760 resultados para QUADRATIC PROGRAMS


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We consider the problem of structured classification, where the task is to predict a label y from an input x, and y has meaningful internal structure. Our framework includes supervised training of Markov random fields and weighted context-free grammars as special cases. We describe an algorithm that solves the large-margin optimization problem defined in [12], using an exponential-family (Gibbs distribution) representation of structured objects. The algorithm is efficient—even in cases where the number of labels y is exponential in size—provided that certain expectations under Gibbs distributions can be calculated efficiently. The method for structured labels relies on a more general result, specifically the application of exponentiated gradient updates [7, 8] to quadratic programs.

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New embedded predictive control applications call for more eficient ways of solving quadratic programs (QPs) in order to meet demanding real-time, power and cost requirements. A single precision QP-on-a-chip controller is proposed, implemented in afield-programmable gate array (FPGA) with an iterative linear solver at its core. A novel offline scaling procedure is introduced to aid the convergence of the reduced precision solver. The feasibility of the proposed approach is demonstrated with a real-time hardware-in-the-loop (HIL) experimental setup where an ML605 FPGA board controls a nonlinear model of a Boeing 747 aircraft running on a desktop PC through an Ethernet link. Simulations show that the quality of the closed-loop control and accuracy of individual solutions is competitive with a conventional double precision controller solving linear systems using a Riccati recursion. © 2012 IFAC.

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En este trabajo se implementa una metodología para incluir momentos de orden superior en la selección de portafolios, haciendo uso de la Distribución Hiperbólica Generalizada, para posteriormente hacer un análisis comparativo frente al modelo de Markowitz.

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A method for linearly constrained optimization which modifies and generalizes recent box-constraint optimization algorithms is introduced. The new algorithm is based on a relaxed form of Spectral Projected Gradient iterations. Intercalated with these projected steps, internal iterations restricted to faces of the polytope are performed, which enhance the efficiency of the algorithm. Convergence proofs are given and numerical experiments are included and commented. Software supporting this paper is available through the Tango Project web page: http://www.ime.usp.br/similar to egbirgin/tango/.

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We propose a positive, accurate moment closure for linear kinetic transport equations based on a filtered spherical harmonic (FP_N) expansion in the angular variable. The FP_N moment equations are accurate approximations to linear kinetic equations, but they are known to suffer from the occurrence of unphysical, negative particle concentrations. The new positive filtered P_N (FP_N+) closure is developed to address this issue. The FP_N+ closure approximates the kinetic distribution by a spherical harmonic expansion that is non-negative on a finite, predetermined set of quadrature points. With an appropriate numerical PDE solver, the FP_N+ closure generates particle concentrations that are guaranteed to be non-negative. Under an additional, mild regularity assumption, we prove that as the moment order tends to infinity, the FP_N+ approximation converges, in the L2 sense, at the same rate as the FP_N approximation; numerical tests suggest that this assumption may not be necessary. By numerical experiments on the challenging line source benchmark problem, we confirm that the FP_N+ method indeed produces accurate and non-negative solutions. To apply the FP_N+ closure on problems at large temporal-spatial scales, we develop a positive asymptotic preserving (AP) numerical PDE solver. We prove that the propose AP scheme maintains stability and accuracy with standard mesh sizes at large temporal-spatial scales, while, for generic numerical schemes, excessive refinements on temporal-spatial meshes are required. We also show that the proposed scheme preserves positivity of the particle concentration, under some time step restriction. Numerical results confirm that the proposed AP scheme is capable for solving linear transport equations at large temporal-spatial scales, for which a generic scheme could fail. Constrained optimization problems are involved in the formulation of the FP_N+ closure to enforce non-negativity of the FP_N+ approximation on the set of quadrature points. These optimization problems can be written as strictly convex quadratic programs (CQPs) with a large number of inequality constraints. To efficiently solve the CQPs, we propose a constraint-reduced variant of a Mehrotra-predictor-corrector algorithm, with a novel constraint selection rule. We prove that, under appropriate assumptions, the proposed optimization algorithm converges globally to the solution at a locally q-quadratic rate. We test the algorithm on randomly generated problems, and the numerical results indicate that the combination of the proposed algorithm and the constraint selection rule outperforms other compared constraint-reduced algorithms, especially for problems with many more inequality constraints than variables.

