Abstract
This article is concerned with the design of an energy management system (EMS) for the hybridization of multiple energy sources (ES's) in electric vehicles, focusing in a particular configuration composed by batteries and supercapacitors (SCs). As a first design step, we investigated an (non-causal) optimal power allocation, targeting the minimization of the energy losses over a complete driving cycle. Albeit the solution obtained with this formulation demands the advance knowledge of the vehicle driving cycle, it also provides a useful benchmark solution to assess the performance of causal EMS's. A more practical EMS is then derived, based on the control allocation (CA) concept. This approach, typically employed in redundant control systems, enable us to address the various objectives and constraints that appear in EMS design problem, such as the DC bus voltage regulation, SC state of charge tracking, minimization of power losses, current and state of charge limits, etc. Simulation results show the effectiveness of the proposed CA based EMS, yielding performances very close to the optimal non-causal power allocation. © 2011 IEEE.

Abstract
In recent years there has been a growing interest by the sport's experts (teachers and coaches) in developing automatic systems for detecting, tracking and identifying player's movements with the purpose of improving the players' performance and accomplishing a consistent and standard analysis of the game metrics. A challenge like this requires sophisticated techniques from the areas of image processing and artificial intelligence. The objective of our work is to study and develop hardware and software techniques in order to build an automatic visual system for detecting and tracking players in indoor sports games that can aid coaches to analyse and improve the players' perfoiniance. Our methodology is based on colour features and therefore several colour image processing techniques such as background subtraction, blob colour definition (RGB and HSL colour spaces) and colour blob manipulation are employed in order to detect the players. Past information and players' velocity allow the tracking algorithm to define probable areas. Tests conducted with a single IP surveillance camera on the sports hall of the Faculty of Sports from the University of Porto showed detection rates from 72.2% to 93.3%.

Abstract

Abstract
Traditionally, recommender systems for the web deal with applications that have two dimensions, users and items. Based on access data that relate these dimensions, a recommendation model can be built and used to identify a set of N items that will be of interest to a certain user. In this paper we propose a multidimensional approach, called DaVI (Dimensions as Virtual Items), that enables the use of common two-dimensional top-N recommender algorithms for the generation of recommendations using additional dimensions (e.g., contextual or background information). We empirically evaluate our approach with two different top-N recommender algorithms, Item-based Collaborative Filtering and Association Rules based, on two real world data sets. The empirical results demonstrate that DaVI enables the application of existing two-dimensional recommendation algorithms to exploit the useful information in multidimensional data. © 2011 IEEE.

Abstract
The scope of this work is to find the best approach to control advanced inverters used to connect electric vehicles to the grid. Phase-locked Loop (PLL) is a grid voltage phase detection that makes use of an orthogonal voltage to lock the grid phase. This method is suitable for both single and three phase systems, although in single-phase, because they have less information, more advanced systems are required. The easiest way to obtain the orthogonal voltage system is using a transport delay block to introduce a phase shift of 90 degrees with respect to the fundamental frequency of the grid voltage. This method is known as Synchronous Reference Frame PLL (SRF-PLL). The use of inverse Park transformation is also possible. To lower the complexity and increasing the filtering of the output signals, methods using adaptive filters are a good alternative. For this approach, the use of a second order generalized integrator (SOGI) or Adaptive Notch filter combined with PLL, Enhanced PLL (EPLL) and Quadrature PLL (QPLL), leads to satisfactory results. © 2011 INESC Coimbra.

Abstract
This work describes a fiber optic sensing structure that is sensitive to curvature, and features a low temperature-and strain cross-sensitivity. It is based on multimode interference, and relies on a singlemode-step index multimode-singlemode fiber structure. It was observed that the transmitted optical power in such a layout is highly sensitive to the wavelength of operation, and to the length of the multimode fiber. The optical spectrum exhibits two dominant loss bands, at wavelengths that have similar responses both to temperature and strain, but different responses to curvature. Based on this result, an interrogation approach is proposed that permits substantial sensitivity to curvature (8.7 +/- 0.1 nm m) and residual sensitivities to temperature and strain (0.3 +/- 0.1 pm degrees C(-1) and (-0.06 +/- 0.01) x 10(-6) m m(-1), respectively). The beam-propagation method was employed for modeling the propagation of light along the optical fiber sensing device proposed.