15 resultados para Approximation Classes

em Universidad Politécnica de Madrid


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This work is part of an on-going collaborative project between the medical and signal processing communities to promote new research efforts on automatic OSA (Obstructive Apnea Syndrome) diagnosis. In this paper, we explore the differences noted in phonetic classes (interphoneme) across groups (control/apnoea) and analyze their utility for OSA detection

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This paper presents some ideas about a new neural network architecture that can be compared to a Taylor analysis when dealing with patterns. Such architecture is based on lineal activation functions with an axo-axonic architecture. A biological axo-axonic connection between two neurons is defined as the weight in a connection in given by the output of another third neuron. This idea can be implemented in the so called Enhanced Neural Networks in which two Multilayer Perceptrons are used; the first one will output the weights that the second MLP uses to computed the desired output. This kind of neural network has universal approximation properties even with lineal activation functions. There exists a clear difference between cooperative and competitive strategies. The former ones are based on the swarm colonies, in which all individuals share its knowledge about the goal in order to pass such information to other individuals to get optimum solution. The latter ones are based on genetic models, that is, individuals can die and new individuals are created combining information of alive one; or are based on molecular/celular behaviour passing information from one structure to another. A swarm-based model is applied to obtain the Neural Network, training the net with a Particle Swarm algorithm.

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For centuries, earth has been used as a construction material. Nevertheless, the normative in this matter is very scattered, and the most developed countries, to carry out a construction with this material implies a variety of technical and legal problems. In this paper we review, in an international level, the normative panorama about earth constructions. It analyzes ninety one standards and regulations of countries all around the five continents. These standards represent the state of art that normalizes the earth as a construction material. In this research we analyze the international standards to earth construction, focusing on durability test (spray and drip erosion tests). It analyzes the differences between methods of test. Also we show all results about these tests in two types of compressed earth block.

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We introduce a diffusion-based algorithm in which multiple agents cooperate to predict a common and global statevalue function by sharing local estimates and local gradient information among neighbors. Our algorithm is a fully distributed implementation of the gradient temporal difference with linear function approximation, to make it applicable to multiagent settings. Simulations illustrate the benefit of cooperation in learning, as made possible by the proposed algorithm.

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We present analytical formulas to estimate the variation of achieved deflection for an Earth-impacting asteroid following a continuous tangential low-thrust deflection strategy. Relatively simple analytical expressions are obtained with the aid of asymptotic theory and the use of Peláez orbital elements set, an approach that is particularly suitable to the asteroid deflection problem and is not limited to small eccentricities. The accuracy of the proposed formulas is evaluated numerically showing negligible error for both early and late deflection campaigns. The results will be of aid in planning future low-thrust asteroid deflection missions

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This paper contributes with a unified formulation that merges previ- ous analysis on the prediction of the performance ( value function ) of certain sequence of actions ( policy ) when an agent operates a Markov decision process with large state-space. When the states are represented by features and the value function is linearly approxi- mated, our analysis reveals a new relationship between two common cost functions used to obtain the optimal approximation. In addition, this analysis allows us to propose an efficient adaptive algorithm that provides an unbiased linear estimate. The performance of the pro- posed algorithm is illustrated by simulation, showing competitive results when compared with the state-of-the-art solutions.

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Intensity and volume of training in Artisti Gymnastics are increasing as the sooner athlete's age of incorporation creating some disturbance in them.

