965 resultados para General variable neighborhood search


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OBJECTIVE: To assess the frequency of combination of antidepressants with other drugs and risk of drug interactions in the setting public hospital units in Brazil. METHODS: Prescriptions of all patients admitted to a public hospital from November 1996 to February 1997 were surveyed from the hospital's data processing center in São Paulo, Brazil. A manual search of case notes of all patients admitted to the psychiatric unit from January 1993 to December 1995 and all patients registered in the affective disorders outpatient clinic in December 1996 was carried out. Patients taking any antidepressant were identified and concomitant use of drugs was checked. By means of a software program (Micromedex®) drug interactions were identified. RESULTS: Out of 6,844 patients admitted to the hospital, 63 (0.9%) used antidepressants and 16 (25.3%) were at risk of drug interaction. Out of 311 patients in the psychiatric unit, 63 (20.2%) used antidepressants and 13 of them (20.6%) were at risk. Out of 87 patients in the affective disorders outpatient clinic, 43 (49.4%) took antidepressants and 7 (16.2%) were at risk. In general, the use of antidepressants was recorded in 169 patients and 36 (21.3%) were at risk of drug interactions. Twenty different forms of combinations at risk of drug interactions were identified: four were classified as mild, 15 moderate and one severe interaction. CONCLUSION: In the hospital general units the number of drug interactions per patient was higher than in the psychiatric unit; and prescription for depression was lower than expected.

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Power converters play a vital role in the integration of wind power into the electrical grid. Variable-speed wind turbine generator systems have a considerable interest of application for grid connection at constant frequency. In this paper, comprehensive simulation studies are carried out with three power converter topologies: matrix, two-level and multilevel. A fractional-order control strategy is studied for the variable-speed operation of wind turbine generator systems. The studies are in order to compare power converter topologies and control strategies. The studies reveal that the multilevel converter and the proposed fractional-order control strategy enable an improvement in the power quality, in comparison with the other power converters using a classical integer-order control strategy. (C) 2010 Elsevier Ltd. All rights reserved.

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In practical applications of optimization it is common to have several conflicting objective functions to optimize. Frequently, these functions are subject to noise or can be of black-box type, preventing the use of derivative-based techniques. We propose a novel multiobjective derivative-free methodology, calling it direct multisearch (DMS), which does not aggregate any of the objective functions. Our framework is inspired by the search/poll paradigm of direct-search methods of directional type and uses the concept of Pareto dominance to maintain a list of nondominated points (from which the new iterates or poll centers are chosen). The aim of our method is to generate as many points in the Pareto front as possible from the polling procedure itself, while keeping the whole framework general enough to accommodate other disseminating strategies, in particular, when using the (here also) optional search step. DMS generalizes to multiobjective optimization (MOO) all direct-search methods of directional type. We prove under the common assumptions used in direct search for single objective optimization that at least one limit point of the sequence of iterates generated by DMS lies in (a stationary form of) the Pareto front. However, extensive computational experience has shown that our methodology has an impressive capability of generating the whole Pareto front, even without using a search step. Two by-products of this paper are (i) the development of a collection of test problems for MOO and (ii) the extension of performance and data profiles to MOO, allowing a comparison of several solvers on a large set of test problems, in terms of their efficiency and robustness to determine Pareto fronts.

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OBJETIVO: El objetivo del estudio es identificar factores socioeconómicos, gineco-obstétricos y del producto asociados a mortalidad perinatal. MÉTODOS: Se realizó un estudio de casos y controles pareado. Se consideró caso a los nacidos vivos o muertos que nacieron y fallecieron entre las 28 semanas de gestación a los 7 días de vida extrauterina. y control al producto nacido vivo entre las 28 semanas de gestación y los 7 días de vida extrauterina. Los datos se obtuvieron de los expedientes clínicos hospitalarios. Se estudiaron 99 casos y 197 controles. Se hizo un análisis estadístico utilizando Stata 6.0. RESULTADOS La media de edad de la madre fue de 24.82 años y del producto de 37.78 semanas de gestación. El promedio de peso del producto fue de 2,760 gramos. Los factores asociados a mortalidad perinatal fueron: ocupación del padre agricultor (RM ajustada 3,31; IC 95% 1,26-8,66); índice de riesgo obstétrico alto (RM ajustada 10,57; IC 95% 2,82-39,66), antecedente de cesárea (RM ajustada 2,75; IC 95% 1,37-5,51); cinco y más consultas prenatales (RM ajustada 4,43; IC 95% 1.86-10,54); producto pretérmino (RM ajustada 9,20; IC 95% 4,39-19,25). CONCLUSIONES: Los resultados muestran que es necesario implementar medidas de prevención y control que aseguren la identificación del riesgo en las mujeres embarazadas, con el fin de abatir la incidencia de mortalidad perinatal.

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As wind power generation undergoes rapid growth, new technical challenges emerge: dynamic stability and power quality. The influence of wind speed disturbances and a pitch control malfunction on the quality of the energy injected into the electric grid is studied for variable-speed wind turbines with different power-electronic converter topologies. Additionally, a new control strategy is proposed for the variable-speed operation of wind turbines with permanent magnet synchronous generators. The performance of disturbance attenuation and system robustness is ascertained. Simulation results are presented and conclusions are duly drawn. (C) 2010 Elsevier Ltd. All rights reserved.

