Abstract
This paper presents a multi-temporal approach for the energy scheduling and voltage/var control problem in a microgrid (MG) system with photovoltaic (PV) generation and energy storage devices (PV-battery MG) during islanded operation conditions. A MG is often defined as a low voltage (LV) distribution grid that encompasses distributed energy resources and loads that operate in a coordinated way, either connected to the upstream distribution grid or autonomously (islanded from the main grid). Considering the islanded operation of the MG during a given period, it is necessary to develop proper tools that allow the effective coordination of the existing resources. Such tools should be incorporated in the MG control system hierarchy in order to assure proper conditions for the operation of the autonomous MG in terms of active power, voltage and reactive power management. Energy storage devices are essential components for the successful operation of islanded MG. These devices have a very fast response and are able to absorb/inject the right amount of power. For the operation of the MG in islanding conditions during a longer period, it is necessary to integrate information related to the forecasting of loads and PV-based generation for the upcoming hours for which is intended to maintain MG in islanded operation. Therefore, this paper presents a tool to be integrated in the Microgrid Central Controller (MGCC) that is responsible to perform a multi-temporal optimal power flow (OPF) in order to schedule the active and reactive power within the MG for the next time intervals. © 2019, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

Abstract
[No abstract available]

Abstract
In the context of the CloudDBAppliance (CDBA) project, fault tolerance and high-availability are provided in layers: within each appliance, within a data centre and between datacentres. This paper presents the recovery mechanisms in place to fulfill the provision of high-availability within a datacentre. The recovery mechanism takes advantage of CDBA's in-middleware replication mechanism to bring failed replicas up-to-date. Along with the description of different variants of the recovery mechanism, this paper provides their comparative evaluation, focusing on the time it takes to recover a failed replica and how the recovery process impacts throughput.

Abstract
In order to increase the adoption of machine learning models in areas like medicine and finance, it is necessary to have correct and diverse explanations for the decisions that the models provide, to satisfy the curiosity of decision-makers and the needs of the regulators. In this paper, we introduced a method, based in a previously presented framework, to explain the decisions of an Ensemble Model. Moreover, we instantiate the proposed approach to an ensemble composed of a Scorecard, a Random Forest, and a Deep Neural Network, to produce accurate decisions along with correct and diverse explanations. Our methods are tested on two biomedical datasets and one financial dataset. The proposed ensemble leads to an improvement in the quality of the decisions, and in the correctness of the explanations, when compared to its constituents alone. Qualitatively, it produces diverse explanations that make sense and convince the experts.

Abstract
The aim of computer-aided musical orchestration (CAMO) is to find a combination of musical instrument sounds that perceptually approximates a reference sound when played together. The complexity of timbre perception and the combinatorial explosion of all possible musical instrument sound combinations make it very challenging to find even one orchestration for a reference sound. However, finding only one orchestration is seldom enough given the creative nature of the compositional process. Compositional applications of computer-aided musical orchestration can greatly benefit from multiple orchestrations with diversity. In this work, we use an artificial immune system (AIS) called opt-aiNet to search for combinations of musical instrument sounds that minimize the distance to a reference sound encoded in a fitness function. Opt-aiNet was developed to maximize diversity in the solution set of multi-modal optimization problems, which results in multiple alternative orchestrations for the same reference sound that are different among themselves. We compared the diversity and the similarity of the orchestrations proposed by opt-aiNet (CAMO-AIS) against a standard genetic algorithm (CAMO-GA) and Orchids, which is considered the state of the art for CAMO, for 13 reference sounds. In general, CAMO-AIS outperformed CAMO-GA and Orchids for several measures of objective diversity. We performed a listening test to evaluate and compare the perceptual similarity of the orchestrations by CAMO-AIS and Orchids. CAMO-AIS generated orchestrations that were perceived to be as similar to the reference sounds as those returned by Orchids. Therefore, CAMO-AIS has higher diversity of orchestrations than Orchids without loss of perceptual similarity.

Abstract
With the advent of social media, the boundaries of mainstream journalism and social networks are becoming blurred. User-generated content is increasing, and hence, journalists dedicate considerable time searching platforms such as Facebook and Twitter to announce, spread, and monitor news and crowd check information. Many studies have looked at social networks as news sources, but the relationship and interconnections between this type of platform and news media have not been thoroughly investigated. In this work, we have studied a series of news articles and examined a set of related comments on a social network during a period of six months. Specifically, a sample of articles from generalist Portuguese news sources published on the first semester of 2016 was clustered, and the resulting clusters were then associated with tweets of Portuguese users with the recourse to a similarity measure. Focusing on a subset of clusters, we have performed a temporal analysis by examining the evolution of the two types of documents (articles and tweets) and the timing of when they appeared. It appears that for some stories, namely Brexit and the European Football Cup, the publishing of news articles intensifies on key dates (event-oriented), while the discussion on social media is more balanced throughout the months leading up to those events. Copyright