Abstract

Abstract
One of the most common ways of collecting ocean data is to deploy sensors from the surface, allowing to understand the variation of water properties with depth. Autonomous vertical profilers are robotic vehicles that replace human operators in this task. They form a particular class of autonomous underwater vehicles that move predominantly along the vertical axis, typically with reduced control on the horizontal axis. This paper describes a propeller driven autonomous underwater profiler, optimized for shallow waters. The vehicle has no fins or other control surfaces, and uses four independent thrusters to provide both vertical and horizontal motion, including hovering in the water column. The paper describes the main subsystems, including the hardware implementation, the software structure, and the motion controllers, with experimental data from the first trials. © 2017 Marine Technology Society.

Abstract
Entropy and compression have been used to distinguish fetuses at risk of hypoxia from their healthy counterparts through the analysis of Fetal Heart Rate (FHR). Low correlation that was observed between these two approaches suggests that they capture different complexity features. This study aims at characterizing the complexity of FHR features captured by entropy and compression, using as reference international guidelines. Single and multi-scale approaches were considered in the computation of entropy and compression. The following physiologic-based features were considered: FHR baseline; percentage of abnormal long (% abLTV) and short (% abSTV) term variability; average short term variability; and, number of acceleration and decelerations. All of the features were computed on a set of 68 intrapartum FHR tracings, divided as normal, mildly, and moderately-severely acidemic born fetuses. The correlation between entropy/compression features and the physiologic-based features was assessed. There were correlations between compressions and accelerations and decelerations, but neither accelerations nor decelerations were significantly correlated with entropies. The % abSTV was significantly correlated with entropies (ranging between 0.54 and 0.62), and to a higher extent with compression (ranging between 0.80 and 0.94). Distinction between groups was clearer in the lower scales using entropy and in the higher scales using compression. Entropy and compression are complementary complexity measures.

Abstract
Collaborative Economy (CE) promotes significant changes in several sectors around the world, e.g. the famous companies Uber, Airbnb, and Turo. The general idea behind CE is the establishment of a win-win partnership between two agents. One agent has a potential need for a resource of high cost for acquisition or location, and the other agent has the resource frequently idle. Software quality verification on Android ecosystem is a hard task due to the fragmentation among the devices, i.e. the large number of devices configurations. In this scenario, compatibility testing demands the acquisition or location of several different devices of high cost and volatility due to technology evolution. On the other hand, there are several devices around the world with a high rate of idle time and which could be used for testing, generating an extra budget for their owners. In this sense, this paper defends the principles of CE for supporting the testing activity of Android applications. We implemented a platform to use and evaluate the practical usefulness and applicability of CE principles in Android software testing context. The platform makes it possible to run system testing on several devices, geographically distributed, simultaneously. The general idea is to record system testing by using an extension of Expresso, a Google proposed framework for user interface (UI) testing, and execute the test cases on idle devices previous registered on the platform, according to the test requirements. We carried out some exploratory studies which evidentiate the potential of the proposed platform, its benefits, and its impact not only on the market but also on the way we can run efficiently testing on Android ecosystem.

Abstract
Distributed Generation (DG) using renewable technologies is increasing due to their benefits including energy security and emission reduction. However, installing new DGs in distributed networks is limited due to network constraints such as feeder capacity and short circuit level, as well as higher investment costs. In this paper, network reconfiguration and reactive power planning are used to maximize DG penetration level and to minimize annual loss for DGs with biomass technologies. In order to model the problem uncertainties, 96 scenarios considering ten different network load levels are studied. A multi objective method is applied for solving this optimization problem by using Pareto front. The numerical results indicate the positive impacts of the proposed approach on improving the network security.

Abstract
The quality and composition of biomass as used in Portugal's thermal power plants is highly variable. The biomass consists mainly of residual forest biomass derived from forestry operations and wood waste from industrial processes, in particular paper and pulp industry. Its quality and composition is influenced by the presence of moisture and inert fragments, the latter being incorporated during collection or as a consequence of adherence to the biomass prior to collection. This variability presents difficulties for the thermal power plants; besides being an additional operational cost, the presence of large amounts of water and inerts in biomass used as a fuel, can result in problems related to the instability of the combustion and the accumulation of ash or rock that have to be removed and discarded. The objective of this paper is to review the main parameters that influence the quality of biomass, while analysing the current state-of-the-art power generation from the biomass sector in Portugal, as a new contribution to earlier studies.