Abstract
This paper addresses the development of a new generation of lightweight intelligent buoys. These buoys are used to support underwater acoustic positioning systems, but were also designed to be elements of portable coastal observatories for short term deployments. We will present the main features of a buoy prototype including the physical structure, the computational system and algorithms developed to support operations. The paper also shows how to take advantage of this new tool to implement different navigation algorithms for AUVs.

Abstract
The last few years have seen great interest in developing models that can describe real-life large-scale structured systems. A popular approach is to address these problems by using logic to describe the patterns or structure of the problems, and by using a calculus of probabilities to address the uncertainty so often found in real life situations. The CLP(BN) language is an extension of Prolog that allows the representation, inference, and learning of bayesian networks. The language was inspired on Koller's Probabilistic Relational Models, and is close to other probabilistic relational languages based in Prolog, such as Sato's PRISM. We present the implementation of CLP(BN), showing how bayesian networks are represented in CLP(BN) and presenting the implementation of three different inference algorithms: Gibbs Sampling, Variable Elimination, and Junction Trees. We show that these algorithms can be implemented effectively by using a matrix library and a graph manipulation library, and study how the system performs on real-life applications.

Abstract
This paper addresses issues concerning the integration of single-phase charging devices for electric vehicles (EV) in low-voltage microgrids Fast release energy storage is a key issue for microgrid islanding operation. EV batteries provide an additional storage capacity, which can now be exploited in order to improve MG islanding Aiming to do so, different control strategies were developed and tested (1) a local control approach where no communication link is required and (2) a centralized charging control solution The local control approach is based on the measuring of EV terminal voltage and frequency in order to define the charging or discharging rates of the batteries The centralized control strategy allows balancing single-phase loads connected to the microgrid by adapting the charging rates of the EV storage devices. Simulation results show that EV batteries can actively contribute for voltage balancing and frequency control during islanding operating conditions

Abstract
Inter-camera registration in multi-view systems with overlapped views has a particularly long and sophisticated research history within the computer vision community. Moreover, when applied to Distributed Video Coding, in systems with at least one moving camera it represents a real challenge due to the necessary data at decoder for generating the side information without any a priori knowledge of each instant camera position. This paper proposes a solution to this problem based on successive multi-view registration and motion compensated extrapolation for on-the-fly re-correlation of two views at decoder. This novel technique for side information generation is codec-independent, robust and flexible with regard to any free motion of the cameras. Furthermore, it doesn't require any additional information from encoders nor communication between cameras or offline training stage. We also propose a metric for an objective assessment of the multi-view correlation performance.

Abstract
This paper is on wind energy conversion systems with full-power converter and permanent magnet synchronous generator. Different topologies for the power-electronic converters are considered, namely two-level and multilevel converters. Also, a new fractional-order control strategy is proposed for the variable-speed operation of the wind turbines. Simulation studies are carried out in order to adequately assess the quality of the energy injected into the electrical grid. Conclusions are duly drawn.

Abstract
The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. In this paper, a neuro-fuzzy approach is proposed for short-term wind power forecasting in Portugal. Results from a real-world case study are presented. A thorough comparison is carried out, taking into account the results obtained with other approaches. Conclusions are duly drawn.