980 resultados para Proximal Point Algorithm


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Pós-graduação em Engenharia Elétrica - FEB

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[ES]El proyecto contiene módulos de simulación, procesado de datos, mapeo y localización, desarrollados en C++ utilizando ROS (Robot Operating System) y PCL (Point Cloud Library). Ha sido desarrollado bajo el proyecto de robótica submarina AVORA.Se han caracterizado el vehículo y el sensor, y se han analizado diferentes tecnologías de sensores y mapeo. Los datos pasan por tres etapas: Conversión a nube de puntos, filtrado por umbral, eliminación de puntos espureos y, opcionalmente, detección de formas. Estos datos son utilizados para construir un mapa de superficie multinivel. La otra herramienta desarrollada es un algoritmo de Punto más Cercano Iterativo (ICP) modificado, que tiene en cuenta el modo de funcionamiento del sonar de imagen utilizado.

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El Análisis de Consumo de Recursos o Análisis de Coste trata de aproximar el coste de ejecutar un programa como una función dependiente de sus datos de entrada. A pesar de que existen trabajos previos a esta tesis doctoral que desarrollan potentes marcos para el análisis de coste de programas orientados a objetos, algunos aspectos avanzados, como la eficiencia, la precisión y la fiabilidad de los resultados, todavía deben ser estudiados en profundidad. Esta tesis aborda estos aspectos desde cuatro perspectivas diferentes: (1) Las estructuras de datos compartidas en la memoria del programa son una pesadilla para el análisis estático de programas. Trabajos recientes proponen una serie de condiciones de localidad para poder mantener de forma consistente información sobre los atributos de los objetos almacenados en memoria compartida, reemplazando éstos por variables locales no almacenadas en la memoria compartida. En esta tesis presentamos dos extensiones a estos trabajos: la primera es considerar, no sólo los accesos a los atributos, sino también los accesos a los elementos almacenados en arrays; la segunda se centra en los casos en los que las condiciones de localidad no se cumplen de forma incondicional, para lo cual, proponemos una técnica para encontrar las precondiciones necesarias para garantizar la consistencia de la información acerca de los datos almacenados en memoria. (2) El objetivo del análisis incremental es, dado un programa, los resultados de su análisis y una serie de cambios sobre el programa, obtener los nuevos resultados del análisis de la forma más eficiente posible, evitando reanalizar aquellos fragmentos de código que no se hayan visto afectados por los cambios. Los analizadores actuales todavía leen y analizan el programa completo de forma no incremental. Esta tesis presenta un análisis de coste incremental, que, dado un cambio en el programa, reconstruye la información sobre el coste del programa de todos los métodos afectados por el cambio de forma incremental. Para esto, proponemos (i) un algoritmo multi-dominio y de punto fijo que puede ser utilizado en todos los análisis globales necesarios para inferir el coste, y (ii) una novedosa forma de almacenar las expresiones de coste que nos permite reconstruir de forma incremental únicamente las funciones de coste de aquellos componentes afectados por el cambio. (3) Las garantías de coste obtenidas de forma automática por herramientas de análisis estático no son consideradas totalmente fiables salvo que la implementación de la herramienta o los resultados obtenidos sean verificados formalmente. Llevar a cabo el análisis de estas herramientas es una tarea titánica, ya que se trata de herramientas de gran tamaño y complejidad. En esta tesis nos centramos en el desarrollo de un marco formal para la verificación de las garantías de coste obtenidas por los analizadores en lugar de analizar las herramientas. Hemos implementado esta idea mediante la herramienta COSTA, un analizador de coste para programas Java y KeY, una herramienta de verificación de programas Java. De esta forma, COSTA genera las garantías de coste, mientras que KeY prueba la validez formal de los resultados obtenidos, generando de esta forma garantías de coste verificadas. (4) Hoy en día la concurrencia y los programas distribuidos son clave en el desarrollo de software. Los objetos concurrentes son un modelo de concurrencia asentado para el desarrollo de sistemas concurrentes. En este modelo, los objetos son las unidades de concurrencia y se comunican entre ellos mediante llamadas asíncronas a sus métodos. La distribución de las tareas sugiere que el análisis de coste debe inferir el coste de los diferentes componentes distribuidos por separado. En esta tesis proponemos un análisis de coste sensible a objetos que, utilizando los resultados obtenidos mediante un análisis de apunta-a, mantiene el coste de los diferentes componentes de forma independiente. Abstract Resource Analysis (a.k.a. Cost Analysis) tries to approximate the cost of executing programs as functions on their input data sizes and without actually having to execute the programs. While a powerful resource analysis framework on object-oriented programs existed before this thesis, advanced aspects to improve the efficiency, the accuracy and the reliability of the results of the analysis still need to be further investigated. This thesis tackles this need from the following four different perspectives. (1) Shared mutable data structures are the bane of formal reasoning and static analysis. Analyses which keep track of heap-allocated data are referred to as heap-sensitive. Recent work proposes locality conditions for soundly tracking field accesses by means of ghost non-heap allocated variables. In this thesis we present two extensions to this approach: the first extension is to consider arrays accesses (in addition to object fields), while the second extension focuses on handling cases for which the locality conditions cannot be proven unconditionally by finding aliasing preconditions under which tracking such heap locations is feasible. (2) The aim of incremental analysis is, given a program, its analysis results and a series of changes to the program, to obtain the new analysis results as efficiently as possible and, ideally, without having to (re-)analyze fragments of code that are not affected by the changes. During software development, programs are permanently modified but most analyzers still read and analyze the entire program at once in a non-incremental way. This thesis presents an incremental resource usage analysis which, after a change in the program is made, is able to reconstruct the upper-bounds of all affected methods in an incremental way. To this purpose, we propose (i) a multi-domain incremental fixed-point algorithm which can be used by all global analyses required to infer the cost, and (ii) a novel form of cost summaries that allows us to incrementally reconstruct only those components of cost functions affected by the change. (3) Resource guarantees that are automatically inferred by static analysis tools are generally not considered completely trustworthy, unless the tool implementation or the results are formally verified. Performing full-blown verification of such tools is a daunting task, since they are large and complex. In this thesis we focus on the development of a formal framework for the verification of the resource guarantees obtained by the analyzers, instead of verifying the tools. We have implemented this idea using COSTA, a state-of-the-art cost analyzer for Java programs and KeY, a state-of-the-art verification tool for Java source code. COSTA is able to derive upper-bounds of Java programs while KeY proves the validity of these bounds and provides a certificate. The main contribution of our work is to show that the proposed tools cooperation can be used for automatically producing verified resource guarantees. (4) Distribution and concurrency are today mainstream. Concurrent objects form a well established model for distributed concurrent systems. In this model, objects are the concurrency units that communicate via asynchronous method calls. Distribution suggests that analysis must infer the cost of the diverse distributed components separately. In this thesis we propose a novel object-sensitive cost analysis which, by using the results gathered by a points-to analysis, can keep the cost of the diverse distributed components separate.

