876 resultados para Soft real-time distributed systems


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Electrical Protection systems and Automatic Voltage Regulators (AVR) are essential components of actual power plants. Its installation and setting is performed during the commissioning, and it needs extensive experience since any failure in this process or in the setting, may entails some risk not only for the generator of the power plant, but also for the reliability of the power grid. In this paper, a real time power plant simulation platform is presented as a tool for improving the training and learning process on electrical protections and automatic voltage regulators. The activities of the commissioning procedure which can be practiced are described, and the applicability of this tool for improving the comprehension of this important part of the power plants is discussed. A commercial AVR and a multifunction protective relay have been tested with satisfactory results.

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El estudio del comportamiento de la atmósfera ha resultado de especial importancia tanto en el programa SESAR como en NextGen, en los que la gestión actual del tránsito aéreo (ATM) está experimentando una profunda transformación hacia nuevos paradigmas tanto en Europa como en los EE.UU., respectivamente, para el guiado y seguimiento de las aeronaves en la realización de rutas más eficientes y con mayor precisión. La incertidumbre es una característica fundamental de los fenómenos meteorológicos que se transfiere a la separación de las aeronaves, las trayectorias de vuelo libres de conflictos y a la planificación de vuelos. En este sentido, el viento es un factor clave en cuanto a la predicción de la futura posición de la aeronave, por lo que tener un conocimiento más profundo y preciso de campo de viento reducirá las incertidumbres del ATC. El objetivo de esta tesis es el desarrollo de una nueva técnica operativa y útil destinada a proporcionar de forma adecuada y directa el campo de viento atmosférico en tiempo real, basada en datos de a bordo de la aeronave, con el fin de mejorar la predicción de las trayectorias de las aeronaves. Para lograr este objetivo se ha realizado el siguiente trabajo. Se han descrito y analizado los diferentes sistemas de la aeronave que proporcionan las variables necesarias para obtener la velocidad del viento, así como de las capacidades que permiten la presentación de esta información para sus aplicaciones en la gestión del tráfico aéreo. Se ha explorado el uso de aeronaves como los sensores de viento en un área terminal para la estimación del viento en tiempo real con el fin de mejorar la predicción de las trayectorias de aeronaves. Se han desarrollado métodos computacionalmente eficientes para estimar las componentes horizontales de la velocidad del viento a partir de las velocidades de las aeronaves (VGS, VCAS/VTAS), la presión y datos de temperatura. Estos datos de viento se han utilizado para estimar el campo de viento en tiempo real utilizando un sistema de procesamiento de datos a través de un método de mínima varianza. Por último, se ha evaluado la exactitud de este procedimiento para que esta información sea útil para el control del tráfico aéreo. La información inicial proviene de una muestra de datos de Registradores de Datos de Vuelo (FDR) de aviones que aterrizaron en el aeropuerto Madrid-Barajas. Se dispuso de datos de ciertas aeronaves durante un periodo de más de tres meses que se emplearon para calcular el vector viento en cada punto del espacio aéreo. Se utilizó un modelo matemático basado en diferentes métodos de interpolación para obtener los vectores de viento en áreas sin datos disponibles. Se han utilizado tres escenarios concretos para validar dos métodos de interpolación: uno de dos dimensiones que trabaja con ambas componentes horizontales de forma independiente, y otro basado en el uso de una variable compleja que relaciona ambas componentes. Esos métodos se han probado en diferentes escenarios con resultados dispares. Esta metodología se ha aplicado en un prototipo de herramienta en MATLAB © para analizar automáticamente los datos de FDR y determinar el campo vectorial del viento que encuentra la aeronave al volar en el espacio aéreo en estudio. Finalmente se han obtenido las condiciones requeridas y la precisión de los resultados para este modelo. El método desarrollado podría utilizar los datos de los aviones comerciales como inputs utilizando los datos actualmente disponibles y la capacidad computacional, para proporcionárselos a los sistemas ATM donde se podría ejecutar el método propuesto. Estas velocidades del viento calculadas, o bien la velocidad respecto al suelo y la velocidad verdadera, se podrían difundir, por ejemplo, a través del sistema de direccionamiento e informe para comunicaciones de aeronaves (ACARS), mensajes de ADS-B o Modo S. Esta nueva fuente ayudaría a actualizar la información del viento suministrada en los productos aeronáuticos meteorológicos (PAM), informes meteorológicos de aeródromos (AIRMET), e información meteorológica significativa (SIGMET). ABSTRACT The study of the atmosphere behaviour is been of particular importance both in SESAR and NextGen programs, where the current air traffic management (ATM) system is undergoing a profound transformation to the new paradigms both in Europe and the USA, respectively, to guide and track aircraft more precisely on more efficient routes. Uncertainty is a fundamental characteristic of weather phenomena which is transferred to separation assurance, flight path de-confliction and flight planning applications. In this respect, the wind is a key factor regarding the prediction of the future position of the aircraft, so that having a deeper and accurate knowledge of wind field will reduce ATC uncertainties. The purpose of this thesis is to develop a new and operationally useful technique intended to provide adequate and direct real-time atmospheric winds fields based on on-board aircraft data, in order to improve aircraft trajectory prediction. In order to achieve this objective the following work has been accomplished. The different sources in the aircraft systems that provide the variables needed to derivate the wind velocity have been described and analysed, as well as the capabilities which allow presenting this information for air traffic management applications. The use of aircraft as wind sensors in a terminal area for real-time wind estimation in order to improve aircraft trajectory prediction has been explored. Computationally efficient methods have been developed to estimate horizontal wind components from aircraft velocities (VGS, VCAS/VTAS), pressure, and temperature data. These wind data were utilized to estimate a real-time wind field using a data processing approach through a minimum variance method. Finally, the accuracy of this procedure has been evaluated for this information to be useful to air traffic control. The initial information comes from a Flight Data Recorder (FDR) sample of aircraft landing in Madrid-Barajas Airport. Data available for more than three months were exploited in order to derive the wind vector field in each point of the airspace. Mathematical model based on different interpolation methods were used in order to obtain wind vectors in void areas. Three particular scenarios were employed to test two interpolation methods: a two-dimensional one that works with both horizontal components in an independent way, and also a complex variable formulation that links both components. Those methods were tested using various scenarios with dissimilar results. This methodology has been implemented in a prototype tool in MATLAB © in order to automatically analyse FDR and determine the wind vector field that aircraft encounter when flying in the studied airspace. Required conditions and accuracy of the results were derived for this model. The method developed could be fed by commercial aircraft utilizing their currently available data sources and computational capabilities, and providing them to ATM system where the proposed method could be run. Computed wind velocities, or ground and true airspeeds, would then be broadcasted, for example, via the Aircraft Communication Addressing and Reporting System (ACARS), ADS-B out messages, or Mode S. This new source would help updating the wind information furnished in meteorological aeronautical products (PAM), meteorological aerodrome reports (AIRMET), and significant meteorological information (SIGMET).