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This document is the result of a process of web development to create a tool that will allow to Cracow University of Technology consult, create and manage timetables. The technologies chosen for this purpose are Apache Tomcat Server, My SQL Community Server, JDBC driver, Java Servlets and JSPs for the server side. The client part counts on Javascript, jQuery, AJAX and CSS technologies to perform the dynamism. The document will justify the choice of these technologies and will explain some development tools that help in the integration and development of all this elements: specifically, NetBeans IDE and MySQL workbench have been used as helpful tools. After explaining all the elements involved in the development of the web application, the architecture and the code developed are explained through UML diagrams. Some implementation details related to security are also deeper explained through sequence diagrams. As the source code of the application is provided, an installation manual has been developed to run the project. In addition, as the platform is intended to be a beta that will be grown, some unimplemented ideas for future development are also exposed. Finally, some annexes with important files and scripts related to the initiation of the platform are attached. This project started through an existing tool that needed to be expanded. The main purpose of the project along its development has focused on setting the roots for a whole new platform that will replace the existing one. For this goal, it has been needed to make a deep inspection on the existing web technologies: a web server and a SQL database had to be chosen. Although the alternatives were a lot, Java technology for the server was finally selected because of the big community backwards, the easiness of modelling the language through UML diagrams and the fact of being free license software. Apache Tomcat is the open source server that can use Java Servlet and JSP technology. Related to the SQL database, MySQL Community Server is the most popular open-source SQL Server, with a big community after and quite a lot of tools to manage the server. JDBC is the driver needed to put in contact Java and MySQL. Once we chose the technologies that would be part of the platform, the development process started. After a detailed explanation of the development environment installation, we used UML use case diagrams to set the main tasks of the platform; UML class diagrams served to establish the existing relations between the classes generated; the architecture of the platform was represented through UML deployment diagrams; and Enhanced entity–relationship (EER) model were used to define the tables of the database and their relationships. Apart from the previous diagrams, some implementation issues were explained to make a better understanding of the developed code - UML sequence diagrams helped to explain this. Once the whole platform was properly defined and developed, the performance of the application has been shown: it has been proved that with the current state of the code, the platform covers the use cases that were set as the main target. Nevertheless, some requisites needed for the proper working of the platform have been specified. As the project is aimed to be grown, some ideas that could not be added to this beta have been explained in order not to be missed for future development. Finally, some annexes containing important configuration issues for the platform have been added after proper explanation, as well as an installation guide that will let a new developer get the project ready. In addition to this document some other files related to the project are provided: - Javadoc. The Javadoc containing the information of every Java class created is necessary for a better understanding of the source code. - database_model.mwb. This file contains the model of the database for MySQL Workbench. This model allows, among other things, generate the MySQL script for the creation of the tables. - ScheduleManager.war. The WAR file that will allow loading the developed application into Tomcat Server without using NetBeans. - ScheduleManager.zip. The source code exported from NetBeans project containing all Java packages, JSPs, Javascript files and CSS files that are part of the platform. - config.properties. The configuration file to properly get the names and credentials to use the database, also explained in Annex II. Example of config.properties file. - db_init_script.sql. The SQL query to initiate the database explained in Annex III. SQL statements for MySQL initialization. RESUMEN. Este proyecto tiene como punto de partida la necesidad de evolución de una herramienta web existente. El propósito principal del proyecto durante su desarrollo se ha centrado en establecer las bases de una completamente nueva plataforma que reemplazará a la existente. Para lograr esto, ha sido necesario realizar una profunda inspección en las tecnologías web existentes: un servidor web y una base de datos SQL debían ser elegidos. Aunque existen muchas alternativas, la tecnología Java ha resultado ser elegida debido a la gran comunidad de desarrolladores que tiene detrás, además de la facilidad que proporciona este lenguaje a la hora de modelarlo usando diagramas UML. Tampoco hay que olvidar que es una tecnología de uso libre de licencia. Apache Tomcat es el servidor de código libre que permite emplear Java Servlets y JSPs para hacer uso de la tecnología de Java. Respecto a la base de datos SQL, el servidor más popular de código libre es MySQL, y cuenta también con una gran comunidad detrás y buenas herramientas de modelado, creación y gestión de la bases de datos. JDBC es el driver que va a permitir comunicar las aplicaciones Java con MySQL. Tras elegir las tecnologías que formarían parte de esta nueva plataforma, el proceso de desarrollo tiene comienzo. Tras una extensa explicación de la instalación del entorno de desarrollo, se han usado diagramas de caso de UML para establecer cuáles son los objetivos principales de la plataforma; los diagramas de clases nos permiten realizar una organización del código java desarrollado de modo que sean fácilmente entendibles las relaciones entre las diferentes clases. La arquitectura de la plataforma queda definida a través de diagramas de despliegue. Por último, diagramas EER van a definir las relaciones entre las tablas creadas en la base de datos. Aparte de estos diagramas, algunos detalles de implementación se van a justificar para tener una mejor comprensión del código desarrollado. Diagramas de secuencia ayudarán en estas explicaciones. Una vez que toda la plataforma haya quedad debidamente definida y desarrollada, se va a realizar una demostración de la misma: se demostrará cómo los objetivos generales han sido alcanzados con el desarrollo actual del proyecto. No obstante, algunos requisitos han sido aclarados para que la plataforma trabaje adecuadamente. Como la intención del proyecto es crecer (no es una versión final), algunas ideas que se han podido llevar acabo han quedado descritas de manera que no se pierdan. Por último, algunos anexos que contienen información importante acerca de la plataforma se han añadido tras la correspondiente explicación de su utilidad, así como una guía de instalación que va a permitir a un nuevo desarrollador tener el proyecto preparado. Junto a este documento, ficheros conteniendo el proyecto desarrollado quedan adjuntos. Estos ficheros son: - Documentación Javadoc. Contiene la información de las clases Java que han sido creadas. - database_model.mwb. Este fichero contiene el modelo de la base de datos para MySQL Workbench. Esto permite, entre otras cosas, generar el script de iniciación de la base de datos para la creación de las tablas. - ScheduleManager.war. El fichero WAR que permite desplegar la plataforma en un servidor Apache Tomcat. - ScheduleManager.zip. El código fuente exportado directamente del proyecto de Netbeans. Contiene todos los paquetes de Java generados, ficheros JSPs, Javascript y CSS que forman parte de la plataforma. - config.properties. Ejemplo del fichero de configuración que permite obtener los nombres de la base de datos - db_init_script.sql. Las consultas SQL necesarias para la creación de la base de datos.

