30 resultados para games as learning environments
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¿Qué es un índice? ¿Cómo se estructura? ¿Cómo se almacena la información en una tabla? Esta presentación describe cada uno de estos aspectos y nos da consejos de cómo optimizar las tablas, índices y consultas.
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This article presents an interactive Java software platform which enables any user to easily create advanced virtual laboratories (VLs) for Robotics. This novel tool provides both support for developing applications with full 3D interactive graphical interface and a complete functional framework for modelling and simulation of arbitrary serial-link manipulators. In addition, its software architecture contains a high number of functionalities included as high-level tools, with the advantage of allowing any user to easily develop complex interactive robotic simulations with a minimum of programming. In order to show the features of the platform, the article describes, step-by-step, the implementation methodology of a complete VL for Robotics education using the presented approach. Finally, some educational results about the experience of implementing this approach are reported.
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Transparencias de la sesión 3 sobre sistemas informáticos para la asignatura de Informática Aplicada a las Ciencias Forenses.
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Tema 1. Introducción a las humanidades digitales.
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Tema 2. Un nuevo enfoque: la literatura desde lejos.
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Tema 3. Diseño y compilación de corpus.
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Tema 5. Anotación de corpus literario. XML. El estándar TEI.
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Tema 6. Text Mining con Topic Modeling.
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Guía rápida de análisis de corpus (con AntConc).
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Realizar copias de seguridad e imágenes de dispositivos, borrados profundos y recuperación de datos.
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Transparencias de Gestión de Índices de MySQL
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Los arquitectos y urbanistas tienen una larga tradición en el aprendizaje de las herramientas de las ciencias sociales, especialmente las que les permiten analizar y describir mejor los entornos y las personas para las que trabajan. Esto ha llevado a los arquitectos a desarrollar mejores herramientas de observación y descripción del ámbito social y no sólo el material. Sin embargo, la mayoría de las veces este acercamiento interdisciplinar ha identificado las ciencias sociales, especialmente la antropología, con la etnografía. Este artículo parte de la crítica a esta identificación hecha por el antropólogo Tim Ingold y se centra en lo que él propone como el método central de la antropología, la observación participante. Para después revisar varias propuestas actuales de científicos sociales que tratan de desarrollar una disciplina no representacional y orientada al futuro, un objetivo más cercano al de la arquitectura. El artículo intenta imaginar cómo esta práctica transdisciplinar podría desarrollarse.
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Presentaciones de la asignatura Interfaces para Entornos Inteligentes del Máster en Tecnologías de la Informática/Machine Learning and Data Mining.
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Nowadays, new computers generation provides a high performance that enables to build computationally expensive computer vision applications applied to mobile robotics. Building a map of the environment is a common task of a robot and is an essential part to allow the robots to move through these environments. Traditionally, mobile robots used a combination of several sensors from different technologies. Lasers, sonars and contact sensors have been typically used in any mobile robotic architecture, however color cameras are an important sensor due to we want the robots to use the same information that humans to sense and move through the different environments. Color cameras are cheap and flexible but a lot of work need to be done to give robots enough visual understanding of the scenes. Computer vision algorithms are computational complex problems but nowadays robots have access to different and powerful architectures that can be used for mobile robotics purposes. The advent of low-cost RGB-D sensors like Microsoft Kinect which provide 3D colored point clouds at high frame rates made the computer vision even more relevant in the mobile robotics field. The combination of visual and 3D data allows the systems to use both computer vision and 3D processing and therefore to be aware of more details of the surrounding environment. The research described in this thesis was motivated by the need of scene mapping. Being aware of the surrounding environment is a key feature in many mobile robotics applications from simple robotic navigation to complex surveillance applications. In addition, the acquisition of a 3D model of the scenes is useful in many areas as video games scene modeling where well-known places are reconstructed and added to game systems or advertising where once you get the 3D model of one room the system can add furniture pieces using augmented reality techniques. In this thesis we perform an experimental study of the state-of-the-art registration methods to find which one fits better to our scene mapping purposes. Different methods are tested and analyzed on different scene distributions of visual and geometry appearance. In addition, this thesis proposes two methods for 3d data compression and representation of 3D maps. Our 3D representation proposal is based on the use of Growing Neural Gas (GNG) method. This Self-Organizing Maps (SOMs) has been successfully used for clustering, pattern recognition and topology representation of various kind of data. Until now, Self-Organizing Maps have been primarily computed offline and their application in 3D data has mainly focused on free noise models without considering time constraints. Self-organising neural models have the ability to provide a good representation of the input space. In particular, the Growing Neural Gas (GNG) is a suitable model because of its flexibility, rapid adaptation and excellent quality of representation. However, this type of learning is time consuming, specially for high-dimensional input data. Since real applications often work under time constraints, it is necessary to adapt the learning process in order to complete it in a predefined time. This thesis proposes a hardware implementation leveraging the computing power of modern GPUs which takes advantage of a new paradigm coined as General-Purpose Computing on Graphics Processing Units (GPGPU). Our proposed geometrical 3D compression method seeks to reduce the 3D information using plane detection as basic structure to compress the data. This is due to our target environments are man-made and therefore there are a lot of points that belong to a plane surface. Our proposed method is able to get good compression results in those man-made scenarios. The detected and compressed planes can be also used in other applications as surface reconstruction or plane-based registration algorithms. Finally, we have also demonstrated the goodness of the GPU technologies getting a high performance implementation of a CAD/CAM common technique called Virtual Digitizing.