27 resultados para Parallel numerical algorithms

em Universidad Politécnica de Madrid


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La segmentación de imágenes es un campo importante de la visión computacional y una de las áreas de investigación más activas, con aplicaciones en comprensión de imágenes, detección de objetos, reconocimiento facial, vigilancia de vídeo o procesamiento de imagen médica. La segmentación de imágenes es un problema difícil en general, pero especialmente en entornos científicos y biomédicos, donde las técnicas de adquisición imagen proporcionan imágenes ruidosas. Además, en muchos de estos casos se necesita una precisión casi perfecta. En esta tesis, revisamos y comparamos primero algunas de las técnicas ampliamente usadas para la segmentación de imágenes médicas. Estas técnicas usan clasificadores a nivel de pixel e introducen regularización sobre pares de píxeles que es normalmente insuficiente. Estudiamos las dificultades que presentan para capturar la información de alto nivel sobre los objetos a segmentar. Esta deficiencia da lugar a detecciones erróneas, bordes irregulares, configuraciones con topología errónea y formas inválidas. Para solucionar estos problemas, proponemos un nuevo método de regularización de alto nivel que aprende información topológica y de forma a partir de los datos de entrenamiento de una forma no paramétrica usando potenciales de orden superior. Los potenciales de orden superior se están popularizando en visión por computador, pero la representación exacta de un potencial de orden superior definido sobre muchas variables es computacionalmente inviable. Usamos una representación compacta de los potenciales basada en un conjunto finito de patrones aprendidos de los datos de entrenamiento que, a su vez, depende de las observaciones. Gracias a esta representación, los potenciales de orden superior pueden ser convertidos a potenciales de orden 2 con algunas variables auxiliares añadidas. Experimentos con imágenes reales y sintéticas confirman que nuestro modelo soluciona los errores de aproximaciones más débiles. Incluso con una regularización de alto nivel, una precisión exacta es inalcanzable, y se requeire de edición manual de los resultados de la segmentación automática. La edición manual es tediosa y pesada, y cualquier herramienta de ayuda es muy apreciada. Estas herramientas necesitan ser precisas, pero también lo suficientemente rápidas para ser usadas de forma interactiva. Los contornos activos son una buena solución: son buenos para detecciones precisas de fronteras y, en lugar de buscar una solución global, proporcionan un ajuste fino a resultados que ya existían previamente. Sin embargo, requieren una representación implícita que les permita trabajar con cambios topológicos del contorno, y esto da lugar a ecuaciones en derivadas parciales (EDP) que son costosas de resolver computacionalmente y pueden presentar problemas de estabilidad numérica. Presentamos una aproximación morfológica a la evolución de contornos basada en un nuevo operador morfológico de curvatura que es válido para superficies de cualquier dimensión. Aproximamos la solución numérica de la EDP de la evolución de contorno mediante la aplicación sucesiva de un conjunto de operadores morfológicos aplicados sobre una función de conjuntos de nivel. Estos operadores son muy rápidos, no sufren de problemas de estabilidad numérica y no degradan la función de los conjuntos de nivel, de modo que no hay necesidad de reinicializarlo. Además, su implementación es mucho más sencilla que la de las EDP, ya que no requieren usar sofisticados algoritmos numéricos. Desde un punto de vista teórico, profundizamos en las conexiones entre operadores morfológicos y diferenciales, e introducimos nuevos resultados en este área. Validamos nuestra aproximación proporcionando una implementación morfológica de los contornos geodésicos activos, los contornos