995 resultados para Self-Optimization


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Adhesively-bonded techniques offer an attractive option for repair of aluminium structures, and currently there are three widely used configurations, i.e., single-strap (SS), double-strap (DS) and scarf repairs. SS and DS repairs are straightforward to execute but stresses in the adhesive layer peak at the ends of the overlap. DS repairs additionally require both sides of the damaged structures to be reachable for repair, which is often not possible. In these repair configurations, some limitations emerge such as the weight, aerodynamic performance and aesthetics. The scarf repair is more complex to fabricate but stresses are more uniform along the adhesive bondline. Few studies of SS and DS repairs with embedded patches, such that these are completely flush with the adherends, are available in the literature. Furthermore, no data is available about the effects of geometrical and material parameters (e.g. the Young’s modulus of adhesive, E) on the mechanical behaviour optimization of embedded repairs. For this purpose, in this work standard SS and DD repairs, and also with embedded patches in the adherends, were tested under tension to allow the geometry optimization, by varying the overlap length (LO), thus allowing the maximization of the repairs strength. The influence of the patch embedding technique, showing notorious advantages such as aerodynamic or aesthetics, was compared in strength with standard strap repairs, for the viability analysis of its implementation. As a result of this work, some conclusions were drawn for the design optimization of bonded repairs on aluminium structures.

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This paper is on the self-scheduling for a power producer taking part in day-ahead joint energy and spinning reserve markets and aiming at a short-term coordination of wind power plants with concentrated solar power plants having thermal energy storage. The short-term coordination is formulated as a mixed-integer linear programming problem given as the maximization of profit subjected to technical operation constraints, including the ones related to a transmission line. Probability density functions are used to model the variability of the hourly wind speed and the solar irradiation in regard to a negative correlation. Case studies based on an Iberian Peninsula wind and concentrated solar power plants are presented, providing the optimal energy and spinning reserve for the short-term self-scheduling in order to unveil the coordination benefits and synergies between wind and solar resources. Results and sensitivity analysis are in favour of the coordination, showing an increase on profit, allowing for spinning reserve, reducing the need for curtailment, increasing the transmission line capacity factor. (C) 2014 Elsevier Ltd. All rights reserved.

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In the last twenty years genetic algorithms (GAs) were applied in a plethora of fields such as: control, system identification, robotics, planning and scheduling, image processing, and pattern and speech recognition (Bäck et al., 1997). In robotics the problems of trajectory planning, collision avoidance and manipulator structure design considering a single criteria has been solved using several techniques (Alander, 2003). Most engineering applications require the optimization of several criteria simultaneously. Often the problems are complex, include discrete and continuous variables and there is no prior knowledge about the search space. These kind of problems are very more complex, since they consider multiple design criteria simultaneously within the optimization procedure. This is known as a multi-criteria (or multiobjective) optimization, that has been addressed successfully through GAs (Deb, 2001). The overall aim of multi-criteria evolutionary algorithms is to achieve a set of non-dominated optimal solutions known as Pareto front. At the end of the optimization procedure, instead of a single optimal (or near optimal) solution, the decision maker can select a solution from the Pareto front. Some of the key issues in multi-criteria GAs are: i) the number of objectives, ii) to obtain a Pareto front as wide as possible and iii) to achieve a Pareto front uniformly spread. Indeed, multi-objective techniques using GAs have been increasing in relevance as a research area. In 1989, Goldberg suggested the use of a GA to solve multi-objective problems and since then other researchers have been developing new methods, such as the multi-objective genetic algorithm (MOGA) (Fonseca & Fleming, 1995), the non-dominated sorted genetic algorithm (NSGA) (Deb, 2001), and the niched Pareto genetic algorithm (NPGA) (Horn et al., 1994), among several other variants (Coello, 1998). In this work the trajectory planning problem considers: i) robots with 2 and 3 degrees of freedom (dof ), ii) the inclusion of obstacles in the workspace and iii) up to five criteria that are used to qualify the evolving trajectory, namely the: joint traveling distance, joint velocity, end effector / Cartesian distance, end effector / Cartesian velocity and energy involved. These criteria are used to minimize the joint and end effector traveled distance, trajectory ripple and energy required by the manipulator to reach at destination point. Bearing this ideas in mind, the paper addresses the planning of robot trajectories, meaning the development of an algorithm to find a continuous motion that takes the manipulator from a given starting configuration up to a desired end position without colliding with any obstacle in the workspace. The chapter is organized as follows. Section 2 describes the trajectory planning and several approaches proposed in the literature. Section 3 formulates the problem, namely the representation adopted to solve the trajectory planning and the objectives considered in the optimization. Section 4 studies the algorithm convergence. Section 5 studies a 2R manipulator (i.e., a robot with two rotational joints/links) when the optimization trajectory considers two and five objectives. Sections 6 and 7 show the results for the 3R redundant manipulator with five goals and for other complementary experiments are described, respectively. Finally, section 8 draws the main conclusions.

