L'Exercici de la docència de la psicologia i el Burnout

En l’actualitat el burnout o síndrome de cremar-se per la feina és considerat un risc emergent als països occidentals essent el col·lectiu docent un dels més afectats. L’espai europeu d’educació superior proposa un nou rol pel professor que haurà de ser compaginat amb la gestió, la recerca i la transferència de coneixement. En la present recerca s’analitza el nivell de burnout en una mostra formada per 42 docents (mitjana d’edat: 37,21 anys; D.T.: 8,98; 70,8% dones) del departament de Psicologia de la Universitat de Girona. El burnout s’ha avaluat amb el Maslach Burnout Inventory (MBI) així com amb un qüestionari d’elaboració pròpia que recull variables sociodemogràfiques, característiques del tipus de treball i de l’ús del temps lliure, el locus de control i el burnout percebut. Els resultats obtinguts indiquen valors mitjans en les puntuacions de les dimensions Cansament Emocional i Despersonalització, i valors elevats en Realització Personal. El 20,5% dels docents es percep cremat per la feina

A behavior-based scheme using reinforcement learning for autonomous underwater vehicles

This paper presents a hybrid behavior-based scheme using reinforcement learning for high-level control of autonomous underwater vehicles (AUVs). Two main features of the presented approach are hybrid behavior coordination and semi on-line neural-Q_learning (SONQL). Hybrid behavior coordination takes advantages of robustness and modularity in the competitive approach as well as efficient trajectories in the cooperative approach. SONQL, a new continuous approach of the Q_learning algorithm with a multilayer neural network is used to learn behavior state/action mapping online. Experimental results show the feasibility of the presented approach for AUVs

Simplification, approximation and deformation of large models

The high level of realism and interaction in many computer graphic applications requires techniques for processing complex geometric models. First, we present a method that provides an accurate low-resolution approximation from a multi-chart textured model that guarantees geometric fidelity and correct preservation of the appearance attributes. Then, we introduce a mesh structure called Compact Model that approximates dense triangular meshes while preserving sharp features, allowing adaptive reconstructions and supporting textured models. Next, we design a new space deformation technique called *Cages based on a multi-level system of cages that preserves the smoothness of the mesh between neighbouring cages and is extremely versatile, allowing the use of heterogeneous sets of coordinates and different levels of deformation. Finally, we propose a hybrid method that allows to apply any deformation technique on large models obtaining high quality results with a reduced memory footprint and a high performance.

Integration of knowledge-based, qualitative and numeric tools for real time dynamic systems supervision

The proposal presented in this thesis is to provide designers of knowledge based supervisory systems of dynamic systems with a framework to facilitate their tasks avoiding interface problems among tools, data flow and management. The approach is thought to be useful to both control and process engineers in assisting their tasks. The use of AI technologies to diagnose and perform control loops and, of course, assist process supervisory tasks such as fault detection and diagnose, are in the scope of this work. Special effort has been put in integration of tools for assisting expert supervisory systems design. With this aim the experience of Computer Aided Control Systems Design (CACSD) frameworks have been analysed and used to design a Computer Aided Supervisory Systems (CASSD) framework. In this sense, some basic facilities are required to be available in this proposed framework: ·