879 resultados para Conflict-based method


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Contention on the memory bus in COTS based multicore systems is becoming a major determining factor of the execution time of a task. Analyzing this extra execution time is non-trivial because (i) bus arbitration protocols in such systems are often undocumented and (ii) the times when the memory bus is requested to be used are not explicitly controlled by the operating system scheduler; they are instead a result of cache misses. We present a method for finding an upper bound on the extra execution time of a task due to contention on the memory bus in COTS based multicore systems. This method makes no assumptions on the bus arbitration protocol (other than assuming that it is work-conserving).

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This article describes a finite element-based formulation for the statistical analysis of the response of stochastic structural composite systems whose material properties are described by random fields. A first-order technique is used to obtain the second-order statistics for the structural response considering means and variances of the displacement and stress fields of plate or shell composite structures. Propagation of uncertainties depends on sensitivities taken as measurement of variation effects. The adjoint variable method is used to obtain the sensitivity matrix. This method is appropriated for composite structures due to the large number of random input parameters. Dominant effects on the stochastic characteristics are studied analyzing the influence of different random parameters. In particular, a study of the anisotropy influence on uncertainties propagation of angle-ply composites is carried out based on the proposed approach.

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An approach for the analysis of uncertainty propagation in reliability-based design optimization of composite laminate structures is presented. Using the Uniform Design Method (UDM), a set of design points is generated over a domain centered on the mean reference values of the random variables. A methodology based on inverse optimal design of composite structures to achieve a specified reliability level is proposed, and the corresponding maximum load is outlined as a function of ply angle. Using the generated UDM design points as input/output patterns, an Artificial Neural Network (ANN) is developed based on an evolutionary learning process. Then, a Monte Carlo simulation using ANN development is performed to simulate the behavior of the critical Tsai number, structural reliability index, and their relative sensitivities as a function of the ply angle of laminates. The results are generated for uniformly distributed random variables on a domain centered on mean values. The statistical analysis of the results enables the study of the variability of the reliability index and its sensitivity relative to the ply angle. Numerical examples showing the utility of the approach for robust design of angle-ply laminates are presented.

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Constraints nonlinear optimization problems can be solved using penalty or barrier functions. This strategy, based on solving the problems without constraints obtained from the original problem, have shown to be e ective, particularly when used with direct search methods. An alternative to solve the previous problems is the lters method. The lters method introduced by Fletcher and Ley er in 2002, , has been widely used to solve problems of the type mentioned above. These methods use a strategy di erent from the barrier or penalty functions. The previous functions de ne a new one that combine the objective function and the constraints, while the lters method treat optimization problems as a bi-objective problems that minimize the objective function and a function that aggregates the constraints. Motivated by the work of Audet and Dennis in 2004, using lters method with derivative-free algorithms, the authors developed works where other direct search meth- ods were used, combining their potential with the lters method. More recently. In a new variant of these methods was presented, where it some alternative aggregation restrictions for the construction of lters were proposed. This paper presents a variant of the lters method, more robust than the previous ones, that has been implemented with a safeguard procedure where values of the function and constraints are interlinked and not treated completely independently.

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Constrained nonlinear optimization problems are usually solved using penalty or barrier methods combined with unconstrained optimization methods. Another alternative used to solve constrained nonlinear optimization problems is the lters method. Filters method, introduced by Fletcher and Ley er in 2002, have been widely used in several areas of constrained nonlinear optimization. These methods treat optimization problem as bi-objective attempts to minimize the objective function and a continuous function that aggregates the constraint violation functions. Audet and Dennis have presented the rst lters method for derivative-free nonlinear programming, based on pattern search methods. Motivated by this work we have de- veloped a new direct search method, based on simplex methods, for general constrained optimization, that combines the features of the simplex method and lters method. This work presents a new variant of these methods which combines the lters method with other direct search methods and are proposed some alternatives to aggregate the constraint violation functions.