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This paper proposes a stochastic mixed-integer linear approach to deal with a short-term unit commitment problem with uncertainty on a deregulated electricity market that includes day-ahead bidding and bilateral contracts. The proposed approach considers the typically operation constraints on the thermal units and a spinning reserve. The uncertainty is due to the electricity prices, which are modeled by a scenario set, allowing an acceptable computation. Moreover, emission allowances are considered in a manner to allow for the consideration of environmental constraints. A case study to illustrate the usefulness of the proposed approach is presented and an assessment of the cost for the spinning reserve is obtained by a comparison between the situation with and without spinning reserve.

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This chapter considers the particle swarm optimization algorithm as a system, whose dynamics is studied from the point of view of fractional calculus. In this study some initial swarm particles are randomly changed, for the system stimulation, and its response is compared with a non-perturbed reference response. The perturbation effect in the PSO evolution is observed in the perspective of the fitness time behaviour of the best particle. The dynamics is represented through the median of a sample of experiments, while adopting the Fourier analysis for describing the phenomena. The influence upon the global dynamics is also analyzed. Two main issues are reported: the PSO dynamics when the system is subjected to random perturbations, and its modelling with fractional order transfer functions.

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OBJECTIVE To validate a screening instrument using self-reported assessment of frailty syndrome in older adults.METHODS This cross-sectional study used data from the Saúde, Bem-estar e Envelhecimento study conducted in Sao Paulo, SP, Southeastern Brazil. The sample consisted of 433 older adult individuals (≥ 75 years) assessed in 2009. The self-reported instrument can be applied to older adults or their proxy respondents and consists of dichotomous questions directly related to each component of the frailty phenotype, which is considered the gold standard model: unintentional weight loss, fatigue, low physical activity, decreased physical strength, and decreased walking speed. The same classification proposed in the phenotype was utilized: not frail (no component identified); pre-frail (presence of one or two components), and frail (presence of three or more components). Because this is a screening instrument, “process of frailty” was included as a category (pre-frail and frail). Cronbach’s α was used in psychometric analysis to evaluate the reliability and validity of the criterion, the sensitivity, the specificity, as well as positive and negative predictive values. Factor analysis was used to assess the suitability of the proposed number of components.RESULTS Decreased walking speed and decreased physical strength showed good internal consistency (α = 0.77 and 0.72, respectively); however, low physical activity was less satisfactory (α = 0.63). The sensitivity and specificity for identifying pre-frail individuals were 89.7% and 24.3%, respectively, while those for identifying frail individuals were 63.2% and 71.6%, respectively. In addition, 89.7% of the individuals from both the evaluations were identified in the “process of frailty” category.CONCLUSIONS The self-reported assessment of frailty can identify the syndrome among older adults and can be used as a screening tool. Its advantages include simplicity, rapidity, low cost, and ability to be used by different professionals.

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OBJECTIVE To investigate the association between social capital and social capital and self-perception of health based on examining the influence of health-related behaviors as possible mediators of this relationship.METHODS A cross-sectional study was used with 1,081 subjects, which is representative of the population of individuals aged 40 years or more in a medium-sized city in Southern Brazil. The subjects who perceived their health as fine, bad or very bad were considered to have a negative self-perception of their health. The social capital indicators were: number of friends, people from whom they could borrow money from when needed; the extent of trust in community members; whether or not members of the community helped each other; community safety; and extent of participation in community activities. The behaviors were: physical activity during leisure time, fruits and vegetable consumption, tobacco use and alcohol abuse. The odds ratios (OR) and confidence intervals (CI) 95% were calculated by binary logistic regression. The significance of mediation was verified using the Sobel test.RESULTS Following adjustment for demographic and clinical variables, subjects with fewer friends (OR = 1.39, 95%CI 1.08;1.80), those who perceived less frequently help from people in the neighborhood (OR = 1.30, 95%CI 1.01;1.68), who saw the violent neighborhood (OR = 1.33, 95%CI 1.01;1.74) and who had not participated in any community activity (OR = 1.39, 95%CI 1.07;1.80) had more negative self-perception of their health. Physical activity during leisure time was a significant mediator in the relationship between all social capital indicators (except for the borrowed money variable) and self-perceived health. Fruit and vegetable consumption was a significant mediator of the relationship between the extent of participation in community activities and self-perceived health. Tobacco use and alcohol abuse did not seem to have a mediating role in any relationship.CONCLUSIONS Lifestyle seems to only partially explain the relationship between social capital and self-perceived health. Among the investigated behaviors, physical activity during leisure time is what seems to have the most important role as a mediator of this relationship.