activos sin bordes, y los turbopíxeles. En los experimentos realizados, las implementaciones morfológicas convergen a soluciones equivalentes a aquéllas logradas mediante soluciones numéricas tradicionales, pero con ganancias significativas en simplicidad, velocidad y estabilidad. ABSTRACT Image segmentation is an important field in computer vision and one of its most active research areas, with applications in image understanding, object detection, face recognition, video surveillance or medical image processing. Image segmentation is a challenging problem in general, but especially in the biological and medical image fields, where the imaging techniques usually produce cluttered and noisy images and near-perfect accuracy is required in many cases. In this thesis we first review and compare some standard techniques widely used for medical image segmentation. These techniques use pixel-wise classifiers and introduce weak pairwise regularization which is insufficient in many cases. We study their difficulties to capture high-level structural information about the objects to segment. This deficiency leads to many erroneous detections, ragged boundaries, incorrect topological configurations and wrong shapes. To deal with these problems, we propose a new regularization method that learns shape and topological information from training data in a nonparametric way using high-order potentials. High-order potentials are becoming increasingly popular in computer vision. However, the exact representation of a general higher order potential defined over many variables is computationally infeasible. We use a compact representation of the potentials based on a finite set of patterns learned fromtraining data that, in turn, depends on the observations. Thanks to this representation, high-order potentials can be converted into pairwise potentials with some added auxiliary variables and minimized with tree-reweighted message passing (TRW) and belief propagation (BP) techniques. Both synthetic and real experiments confirm that our model fixes the errors of weaker approaches. Even with high-level regularization, perfect accuracy is still unattainable, and human editing of the segmentation results is necessary. The manual edition is tedious and cumbersome, and tools that assist the user are greatly appreciated. These tools need to be precise, but also fast enough to be used in real-time. Active contours are a good solution: they are good for precise boundary detection and, instead of finding a global solution, they provide a fine tuning to previously existing results. However, they require an implicit representation to deal with topological changes of the contour, and this leads to PDEs that are computationally costly to solve and may present numerical stability issues. We present a morphological approach to contour evolution based on a new curvature morphological operator valid for surfaces of any dimension. We approximate the numerical solution of the contour evolution PDE by the successive application of a set of morphological operators defined on a binary level-set. These operators are very fast, do not suffer numerical stability issues, and do not degrade the level set function, so there is no need to reinitialize it. Moreover, their implementation is much easier than their PDE counterpart, since they do not require the use of sophisticated numerical algorithms. From a theoretical point of view, we delve into the connections between differential andmorphological operators, and introduce novel results in this area. We validate the approach providing amorphological implementation of the geodesic active contours, the active contours without borders, and turbopixels. In the experiments conducted, the morphological implementations converge to solutions equivalent to those achieved by traditional numerical solutions, but with significant gains in simplicity, speed, and stability.