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As embedded systems evolve, problems inherent to technology become important limitations. In less than ten years, chips will exceed the maximum allowed power consumption affecting performance, since, even though the resources available per chip are increasing, frequency of operation has stalled. Besides, as the level of integration is increased, it is difficult to keep defect density under control, so new fault tolerant techniques are required. In this demo work, a new dynamically adaptable virtual architecture (ARTICo3) to allow dynamic and context-aware use of resources is implemented in a high performance Wireless Sensor node (HiReCookie) to perform an image processing application.

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This paper presents a novel robust visual tracking framework, based on discriminative method, for Unmanned Aerial Vehicles (UAVs) to track an arbitrary 2D/3D target at real-time frame rates, that is called the Adaptive Multi-Classifier Multi-Resolution (AMCMR) framework. In this framework, adaptive Multiple Classifiers (MC) are updated in the (k-1)th frame-based Multiple Resolutions (MR) structure with compressed positive and negative samples, and then applied them in the kth frame-based Multiple Resolutions (MR) structure to detect the current target. The sample importance has been integrated into this framework to improve the tracking stability and accuracy. The performance of this framework was evaluated with the Ground Truth (GT) in different types of public image databases and real flight-based aerial image datasets firstly, then the framework has been applied in the UAV to inspect the Offshore Floating Platform (OFP). The evaluation and application results show that this framework is more robust, efficient and accurate against the existing state-of-art trackers, overcoming the problems generated by the challenging situations such as obvious appearance change, variant illumination, partial/full target occlusion, blur motion, rapid pose variation and onboard mechanical vibration, among others. To our best knowledge, this is the first work to present this framework for solving the online learning and tracking freewill 2D/3D target problems, and applied it in the UAVs.

