Las maquetas como material didáctico para la enseñanza y aprendizaje de la lectura e interpretación de planos en la ingeniería

Utilizamos las maquetas como herramientas auxiliares para proyectar y mostrar proyectos de ingeniería, pero también pueden ser un excelente material didáctico para la enseñanza y aprendizaje de la lectura, interpretación y realización de los planos que definen un proyecto o sus diferentes elementos. En este trabajo se refiere la experiencia realizada por los autores con los alumnos de Ingeniería Técnica de Obras Públicas dentro de la unidad de Interpretación de Planos de la asignatura de Sistemas de Representación. La dificultad que los alumnos de la materia tienen para interpretar el lenguaje, códigos y convenciones de la expresión gráfica está entre los motivos por los que se ha utilizado las maquetas como método de representación tridimensional que permite hacer comprensibles y fácilmente interpretadas las características constructivas de los diferentes elementos y las operaciones necesarias para pasar de la representación a la realización de la unidad de obra. En la comunicación se describe la actividad realizada con los alumnos, la selección de las unidades a representar, la elaboración de las maquetas y planos, poniendo especial acento en la concordancia entre la representación gráfica y el modelo tridimensional. Asimismo se han analizado las capacidades didácticas de uno de los trabajos realizados por los alumnos así como la evaluación y conclusiones de la experiencia realizada.

The representation of the world in national Arab news agencies: an exploration of (trans)national networks in the official Arab media

The purpose of this paper is to draw a map of the representation of the world and of Arab states as reflected by the countries of the region. To do so, we have analysed the news (4,093 news randomly collected on February and August 2005) produced by the governments of the Arab states through their national news agencies. Several regional and world maps had been constructed to show the official Arab representation of the World, the Arab countries conflict agenda, the persistence of colonial ties (with the European metropolis) and the emergence of new relationships (Asian countries). The representation of the world that appeared in the analysis focuses its interest on the USA, the war in Iraq, the Israel-Palestine conflict, the United Kingdom, France, and Iran. The Arab regional powers organise the flow of information (Saudi Arabia and Egypt) and the colonial past determines the current structure of communication (French-speaking bloc and English-speaking bloc).

Parallel Computational Intelligence-Based Multi-Camera Surveillance System

In this work, we present a multi-camera surveillance system based on the use of self-organizing neural networks to represent events on video. The system processes several tasks in parallel using GPUs (graphic processor units). It addresses multiple vision tasks at various levels, such as segmentation, representation or characterization, analysis and monitoring of the movement. These features allow the construction of a robust representation of the environment and interpret the behavior of mobile agents in the scene. It is also necessary to integrate the vision module into a global system that operates in a complex environment by receiving images from multiple acquisition devices at video frequency. Offering relevant information to higher level systems, monitoring and making decisions in real time, it must accomplish a set of requirements, such as: time constraints, high availability, robustness, high processing speed and re-configurability. We have built a system able to represent and analyze the motion in video acquired by a multi-camera network and to process multi-source data in parallel on a multi-GPU architecture.

Generation of representation models for complex systems using Lagrangian functions

In this article, a new methodology is presented to obtain representation models for a priori relation z = u(x1, x2, . . . ,xn) (1), with a known an experimental dataset zi; x1i ; x2i ; x3i ; . . . ; xni i=1;2;...;p· In this methodology, a potential energy is initially defined over each possible model for the relationship (1), what allows the application of the Lagrangian mechanics to the derived system. The solution of the Euler–Lagrange in this system allows obtaining the optimal solution according to the minimal action principle. The defined Lagrangian, corresponds to a continuous medium, where a n-dimensional finite elements model has been applied, so it is possible to get a solution for the problem solving a compatible and determined linear symmetric equation system. The computational implementation of the methodology has resulted in an improvement in the process of get representation models obtained and published previously by the authors.

Contributions to 3D Data Registration and Representation

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.