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The paper presents a high accuracy fully analytical formulation to compute the miss distance and collision probability of two approaching objects following an impulsive collision avoidance maneuver. The formulation hinges on a linear relation between the applied impulse and the objects relative motion in the b-plane, which allows to formulate the maneuver optimization problem as an eigenvalue problem. The optimization criterion consists of minimizing the maneuver cost in terms of delta-V magnitude in order to either maximize collision miss distance or to minimize Gaussian collision probability. The algorithm, whose accuracy is verified in representative mission scenarios, can be employed for collision avoidance maneuver planning with reduced computational cost when compared to fully numerical algorithms.

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El objetivo de la tesis es la investigación de algoritmos numéricos para el desarrollo de herramientas numéricas para la simulación de problemas tanto de comportamiento en la mar como de resistencia al avance de buques y estructuras flotantes. La primera herramienta desarrollada resuelve el problema de difracción y radiación de olas. Se basan en el método de los elementos finitos (MEF) para la resolución de la ecuación de Laplace, así como en esquemas basados en MEF, integración a lo largo de líneas de corriente, y en diferencias finitas desarrollados para la condición de superficie libre. Se han desarrollado herramientas numéricas para la resolución de la dinámica de sólido rígido en sistemas multicuerpos con ligaduras. Estas herramientas han sido integradas junto con la herramienta de resolución de olas difractadas y radiadas para la resolución de problemas de interacción de cuerpos con olas. También se han diseñado algoritmos de acoplamientos con otras herramientas numéricas para la resolución de problemas multifísica. En particular, se han realizado acoplamientos con una herramienta numérica basada de cálculo de estructuras con MEF para problemas de interacción fluido-estructura, otra de cálculo de líneas de fondeo, y con una herramienta numérica de cálculo de flujos en tanques internos para problemas acoplados de comportamiento en la mar con “sloshing”. Se han realizado simulaciones numéricas para la validación y verificación de los algoritmos desarrollados, así como para el análisis de diferentes casos de estudio con aplicaciones diversas en los campos de la ingeniería naval, oceánica, y energías renovables marinas. ABSTRACT The objective of this thesis is the research on numerical algorithms to develop numerical tools to simulate seakeeping problems as well as wave resistance problems of ships and floating structures. The first tool developed is a wave diffraction-radiation solver. It is based on the finite element method (FEM) in order to solve the Laplace equation, as well as numerical schemes based on FEM, streamline integration, and finite difference method tailored for solving the free surface boundary condition. It has been developed numerical tools to solve solid body dynamics of multibody systems with body links across them. This tool has been integrated with the wave diffraction-radiation solver to solve wave-body interaction problems. Also it has been tailored coupling algorithms with other numerical tools in order to solve multi-physics problems. In particular, it has been performed coupling with a MEF structural solver to solve fluid-structure interaction problems, with a mooring solver, and with a solver capable of simulating internal flows in tanks to solve couple seakeeping-sloshing problems. Numerical simulations have been carried out to validate and verify the developed algorithms, as well as to analyze case studies in the areas of marine engineering, offshore engineering, and offshore renewable energy.

