Abstract
In this paper is presented the work relative to the design of an aid system, for athletes with special needs in terms of vision. The system is based on Radio Frequency Identification (RFID) technology and serves to help visually impaired athletes. Relatively to Paralympic athletics competitions, the main goal is the elimination of current guide runners. The system is prepared to give a stereo audio alert, when a runner deviates from his lane central area. The paper presents the main components, namely, the RFID infrastructure and the mobile parts. Tests to tags, infrastructure setting and positioning functions are also presented. (C) 2014 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND License (http://creativecommons.org/licenses/by-nc-nd/3.0/).

Abstract
The very nature of universities makes them unique environments for research and teaching. Although both activities constantly borrow from each other, a deeper level of interaction is not always achieved for several reasons. This paper presents a successful experience on conducting an undergraduate course on embedded systems, based on strong interaction with related research activities previously conducted by the authors. Known for being everywhere, embedded systems are constantly expanding in both complexity and volume production. In addition, heterogeneous systems are becoming prevalent in modern applications, standing as an additional difficulty to students in this area. In this context, this paper presents experiences in teaching embedded systems using a project-based learning pedagogical approach, with strong emphasis on mobile robotic applications previously developed by MSc and PhD students. As a result, it has been observed that undergraduate students have the opportunity to build a strong background and feel better prepared to face the challenges to be found in their future professional activities. © 2014 Vanderlei Bonato et al.

Abstract
This paper focuses on process visualization that is applicable to managing a Virtual Factory (VF) business environment. It briefly provides all aspects of implementing the dashboard user interface that is to be used by the VF partners. The dashboard features state-of-The art business intelligence and provides data visualization, user interfaces and menus to support VF partners to execute collaborative processes. With advanced visualizations that produce quality graphics it offers a variety of information visualizations that brings the process data to life with clarity. This data visualization provides critical operational matrices (e.g. KPIs) required to manage virtual factories. Various technical aspects of this dashboard user interface portal are elaborated within the scope of this research such as installation instructions, technical requirements for the users and developers, execution and usage aspects, limitations and future works. The dashboard user interface portal presents different widgets according to the VF requirements that are to be needed to support the visualization and monitoring of various business processes within a VF. The research work highlighted in this paper is conceptualized, developed and validated within the scope of the European Commission NMP priority of the Seventh RTD Framework Programme for the ADVENTURE (ADaptive Virtual ENterprise ManufacTURing Environment) project. Copyright © 2014 SCITEPRESS - Science and Technology Publications.

Abstract
Stepwise refinement of algebraic specifications is a well known formal methodology for program development. However, traditional notions of refinement based on signature morphisms are often too rigid to capture a number of relevant transformations in the context,at of software design, reuse, and adaptation. This paper proposes a new approach to refinement in which signature morphisms are replaced by logical interpretations as a means to witness refinements. The approach is first presented in the context of equational logic, and later generalised to deductive systems of arbitrary dimension. This allows, for example, relining sentential into equational specifications and the latter into modal ones.

Abstract
Many applications of Fuzzy Power Flow have been proposed not only for operational purposes considering uncertainties, but also for planning exercises with high level of intermittent sources, interconnection presence and, more recently, electric vehicles load. However, their use in real systems is not usual, mainly where the uncertainty level can be significant. This is due to the low accuracy of the results related to the classical methods, and the computational burden needed to achieve a high level of accuracy in the symmetric approaches. This paper aims to present a linearization of the Symmetric Fuzzy Power Flow in order to reduce the computational effort and make it possible for it to achieve high levels of accuracy when applied to real systems. With the purposes of demonstrating the applicability of the proposed approach, several IEEE test systems and a planning configuration of the Portuguese Transmission System will be studied.

Abstract
Hand gesture recognition for human computer interaction, 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. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. In this study we try to identify hand features that, isolated, respond better in various situations in human-computer interaction. The extracted features are used to train a set of classifiers with the help of RapidMiner in order to find the best learner. A dataset with our own gesture vocabulary consisted of 10 gestures, recorded from 20 users was created for later processing. Experimental results show that the radial signature and the centroid distance are the features that when used separately obtain better results, with an accuracy of 91 % and 90,1 % respectively obtained with a Neural Network classifier. These to methods have also the advantage of being simple in terms of computational complexity, which make them good candidates for real-time hand gesture recognition.