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The aim of this work is to provide the necessary methods to register and fuse the endo-epicardial signal intensity (SI) maps extracted from contrast-enhanced magnetic resonance imaging (ceMRI) with X-ray coronary ngiograms using an intrinsic registrationbased algorithm to help pre-planning and guidance of catheterization procedures. Fusion of angiograms with SI maps was treated as a 2D-3D pose estimation, where each image point is projected to a Plücker line, and the screw representation for rigid motions is minimized using a gradient descent method. The resultant transformation is applied to the SI map that is then projected and fused on each angiogram. The proposed method was tested in clinical datasets from 6 patients with prior myocardial infarction. The registration procedure is optionally combined with an iterative closest point algorithm (ICP) that aligns the ventricular contours segmented from two ventriculograms.

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To translate and transfer solution data between two totally different meshes (i.e. mesh 1 and mesh 2), a consistent point-searching algorithm for solution interpolation in unstructured meshes consisting of 4-node bilinear quadrilateral elements is presented in this paper. The proposed algorithm has the following significant advantages: (1) The use of a point-searching strategy allows a point in one mesh to be accurately related to an element (containing this point) in another mesh. Thus, to translate/transfer the solution of any particular point from mesh 2 td mesh 1, only one element in mesh 2 needs to be inversely mapped. This certainly minimizes the number of elements, to which the inverse mapping is applied. In this regard, the present algorithm is very effective and efficient. (2) Analytical solutions to the local co ordinates of any point in a four-node quadrilateral element, which are derived in a rigorous mathematical manner in the context of this paper, make it possible to carry out an inverse mapping process very effectively and efficiently. (3) The use of consistent interpolation enables the interpolated solution to be compatible with an original solution and, therefore guarantees the interpolated solution of extremely high accuracy. After the mathematical formulations of the algorithm are presented, the algorithm is tested and validated through a challenging problem. The related results from the test problem have demonstrated the generality, accuracy, effectiveness, efficiency and robustness of the proposed consistent point-searching algorithm. Copyright (C) 1999 John Wiley & Sons, Ltd.

