Abstract
The use of unmanned vehicle networks for diverse applications is becoming widespread. It is generally hard to program unmanned vehicle networks as a "whole", however. The coordination of multiple vehicles requires careful planning through intricate human intervention, and a high degree of informality is implied in what concerns the specification of a "network program" for an application scenario. In this context, we have been developing a programming language for expressing global specifications of coordinated behavior in unmanned vehicle networks, the Networked Vehicles' Language (NVL). In this paper we illustrate the use of the language for a thermal pollution plume tracking scenario employing unmanned underwater vehicles.

Abstract
O presente artigo tem como objeto os resultados dum estudo que teve por objetivo a investigação do uso dos sistemas e tecnologias de informação (STI) no turismo em espaço rural (TER) na região do Algarve. Os resultados foram obtidos através de um questionário eletrónico, direcionado a proprietários e/ou gestores de 51 unidades TER, no qual se procurou identificar o impacto dos STI nas variáveis: tomada de decisão; satisfação dos gestores quanto ao uso dos STI; qualidade do serviço de reservas de quarto; e resultados financeiros. O estudo permitiu concluir que, de uma forma geral, a utilização dos STI são uma componente importante na gestão das unidades TER e têm impactos positivos na identificação de problemas e minimização do seu tempo de resolução; na confiança depositada no sistema e linguagem utilizada no computador; na qualidade das reservas de quartos; e nos resultados financeiros por via da inovação em tecnologia e existência de rede na organização.;This article aims to present the results of a study that investigated the use of information systems and technologies (IST) in tourism in rural space (TRS) in the Algarve region. The results were obtained through an electronic questionnaire given to the owners and/or managers of fifty one units TRS, in which we tried to identify the impact of IST in the following variables: decision making, satisfaction of managers in the use of IST, quality of room reservations service, and financial results. The study concluded that, in general, the use of IST are an important component in the TRS units of management and have positive impacts in identifying problems and minimizing their time resolution, confidence in the system and language used in the computer, the quality of rooms reservations, and financial results through innovation in technology, and network existence in the organization.

Abstract
Distributed Generation (DG) is providing end consumers the possibility to satisfy part of their electricity consumption by using their own small-scale power generators. To regulate DG, new regulation schemes are needed, being net metering one of the most used. However, regulators appreciate that net metering could jeopardize the incomes to cover the regulated activities' cost. This paper proposes a mathematical bi-level model to obtain the evolution of the access tariffs and their corresponding incomes needed to cover the regulated costs, as well as the optimal DG investment of the consumers under a net metering regulation, in a simplified framework. © 2015 IEEE.

Abstract
Adverse Drug Events (ADEs) are a major health problem, and developing accurate prediction methods may have a significant impact in public health. Ideally, we would like to have predictive methods, that could pinpoint possible ADRs during the drug development process. Unfortunately, most relevant information on possible ADRs is only available after the drug is commercially available. As a first step, we propose using prior information on existing interactions through recommendation systems algorithms. We have evaluated our proposal using data from the ADReCS database with promising results.

Abstract
Probabilistic Inductive Logic Programming (PILP) is a relatively unexplored area of Statistical Relational Learning which extends classic Inductive Logic Programming (ILP). Within this scope, we introduce SkILL, a Stochastic Inductive Logic Learner, which takes probabilistic annotated data and produces First Order Logic (FOL) theories. Data in several domains such as medicine and bioinformatics have an inherent degree of uncertainty, and because SkILL can handle this type of data, the models produced for these areas are closer to reality. SkILL can then use probabilistic data to extract non-trivial knowledge from databases, and also address efficiency issues by introducing an efficient search strategy for finding hypotheses in PILP environments. SkILL's capabilities are demonstrated using a real world medical dataset in the breast cancer domain.

Abstract
The volatility of the wind generation reduces the profits of wind generators as a consequence of the differences between the real wind generation and the wind power offered in the electricity markets. This paper presents two models: i) wind and generic storage system offering without a physical connection and ii) wind and generic storage system offering with a physical connection to mitigate the wind positive imbalances (excess of the wind generation with respect to the wind power offered). The objective of the models is to maximize the expected profit of selling the energy in the day-ahead market, where the energy can come from the wind power and the storage system. Moreover, the wind power imbalance is penalized in the balancing market reducing the profits. The problems are modeled using stochastic mixed integer linear programming. A case study of a week (168 hours) is simulated to evaluate the models. After the simulations, the results are discussed and a summary of the main conclusions are presented.