9 resultados para Low-level laser

em Universitat de Girona, Spain


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En una muestra de 119 estudiantes de cuarto de Educación Secundaria Obligatoria (ESO) y primero de Bachillerato (52,6% mujeres) se analizan los conocimientos sobre la prevención de la transmisión sexual del virus del sida, las expectativas de resultados y de autoeficacia respecto a los métodos preventivos y el tipo de prevención utilizada durante la última relación sexual. Para evitar las respuestas inducidas respecto a los comportamientos preventivos se emplea un formato de pregunta abierta. Los resultados muestran que sólo el 23,5% de los estudiantes han dado dos respuestas totalmente correctas sobre estrategias consideradas eficaces en la prevención sexual del VIH: uso del preservativo y abstinencia (por este orden). El 70,5% valoran totalmente o muy eficaz el preservativo para evitar la transmisión sexual del VIH y el 95% de los que dan la segunda respuesta juzgan totalmente eficaz la práctica de la abstinencia con la misma finalidad. En el caso del preservativo se sienten totalmente o muy capaces de usarlo el 64,3%, mientras que cuando se trata de la abstinencia sólo se perciben con esa competencia el 20%. Por lo que se refiere al uso autoinformado de métodos preventivos en la última relación, por parte de los 29 estudiantes que tuvieron actividad sexual durante el mes anterior, se observa que 21 de ellos emplearon el preservativo, dos la píldora anticonceptiva, otros dos no precisan el tipo de precaución y el resto no tomó ninguna. Tanto el reducido nivel de conocimientos sobre prevención, como la baja percepción de autoeficacia para mantenerse abstinentes, nos alertan sobre la necesidad de hacer un mayor esfuerzo de información para eliminar creencias equivocadas, como por ejemplo: sobre la pretendida eficacia protectora de tener relaciones sexuales con una pareja estable o conocida. Así mismo, conviene insistir en el uso del preservativo como anticonceptivo de elección entre los adolescentes

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Inicialmente integrada en el piloto de gvSIG Mobile, la librería libLocation tiene como objetivo dotar a los proyectos gvSIG Desktop y gvSIG Mobile un acceso transparente a fuentes de localización. La librería se fundamenta en las especificaciones JSR-179 -API de localización para J2ME- y JSR-293 -API de localización para J2ME v2.0-, proporcionando una interfaz uniforme a diferentes fuentes de localización, mediante funciones de alto nivel. Asimismo, se extiende la funcionalidad de estas APIs para permitir la gestión de datos específicos del tipo de fuente de localización y el ajuste de parámetros de bajo nivel, además de incorporar métodos de localización adicionales, como la aplicación de correcciones vía protocolo NTRIP. La librería libLocation está actualmente en proceso de desarrollo y será publicada y liberada junto con la versión definitiva de gvSIG Mobile. Junto con libLocation se están desarrollando extensiones que permiten el acceso a esta librería desde gvSIG Desktop y gvSIG Mobile

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This paper presents a vision-based localization approach for an underwater robot in a structured environment. The system is based on a coded pattern placed on the bottom of a water tank and an onboard down looking camera. Main features are, absolute and map-based localization, landmark detection and tracking, and real-time computation (12.5 Hz). The proposed system provides three-dimensional position and orientation of the vehicle along with its velocity. Accuracy of the drift-free estimates is very high, allowing them to be used as feedback measures of a velocity-based low-level controller. The paper details the localization algorithm, by showing some graphical results, and the accuracy of the system

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It is well known that image processing requires a huge amount of computation, mainly at low level processing where the algorithms are dealing with a great number of data-pixel. One of the solutions to estimate motions involves detection of the correspondences between two images. For normalised correlation criteria, previous experiments shown that the result is not altered in presence of nonuniform illumination. Usually, hardware for motion estimation has been limited to simple correlation criteria. The main goal of this paper is to propose a VLSI architecture for motion estimation using a matching criteria more complex than Sum of Absolute Differences (SAD) criteria. Today hardware devices provide many facilities for the integration of more and more complex designs as well as the possibility to easily communicate with general purpose processors

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This paper proposes a parallel architecture for estimation of the motion of an underwater robot. It is well known that image processing requires a huge amount of computation, mainly at low-level processing where the algorithms are dealing with a great number of data. In a motion estimation algorithm, correspondences between two images have to be solved at the low level. In the underwater imaging, normalised correlation can be a solution in the presence of non-uniform illumination. Due to its regular processing scheme, parallel implementation of the correspondence problem can be an adequate approach to reduce the computation time. Taking into consideration the complexity of the normalised correlation criteria, a new approach using parallel organisation of every processor from the architecture is proposed

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Behavior-based navigation of autonomous vehicles requires the recognition of the navigable areas and the potential obstacles. In this paper we describe a model-based objects recognition system which is part of an image interpretation system intended to assist the navigation of autonomous vehicles that operate in industrial environments. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using a rule-based cooperative expert system

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We describe a model-based objects recognition system which is part of an image interpretation system intended to assist autonomous vehicles navigation. The system is intended to operate in man-made environments. Behavior-based navigation of autonomous vehicles involves the recognition of navigable areas and the potential obstacles. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using CEES, the C++ embedded expert system shell developed in the Systems Engineering and Automatic Control Laboratory (University of Girona) as a specific rule-based problem solving tool. It has been especially conceived for supporting cooperative expert systems, and uses the object oriented programming paradigm

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Due to the high cost of a large ATM network working up to full strength to apply our ideas about network management, i.e., dynamic virtual path (VP) management and fault restoration, we developed a distributed simulation platform for performing our experiments. This platform also had to be capable of other sorts of tests, such as connection admission control (CAC) algorithms, routing algorithms, and accounting and charging methods. The platform was posed as a very simple, event-oriented and scalable simulation. The main goal was the simulation of a working ATM backbone network with a potentially large number of nodes (hundreds). As research into control algorithms and low-level, or rather cell-level methods, was beyond the scope of this study, the simulation took place at a connection level, i.e., there was no real traffic of cells. The simulated network behaved like a real network accepting and rejecting SNMP ones, or experimental tools using the API node

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This research work deals with the problem of modeling and design of low level speed controller for the mobile robot PRIM. The main objective is to develop an effective educational tool. On one hand, the interests in using the open mobile platform PRIM consist in integrating several highly related subjects to the automatic control theory in an educational context, by embracing the subjects of communications, signal processing, sensor fusion and hardware design, amongst others. On the other hand, the idea is to implement useful navigation strategies such that the robot can be served as a mobile multimedia information point. It is in this context, when navigation strategies are oriented to goal achievement, that a local model predictive control is attained. Hence, such studies are presented as a very interesting control strategy in order to develop the future capabilities of the system