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Decimal multiplication is an integral part of financial, commercial, and internet-based computations. A novel design for single digit decimal multiplication that reduces the critical path delay and area for an iterative multiplier is proposed in this research. The partial products are generated using single digit multipliers, and are accumulated based on a novel RPS algorithm. This design uses n single digit multipliers for an n × n multiplication. The latency for the multiplication of two n-digit Binary Coded Decimal (BCD) operands is (n + 1) cycles and a new multiplication can begin every n cycle. The accumulation of final partial products and the first iteration of partial product generation for next set of inputs are done simultaneously. This iterative decimal multiplier offers low latency and high throughput, and can be extended for decimal floating-point multiplication.

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An input variable selection procedure is introduced for the identification and construction of multi-input multi-output (MIMO) neurofuzzy operating point dependent models. The algorithm is an extension of a forward modified Gram-Schmidt orthogonal least squares procedure for a linear model structure which is modified to accommodate nonlinear system modeling by incorporating piecewise locally linear model fitting. The proposed input nodes selection procedure effectively tackles the problem of the curse of dimensionality associated with lattice-based modeling algorithms such as radial basis function neurofuzzy networks, enabling the resulting neurofuzzy operating point dependent model to be widely applied in control and estimation. Some numerical examples are given to demonstrate the effectiveness of the proposed construction algorithm.

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Reconstruction of patient-specific 3D bone surface from 2D calibrated fluoroscopic images and a point distribution model is discussed. We present a 2D/3D reconstruction scheme combining statistical extrapolation and regularized shape deformation with an iterative image-to-model correspondence establishing algorithm, and show its application to reconstruct the surface of proximal femur. The image-to-model correspondence is established using a non-rigid 2D point matching process, which iteratively uses a symmetric injective nearest-neighbor mapping operator and 2D thin-plate splines based deformation to find a fraction of best matched 2D point pairs between features detected from the fluoroscopic images and those extracted from the 3D model. The obtained 2D point pairs are then used to set up a set of 3D point pairs such that we turn a 2D/3D reconstruction problem to a 3D/3D one. We designed and conducted experiments on 11 cadaveric femurs to validate the present reconstruction scheme. An average mean reconstruction error of 1.2 mm was found when two fluoroscopic images were used for each bone. It decreased to 1.0 mm when three fluoroscopic images were used.

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Constructing a 3D surface model from sparse-point data is a nontrivial task. Here, we report an accurate and robust approach for reconstructing a surface model of the proximal femur from sparse-point data and a dense-point distribution model (DPDM). The problem is formulated as a three-stage optimal estimation process. The first stage, affine registration, is to iteratively estimate a scale and a rigid transformation between the mean surface model of the DPDM and the sparse input points. The estimation results of the first stage are used to establish point correspondences for the second stage, statistical instantiation, which stably instantiates a surface model from the DPDM using a statistical approach. This surface model is then fed to the third stage, kernel-based deformation, which further refines the surface model. Handling outliers is achieved by consistently employing the least trimmed squares (LTS) approach with a roughly estimated outlier rate in all three stages. If an optimal value of the outlier rate is preferred, we propose a hypothesis testing procedure to automatically estimate it. We present here our validations using four experiments, which include 1 leave-one-out experiment, 2 experiment on evaluating the present approach for handling pathology, 3 experiment on evaluating the present approach for handling outliers, and 4 experiment on reconstructing surface models of seven dry cadaver femurs using clinically relevant data without noise and with noise added. Our validation results demonstrate the robust performance of the present approach in handling outliers, pathology, and noise. An average 95-percentile error of 1.7-2.3 mm was found when the present approach was used to reconstruct surface models of the cadaver femurs from sparse-point data with noise added.

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Vector reconstruction of objects from an unstructured point cloud obtained with a LiDAR-based system (light detection and ranging) is one of the most promising methods to build three dimensional models of orchards. The cylinder fitting method for woody structure reconstruction of leafless trees from point clouds obtained with a mobile terrestrial laser scanner (MTLS) has been analysed. The advantage of this method is that it performs reconstruction in a single step. The most time consuming part of the algorithm is generation of the cylinder direction, which must be recalculated at the inclusion of each point in the cylinder. The tree skeleton is obtained at the same time as the cluster of cylinders is formed. The method does not guarantee a unique convergence and the reconstruction parameter values must be carefully chosen. A balanced processing of clusters has also been defined which has proven to be very efficient in terms of processing time by following the hierarchy of branches, predecessors and successors. The algorithm was applied to simulated MTLS of virtual orchard models and to MTLS data of real orchards. The constraints applied in the method have been reviewed to ensure better convergence and simpler use of parameters. The results obtained show a correct reconstruction of the woody structure of the trees and the algorithm runs in linear logarithmic time