Abstract
Certain professions rely on the ability to maintain attention constant throughout long periods of time, like truck drivers, air traffic controllers, health professionals, among others. These could greatly benefit from the development of a real-time alerting system that will call subjects back to task even before lapses occur or shortly after they happened. Attention levels have been shown to relate to the properties of the electroencephalogram (EEG). In this paper, we propose for the first time a regression approach to detect fluctuating levels of attention, based on spatiotemporal patterns extracted from EEG recordings. Previous studies have shown that reaction time is related to the level of task related attention. Moment-to-moment fluctuations in attention level are paralleled by moment-tomoment fluctuations in reaction time (faster reaction times are related to high attention allocation). We took advantage of this parallel and used reaction time data obtained during a repetitive visuomotor task as a proxy for task related attention level. Furthermore, instead of defining high attention versus low attention periods, we labeled each moment according to a continuum based on each trial's reaction time. In order to determine if it is possible to predict attention level from EEG features, we developed regression models between the extracted features and the subject's reaction time.

Abstract
Nowadays, the technological and scientific research related to underwater perception is focused in developing more cost-effective tools to support activities related with the inspection, search and rescue of wreckages and site exploration: devices with higher autonomy, endurance and capabilities. Currently, specific tasks are already carried out by remotely-operated vehicles (ROV) and autonomous underwater vehicles (AUV) that can be equipped with multiple sensors, including optical cameras which are extremely valuable for perceiving marine environments; however, the current perceptual capability of these vehicles is still limited. In this context, the paper presents a novel mosaicking method that composes the sea-floor from a set of visual observations. This method is called RObust and Large-scale MOSaicking (ROLAMOS) and it enables an efficient frame-to-frame motion estimation with outliers removal and consistence checking, a robust registration of monocular images and, finally, a mosaic management methodology that makes it possible to map large visual areas with a high resolution. The experiments conducted with realistic images have proven that the ROLAMOS is suitable for mapping large-scale sea-floor scenarios because the visual information is registered by managing the computational resources that are available onboard, which makes it appropriate for applications that do not have specialized computers. Further, this is a major advantage for automatic mosaic creation based on robotic applications, that require the location of objects or even structures with high detail and precision.

Abstract

Abstract
Particle filters are sequential Monte Carlo estimation methods with applications in the field of mobile robotics for performing tasks such as tracking, simultaneous localization and mapping (SLAM) and navigation, by dealing with the uncertainties and/or noise generated by the sensors as well as with the intrinsic uncertainties of the environment. This work presents a field programmable gate arrays (FPGA) implementation of a particle filter applied to SLAM problem based on a low cost Neato XV-11 laser scanner sensor. Post processing is performed on data provided by a realistic simulation of a differential robot, equipped with a hacked Neato XV-11 laser scanner, that navigates in the Robot@Factory competition maze. The robot was simulated using SimTwo, which is a realistic simulation software that can support several types of robots. The simulator provides the robot ground truth, odometry and the laser scanner data. The results achieved from this study confirmed the possible use such low cost laser scanner for different robotics applications.

Abstract
Private individual transportation is becoming cumbersome and expensive, as urban traffic turns more chaotic, fuel prices increase and the effects of pollutant emissions become evident. Public buses are an attractive approach to reducing the cars in use, as they mostly depend on preexistent infrastructure. Making these buses electric would mean even less tailpipe emissions and cheaper consumption costs, when compared to conventional vehicle fleets. However, fully electric bus fleets can prove disadvantageous. We can tackle this with a more conservative approach - using mixed bus fleets, comprised by both electric and conventional buses. This work intends on studying how to obtain a good balance of the different vehicle typologies in the fleet. To fulfill these goals, real data of a bus network in Porto, Portugal, is studied and an evolutionary algorithm devises mixed fleet arrangements, with a brief sensitivity analysis giving us an overview of how to improve our results. As a means of decision support, this work contributes not only with an approach to configure optimized mixed bus fleets, but also with general considerations for managing public transit with electric vehicle fleets.

Abstract
Online gambling has skyrocketed in recent years. As such, knowing the determinants of consumer usage behavior is crucial in understanding online gambling services. This study has as main objective the construction of an explanatory model of the online gambling services usage behavior, based on the incorporation of perceived risk in the conceptual framework of the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). The empirical validation of the model was performed by conducting an online survey to a convenience sample of 212 Portuguese online players. Data were processed using the PLS-SEM methodology. The results evidence that performance expectancy, social influence, facilitating conditions, hedonic motivations, price value, habits, as well as perceived risk influence the intention to use online gambling services.