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El objetivo de ésta tesis es estudiar cómo desarrollar una aplicación informática que implemente algoritmos numéricos de evaluación de características hidrodinámicas de modelos geométricos representativos de carenas de buques. Se trata de especificar los requisitos necesarios que debe cumplir un programa para informático orientado a dar solución a un determinado problema hidródinámico, como es simular el comportamiento en balance de un buque sometido a oleaje, de popa o proa. una vez especificada la aplicación se realizará un diseño del programa; se estudiarán alternativas para implementar la aplicación; se explicará el proceso que ha de seguirse para obtener la aplicación en funcionamiento y se contrastarán los resultados obtenidos en la medida que sea posible. Se pretende sistematizar y sintetizar todo el proceso de desarrollo de software, orientado a la simulación del comportamiento hidrodinámico de un buque, en una metodología que se pondrá a disposición de la comunidad académica y científica en la forma que se considere más adecuada. Se trata, por tanto, de proponer una metodología de desarrollo de software para obetener una aplicación que facilite la evaluación de diferentes alternativas de estudio variando parámetros relativos al problema en estudio y que sea capaz de proporcionar resultados para su análisis. Así mismo se incide en cómo ha de conducirse en el proceso para que dicha aplicación pueda crecer, incorporando soluciones existentes no implementadas o nuevas soluciones que aparezcan en este ámbito de conocimiento. Como aplicación concreta de la aplicación se ha elegido implementar los algoritmos necesarios para evaluar la aparición del balance paramétrico en un buque. En el análisis de éste problema se considera de interés la representación geométrica que se hace de la carena del buque. Además de la carena aparecen otros elementos que tienen influencia determinante en éste estudio, como son las situación de mar y las situaciones de carga. Idealmente, el problema sería resuelto si se consiguiera determinar el ángulo de balance que se produce al enfrentar un buque a las diferentes condiciones de mar. Se pretende preparar un programa utilizando el paradigma de la orientación a objetos. Considero que es la más adecuada forma de modularizar el programa para poder utilizar diferentes modelos de una misma carena y así comparar los resultados de la evaluación del balance paramétrico entre sí. En una etapa posterior se podrían comparar los resultados con otros obtenidos empíricamente. Hablo de una nueva metodología porque pretendo indicar cómo se ha de construir una aplicación de software que sea usable y sobre la que se pueda seguir desarrollando. Esto justifica la selección del lenguaje de programación C++. Se seleccionará un núcleo geométrico de software que permita acoplar de forma versátil los distintos componentes de software que van a construir el programa. Este trabajo pretende aplicar el desarrollo de software a un aspecto concreto del área de conocimiento de la hidrodinámica. No se pretende aportar nuevos algoritmos para resolver problemas de hidrodinámica, sino diseñar un conjunto de objetos de software que implementen soluciones existentes a conocidas soluciones numéricas a dichos problemas. Se trata fundamentalmente de un trabajo de software, más que de hidrodinámica. Lo que aporta de novedad es una nueva forma de realizar un programa aplicado a los cálculos hidrodinámicos relativos a la determinación del balance paramétrico, que pueda crecer e incorporar cualquier novedad que pueda surgir más adelante. Esto será posible por la programación modular utilizada y los objetos que representan cada uno de los elementos que intervienen en la determinación del balance paramétrico. La elección de aplicar la metodología a la predicción del balance paramétrico se debe a que este concepto es uno de los elementos que intervienen en la evaluación de criterios de estabilidad de segunda generación que estan en estudio para su futura aplicación en el ámbito de la construcción naval. Es por tanto un estudio que despierta interés por su próxima utilidad. ABSTRACT The aim of this thesis is to study how to develop a computer application implementing numerical algorithms to assess hydrodynamic features of geometrical models of vessels. It is therefore to propose a methodology for software development applied to an hydrodynamic problem, in order to evaluate different study alternatives by varying different parameters related to the problem and to be capable of providing results for analysis. As a concrete application of the program it has been chosen to implement the algorithms necessary for evaluating the appearance of parametric rolling in a vessel. In the analysis of this problem it is considered of interest the geometrical representation of the hull of the ship and other elements which have decisive influence in this phenomena, such as the sea situation and the loading condition. Ideally, the application would determine the roll angle that occurs when a ship is on waves of different characteristics. It aims to prepare a program by using the paradigm of object oriented programming. I think it is the best methodology to modularize the program. My intention is to show how face the global process of developing an application from the initial specification until the final release of the program. The process will keep in mind the spefici objetives of usability and the possibility of growing in the scope of the software. This work intends to apply software development to a particular aspect the area of knowledge of hydrodynamics. It is not intended to provide new algorithms for solving problems of hydrodynamics, but designing a set of software objects that implement existing solutions to these problems. This is essentially a job software rather than hydrodynamic. The novelty of this thesis stands in this work focuses in describing how to apply the whole proccess of software engineering to hydrodinamics problems. The choice of the prediction of parametric balance as the main objetive to be applied to is because this concept is one of the elements involved in the evaluation of the intact stability criteria of second generation. Therefore, I consider this study as relevant usefull for the future application in the field of shipbuilding.

