major top-down effects on T. viridana populations. An unknown factor causing a linear decline in T. viridana populations over the 16-year study period accounts for most of the remaining unexplained variance. We discuss the observed differences between the insect species and the utility of time–series analysis as a tool in assessing the relative importance of top-down and bottom-up forces on herbivore populations.
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Indian mustard (Brassica juncea) plants exposed to Pb and EDTA in hydroponic solution were able to accumulate up to 55 mmol kg−1 Pb in dry shoot tissue (1.1% [w/w]). This represents a 75-fold concentration of Pb in shoot tissue over that in solution. A threshold concentration of EDTA (0.25 mm) was found to be required to stimulate this dramatic accumulation of both Pb and EDTA in shoots. Below this threshold concentration, EDTA also accumulated in shoots but at a reduced rate. Direct measurement of a complex of Pb and EDTA (Pb-EDTA) in xylem exudate of Indian mustard confirmed that the majority of Pb in these plants is transported in coordination with EDTA. The accumulation of EDTA in shoot tissue was also observed to be directly correlated with the accumulation of Pb. Exposure of Indian mustard to high concentrations of Pb and EDTA caused reductions in both the transpiration rate and the shoot water content. The onset of these symptoms was correlated with the presence of free protonated EDTA (H-EDTA) in the hydroponic solution, suggesting that free H-EDTA is more phytotoxic than Pb-EDTA. These studies clearly demonstrate that coordination of Pb transport by EDTA enhances the mobility within the plants of this otherwise insoluble metal ion, allowing plants to accumulate high concentrations of Pb in shoots. The finding that both H-EDTA and Pb-EDTA are mobile within plants also has important implications for the use of metal chelates in plant nutritional research.
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Excessive leverage and risk-taking by large international banks were the main causes of the 2008-09 financial crisis and the ensuing sharp drop in economic activity and employment. World leaders and central bankers promised that it would not happen again and, to this end, undertook to overhaul banking regulation, first and foremost by rectifying Basel prudential rules. This study argues that the new Basel III Accord and the ensuing EU Capital Requirements Directive IV fail to correct the two main shortcomings of international prudential rules: 1) reliance on banks’ risk management models for the calculation of capital requirements and 2) the lack of accountability by supervisors. Accordingly, the authors propose the calculation of capital requirements without risk adjustment and creation of a system of mandated action by supervisors modelled on the US framework of Prompt Corrective Action (PCA). They also recommend that banks should be required to issue large amounts of debentures that are convertible into equity in order to strengthen market discipline on management and shareholders.
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Federal Highway Administration, Washington, D.C.
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Mode of access: Internet.
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Author's name on cover.
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"DOT-T-92-04"--P. 4 of cover.