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El propósito de esta tesis es presentar una metodología para realizar análisis de la dinámica en pequeña señal y el comportamiento de sistemas de alimentación distribuidos de corriente continua (CC), formados por módulos comerciales. Para ello se hace uso de un método sencillo que indica los márgenes de estabilidad menos conservadores posibles mediante un solo número. Este índice es calculado en cada una de las interfaces que componen el sistema y puede usarse para obtener un índice global que indica la estabilidad del sistema global. De esta manera se posibilita la comparación de sistemas de alimentación distribuidos en términos de robustez. La interconexión de convertidores CC-CC entre ellos y con los filtros EMI necesarios puede originar interacciones no deseadas que dan lugar a la degradación del comportamiento de los convertidores, haciendo el sistema más propenso a inestabilidades. Esta diferencia en el comportamiento se debe a interacciones entre las impedancias de los diversos elementos del sistema. En la mayoría de los casos, los sistemas de alimentación distribuida están formados por módulos comerciales cuya estructura interna es desconocida. Por ello los análisis presentados en esta tesis se basan en medidas de la respuesta en frecuencia del convertidor que pueden realizarse desde los terminales de entrada y salida del mismo. Utilizando las medidas de las impedancias de entrada y salida de los elementos del sistema, se puede construir una función de sensibilidad que proporciona los márgenes de estabilidad de las diferentes interfaces. En esta tesis se utiliza el concepto del valor máximo de la función de sensibilidad (MPC por sus siglas en inglés) para indicar los márgenes de estabilidad como un único número. Una vez que la estabilidad de todas las interfaces del sistema se han evaluado individualmente, los índices obtenidos pueden combinarse para obtener un único número con el que comparar la estabilidad de diferentes sistemas. Igualmente se han analizado las posibles interacciones en la entrada y la salida de los convertidores CC-CC, obteniéndose expresiones analíticas con las que describir en detalle los acoplamientos generados en el sistema. Los estudios analíticos realizados se han validado experimentalmente a lo largo de la tesis. El análisis presentado en esta tesis se culmina con la obtención de un índice que condensa los márgenes de estabilidad menos conservativos. También se demuestra que la robustez del sistema está asegurada si las impedancias utilizadas en la función de sensibilidad se obtienen justamente en la entrada o la salida del subsistema que está siendo analizado. Por otra parte, la tesis presenta un conjunto de parámetros internos asimilados a impedancias, junto con sus expresiones analíticas, que permiten una explicación detallada de las interacciones en el sistema. Dichas expresiones analíticas pueden obtenerse bien mediante las funciones de transferencia analíticas si se conoce la estructura interna, o utilizando medidas en frecuencia o identificación de las mismas a través de la respuesta temporal del convertidor. De acuerdo a las metodologías presentadas en esta tesis se puede predecir la estabilidad y el comportamiento de sistemas compuestos básicamente por convertidores CC-CC y filtros, cuya estructura interna es desconocida. La predicción se basa en un índice que condensa la información de los márgenes de estabilidad y que permite la obtención de un indicador de la estabilidad global de todo el sistema, permitiendo la comparación de la estabilidad de diferentes arquitecturas de sistemas de alimentación distribuidos. ABSTRACT The purpose of this thesis is to present dynamic small-signal stability and performance analysis methodology for dc-distributed systems consisting of commercial power modules. Furthermore, the objective is to introduce simple method to state the least conservative margins for robust stability as a single number. In addition, an index characterizing the overall system stability is obtained, based on which different dc-distributed systems can be compared in terms of robustness. The interconnected systems are prone to impedance-based interactions which might lead to transient-performance degradation or even instability. These systems typically are constructed using commercial converters with unknown internal structure. Therefore, the analysis presented throughout this thesis is based on frequency responses measurable from the input and output terminals. The stability margins are stated utilizing a concept of maximum peak criteria, derived from the behavior of impedance-based sensitivity function that provides a single number to state robust stability. Using this concept, the stability information at every system interface is combined to a meaningful number to state the average robustness of the system. In addition, theoretical formulas are extracted to assess source and load side interactions in order to describe detailed couplings within the system. The presented theoretical analysis methodologies are experimentally validated throughout the thesis. In this thesis, according to the presented analysis, the least conservative stability margins are provided as a single number guaranteeing robustness. It is also shown that within the interconnected system the robust stability is ensured only if the impedance-based minor-loop gain is determined at the very input or output of each subsystem. Moreover, a complete set of impedance-type internal parameters as well as the formulas according to which the interaction sensitivity can be fully explained and analyzed, is provided. The given formulation can be utilized equally either based on measured frequency responses, time-domain identified internal parameters or extracted analytic transfer functions. Based on the analysis methodologies presented in this thesis, the stability and performance of interconnected systems consisting of converters with unknown internal structure, can be predicted. Moreover, the provided concept to assess the least conservative stability margins enables to obtain an index to state the overall robust stability of distributed power architecture and thus to compare different systems in terms of stability.

