Abstract
Informed driving is increasingly becoming a key feature for increasing the sustainability of taxi companies. The sensors that are installed in each vehicle are providing new opportunities for automatically discovering knowledge, which, in return, delivers information for real-time decision making. Intelligent transportation systems for taxi dispatching and for finding time-saving routes are already exploring these sensing data. This paper introduces a novel methodology for predicting the spatial distribution of taxi-passengers for a short-term time horizon using streaming data. First, the information was aggregated into a histogram time series. Then, three time-series forecasting techniques were combined to originate a prediction. Experimental tests were conducted using the online data that are transmitted by 441 vehicles of a fleet running in the city of Porto, Portugal. The results demonstrated that the proposed framework can provide effective insight into the spatiotemporal distribution of taxi-passenger demand for a 30-min horizon.

Abstract
The MARES is a small, torpedo-shaped AUV 1.5 meters long and 32 kilograms in weight in the basic version. In a typical configuration, a PC/104 computational system manages the entire mission, including communications with other devices and a control station. Navigation is provided by the fusion of data from an inertial measurement unit (IMU) and an acoustic system for long baseline localization (LBL), complemented by a small GPS receiver, when the vehicle is at the surface. Four thrusters provide the capability to move as fast as 5 knots and to hover in the water column, with a set of lithium-ion batteries ensuring 10 hours of operation. MARES is a highly modular vehicle, with the ability to integrate a great variety of payload sensors, and it has been operating since 2007, mainly in environmental- monitoring missions. The capability of vehicles to follow a given trajectory and maintain reliable data exchange is among the most relevant topics when it comes to coordination of marine robots.

Abstract
Acoustic emission monitoring is often used in the diagnosis of electrical and mechanical incipient faults in the high voltage apparatus. Partial discharges are a major source of insulation failure in electric power transformers, and the differentiation from other sources of acoustic emission is of the utmost importance. This paper reports the development of a new sensor concept - a fiber laser sensor based on a phase-shifted chirped fiber grating - for the acoustic emission detection of incipient faults in oil-filled power transformers. These sensors can be placed in the inner surface of the transformer tank wall, not affecting the insulation integrity of the structure and improving fault detection and location. The performance of the sensing head is characterized and compared for different surrounding media: air, water, and oil. The results obtained indicate the feasibility of this sensing approach for the industrial development of practical solutions. © 2012 The Author(s).

Abstract
We present work in progress on the development of EasyBV, a specialized theorem prover for fixed-size bit-vector arithmetic. © 2013 Authors.

Abstract
Taking in account the conclusions of our previous case-study in the civil engineering course at UTAD (University of Tras-os-Montes e Alto Douro, Vila Real, Portugal) this work presents the results of a case study in an energy engineering undergraduate course. Based on the quantitative and qualitative analysis of collected data, it examines students.' attitudes towards web-based peer assessment, distinguishing their role as reviewers or as feedback receivers. It identifies which factors are related to students.' use and appreciation of feedback. Moreover, an analysis of the type of feedback is presented in an attempt to evaluate students.' written communication skills. The results of this study allow deepening the reflexion on how to improve the design and implementation of future web-based peer assessment tasks.

Abstract
The Robotic Darwinian Particle Swarm Optimization (RDPSO) recently introduced in the literature has the ability to dynamically partition the whole population of robots based on simple "punish-reward" rules. Although this evolutionary algorithm enables the reduction of the amount of required information exchange among robots, a further analysis on the communication complexity of the RDPSO needs to be carried out so as to evaluate its scalability. This paper analyses the architecture of the RDPSO communication system, thus describing the dynamics of the communication data packet structure shared between teammates. Moreover, a set of simple communication rules is also proposed in order to reduce the communication overhead within swarms of robots. Experimental results with teams of 15 real robots show that the proposed methodology reduces the communication overhead, thus improving the scalability and applicability of the RDPSO algorithm.