Abstract
Optimization in current decision support systems has a highly interdisciplinary nature related with the need to integrate different techniques and paradigms for solving real-world complex problems. Computing optimal solutions in many of these problems are unmanageable. Heuristic search methods are known to obtain good results in an acceptable time interval. However, parameters need to be adjusted to allow good results. In this sense, learning strategies can enhance the performance of a system, providing it with the ability to learn, for instance, the most suitable optimization technique for solving a particular class of problems, or the most suitable parameterization of a given algorithm on a given scenario. Hyper-heuristics arise in this context as efficient methodologies for selecting or generating (meta) heuristics to solve NP-hard optimization problems. This paper presents the specification of a hyper-heuristic for selecting techniques inspired in nature, for solving the problem of scheduling in manufacturing systems, based on previous experience. The proposed hyper-heuristic module uses a reinforcement learning algorithm, which enables the system with the ability to autonomously select the meta-heuristic to use in optimization process as well as the respective parameters. A computational study was carried out to evaluate the influence of the hyper-heuristics on the performance of a scheduling system. The obtained results allow to conclude about the effectiveness of the proposed approach.

Abstract

Abstract
Robotics constitutes a multidisciplinary area, congregating knowledge from different scientific domains. The learning of robotic systems requires the acquisition of multidisciplinary scientific bases, and high integration and synthesis abilities, which is not an easy task. This paper describes the implementation of a lifelong course that aims to provide a global insight on robotics field, introducing the concepts and technologies for different domain applications, namely industrial robotics, autonomous mobile robotics and robotics applied in medicine. This is accomplished in an international framework where individual knowledge and experiences will be confronted in a multidisciplinary level and intercultural environment.

Abstract
With this study we intent to better understand how a group with intellectual disabilities interacts with digital content, namely web content, when performing equivalent tasks from their daily school activities, such as: painting, making puzzles, playing games. To accomplish this we observed how a group with intellectual disabilities, without experience using computers, performed universal tasks (selection, manipulation and navigation) when presented with different activities on the Web such as painting, playing games or searching. We aimed at evaluating usability and accessibility and for this we registered the following variables: successful conclusion of activities, type of difficulties found, errors, satisfaction, motivation and autonomy indicators. Participants showed motivation and learning skills when performing all the three universal tasks (selection, manipulation and navigation) which is confirmed by the number of participants that was able to conclude the activities. Concerning errors, it was observed that despite the large number of errors made by the participants, their motivation lead them to complete the tasks. When handling the input devices the participants had a good performance using the computer mouse. On the other hand, they could not use the keyboard alone because of their reading/ writing difficulties. © 2015 ACM.

Abstract
The communication with deaf by means of written text is not as efficient as it might seem. In fact, there is a very deep gap between sign language and spoken/written language. The deployment of tools to assist the daily communication between deaf people and the rest may be a significant contribution to the social inclusion of the deaf community. The work described in this paper addresses the development of a bidirectional translator between Portuguese Sign Language and Portuguese text and a serious game to promote the learning of the Portuguese Sign Language. The translator from sign language to text employs two devices, namely the Microsoft Kinect and 5DT Sensor Gloves in order to gather data about the motion and shape of the hands. The hands configurations are classified using Support Vector Machines. The classification of the movement and orientation of the hands is achieved through the use of Dynamic Time Warping algorithm. The translator exhibits a precision higher than 90%. In the other direction, the translation of Portuguese text to Portuguese Sign Language is supported by a 3D avatar which interprets the entered text and performs the corresponding animations. As a complement, we also present a serious game directed to assist in the difficult task of learning the Portuguese Sign Language.

Abstract