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To “control” a system is to make it behave (hopefully) according to our “wishes,” in a way compatible with safety and ethics, at the least possible cost. The systems considered here are distributed—i.e., governed (modeled) by partial differential equations (PDEs) of evolution. Our “wish” is to drive the system in a given time, by an adequate choice of the controls, from a given initial state to a final given state, which is the target. If this can be achieved (respectively, if we can reach any “neighborhood” of the target) the system, with the controls at our disposal, is exactly (respectively, approximately) controllable. A very general (and fuzzy) idea is that the more a system is “unstable” (chaotic, turbulent) the “simplest,” or the “cheapest,” it is to achieve exact or approximate controllability. When the PDEs are the Navier–Stokes equations, it leads to conjectures, which are presented and explained. Recent results, reported in this expository paper, essentially prove the conjectures in two space dimensions. In three space dimensions, a large number of new questions arise, some new results support (without proving) the conjectures, such as generic controllability and cases of decrease of cost of control when the instability increases. Short comments are made on models arising in climatology, thermoelasticity, non-Newtonian fluids, and molecular chemistry. The Introduction of the paper and the first part of all sections are not technical. Many open questions are mentioned in the text.

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The challenge of the Human Genome Project is to increase the rate of DNA sequence acquisition by two orders of magnitude to complete sequencing of the human genome by the year 2000. The present work describes a rapid detection method using a two-dimensional optical wave guide that allows measurement of real-time binding or melting of a light-scattering label on a DNA array. A particulate label on the target DNA acts as a light-scattering source when illuminated by the evanescent wave of the wave guide and only the label bound to the surface generates a signal. Imaging/visual examination of the scattered light permits interrogation of the entire array simultaneously. Hybridization specificity is equivalent to that obtained with a conventional system using autoradiography. Wave guide melting curves are consistent with those obtained in the liquid phase and single-base discrimination is facile. Dilution experiments showed an apparent lower limit of detection at 0.4 nM oligonucleotide. This performance is comparable to the best currently known fluorescence-based systems. In addition, wave guide detection allows manipulation of hybridization stringency during detection and thereby reduces DNA chip complexity. It is anticipated that this methodology will provide a powerful tool for diagnostic applications that require rapid cost-effective detection of variations from known sequences.

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Feature vectors can be anything from simple surface normals to more complex feature descriptors. Feature extraction is important to solve various computer vision problems: e.g. registration, object recognition and scene understanding. Most of these techniques cannot be computed online due to their complexity and the context where they are applied. Therefore, computing these features in real-time for many points in the scene is impossible. In this work, a hardware-based implementation of 3D feature extraction and 3D object recognition is proposed to accelerate these methods and therefore the entire pipeline of RGBD based computer vision systems where such features are typically used. The use of a GPU as a general purpose processor can achieve considerable speed-ups compared with a CPU implementation. In this work, advantageous results are obtained using the GPU to accelerate the computation of a 3D descriptor based on the calculation of 3D semi-local surface patches of partial views. This allows descriptor computation at several points of a scene in real-time. Benefits of the accelerated descriptor have been demonstrated in object recognition tasks. Source code will be made publicly available as contribution to the Open Source Point Cloud Library.