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This paper presents a high-accuracy fully analytical formulation to compute the miss distance and collision probability of two approaching objects following an impulsive collision avoidance maneuver. The formulation hinges on a linear relation between the applied impulse and the objects? relative motion in the b-plane, which allows one to formulate the maneuver optimization problem as an eigenvalue problem coupled to a simple nonlinear algebraic equation. The optimization criterion consists of minimizing the maneuver cost in terms of delta-V magnitude to either maximize collision miss distance or to minimize Gaussian collision probability. The algorithm, whose accuracy is verified in representative mission scenarios, can be employed for collision avoidance maneuver planning with reduced computational cost when compared with fully numerical algorithms.

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La evolución de los teléfonos móviles inteligentes, dotados de cámaras digitales, está provocando una creciente demanda de aplicaciones cada vez más complejas que necesitan algoritmos de visión artificial en tiempo real; puesto que el tamaño de las señales de vídeo no hace sino aumentar y en cambio el rendimiento de los procesadores de un solo núcleo se ha estancado, los nuevos algoritmos que se diseñen para visión artificial han de ser paralelos para poder ejecutarse en múltiples procesadores y ser computacionalmente escalables. Una de las clases de procesadores más interesantes en la actualidad se encuentra en las tarjetas gráficas (GPU), que son dispositivos que ofrecen un alto grado de paralelismo, un excelente rendimiento numérico y una creciente versatilidad, lo que los hace interesantes para llevar a cabo computación científica. En esta tesis se exploran dos aplicaciones de visión artificial que revisten una gran complejidad computacional y no pueden ser ejecutadas en tiempo real empleando procesadores tradicionales. En cambio, como se demuestra en esta tesis, la paralelización de las distintas subtareas y su implementación sobre una GPU arrojan los resultados deseados de ejecución con tasas de refresco interactivas. Asimismo, se propone una técnica para la evaluación rápida de funciones de complejidad arbitraria especialmente indicada para su uso en una GPU. En primer lugar se estudia la aplicación de técnicas de síntesis de imágenes virtuales a partir de únicamente dos cámaras lejanas y no paralelas—en contraste con la configuración habitual en TV 3D de cámaras cercanas y paralelas—con información de color y profundidad. Empleando filtros de mediana modificados para la elaboración de un mapa de profundidad virtual y proyecciones inversas, se comprueba que estas técnicas son adecuadas para una libre elección del punto de vista. Además, se demuestra que la codificación de la información de profundidad con respecto a un sistema de referencia global es sumamente perjudicial y debería ser evitada. Por otro lado se propone un sistema de detección de objetos móviles basado en técnicas de estimación de densidad con funciones locales. Este tipo de técnicas es muy adecuada para el modelado de escenas complejas con fondos multimodales, pero ha recibido poco uso debido a su gran complejidad computacional. El sistema propuesto, implementado en tiempo real sobre una GPU, incluye propuestas para la estimación dinámica de los anchos de banda de las funciones locales, actualización selectiva del modelo de fondo, actualización de la posición de las muestras de referencia del modelo de primer plano empleando un filtro de partículas multirregión y selección automática de regiones de interés para reducir el coste computacional. Los resultados, evaluados sobre diversas bases de datos y comparados con otros algoritmos del estado del arte, demuestran la gran versatilidad y calidad de la propuesta. Finalmente se propone un método para la aproximación de funciones arbitrarias empleando funciones continuas lineales a tramos, especialmente indicada para su implementación en una GPU mediante el uso de las unidades de filtraje de texturas, normalmente no utilizadas para cómputo numérico. La propuesta incluye un riguroso análisis matemático del error cometido en la aproximación en función del número de muestras empleadas, así como un método para la obtención de una partición cuasióptima del dominio de la función para minimizar el error. ABSTRACT The evolution of smartphones, all equipped with digital cameras, is driving a growing demand for ever more complex applications that need to rely on real-time computer vision algorithms. However, video signals are only increasing in size, whereas the performance of single-core processors has somewhat stagnated in the past few years. Consequently, new computer vision algorithms will need to be parallel to run on multiple processors and be computationally scalable. One of the most promising classes of processors nowadays can be found in graphics processing units (GPU). These are devices offering a high parallelism degree, excellent numerical performance and increasing versatility, which makes them interesting to run scientific computations. In this thesis, we explore two computer vision applications with a high computational complexity that precludes them from running in real time on traditional uniprocessors. However, we show that by parallelizing subtasks and implementing them on a GPU, both applications attain their goals of running at interactive frame rates. In addition, we propose a technique for fast evaluation of arbitrarily complex functions, specially designed for GPU implementation. First, we explore the application of depth-image–based rendering techniques to the unusual configuration of two convergent, wide baseline cameras, in contrast to the usual configuration used in 3D TV, which are narrow baseline, parallel cameras. By using a backward mapping approach with a depth inpainting scheme based on median filters, we show that these techniques are adequate for free viewpoint video applications. In addition, we show that referring depth information to a global reference system is ill-advised and should be avoided. Then, we propose a background subtraction system based on kernel density estimation techniques. These techniques are very adequate for modelling complex scenes featuring multimodal backgrounds, but have not been so popular due to their huge computational and memory complexity. The proposed system, implemented in real time on a GPU, features novel proposals for dynamic kernel bandwidth estimation for the background model, selective update of the background model, update of the position of reference samples of the foreground model using a multi-region particle filter, and automatic selection of regions of interest to reduce computational cost. The results, evaluated on several databases and compared to other state-of-the-art algorithms, demonstrate the high quality and versatility of our proposal. Finally, we propose a general method for the approximation of arbitrarily complex functions using continuous piecewise linear functions, specially formulated for GPU implementation by leveraging their texture filtering units, normally unused for numerical computation. Our proposal features a rigorous mathematical analysis of the approximation error in function of the number of samples, as well as a method to obtain a suboptimal partition of the domain of the function to minimize approximation error.

