PlayingCLIL, a new game-based methodology using drama pedagogy

[EN]Linguistic immersion programs are increasing nowadays. The concept of being bilingual, that started being used by schools for the elite in the 19th century, and that in the mid- 20th century became an educational option, has given raise to CLIL (Content and Language Integrated Learning), a methodology through which students work in a bilingual environment, acquiring knowledge of curricular subject and developing their competences in a foreign language. In this teaching context started a new European project called PlayingCLIL. Six partners from different European countries (Germany, United Kingdom, Spain and Romania) are working in this project. Our main aim is to develop a new methodology to learn a foreign language combining elements from the pedagogic drama (interactive games) with the CLIL classroom. At present we are testing the games in different schools and high schools and we are compiling the results to be collected in a handbook (printed and e-book).

Puzzle game online running on a bidirectional communication framework based on Node.js and Socket.io

Máster Universitario en Ingeniería Informática (Escuela Universitaria de Informática)

A GIS based model for solving the planar Huff problem considering different demand distributions and forbidden regions

[EN] In this paper, we have used Geographical Information Systems (GIS) to solve the planar Huff problem considering different demand distributions and forbidden regions. Most of the papers connected with the competitive location problems consider that the demand is aggregated in a finite set of points. In other few cases, the models suppose that the demand is distributed along the feasible region according to a functional form, mainly a uniform distribution. In this case, in addition to the discrete and uniform demand distributions we have considered that the demand is represented by a population surface model, that is, a raster map where each pixel has associated a value corresponding to the population living in the area that it covers...

A low complexity system based on multiple weighted decision trees for indoor localization

[EN] Indoor position estimation has become an attractive research topic due to growing interest in location-aware services. Nevertheless, satisfying solutions have not been found with the considerations of both accuracy and system complexity. From the perspective of lightweight mobile devices, they are extremely important characteristics, because both the processor power and energy availability are limited. Hence, an indoor localization system with high computational complexity can cause complete battery drain within a few hours. In our research, we use a data mining technique named boosting to develop a localization system based on multiple weighted decision trees to predict the device location, since it has high accuracy and low computational complexity.