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The problem of selecting suppliers/partners is a crucial and important part in the process of decision making for companies that intend to perform competitively in their area of activity. The selection of supplier/partner is a time and resource-consuming task that involves data collection and a careful analysis of the factors that can positively or negatively influence the choice. Nevertheless it is a critical process that affects significantly the operational performance of each company. In this work, there were identified five broad selection criteria: Quality, Financial, Synergies, Cost, and Production System. Within these criteria, it was also included five sub-criteria. After the identification criteria, a survey was elaborated and companies were contacted in order to understand which factors have more weight in their decisions to choose the partners. Interpreted the results and processed the data, it was adopted a model of linear weighting to reflect the importance of each factor. The model has a hierarchical structure and can be applied with the Analytic Hierarchy Process (AHP) method or Value Analysis. The goal of the paper it's to supply a selection reference model that can represent an orientation/pattern for a decision making on the suppliers/partners selection process

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The Maxwell equations play a fundamental role in the electromagnetic theory and lead to models useful in physics and engineering. This formalism involves integer-order differential calculus, but the electromagnetic diffusion points towards the adoption of a fractional calculus approach. This study addresses the skin effect and develops a new method for implementing fractional-order inductive elements. Two genetic algorithms are adopted, one for the system numerical evaluation and another for the parameter identification, both with good results.

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This paper presents a new predictive digital control method applied to Matrix Converters (MC) operating as Unified Power Flow Controllers (UPFC). This control method, based on the inverse dynamics model equations of the MC operating as UPFC, just needs to compute the optimal control vector once in each control cycle, in contrast to direct dynamics predictive methods that needs 27 vector calculations. The theoretical principles of the inverse dynamics power flow predictive control of the MC based UPFC with input filter are established. The proposed inverse dynamics predictive power control method is tested using Matlab/Simulink Power Systems toolbox and the obtained results show that the designed power controllers guarantees decoupled active and reactive power control, zero error tracking, fast response times and an overall good dynamic and steady-state response.

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This paper presents a methodology for applying scheduling algorithms using Monte Carlo simulation. The methodology is based on a decision support system (DSS). The proposed methodology combines a genetic algorithm with a new local search using Monte Carlo Method. The methodology is applied to the job shop scheduling problem (JSSP). The JSSP is a difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms. The methodology is tested on a set of standard instances taken from the literature and compared with others. The computation results validate the effectiveness of the proposed methodology. The DSS developed can be utilized in a common industrial or construction environment.

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This paper introduces a new unsupervised hyperspectral unmixing method conceived to linear but highly mixed hyperspectral data sets, in which the simplex of minimum volume, usually estimated by the purely geometrically based algorithms, is far way from the true simplex associated with the endmembers. The proposed method, an extension of our previous studies, resorts to the statistical framework. The abundance fraction prior is a mixture of Dirichlet densities, thus automatically enforcing the constraints on the abundance fractions imposed by the acquisition process, namely, nonnegativity and sum-to-one. A cyclic minimization algorithm is developed where the following are observed: 1) The number of Dirichlet modes is inferred based on the minimum description length principle; 2) a generalized expectation maximization algorithm is derived to infer the model parameters; and 3) a sequence of augmented Lagrangian-based optimizations is used to compute the signatures of the endmembers. Experiments on simulated and real data are presented to show the effectiveness of the proposed algorithm in unmixing problems beyond the reach of the geometrically based state-of-the-art competitors.

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The behavior of robotic manipulators with backlash is analyzed. Based on the pseudo-phase plane two indices are proposed to evaluate the backlash effect upon the robotic system: the root mean square error and the fractal dimension. For the dynamical analysis the noisy signals captured from the system are filtered through wavelets. Several tests are developed that demonstrate the coherence of the results.

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A cross: sectional survey on schistosomiasis was done in Comercinho (Minas Gerais State, Brazil), a town with 1474 inhabitants. Stool (Kato-Katz method) and physical examinations were done on 90% of the population and on 84% of the individuals over 2 years of age, respectively. The ecological and individual (case-control) analysis were used to investigate the relation between splenomegaly and S. mansoni egg counts in different age groups. In the ecological analysis there was a clearly correspondence between higher geometric mean of eggs and higher percentage of splenomegaly in the age groups 5-9 and 10-12 years. In the individual analysis it was found that only in the youngest individuals (5-8 or 5-9 years old) the splenomegaly was related with higher mean egg counts in the feces, having been a tendency to the decrease of excretion of eggs in patients with splenomegaly as the age increased. These results strongly suggest that the ecological data are' better indicator of the severity of schistosomiasis in endemic areas, as the decrease of the egg excretion in patients with splenomegaly may be a confounding variable for the individual analysis.