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Background: Gene expression connectivity mapping has proven to be a powerful and flexible tool for research. Its application has been shown in a broad range of research topics, most commonly as a means of identifying potential small molecule compounds, which may be further investigated as candidates for repurposing to treat diseases. The public release of voluminous data from the Library of Integrated Cellular Signatures (LINCS) programme further enhanced the utilities and potentials of gene expression connectivity mapping in biomedicine. Results: We describe QUADrATiC (http://go.qub.ac.uk/QUADrATiC), a user-friendly tool for the exploration of gene expression connectivity on the subset of the LINCS data set corresponding to FDA-approved small molecule compounds. It enables the identification of compounds for repurposing therapeutic potentials. The software is designed to cope with the increased volume of data over existing tools, by taking advantage of multicore computing architectures to provide a scalable solution, which may be installed and operated on a range of computers, from laptops to servers. This scalability is provided by the use of the modern concurrent programming paradigm provided by the Akka framework. The QUADrATiC Graphical User Interface (GUI) has been developed using advanced Javascript frameworks, providing novel visualization capabilities for further analysis of connections. There is also a web services interface, allowing integration with other programs or scripts.Conclusions: QUADrATiC has been shown to provide an improvement over existing connectivity map software, in terms of scope (based on the LINCS data set), applicability (using FDA-approved compounds), usability and speed. It offers potential to biological researchers to analyze transcriptional data and generate potential therapeutics for focussed study in the lab. QUADrATiC represents a step change in the process of investigating gene expression connectivity and provides more biologically-relevant results than previous alternative solutions.

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In order to succeed in biological control programs, not only is it crucial to understand the number of natural enemies to be released but also on how many sites per area this releasing must be performed. These variables might differ deeply among egg parasitoid species and crops worked. Therefore, these trials were carried out to evaluate the parasitism (%) in eggs of Anticarsia gemmatalis and Pseudoplusia includens after the release of different densities of the egg parasitoid Trichogramma pretiosum. Field dispersal was also studied, in order to determine appropriate recommendations for the release of this parasitoid in soybean fields. The regression analysis between parasitism (%) and densities of the parasitoid indicated a quadratic effect for both A. gemmatalis and P. includens. The maximum parasitism within 24 h after the release was reached with densities of 25.6 and 51.2 parasitoids per host egg, respectively, for the two pests. Parasitism of T. pretiosum in eggs of P. includens decreased linearly as the distance of the pest eggs from the parasitoid release sites increased. For P. includens, the mean radius of T. pretiosum action and the area of parasitoid dispersal in the soybean crop were 8.01 m and 85.18 m(2), respectively. We conclude that for a successful biological control program of lepidopteran pests using T. pretiosum in soybean fields, a density of 25.6 parasitoids per host egg, divided into 117 sites per hectare, should be used.