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A quasi-cylindrical approximation is used to analyse the axisymmetric swirling flow of a liquid with a hollow air core in the chamber of a pressure swirl atomizer. The liquid is injected into the chamber with an azimuthal velocity component through a number of slots at the periphery of one end of the chamber, and flows out as an anular sheet through a central orifice at the other end, following a conical convergence of the chamber wall. An effective inlet condition is used to model the effects of the slots and the boundary layer that develops at the nearby endwall of the chamber. An analysis is presented of the structure of the liquid sheet at the end of the exit orifice, where the flow becomes critical in the sense that upstream propagation of long-wave perturbations ceases to be possible. This nalysis leads to a boundary condition at the end of the orifice that is an extension of the condition of maximum flux used with irrotational models of the flow. As is well known, the radial pressure gradient induced by the swirling flow in the bulk of the chamber causes the overpressure that drives the liquid towards the exit orifice, and also leads to Ekman pumping in the boundary layers of reduced azimuthal velocity at the convergent wall of the chamber and at the wall opposite to the exit orifice. The numerical results confirm the important role played by the boundary layers. They make the thickness of the liquid sheet at the end of the orifice larger than predicted by rrotational models, and at the same time tend to decrease the overpressure required to pass a given flow rate through the chamber, because the large axial velocity in the boundary layers takes care of part of the flow rate. The thickness of the boundary layers increases when the atomizer constant (the inverse of a swirl number, proportional to the flow rate scaled with the radius of the exit orifice and the circulation around the air core) decreases. A minimum value of this parameter is found below which the layer of reduced azimuthal velocity around the air core prevents the pressure from increasing and steadily driving the flow through the exit orifice. The effects of other parameters not accounted for by irrotational models are also analysed in terms of their influence on the boundary layers.

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The multi-dimensional classification problem is a generalisation of the recently-popularised task of multi-label classification, where each data instance is associated with multiple class variables. There has been relatively little research carried out specific to multi-dimensional classification and, although one of the core goals is similar (modelling dependencies among classes), there are important differences; namely a higher number of possible classifications. In this paper we present method for multi-dimensional classification, drawing from the most relevant multi-label research, and combining it with important novel developments. Using a fast method to model the conditional dependence between class variables, we form super-class partitions and use them to build multi-dimensional learners, learning each super-class as an ordinary class, and thus explicitly modelling class dependencies. Additionally, we present a mechanism to deal with the many class values inherent to super-classes, and thus make learning efficient. To investigate the effectiveness of this approach we carry out an empirical evaluation on a range of multi-dimensional datasets, under different evaluation metrics, and in comparison with high-performing existing multi-dimensional approaches from the literature. Analysis of results shows that our approach offers important performance gains over competing methods, while also exhibiting tractable running time.