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Functionally graded materials are a type of composite materials which are tailored to provide continuously varying properties, according to specific constituent's mixing distributions. These materials are known to provide superior thermal and mechanical performances when compared to the traditional laminated composites, because of this continuous properties variation characteristic, which enables among other advantages, smoother stresses distribution profiles. Therefore the growing trend on the use of these materials brings together the interest and the need for getting optimum configurations concerning to each specific application. In this work it is studied the use of particle swarm optimization technique for the maximization of a functionally graded sandwich beam bending stiffness. For this purpose, a set of case studies is analyzed, in order to enable to understand in a detailed way, how the different optimization parameters tuning can influence the whole process. It is also considered a re-initialization strategy, which is not a common approach in particle swarm optimization as far as it was possible to conclude from the published research works. As it will be shown, this strategy can provide good results and also present some advantages in some conditions. This work was developed and programmed on symbolic computation platform Maple 14. (C) 2013 Elsevier B.V. All rights reserved.

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Magneto-electro-elastic structures are built from materials that provide them the ability to convert in an interchangeable way, magnetic, electric and mechanical forms of energy. This characteristic can therefore provide an adaptive behaviour to a general configuration elastic structure, being commonly used in association with any type of composite material in an embedded or surface mounted mode, or by considering the usage of multiphase materials that enable achieving different magneto-electro-elastic properties. In a first stage of this work, a few cases studies will be considered to enable the validation of the model considered and the influence of the coupling characteristics of this type of adaptive structures. After that we consider the application of a recent computational intelligence technique, the differential evolution, in a deflection profile minimization problem. Studies on the influence of optimization parameters associated to the problem considered will be performed as well as the adoption of an adaptive scheme for the perturbation factor. Results are also compared with those obtained using an enhanced particle swarm optimization technique. (C) 2013 Elsevier Ltd. All rights reserved.

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Radial basis functions are being used in different scientific areas in order to reproduce the geometrical modeling of an object/structure, as well as to predict its behavior. Due to its characteristics, these functions are well suited for meshfree modeling of physical quantities, which for instances can be associated to the data sets of 3D laser scanning point clouds. In the present work the geometry of a structure is modeled by using multiquadric radial basis functions, and its configuration is further optimized in order to obtain better performances concerning to its static and dynamic behavior. For this purpose the authors consider the particle swarm optimization technique. A set of case studies is presented to illustrate the adequacy of the meshfree model used, as well as its link to particle swarm optimization technique. © 2014 IEEE.

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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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The trajectory planning of redundant robots is an important area of research and efficient optimization algorithms have been investigated in the last years. This paper presents a new technique that combines the closed-loop pseudoinverse method with genetic algorithms. In this case the trajectory planning is formulated as an optimization problem with constraints.

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The increasing use of Carbon-Fibre Reinforced Plastic (CFRP) laminates in high responsibility applications introduces an issue regarding their handling after damage. The availability of efficient repair methods is essential to restore the strength of the structure. The availability of accurate predictive tools for the repairs behaviour is also essential for the reduction of costs and time associated to extensive tests. This work reports on a numerical study of the tensile behaviour of three-dimensional (3D) adhesively-bonded scarf repairs in CFRP structures, using a ductile adhesive. The Finite Element (FE) analysis was performed in ABAQUS® and Cohesive Zone Models (CZM’s) was used for the simulation of damage in the adhesive layer. A parametric study was performed on two geometric parameters. The use of overlaminating plies covering the repaired region at the outer or both repair surfaces was also tested as an attempt to increase the repairs efficiency. The results allowed the proposal of design principles for repairing CFRP structures.

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This paper proposes a novel method for controlling the convergence rate of a particle swarm optimization algorithm using fractional calculus (FC) concepts. The optimization is tested for several well-known functions and the relationship between the fractional order velocity and the convergence of the algorithm is observed. The FC demonstrates a potential for interpreting evolution of the algorithm and to control its convergence.

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OBJECTIVE To evaluate the prevalence of self-medication in Brazil’s adult population.METHODS Systematic review of cross-sectional population-based studies. The following databases were used: Medline, Embase, Scopus, ISI, CINAHL, Cochrane Library, CRD, Lilacs, SciELO, the Banco de teses brasileiras(Brazilian theses database) (Capes) and files from the Portal Domínio Público (Brazilian Public Domain). In addition, the reference lists from relevant studies were examined to identify potentially eligible articles. There were no applied restrictions in terms of the publication date, language or publication status. Data related to publication, population, methods and prevalence of self-medication were extracted by three independent researchers. Methodological quality was assessed following eight criteria related to sampling, measurement and presentation of results. The prevalences were measured from participants who used at least one medication during the recall period of the studies.RESULTS The literature screening identified 2,778 records, from which 12 were included for analysis. Most studies were conducted in the Southeastern region of Brazil, after 2000 and with a 15-day recall period. Only five studies achieved high methodological quality, of which one study had a 7-day recall period, in which the prevalence of self-medication was 22.9% (95%CI 14.6;33.9). The prevalence of self-medication in three studies of high methodological quality with a 15-day recall period was 35.0% (95%CI 29.0;40.0, I2 = 83.9%) in the adult Brazilian population.CONCLUSIONS Despite differences in the methodologies of the included studies, the results of this systematic review indicate that a significant proportion of the adult Brazilian population self-medicates. It is suggested that future research projects that assess self-medication in Brazil standardize their methods.