Abstract
In order to assess the atherosclerotic plaque disruption risk from B-mode ultrasound images of the carotid, an appropriate normalization of the plaque regions is required. This is usually achieved through the manual selection of two sample regions in the image containing blood and adventitia tissues, which are used as reference. In this work, we propose a new plaque region normalization method that takes advantage of multiple blood and adventitia reference samples per image, and a method for the automatic selection of these reference samples. Several preliminary results are provided in order to demonstrate the possible capabilities of the proposed methods.

Abstract
Emerging trends in electric vehicles both in science and industry, as well as increasing popularity of these devices among end-users have laid serious issues in front of a system operator or planner. Higher deployment of available resources in the system will lead to higher flexibility for system operator in its interactions, besides to higher level of user satisfaction. In this study, various states of a 13 bus radial distribution network have been considered for allocation of Plug-in Electric Vehicles' (PEVs') parking lots. As Renewable Energy Resources (RERs) are becoming a main element of power systems, it is investigated how the future distribution network planning has to be organized by employing both RERs and PEV parking lots. Also, it is investigated how the allocation of parking lots varies in the system where these resources exist. Moreover, the costs and revenues obtained by the system operator in such systems are also studied.

Abstract
We describe our experience using magic card tricks to teach algorithmic skills to first-year Computer Science undergraduates. We illustrate our approach with a detailed discussion on a card trick that is typically presented as a test to the psychic abilities of an audience. We use the trick to discuss concepts like problem decomposition, pre- and post-conditions, and invariants. We discuss pedagogical issues and analyse feedback collected from students. The feedback has been very positive and encouraging. © 2014 ACM.

Abstract
The main aim of this research is the development of an autonomous adaptive system for actuation, data acquisition and control of activeankle-foot orthosis. In this paper the design ofa control unit composed by microcontroller, driver and sensor system, and its application to theactuation and position of the foot orthotic segment is presented. The research work combines hardware and software design of the intelligent control device with graphical interface for representation and analysis of the data acquired duringhuman motion. The dynamic system simulation is done in Matlab Simulink and SimMechanics. A laboratory model of the proposed system was implemented to demonstrate its autonomy and verify experimentally its functionality.The proposed control device can be used in several applications involving human motion analysis and control of different types of orthoses or functional electrical stimulation used for gait correction. © Springer Science+Business Media Dordrecht 2014.

Abstract
Discovery of communities in complex networks is a fundamental data analysis problem with applications in various domains. While most of the existing approaches have focused on discovering communities of nodes, recent studies have shown the advantages and uses of link community discovery in networks. Generative models provide a promising class of techniques for the identification of modular structures in networks, but most generative models mainly focus on the detection of node communities rather than link communities. In this work, we propose a generative model, which is based on the importance of each node when forming links in each community, to describe the structure of link communities. We proceed to fit the model parameters by taking it as an optimization problem, and solve it using nonnegative matrix factorization. Thereafter, in order to automatically determine the number of communities, we extend the above method by introducing a strategy of iterative bipartition. This extended method not only finds the number of communities all by itself, but also obtains high efficiency, and thus it is more suitable to deal with large and unexplored real networks. We test this approach on both synthetic benchmarks and real-world networks including an application on a large biological network, and compare it with two highly related methods. Results demonstrate the superior performance of our approach over competing methods for the detection of link communities.

Abstract
This paper presents the first phase of the redevelopment of the Electric Vehicle Scenario Simulator (EVeSSi) tool. A new methodology to generate traffic demand scenarios for the Simulation of Urban MObility (SUMO) tool for urban traffic simulation is described. This methodology is based on a Portugal census database to generate a synthetic population for a given area under study. A realistic case study of a Portuguese city, Vila Real, is assessed. For this area the road network was created along with a synthetic population and public transport. The traffic results were obtained and an electric buses fleet was evaluated assuming that the actual fleet would be replaced in a near future. The energy requirements to charge the electric fleet overnight were estimated in order to evaluate the impacts that it would cause in the local electricity network.