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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores

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A clinical trial involving 80 patients of both sexes, from ages 15 to 55, with chronic intestinal or hepatointestinal schistosomiasis mansoni, was carried out to evaluate the therapeutical efficacy of different dose regimens of praziquantel. The patients were randomly allocated into four groups with an equal number of cases and were then treated with one of the following dosages: 60 mg/kg for 1 day; 60 mg/kg daily for 2 days; 60 mg/kg daily for 3 days; and 30 mg/kg daily for 6 days. The assessment of parasitological cure was based on the quantitative oogram technique through rectal mucosa biopsies which were undertaken prior to, as well as, 1,2,4 and 6 months post-treatment. Concurrently, stool examinations according to the qualitative Hoffman, Pons & Janer (HPJ) and the quantitative Kato-Katz (K-K) methods were also performed. The best tolerability was observed with 30 mg/kg daily for 6 days whereas the highest incidence of side-effects (mainly dizziness and nausea) was found with 60 mg/kg daily for 3 days. No serious adverse drug reaction has occurred. The achieved cure rates were: 25% with 60 mg/kg for 1 day; 60% with 60 mg/kg daily for 2 days; 89.5% with 60 mg/kg daily for 3 days; and 90% with 30 mg/kg daily for 6 days. At the same time there has been a downfall of 64%, 73%, 87% and 84% respectively, in the median number of viable S. mansoni ova per gram of tissue. Thus, a very clear direct correlation between dose and effect could be seen. The corresponding cure rates according to stool examinations by HPJ were 39%, 80%, 100% and 95%; by K-K 89%, 100%, 100% and 100%. This discrepancy in results amongst the three parasitological methods is certainly due to their unequal accuracy. In fact, when the number of viable eggs per gram of tissue fell below 5,000 the difference in the percentage of false negative findings between HPJ (28%) and K-K (80%) became significative. When this number dropped to less than 2,000 the percentage of false negative results obtained with HPJ (49%) turned significant in relation to the oogram as well. In conclusion, it has been proven that praziquantel is a highly efficacious agent against S. mansoni infections. If administered at a total dose of 180 mg/kg divided into either 3 or 6 days, it yields a 90% cure rate. Possibly, one could reach 100% by increasing the total dose to 240 mg/kg. Furthermore, it was confirmed that the quantitative oogram technique is the most reliable parasitological method when evaluating the efficacy of new drugs in schistosomiasis mansoni.

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The development and applications of thermoset polymeric composites, namely fibre reinforced plastics (FRP), have shifted in the last decades more and more into the mass market [1]. Despite of all advantages associated to FRP based products, the increasing production and consume also lead to an increasing amount of FRP wastes, either end-of-lifecycle products, or scrap and by-products generated by the manufacturing process itself. Whereas thermoplastic FRPs can be easily recycled, by remelting and remoulding, recyclability of thermosetting FRPs constitutes a more difficult task due to cross-linked nature of resin matrix. To date, most of the thermoset based FRP waste is being incinerated or landfilled, leading to negative environmental impacts and supplementary added costs to FRP producers and suppliers. This actual framework is putting increasing pressure on the industry to address the options available for FRP waste management, being an important driver for applied research undertaken cost efficient recycling methods. [1-2]. In spite of this, research on recycling solutions for thermoset composites is still at an elementary stage. Thermal and/or chemical recycling processes, with partial fibre recovering, have been investigated mostly for carbon fibre reinforced plastics (CFRP) due to inherent value of carbon fibre reinforcement; whereas for glass fibre reinforced plastics (GFRP), mechanical recycling, by means of milling and grinding processes, has been considered a more viable recycling method [1-2]. Though, at the moment, few solutions in the reuse of mechanically-recycled GFRP composites into valueadded products are being explored. Aiming filling this gap, in this study, a new waste management solution for thermoset GFRP based products was assessed. The mechanical recycling approach, with reduction of GFRP waste to powdered and fibrous materials was applied, and the potential added value of obtained recyclates was experimentally investigated as raw material for polyester based mortars. The use of a cementless concrete as host material for GFRP recyclates, instead of a conventional Portland cement based concrete, presents an important asset in avoiding the eventual incompatibility problems arisen from alkalis silica reaction between glass fibres and cementious binder matrix. Additionally, due to hermetic nature of resin binder, polymer based concretes present greater ability for incorporating recycled waste products [3]. Under this scope, different GFRP waste admixed polymer mortar (PM) formulations were analyzed varying the size grading and content of GFRP powder and fibre mix waste. Added value of potential recycling solution was assessed by means of flexural and compressive loading capacities of modified mortars with regard to waste-free polymer mortars.