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Multi-dimensional classification (MDC) is the supervised learning problem where an instance is associated with multiple classes, rather than with a single class, as in traditional classification problems. Since these classes are often strongly correlated, modeling the dependencies between them allows MDC methods to improve their performance – at the expense of an increased computational cost. In this paper we focus on the classifier chains (CC) approach for modeling dependencies, one of the most popular and highest-performing methods for multi-label classification (MLC), a particular case of MDC which involves only binary classes (i.e., labels). The original CC algorithm makes a greedy approximation, and is fast but tends to propagate errors along the chain. Here we present novel Monte Carlo schemes, both for finding a good chain sequence and performing efficient inference. Our algorithms remain tractable for high-dimensional data sets and obtain the best predictive performance across several real data sets.

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Contributing to the acquisition of professional creativity and teamwork skills has been a special challenge for some of the subjects taught at the Technical University of Madrid (UPM), and this has been a starting point for the work described in this paper. Some professors have intuited that the use of cooperative classrooms could facilitate the acquisition of these skills. We describe the new methodologies applied within cooperative classrooms by some professors, and present the procedure for measuring students’ perception of their own learning outcomes, skill improvements, and overall satisfaction with the use of this kind of classroom. For this project, 250 students enrolled in several subjects answered a questionnaire. The featuresof thesubjectsinvolved intheproject arewidely disparate. We present the results of the statistical analysis with special emphasis on creativity and teamwork skills, and we conclude that the use of cooperative classroom has a positive influence on the acquisition of these skills. This work has the added value of being the first analysis of student perception of the use of cooperative classroom in the acquisition of creativity and teamwork skills.

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Many computer vision and human-computer interaction applications developed in recent years need evaluating complex and continuous mathematical functions as an essential step toward proper operation. However, rigorous evaluation of this kind of functions often implies a very high computational cost, unacceptable in real-time applications. To alleviate this problem, functions are commonly approximated by simpler piecewise-polynomial representations. Following this idea, we propose a novel, efficient, and practical technique to evaluate complex and continuous functions using a nearly optimal design of two types of piecewise linear approximations in the case of a large budget of evaluation subintervals. To this end, we develop a thorough error analysis that yields asymptotically tight bounds to accurately quantify the approximation performance of both representations. It provides an improvement upon previous error estimates and allows the user to control the trade-off between the approximation error and the number of evaluation subintervals. To guarantee real-time operation, the method is suitable for, but not limited to, an efficient implementation in modern Graphics Processing Units (GPUs), where it outperforms previous alternative approaches by exploiting the fixed-function interpolation routines present in their texture units. The proposed technique is a perfect match for any application requiring the evaluation of continuous functions, we have measured in detail its quality and efficiency on several functions, and, in particular, the Gaussian function because it is extensively used in many areas of computer vision and cybernetics, and it is expensive to evaluate.

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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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The segmental approach has been considered to analyze dark and light I-V curves. The photovoltaic (PV) dependence of the open-circuit voltage (Voc), the maximum power point voltage (Vm), the efficiency (?) on the photogenerated current (Jg), or on the sunlight concentration ratio (X), are analyzed, as well as other photovoltaic characteristics of multijunction solar cells. The characteristics being analyzed are split into monoexponential (linear in the semilogarithmic scale) portions, each of which is characterized by a definite value of the ideality factor A and preexponential current J0. The monoexponentiality ensures advantages, since at many steps of the analysis, one can use the analytical dependences instead of numerical methods. In this work, an experimental procedure for obtaining the necessary parameters has been proposed, and an analysis of GaInP/GaInAs/Ge triple-junction solar cell characteristics has been carried out. It has been shown that up to the sunlight concentration ratios, at which the efficiency maximum is achieved, the results of calculation of dark and light I-V curves by the segmental method fit well with the experimental data. An important consequence of this work is the feasibility of acquiring the resistanceless dark and light I-V curves, which can be used for obtaining the I-V curves characterizing the losses in the transport part of a solar cell.