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Introducción. La obesidad puede definirse como una enfermedad metabólica crónica de origen multifactorial, lo que provoca trastornos o problemas físicos y psicológicos a la persona, con patologías asociadas que limitan la esperanza de vida y deterioran la calidad de la misma, siendo determinante para sus áreas sociales y laborales. Este trastorno metabólico crónico se caracteriza por una acumulación excesiva de energía en el cuerpo en forma de grasa, lo que lleva a un aumento de peso con respecto al valor esperado por sexo, edad y altura. La gestión y el tratamiento de la obesidad tienen objetivos más amplios que la pérdida de peso e incluyen la reducción del riesgo y la mejora de la salud. Estos pueden ser alcanzados por la pérdida modesta de peso (es decir, 10.5% del peso corporal inicial), la mejora del contenido nutricional de la dieta y un modesto incremento en la actividad física y condición física. La dieta es uno de los métodos más populares para perder peso corporal. El ejercicio es otra alternativa para perder peso corporal. El aumento de ejercicio provoca un desequilibrio cuando se mantiene la ingesta calórica. También tiene ventajas, como la mejora del tono muscular, la capacidad cardiovascular, fuerza y flexibilidad, aumenta el metabolismo basal y mejora el sistema inmunológico. Objetivos. El objetivo de esta tesis es contribuir en un estudio de intervención para aclarar la evolución del peso corporal durante una intervención de dieta y ejercicio. Para ello, se evaluaron los efectos de la edad, sexo, índice de masa corporal inicial y el tipo de tratamiento en las tendencias de pérdida de peso. Otro objetivo de la tesis era crear un modelo de regresión lineal múltiple capaz de predecir la pérdida de peso corporal después del periodo de intervención. Y, por último, determinar el efecto sobre la composición corporal (peso corporal, índice de masa corporal, la masa grasa, y la masa libre de grasa) de las diferentes intervenciones basadas en ejercicios (fuerza, resistencia, resistencia combinada con fuerza, y las recomendaciones de actividad física (grupo control)) en combinación con dieta de adultos con sobrepeso y obesidad, después de la intervención, así como los cambios de la composición corporal 3 años más tarde. Diseño de la investigación. Los datos empleados en el análisis de esta tesis son parte del proyecto “Programas de Nutrición y Actividad Física para el tratamiento de la obesidad” (PRONAF). El proyecto PRONAF es un estudio clínico sobre programas de nutrición y actividad física para el sobrepeso y la obesidad, desarrollado en España durante varios años de intervención. Fue diseñado, en parte, para comparar diferentes tipos de intervención, con el objetivo de evaluar su impacto en las dinámicas de pérdida de peso, en personas con sobrepeso y obesidad. Como diseño experimental, el estudio se basó en una restricción calórica, a la que, en algunos casos, se le añadió un protocolo de entrenamiento (fuerza, resistencia, o combinado, en igualdad de volumen e intensidad). Las principales variables para la investigación que comprende esta tesis fueron: el peso corporal y la composición corporal (masa grasa y masa libre de grasa). Conclusiones. En esta tesis, para los programas de pérdida de peso en personas con sobrepeso y obesidad con un 25-30% de la restricción calórica, el peso corporal se redujo significativamente en ambos sexos, sin tener en cuenta la edad y el tipo de tratamiento seguido. Según los resultados del estudio, la pérdida de peso realizada por un individuo (hombre o mujer) durante los seis meses puede ser representada por cualquiera de las cinco funciones (lineal, potencial, exponencial, logarítmica y cuadrática) en ambos sexos, siendo la cuadrática la que tiende a representarlo mejor. Además, se puede concluir que la pérdida de peso corporal se ve afectada por el índice de masa corporal inicial y el sexo, siendo mayor para las personas obesas que para las de sobrepeso, que muestran diferencias entre sexos sólo en la condición de sobrepeso. Además, es posible calcular el peso corporal final de cualquier participante involucrado en una intervención utilizando la metodología del proyecto PRONAF sólo conociendo sus variables iniciales de composición corporal. Además, los cuatro tipos de tratamientos tuvieron resultados similares en cambios en la composición corporal al final del período de intervención, con la única excepción de la masa libre de grasa, siendo los grupos de entrenamiento los que la mantuvieron durante la restricción calórica. Por otro lado, sólo el grupo combinado logra mantener la reducción de la masa grasa (%) 3 años después del final de la intervención. ABSTRACT Introduction. Obesity can be defined as a chronic metabolic disease from a multifactorial origin, which leads to physical and psychological impacts to the person, with associated pathologies that limit the life expectancy and deteriorate the quality of it, being determinant for the social and labor areas of the person. This chronic metabolic disorder is characterized by an excessive accumulation of energy in the body as fat, leading to increased weight relative to the value expected by sex, age and height. The management and treatment of obesity have wider objectives than weight loss alone and include risk reduction and health improvement. These may be achieved by