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To maintain a power system within operation limits, a level ahead planning it is necessary to apply competitive techniques to solve the optimal power flow (OPF). OPF is a non-linear and a large combinatorial problem. The Ant Colony Search (ACS) optimization algorithm is inspired by the organized natural movement of real ants and has been successfully applied to different large combinatorial optimization problems. This paper presents an implementation of Ant Colony optimization to solve the OPF in an economic dispatch context. The proposed methodology has been developed to be used for maintenance and repairing planning with 48 to 24 hours antecipation. The main advantage of this method is its low execution time that allows the use of OPF when a large set of scenarios has to be analyzed. The paper includes a case study using the IEEE 30 bus network. The results are compared with other well-known methodologies presented in the literature.

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Dissertação apresentada à Escola Superior de Educação de Lisboa no âmbito do Mestrado em Ensino Especial

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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The aim of this work is to use the MANCOVA model to study the influence of the phenotype of an enzyme - Acid phosphatase - and a genetic factor - Haptoglobin genotype - on two dependent variables - Activity of Acid Phosphatase (ACP1) and the Body Mass Index (BMI). Therefore it's used a general linear model, namely a multivariate analysis of covariance (Two-way MANCOVA). The covariate is the age of the subject. This covariate works as control variable for the independent factors, serving to reduce the error term in the model. The main results showed that only the ACP1 phenotype has a significant effect on the activity of ACP1 and the covariate has a significant effect in both dependent variables. The univariate analysis showed that ACP1 phenotype accounts for about 12.5% of the variability in the activity of ACP1. In respect to this covariate it can be seen that accounts for about 4.6% of the variability in the activity of ACP1 and 37.3% in the BMI.

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Mestrado em Intervenção Sócio-Organizacional na Saúde - Área de especialização: Políticas de Administração e Gestão de Serviços de Saúde.

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OBJECTIVE: To assess the performance of the rubella suspect case definition among patients with rash diseases seen at primary care units. METHODS: From January 1994 to December 2002, patients with acute rash, with or without fever, were seen at two large primary health care units and at a public general hospital in the municipality of Niterói, metropolitan area of Rio de Janeiro, Brazil. Data from clinical and serologic assessment were used to estimate the positive predictive values of the definition of rubella suspect case from the Brazilian Ministry of Health and other combination of signs/symptoms taking serologic status as the reference. Serum samples were tested for anti-rubella virus IgM using commercially available enzyme immunoassays. Positive predictive values and respective 95% confidence intervals were calculated. RESULTS: A total of 1,186 patients with an illness characterized by variable combinations of rash with fever, arthropathy and lymphadenopathy were studied. Patients with rash, regardless of other signs and symptoms, had 8.8% likelihood of being IgM-positive for rubella. The Brazilian suspect case definition (fever and lymphadenopathy in addition to rash) had low predictive value (13.5%). This case definition would correctly identify 42.3% of the IgM-positive cases, and misclassify 26.1% of the IgM-negative cases. CONCLUSIONS: These results support the recommendation to investigate and collect clinical specimens for laboratory diagnosis of all cases of rash, for surveillance purposes. Although this strategy may increase costs, the benefits of interrupting the circulation of rubella virus and preventing the occurrence of congenital rubella syndrome should pay off.

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Copyright © 2013 Springer Netherlands.

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Copyright © 2013 Springer Netherlands.

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In real optimization problems, usually the analytical expression of the objective function is not known, nor its derivatives, or they are complex. In these cases it becomes essential to use optimization methods where the calculation of the derivatives, or the verification of their existence, is not necessary: the Direct Search Methods or Derivative-free Methods are one solution. When the problem has constraints, penalty functions are often used. Unfortunately the choice of the penalty parameters is, frequently, very difficult, because most strategies for choosing it are heuristics strategies. As an alternative to penalty function appeared the filter methods. A filter algorithm introduces a function that aggregates the constrained violations and constructs a biobjective problem. In this problem the step is accepted if it either reduces the objective function or the constrained violation. This implies that the filter methods are less parameter dependent than a penalty function. In this work, we present a new direct search method, based on simplex methods, for general constrained optimization that combines the features of the simplex method and filter methods. This method does not compute or approximate any derivatives, penalty constants or Lagrange multipliers. The basic idea of simplex filter algorithm is to construct an initial simplex and use the simplex to drive the search. We illustrate the behavior of our algorithm through some examples. The proposed methods were implemented in Java.

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The filter method is a technique for solving nonlinear programming problems. The filter algorithm has two phases in each iteration. The first one reduces a measure of infeasibility, while in the second the objective function value is reduced. In real optimization problems, usually the objective function is not differentiable or its derivatives are unknown. In these cases it becomes essential to use optimization methods where the calculation of the derivatives or the verification of their existence is not necessary: direct search methods or derivative-free methods are examples of such techniques. In this work we present a new direct search method, based on simplex methods, for general constrained optimization that combines the features of simplex and filter methods. This method neither computes nor approximates derivatives, penalty constants or Lagrange multipliers.