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García et al. present a class of column generation (CG) algorithms for nonlinear programs. Its main motivation from a theoretical viewpoint is that under some circumstances, finite convergence can be achieved, in much the same way as for the classic simplicial decomposition method; the main practical motivation is that within the class there are certain nonlinear column generation problems that can accelerate the convergence of a solution approach which generates a sequence of feasible points. This algorithm can, for example, accelerate simplicial decomposition schemes by making the subproblems nonlinear. This paper complements the theoretical study on the asymptotic and finite convergence of these methods given in [1] with an experimental study focused on their computational efficiency. Three types of numerical experiments are conducted. The first group of test problems has been designed to study the parameters involved in these methods. The second group has been designed to investigate the role and the computation of the prolongation of the generated columns to the relative boundary. The last one has been designed to carry out a more complete investigation of the difference in computational efficiency between linear and nonlinear column generation approaches. In order to carry out this investigation, we consider two types of test problems: the first one is the nonlinear, capacitated single-commodity network flow problem of which several large-scale instances with varied degrees of nonlinearity and total capacity are constructed and investigated, and the second one is a combined traffic assignment model

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When non linear physical systems of infinite extent are modelled, such as tunnels and perforations, it is necessary to simulate suitably the solution in the infinite as well as the non linearity. The finite element method (FEM) is a well known procedure for simulating the non linear behavior. However, the treatment of the infinite field with domain truncations is often questionable. On the other hand, the boundary element method (BEM) is suitable to simulate the infinite behavior without truncations. Because of this, by the combination of both methods, suitable use of the advantages of each one may be obtained. Several possibilities of FEM-BEM coupling and their performance in some practical cases are discussed in this paper. Parallelizable coupling algorithms based on domain decomposition are developed and compared with the most traditional coupling methods.

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This thesis aims to introduce some fundamental concepts underlying option valuation theory including implementation of computational tools. In many cases analytical solution for option pricing does not exist, thus the following numerical methods are used: binomial trees, Monte Carlo simulations and finite difference methods. First, an algorithm based on Hull and Wilmott is written for every method. Then these algorithms are improved in different ways. For the binomial tree both speed and memory usage is significantly improved by using only one vector instead of a whole price storing matrix. Computational time in Monte Carlo simulations is reduced by implementing a parallel algorithm (in C) which is capable of improving speed by a factor which equals the number of processors used. Furthermore, MatLab code for Monte Carlo was made faster by vectorizing simulation process. Finally, obtained option values are compared to those obtained with popular finite difference methods, and it is discussed which of the algorithms is more appropriate for which purpose.

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Monte Carlo (MC) methods are widely used in signal processing, machine learning and stochastic optimization. A well-known class of MC methods are Markov Chain Monte Carlo (MCMC) algorithms. In this work, we introduce a novel parallel interacting MCMC scheme, where the parallel chains share information using another MCMC technique working on the entire population of current states. These parallel ?vertical? chains are led by random-walk proposals, whereas the ?horizontal? MCMC uses a independent proposal, which can be easily adapted by making use of all the generated samples. Numerical results show the advantages of the proposed sampling scheme in terms of mean absolute error, as well as robustness w.r.t. to initial values and parameter choice.

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This paper describes new improvements for BB-MaxClique (San Segundo et al. in Comput Oper Resour 38(2):571–581, 2011 ), a leading maximum clique algorithm which uses bit strings to efficiently compute basic operations during search by bit masking. Improvements include a recently described recoloring strategy in Tomita et al. (Proceedings of the 4th International Workshop on Algorithms and Computation. Lecture Notes in Computer Science, vol 5942. Springer, Berlin, pp 191–203, 2010 ), which is now integrated in the bit string framework, as well as different optimization strategies for fast bit scanning. Reported results over DIMACS and random graphs show that the new variants improve over previous BB-MaxClique for a vast majority of cases. It is also established that recoloring is mainly useful for graphs with high densities.