modest weight loss (i.e. 5–10% of initial body weight), improved nutritional content of the diet and modest increases in physical activity and fitness. Weight loss through diet is one of the most popular approaches to lose body weight. Exercise is another alternative to lose body weight. The increase of exercise causes an imbalance when the caloric intake is maintained. It also has advantages such as improved muscle tone, cardiovascular fitness, strength and flexibility, increases the basal metabolism and improves immune system. Objectives. The aim of this thesis is to contribute with an interventional study to clarify the evolution of the body weight during a diet and exercise intervention. For this, the effects of age, sex, initial body mass index and type of treatment on weight loss tendencies were evaluated. Another objective of the thesis was to create a multiple linear regression model able to predict the body weight loss after the intervention period. And, finally, to determine the effect upon body composition (body weight, body mass index, fat mass, and fat-free mass of different exercise-based interventions (strength, endurance, combined endurance and strength, and physical activity recommendations group (control group)) combined with diet in overweight and obese adults, after intervention as well as body composition changes 3 years later. Research Design. The data used in the analysis of this thesis are part of the project "Programs of Nutrition and Physical Activity for the treatment of obesity" (PRONAF). The PRONAF project is a clinical trial program about nutrition and physical activity for overweight and obesity, developed in Spain for several years of intervention. It was designed, in part, to compare different types of intervention, in order to assess their impact on the dynamics of weight loss in overweight and obese people. As experimental design, the study was based on caloric restriction, which, in some cases, added a training protocol (strength, endurance, or combined in equal volume and intensity). The main research variables comprising this thesis were: body weight and body composition outcomes (fat mass and fat-free mass). Conclusions. In this thesis, for weight loss programs in overweight and obese people with 25-30% of caloric restriction, the body weight was significantly decreased in both sexes, regardless the age and type of followed treatment. According to the results of the study, the weight loss performed by an individual (male or female) during six months can be represented by any of the five functions (linear, power law, exponential, logarithmic and quadratic) in both sexes, being the quadratic one which tends to represent it better. In addition, it can be concluded that the body weight loss is affected by the initial body mass index and sex condition, being greater for the obese people than for the overweight one, showing differences between sexes only in the overweight condition. Moreover, it is possible to calculate the final body weight of any participant engaged in an intervention using the PRONAF Project methodology only knowing their initial body composition variables. Furthermore, the four types of treatments had similar results on body composition changes at the end of the intervention period, with the only exception of fat-free mass, being the training groups the ones that maintained it during the caloric restriction. On the other hand, only the combined group achieved to maintain the fat mass (%) reduced 3 years after the end of the intervention.

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Linear Programming (LP) is a powerful decision making tool extensively used in various economic and engineering activities. In the early stages the success of LP was mainly due to the efficiency of the simplex method. After the appearance of Karmarkar's paper, the focus of most research was shifted to the field of interior point methods. The present work is concerned with investigating and efficiently implementing the latest techniques in this field taking sparsity into account. The performance of these implementations on different classes of LP problems is reported here. The preconditional conjugate gradient method is one of the most powerful tools for the solution of the least square problem, present in every iteration of all interior point methods. The effect of using different preconditioners on a range of problems with various condition numbers is presented. Decomposition algorithms has been one of the main fields of research in linear programming over the last few years. After reviewing the latest decomposition techniques, three promising methods were chosen the implemented. Sparsity is again a consideration and suggestions have been included to allow improvements when solving problems with these methods. Finally, experimental results on randomly generated data are reported and compared with an interior point method. The efficient implementation of the decomposition methods considered in this study requires the solution of quadratic subproblems. A review of recent work on algorithms for convex quadratic was performed. The most promising algorithms are discussed and implemented taking sparsity into account. The related performance of these algorithms on randomly generated separable and non-separable problems is also reported.

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