Abstract
Introduction The new General Data Protection Regulation (GDPR) compels health care institutions and their software providers to properly document all personal data processing and provide clear evidence that their systems are inline with the GDPR. All applications involved in personal data processing should therefore produce meaningful event logs that can later be used for the effective auditing of complex processes. Aim This paper aims to describe and evaluate HS.Register, a system created to collect and securely manage at scale audit logs and data produced by a large number of systems. Methods HS.Register creates a single audit log by collecting and aggregating all kinds of meaningful event logs and data (e.g. ActiveDirectory, syslog, log4j, web server logs, REST, SOAP and HL7 messages). It also includes specially built dashboards for easy auditing and monitoring of complex processes, crossing different systems in an integrated way, as well as providing tools for helping on the auditing and on the diagnostics of difficult problems, using a simple web application. HS.Register is currently installed at five large Portuguese Hospitals and is composed of the following open-source components: HAproxy, RabbitMQ, Elasticsearch, Logstash and Kibana. Results HS.Register currently collects and analyses an average of 93 million events per week and it is being used to document and audit HL7 communications. Discussion Auditing tools like HS.Register are likely to become mandatory in the near future to allow for traceability and detailed auditing for GDPR compliance. © 2018 European Federation for Medical Informatics (EFMI) and IOS Press.

Abstract
The maximum edge weight clique (MEWC) problem, defined on a simple edge-weighted graph, is to find a subset of vertices inducing a complete subgraph with the maximum total sum of edge weights. We propose a quadratic optimization formulation for the MEWC problem and study characteristics of this formulation in terms of local and global optimality. We establish the correspondence between local maxima of the proposed formulation and maximal cliques of the underlying graph, implying that the characteristic vector of a MEWC in the graph is a global optimizer of the continuous problem. In addition, we present an exact algorithm to solve the MEWC problem. The algorithm is a combinatorial branch-and-bound procedure that takes advantage of a new upper bound as well as an efficient construction heuristic based on the proposed quadratic formulation. Results of computational experiments on some benchmark instances are also presented.

Abstract
The availability of low cost networked wireless devices and video cameras is enabling wireless video sensor networks (WVSNs), which can be used in scenarios such as healthcare, agriculture, smart cities, intelligent transportation systems, and surveillance. These scenarios typically require that each node sends a video stream to a server located in the cloud. The IEEE 802.11 is considered a suitable technology for transmitting video wirelessly, as it supports high data rates. However, when using a multi-hop topology to extend the IEEE 802.11 coverage, the IEEE 802.11-based WVSNs suffer from three problems: low network capacity, throughput unfairness, and energy inefficiency. To overcome these problems, we propose a holistic solution, named Green wiReless vidEo sENsor NEtworks uSing out-of-band Signalling (GREENNESS). GREENNESS combines a node polling mechanism with the use of out-of-band signaling over a low power radio to signal when a video sensor should switch ON and OFF its IEEE 802.11 interface, thus saving energy. The results obtained for random network topologies show that GREENNESS can achieve energy savings up to 92%, and improve network capacity and throughput fairness when compared to state of the art CSMA/CA-based WVSN solutions.

Abstract
The automatic analysis of water-sensitive papers (WSP) is of great relevance in agriculture. SprayImageMobile is a software tool developed for mobile devices (iOS) that provides full processing of WSP, from image acquisition to the final reporting. One of the initial processing tasks on SprayImageMobile is the detection (or segmentation) of the WSP on the image acquired by the device. This paper presents the method developed for the detection of the WSP that was implemented in SprayImageMobile. The method is based on the identification of reference points along the WSP margins, and the modeling of a quadrilateral that takes into account possible false positive and negative identifications. The method was tested on a set of 360 images, failing to detect the WSP in only 1 case (detection accuracy of 99.7%). The segmentation accuracy was evaluated using references obtained by a semi-automatic method. The average values obtained for the 359 images tested were: 0.9980 (precision), 0.9940 (recall) and 0.9921 (Hammoude metric). © 2018, Springer International Publishing AG, part of Springer Nature.

Abstract
Electric Vehicles (EVs) are increasing the interdependence of transportation policies and the electricity market dimension. In this paper, an Electricity Market Model with Electric Vehicles (EMMEV) was developed, exploiting an agent-based model that analyzes how carbon reduction policy in transportation may increase the number of Electric Vehicles and how that would influence electricity price. Agents are Energy Service Providers (ESCOs) which can distribute fuels and their objective is to maximize their profit. In this paper, the EMMEV is used to analyze the impacts of the Low-Carbon Fuel Standard (LCFS), a performance-based policy instrument, on electricity prices and EV sales volume. The agents in EMMEV are regulated parties in LCFS should meet a certain Carbon Intensity (CI) target for their distributed fuel. In case they cannot meet the target, they should buy credits to compensate for their shortfall and if they exceed it, they can sell their excess. The results, considering the assumptions and limitations of the model, show that the banking strategy of the agents contributing in the LCFS might have negative impact on penetration of EVs, unless there is a regular Credit Clearance to trade credits. It is also shown that the electricity price, as a result of implementing the LCFS and increasing number of EVs, has increased between 2% and 3% depending on banking strategy.

Abstract
The present paper addresses the use of evolutionary based algorithms for off-line fractional-order controller tuning. In particular, a linearized model of a motor-rotor propulsion device was assumed whose representativeness is supported by laboratorial measurements. Initially, the controller was calibrated, using the devised linear model, by a procedure that uses a cost function defined as the linear combination between the sum of the squared error and the sum of the absolute error. In this work, it was shown that this process can be improved by using an evolutionary based algorithm in order to find the best controller parameters. This strategy allows a more automatic tuning procedure isolating it from the user intervention. Moreover, the results achieved by this process, lead to an improved rotational speed regulation.