Abstract
The creation of computer-based design tools to help teachers in designing learning scenarios, more precisely teaching-learning activities, has great importance in education. Those tools are most valuable if enriched with special features as, for example, templates, scripts or wizards used to guide the teacher through the design process. Recommendation mechanisms anchored in solid theoretical achievements are currently a huge challenge in the scientific research. This paper presents a proposal for teaching-learning techniques recommendation supported by an ontological modeling approach. The recommendation aims to assist educators in designing of teaching-learning activities. The recommendation process is part of the ACEM model which integrates an authoring design tool. We propose that the recommendation mechanism will help teachers preparing those activities and improving the use of different learning techniques.

Abstract
Interactive visualization of virtual environments is an active research topic. There is a multiplicity of applications such as simulation systems, augmented and mixed reality environments, computer games, amongst others, which endlessly demand for greater levels of realism and interaction. At every stage of the process, including modeling, image synthesis, transmission and navigation, there are identifiable circumstances which may compromise the achievement of high quality solutions for the posed problems. For many of these problems, an effective use of optimization tools can play a major role in order to achieve solutions with better quality. Within this context, an innovative optimization architecture is presented regarding to two major principles. The first principle comprises the possibility to integrate, with reduced effort, the optimization tools with existent applications and systems. Thus, we propose an agent-based framework where the optimization application may operate as an independent process in respect to the visualization application where communication is achieved by means of a specifically developed high-level message based protocol. The second principle establishes on the utilization of a class of intelligent optimization methods, known as metaheuristics, which major distinguishing quality is their great level of problem-independence, thus, enabling a wider application. The paper describes conducted experiments and presents results that demonstrate the utility and efficacy of the proposed framework.

Abstract
Poker is used to measure progresses in extensive-form games research due to its unique characteristics: it is a game where playing agents have to deal with incomplete information and stochastic scenarios and a large number of decision points. The development of Poker agents has seen significant advances in one-on-one matches but there are still no consistent results in multiplayer and in games against human experts. In order to allow for experts to aid the improvement of the agents' performance, we have created a high-level strategy specification language. To support strategy definition, we have also developed an intuitive graphical tool. Additionally, we have also created a strategy inferring system, based on a dynamically weighted Euclidean distance. This approach was validated through the creation of simple agents and by successfully inferring strategies from 10 human players. The created agents were able to beat previously developed mid-level agents by a good profit margin.

Abstract
In software development, coordination allows organizing the team by negotiating/assigning tasks to be performed by a certain order in order to meet the proposed objectives. Coordination is also responsible for managing conflicts associated with attitudes of competition, disorientation, problems of hierarchy and diffusion of responsibility. This work is based on the 4C model dimensions: Communication, Coordination, Cooperation and Collaboration. It is based on the analysis of the interactions between the multidisciplinary team members, that developed the educational resource Courseware Sere - "The Human Being and Natural Resources" concerning the "Coordination" dimension. The results achieved allowed us to detect limitations of Hybrid User Centered Development Methodology used for this courseware development as well as to implement tools to improve the coordination activities.

Abstract
Sports and physical activities allow people with disabilities to have better quality of life. The proposed work aimed to develop a multimodal interaction platform of robotic devices in a simulated environment for users to train different interface options. The suggested scenarios allow a user to interact with an Intelligent Wheelchair (IW) and with an Intelligent Robotic Ramp (IRR) performing different tasks individually or with a multiplayer option. The main objective of this multimodal interaction platform is to allow users, with severe disabilities, to move around and inclusive to play the Boccia Game more independently and autonomously. A preliminary set of experiments with 27 volunteers tested the scenarios and the multimodal interface for driving the intelligent wheelchair and to maneuver the IRR. The results show excellent performance when users maneuver the IRR in which the success achieved 90%. All dimensions of CEGEQ questionnaire presented good results. Therefore the solution created is quite satisfactory for a user point of view.

Abstract
Hand gesture recognition, being a natural way of human computer interaction, is an area of active research in computer vision and machine learning. This is an area with many different possible applications, giving users a simpler and more natural way to communicate with robots/systems interfaces, without the need for extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them to convey information or for device control. This work intends to study and implement a solution, generic enough, able to interpret user commands, composed of a set of dynamic and static gestures, and use those solutions to build an application able to work in a real-time human-computer interaction systems. The proposed solution is composed of two modules controlled by a FSM (Finite State Machine): a real time hand tracking and feature extraction system, supported by a SVM (Support Vector Machine) model for static hand posture classification and a set of HMMs (Hidden Markov Models) for dynamic single stroke hand gesture recognition. The experimental results showed that the system works very reliably, being able to recognize the set of defined commands in real-time. The SVM model for hand posture classification, trained with the selected hand features, achieved an accuracy of 99,2%. The proposed solution as the advantage of being computationally simple to train and use, and at the same time generic enough, allowing its application in any robot/system command interface.