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We have developed a new projector model specifically tailored for fast list-mode tomographic reconstructions in Positron emission tomography (PET) scanners with parallel planar detectors. The model provides an accurate estimation of the probability distribution of coincidence events defined by pairs of scintillating crystals. This distribution is parameterized with 2D elliptical Gaussian functions defined in planes perpendicular to the main axis of the tube of response (TOR). The parameters of these Gaussian functions have been obtained by fitting Monte Carlo simulations that include positron range, acolinearity of gamma rays, as well as detector attenuation and scatter effects. The proposed model has been applied efficiently to list-mode reconstruction algorithms. Evaluation with Monte Carlo simulations over a rotating high resolution PET scanner indicates that this model allows to obtain better recovery to noise ratio in OSEM (ordered-subsets, expectation-maximization) reconstruction, if compared to list-mode reconstruction with symmetric circular Gaussian TOR model, and histogram-based OSEM with precalculated system matrix using Monte Carlo simulated models and symmetries.

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Zernike polynomials are a well known set of functions that find many applications in image or pattern characterization because they allow to construct shape descriptors that are invariant against translations, rotations or scale changes. The concepts behind them can be extended to higher dimension spaces, making them also fit to describe volumetric data. They have been less used than their properties might suggest due to their high computational cost. We present a parallel implementation of 3D Zernike moments analysis, written in C with CUDA extensions, which makes it practical to employ Zernike descriptors in interactive applications, yielding a performance of several frames per second in voxel datasets about 2003 in size. In our contribution, we describe the challenges of implementing 3D Zernike analysis in a general-purpose GPU. These include how to deal with numerical inaccuracies, due to the high precision demands of the algorithm, or how to deal with the high volume of input data so that it does not become a bottleneck for the system.

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This paper outlines the problems found in the parallelization of SPH (Smoothed Particle Hydrodynamics) algorithms using Graphics Processing Units. Different results of some parallel GPU implementations in terms of the speed-up and the scalability compared to the CPU sequential codes are shown. The most problematic stage in the GPU-SPH algorithms is the one responsible for locating neighboring particles and building the vectors where this information is stored, since these specific algorithms raise many dificulties for a data-level parallelization. Because of the fact that the neighbor location using linked lists does not show enough data-level parallelism, two new approaches have been pro- posed to minimize bank conflicts in the writing and subsequent reading of the neighbor lists. The first strategy proposes an efficient coordination between CPU-GPU, using GPU algorithms for those stages that allow a straight forward parallelization, and sequential CPU algorithms for those instructions that involve some kind of vector reduction. This coordination provides a relatively orderly reading of the neighbor lists in the interactions stage, achieving a speed-up factor of x47 in this stage. However, since the construction of the neighbor lists is quite expensive, it is achieved an overall speed-up of x41. The second strategy seeks to maximize the use of the GPU in the neighbor's location process by executing a specific vector sorting algorithm that allows some data-level parallelism. Al- though this strategy has succeeded in improving the speed-up on the stage of neighboring location, the global speed-up on the interactions stage falls, due to inefficient reading of the neighbor vectors. Some changes to these strategies are proposed, aimed at maximizing the computational load of the GPU and using the GPU texture-units, in order to reach the maximum speed-up for such codes. Different practical applications have been added to the mentioned GPU codes. First, the classical dam-break problem is studied. Second, the wave impact of the sloshing fluid contained in LNG vessel tanks is also simulated as a practical example of particle methods

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This article describes a new visual servo control and strategies that are used to carry out dynamic tasks by the Robotenis platform. This platform is basically a parallel robot that is equipped with an acquisition and processing system of visual information, its main feature is that it has a completely open architecture control, and planned in order to design, implement, test and compare control strategies and algorithms (visual and actuated joint controllers). Following sections describe a new visual control strategy specially designed to track and intercept objects in 3D space. The results are compared with a controller shown in previous woks, where the end effector of the robot keeps a constant distance from the tracked object. In this work, the controller is specially designed in order to allow changes in the tracking reference. Changes in the tracking reference can be used to grip an object that is under movement, or as in this case, hitting a hanging Ping-Pong ball. Lyapunov stability is taken into account in the controller design.