Abstract
This PhD work has the goal to develop an inexpensive, easily deployable and widely compatible localization system for indoor use, suitable for pre-installed public address sound systems, avoiding costly installations or significant architectural changes in spaces. Using the audible sound range will allow the use of low cost off-the-shelf equipment suitable for keeping a low deployment cost. The state-of-the-art presented in this paper evidences a technological void in low-cost, reliable and precise localization systems and technologies. This necessity was also confirmed by the authors in a previous project (NAVMETRO (R)) where no suitable technological solution was found to exist to overcome the need to automatically localize people in a public space in a reliable and precise way. Although research work is in its first steps, it already provides a thorough view on the problem while discussing some possible approaches and predicting strategies to overcome the key difficulties. Some experiments were already conducted validating some initial premises and demonstrating how to measure the signal's time-of-flight necessary to infer on distance calculations.

Abstract
Phase-sensitive optical time domain reflectometry (phi OTDR) is a simple and effective tool that allows the distributed monitoring of vibrations along single-mode fibers. In this letter we study the effects of modulation instability (MI) in long-range phi OTDR over conventional optical fibers. We demonstrate both theoretically and experimentally that MI can induce a position-dependent signal fading which leads to a nearly complete visibility loss in the interference signal recorded at certain positions and therefore to a sensitivity loss at these positions. While this effect is detrimental in the context of distributed vibration analysis using phi OTDR, we also believe that the technique provides a clear and insightful way to evidence the Fermi-Pasta-Ulam (FPU) recurrence associated to the MI process.

Abstract
Scand J Caring Sci; 2013; 27; 468474 Evaluation and cross-cultural adaptation of the Hendrich II Fall Risk Model to Portuguese Background: Several tools for the assessment of the risk of falling are used commonly by clinical nurses, but none have been validated in Portuguese. Aims: To adapt and evaluate the Hendrich II Fall Risk Model (HIIFRM) for use with elderly Portuguese inpatients. Method: We conducted a prospective study of 586 older inpatients in acute care hospitals, from November 2007 to May 2010. Results: The study involved 270 men and 316 women. The most frequent risk factor on admission and at discharge was a score 3 on the Get Up and Go' test. The adapted HIIFRM showed a sensitivity of 93.2% and 75.7%, and a specificity of 35% and 46.7%, on admission and at discharge, respectively. A positive predictive value of 17.2% on admission and 17% at discharge and a negative predictive value of 97.3% and 93%, respectively, were estimated. Conclusions: The HIIFRM was shown to be a useful tool in predicting falls by patients. Nevertheless, the research model suggested that only four risk factors affected the occurrence of falls significantly on admission and two risk factors at discharge. Further research is required in Portuguese hospital settings.

Abstract
The recent development of electric vehicles (EVs) has brought a new set of problems regarding their integration in power networks, particularly in terms of the potential growth of peak load. The peak growth leads to the increase of losses and braches charging and to voltage drops. Conversely, optimizing EV charging policy creates new opportunities for both network safety and energy trading through the markets. This paper presents a multi-level framework combining two representations of a medium voltage (MV) network in order to optimize the EV charging policy. A minimizing cost approach is set, modeling day-ahead markets, and taking into account losses. The proposed methodology is tested on a typical MV network.

Abstract
This paper presents a novel localization method for small mobile robots. The proposed technique is especially designed for the Robot@Factory which is a new robotic competition presented in Lisbon 2011. The real-time localization technique resorts to low-cost infra-red sensors, a map-matching method and an Extended Kalman Filter (EKF) to create a pose tracking system that is well-behaved. The sensor information is continuously updated in time and space through the expected motion of the robot. Then, the information is incorporated into the map-matching optimization in order to increase the amount of sensor information that is available at each moment. In addition, a particle filter based on Particle Swarm Optimization (PSO) relocates the robot when the map-matching error is high. Meaning that the map-matching is unreliable and robot is lost. The experiments conducted in this paper prove the ability and accuracy of the presented technique to localize small mobile robots for this competition. Therefore, extensive results show that the proposed method have an interesting localization capability for robots equipped with a limited amount of sensors.

Abstract
A relevant research topic in optimization of power distribution networks is to find the best relationship between system reliability and the allocation of maintenance resources. This paper presents a mathematical formulation that seeks the optimal preventive maintenance budget regarding the system reliability constraints. A dynamic programming approach is proposed to deal with this optimization problem. Some reductions are applied to the dynamic programming approach in order to avoid the combinatorial explosion. Case studies are presented to compare the performance of the dynamic programming approach with a hybrid genetic algorithm previously developed. © 2013 IEEE.