Abstract
The main objective of this paper is to present a new and cost-effective Information and Communication Technology (ICT) tool that can lead to efficient energy management in buildings and optimal operation of electricity networks with increased share of Renewable Energy Sources (RES) and Electric Vehicles (EVs). The new ICT infrastructure is based on the Digital Audio Broadcasting (DAB) standard and its interoperability with smart metering technology, Intelligent Transportation Systems (ITS) and Building Automation Systems (BAS). The main idea involves the attachment of a DAB receiver to electric devices (from small household appliances up to EVs and solar systems and other RES). In this paper, the DAB protocol is described, enabling high cyber-physical security. Moreover, the results of addressing a thermostatically-controlled load using DAB-signaling in Switzerland are also presented. The next steps envisioned are i) the validation of the final protocol version and of the DAB receivers for various electric appliances and DR schemes and, ii) demonstration of the new technology in real-life cases through the National DAB broadcaster in Greece. (C) 2019 The Authors. Published by Elsevier Ltd.

Abstract
Wi-Fi networks lack energy consumption management mechanisms. In particular, during nighttime periods, the energy waste may be significant, since all Access Points (APs) are kept switched on even though there is minimum or null traffic demand. The fact that more than 80% of all wireless traffic is originated or terminated indoor, and served by WiFi, has led the scientific community to look into energy saving mechanisms forWi-Fi networks. State of the art solutions address the problem by switching APs on and off based on manually inserted schedules or by analyzing real-time traffic demand. The first are vendor specific; the second may induce frequent station (STA) handoffs, which has an impact on network performance. The lack of implementability of solutions is also a shortcoming in most works. We propose an algorithm, named Energy Consumption Management Algorithm (ECMA), that learns the daytime and nighttime periods of the Wi-Fi network. ECMA was designed having in mind its implementability over legacyWi-Fi equipment. At daytime, the radio interfaces of the AP (2.4 GHz and 5 GHz) are switched on and off automatically, according to the traffic demand. At nighttime, clusters of APs, covering the same area, are formed, leaving one AP always switched on for basic coverage and the redundant APs swichted off to maximize energy savings, while avoiding coverage and performance hampering. Simulation results show energy savings of up to 50% are possible using the ECMA algorithm.

Abstract
Swallowing is a dynamic, complex and synergistic process, composed of three phases with a refined neuromotor control. A malfunction of this process, denominated dysphasia, can occur in any age like a result of congenital, structural, functional and/or medical problems. The quantitative analysis of this process is crucial to understand the temporal relations between the mechanisms of the oropharyngeal deglutition. Designing a software to support the qualitative and quantitative analysis of the swallowing process through dynamic images obtained by videofluoroscopy is the main motivation and objective of this work. First, a survey of requirements for such a software was made, consisting in a research protocol for assessing dysphagia by videofluoroscopy. Secondly, best practices in human-computer interaction were used to design a conceptual model for the proposed software. Two protocols were selected for the assessment of dysphagia by videofluoroscopy: the Protocol of Boston and the Protocol used in the Hospital Privado da Trofa. These protocols allowed the identification of several events that are evaluated in the swallowing process and that can be recorded, measured and quantified during ingestion of the bolus. The second phase resulted in a conceptual model for an interactive system embodying the evaluation protocol selected and contemplates the integration of automatic algorithms for qualitative and quantitative evaluation of the parameters of swallowing. The proposed software model has a high potential to be a useful tool for assessing parameters of swallowing.

Abstract
This study examines the association between different types of dependency on resources and/or pressures from the international community and the reporting practices on the fight against corruption of companies in an emerging country setting, that of Turkey. More specifically, we focus on the influence of multinationality, cross-listing, and membership of the United Nations Global Compact on this type of reporting. We use ordinal regression analysis to explore the association between the three factors mentioned above and anti-corruption reporting for a sample of Turkish firms on the Borsa Istanbul 100 index, while controlling for some other factors likely to influence anti-corruption reporting. Findings show a low level of reporting. They also suggest that companies with their shares cross-listed and companies which are members of the Uited Nations Global Compact do present higher levels of anticorruption reporting than their counterparts.

Abstract
Vibrational energy harvesters for powering wearable electronics and other electrical energy demanding devices are among the most used approaches. Devices that use magnetic forces to maintain the central mass in magnetic levitation, aligned with several coils as the emf generating transducer mechanism, are becoming a suitable choice since they do not need the usual spring that typically degrades over time. Modeling such energy harvesters poses different challenges due to the difficulty of getting the nonlinear closed-form expression that would describe the resulting magnetic force of the entire system. In this paper, modeling of the magnetic forces resulting from the system magnets interaction is presented. Results give valuable data about how the best energy harvester should be designed taking into account resonance frequency related to system’s mass and dimensions.

Abstract
The effective monitoring and maintenance of power lines are becoming increasingly important due to a global growing dependence on electricity. The costs and risks associated with the traditional foot patrol and helicopter-based inspections can be reduced by using UAVs with the appropriate sensors. However, this implies developing algorithms to make the power line inspection process reliable and autonomous. In order to overcome the limitations of visual methods in the presence of poor light and noisy backgrounds, we propose to address the problem of power line detection and modeling based on LiDAR. The PL2DM, Power Line LiDAR-based Detection and Modeling, is a novel approach to detect power lines. Its basis is a scan-by-scan adaptive neighbor minimalist comparison for all the points in a point cloud. The power line final model is obtained by matching and grouping several line segments, using their collinearity properties. Horizontally, the power lines are modeled as a straight line, and vertically as a catenary curve. Using a real dataset, the algorithm showed promising results both in terms of outputs and processing time, adding real-time object-based perception capabilities for other layers of processing.