Abstract
This paper describes the Hybrid User Centered Development Methodology (HUCDM). This methodology is a simple, iterative and incremental development process. The methodology is based on structured disciplined development processes, on principles of User Centered Development (UCD) processes, specified in the International Organization for Standardization - ISO 13407, as well as practices and values of agile methods for software development. The evaluation during the development process is another pillar of the methodology given the principles of the metrics defined in ISO / IEC 9126-1. HUCDM aims to propose a methodology for the development of educational resources with recognized quality and viable from economic standpoint in Small and Medium Enterprises (SMEs) in Portugal.

Abstract
Both the academic and industry sectors have increased their attention and investment to the fields of Affective Computing and immersive digital environments, the latter imposing itself as a reliable domain, with increasingly cheaper hardware solutions. With all this in mind, the authors envisioned an immersive dynamic digital environment tied with automatic real-time user emotion assessment through biométrie readings. The environment consisted in an aeronautical simulation, with internal variables such as flight plan, weather conditions and maneuver smoothness dynamically altered by the assessed emotional state of the user, based on biométrie readings, including galvanic skin response, respiration rate and amplitude and phalange temperature. The results were consistent with the emotional states reported by the users, with a success rate of 78%.

Abstract

Abstract
The images of Electrical Impedance Tomography are reconstructed using certain approximations and have a low spatial resolution. It is therefore proposed, in order to detect the presence of such tumors, to use neural networks for the recognition of typical patterns in the raw data rather than in the reconstructed images. The results obtained with several types of targets in vitro confirm the feasibility of this approach.

Abstract
Machine Facial Recognition is a problem that consists in exploring still or video images of a scene to identify or verify one or more persons in the scene using stored databases of faces. Research in Facial Recognition is multidisciplinary including disciplines like pattern recognition, image processing and analysis, computer graphics, machine learning and data mining. Sometimes applications include not only facial recognition but also facial expression characteristics identification and classification like blinking of the eyes, open/close mouth among others. This paper presents a comparative study of three algorithms for classification basic facial expressions.

Abstract
This paper presents the evaluation of computational mind model based on temperamental decision algorithms with emotional behaviors. Our computational model of emotion is inspired on appraisal theory and on superior nervous system characteristics. We define the model for temperamental agent with emotions. In this paper we prove that teams of the agents with different temperaments have different performances in the same simulation scenario. The result shows that strategies based on temperamental decision mechanism strongly influence system performance and there are evident dependencies between emotional states of agents and their temperamental type, as well as dependencies between the team performance and team configuration, and this enables us to conclude that modular approach to emotional programming based on temperamental theory is a good choice to develop computational mind models for emotional behavioral Multi-Agent systems.