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In this project, we propose the implementation of a 3D object recognition system which will be optimized to operate under demanding time constraints. The system must be robust so that objects can be recognized properly in poor light conditions and cluttered scenes with significant levels of occlusion. An important requirement must be met: the system must exhibit a reasonable performance running on a low power consumption mobile GPU computing platform (NVIDIA Jetson TK1) so that it can be integrated in mobile robotics systems, ambient intelligence or ambient assisted living applications. The acquisition system is based on the use of color and depth (RGB-D) data streams provided by low-cost 3D sensors like Microsoft Kinect or PrimeSense Carmine. The range of algorithms and applications to be implemented and integrated will be quite broad, ranging from the acquisition, outlier removal or filtering of the input data and the segmentation or characterization of regions of interest in the scene to the very object recognition and pose estimation. Furthermore, in order to validate the proposed system, we will create a 3D object dataset. It will be composed by a set of 3D models, reconstructed from common household objects, as well as a handful of test scenes in which those objects appear. The scenes will be characterized by different levels of occlusion, diverse distances from the elements to the sensor and variations on the pose of the target objects. The creation of this dataset implies the additional development of 3D data acquisition and 3D object reconstruction applications. The resulting system has many possible applications, ranging from mobile robot navigation and semantic scene labeling to human-computer interaction (HCI) systems based on visual information.

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In this study, a methodology based in a dynamical framework is proposed to incorporate additional sources of information to normalized difference vegetation index (NDVI) time series of agricultural observations for a phenological state estimation application. The proposed implementation is based on the particle filter (PF) scheme that is able to integrate multiple sources of data. Moreover, the dynamics-led design is able to conduct real-time (online) estimations, i.e., without requiring to wait until the end of the campaign. The evaluation of the algorithm is performed by estimating the phenological states over a set of rice fields in Seville (SW, Spain). A Landsat-5/7 NDVI series of images is complemented with two distinct sources of information: SAR images from the TerraSAR-X satellite and air temperature information from a ground-based station. An improvement in the overall estimation accuracy is obtained, especially when the time series of NDVI data is incomplete. Evaluations on the sensitivity to different development intervals and on the mitigation of discontinuities of the time series are also addressed in this work, demonstrating the benefits of this data fusion approach based on the dynamic systems.

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Federal Highway Administration, Office of Research, Washington, D.C.

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Federal Highway Administration, Office of Research, Washington, D.C.

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Federal Highway Administration, Office of Research, Washington, D.C.

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Federal Highway Administration, Office of Research, Washington, D.C.

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OBJECTIVES We sought to determine whether assessment of left ventricular (LV) function with real-time (RT) three-dimensional echocardiography (3DE) could reduce the variation of sequential LV measurements and provide greater accuracy than two-dimensional echocardiography (2DE). BACKGROUND Real-time 3DE has become feasible as a standard clinical tool, but its accuracy for LV assessment has not been validated. METHODS Unselected patients (n = 50; 41 men; age, 64 +/- 8 years) presenting for evaluation of LV function were studied with 2DE and RT-3DE. Test-retest variation was performed by a complete restudy by a separate sonographer within 1 h without alteration of hemodynamics or therapy. Magnetic resonance imaging (MRI) images were obtained during a breath-hold, and measurements were made off-line. RESULTS The test-retest variation showed similar measurements for volumes but wider scatter of LV mass measurements with M-mode and 2DE than 3DE. The average MRI end-diastolic volume was 172 +/- 53 ml; LV volumes were underestimated by 2DE (mean difference, -54 +/- 33; p < 0.01) but only slightly by RT-3DE (-4 +/- 29; p = 0.31). Similarly, end-systolic volume by MRI (91 +/- 53 ml) was underestimated by 2DE (mean difference, -28 +/- 28; p < 0.01) and by RT-3DE (mean difference, -3 +/- 18; p = 0.23). Ejection fraction by MRI was similar by 2DE (p = 0.76) and RT-3DE (p = 0.74). Left ventricular mass (183 +/- 50 g) was overestimated by M-mode (mean difference, 68 +/- 86 g; p < 0.01) and 2DE (16 +/- 57; p = 0.04) but not RT-3DE (0 +/- 38 g; p = 0.94). There was good inter- and intra-observer correlation between RT-3DE by two sonographers for volumes, ejection fraction, and mass. CONCLUSIONS Real-time 3DE is a feasible approach to reduce test-retest variation of LV volume, ejection fraction, and mass measurements in follow-up LV assessment in daily practice. (C) 2004 by the American College of Cardiology Foundation.