Abstract
An experimental setup has been developed for different gas species sensing based on the Wavelength Modulation Spectroscopy (WMS) principle. The target is the measurement of ammonia, carbon dioxide and methane concentrations. The WMS is a rather sensitive technique for detecting atomic/molecular species presenting the advantage that it can be used in the near-infrared region using optical telecommunications technology. In this technique, the laser wavelength and intensity are modulated applying a sine wave signal through the injection current, which allows the shift of the detection bandwidth to higher frequencies where laser intensity noise is reduced. The wavelength modulated laser light is tuned to the absorption line of the target gas and the absorption information can be retrieved by means of synchronous detection using a lock-in amplifier, where the amplitude of the second harmonic of the laser modulation frequency is proportional to the gas concentration. The amplitude of the second harmonic is normalised by the average laser intensity and detector gain through a LabVIEW (R) application, where the main advantage of normalising is that the effects of laser output power fluctuations and any variations in laser transmission, or optical-electrical detector gain are eliminated. Two types of sensing heads based on free space light propagation with different optical path length were used, permitting redundancy operation and technology validation.

Abstract
A common migration path for applications to high-performance multicore architectures relies on code annotations with concurrent semantics. Some annotations, however, are very target architecture specific and thus highly non-portable. In this paper we describe a source-to-source code transformation system that allows programmers to specify transformations using an aspect-oriented domain specific language - LARA. LARA allows programmers to specify strategies to search large code transformation design spaces while preserving the original source code. As the experimental results reveal, this approach leads to a substantial reduction in code maintenance costs, and promotes the portability of both programmers and performance. Copyright © 2014 ACM.

Abstract
In this paper it is presented an all-fiber implementation of the hot-wire needle probe concept, widely used to measure the thermal properties of materials, particularly the thermal conductivity. It is based on the heating of a metal thin film deposited on the surface of the fiber induced by the coupling of laser light into the cladding via a long period grating, and determination, using a fiber Bragg grating, of the time dependence of the temperature of the surrounding medium at a fixed distance of the fiber. The medium considered in this research was the air and the results obtained indicate the feasibility of this approach and point out future developments.

Abstract
Hand gesture recognition, 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. This work intends to study and implement a solution, generic enough, able to interpret user commands, composed of a set of dynamic and static gestures, and use those solutions to build an application able to work in a real-time human-computer interaction systems. The proposed solution is composed of two modules controlled by a FSM (Finite State Machine): a real time hand tracking and feature extraction system, supported by a SVM (Support Vector Machine) model for static hand posture classification and a set of HMMs (Hidden Markov Models) for dynamic single stroke hand gesture recognition. The experimental results showed that the system works very reliably, being able to recognize the set of defined commands in real-time. The SVM model for hand posture classification, trained with the selected hand features, achieved an accuracy of 99,2%. The proposed solution as the advantage of being computationally simple to train and use, and at the same time generic enough, allowing its application in any robot/system command interface.

Abstract
A process of risk management in projects is a rational chain of practices by which decision-agents plan and execute actions and control the results in order to keep the implementation of the project under certain conditions (time, cost and quality parameters' set). With the purpose of providing guidelines for the selection of the best practices taking into account the organizational maturity and project complexity, a theoretical framework to classify and associate those practices to each phase of the project life cycle and to each project risk management process is proposed. Future research efforts will be directed towards refining the framework and testing it in multiple case studies. (C) 2014 The Authors. Published by Elsevier Ltd.

Abstract
In most real multi-robot applications, such as search-and-rescue, cooperative robots have to move to complete their tasks while maintaining communication among themselves without the aid of a communication infrastructure. However, initially deploying and ensuring a mobile ad-hoc network in real and complex environments is an arduous task since the strength of the connection between two nodes (i.e., robots) can change rapidly in time or even disappear. An extension of the Particle Swarm Optimization to multi-robot applications has been previously proposed and denoted as Robotic Darwinian PSO (RDPSO). This paper contributes with a further extension of the RDPSO, thus integrating two research aspects: (i) an autonomous, realistic and fault-tolerant initial deployment strategy denoted as Extended Spiral of Theodorus (EST); and (ii) a fault-tolerant distributed search to prevent communication network splits. The exploring agents, denoted as scouts, are autonomously deployed using supporting agents, denoted as rangers. Experimental results with 15 physical scouts and 3 physical rangers show that the algorithm converges to the optimal solution faster and more accurately using the EST approach over the random deployment strategy. Also, a more fault-tolerant strategy clearly influences the time needed to converge to the final solution, but is less susceptible to robot failures.