Abstract
This paper presents two new approaches to solve the reconfiguration problem of electrical distribution systems (EDSs) with variable demands, using the CLONALG and the SGACB algorithms. The CLONALG is a combinatorial optimization technique inspired by biological immune systems, which aims at reproducing the main properties and functions of the system. The SGACB is an optimization algorithm inspired by natural selection and the evolution of species. The reconfiguration problem with variable demands is a complex combinatorial problem that aims at identifying the best radial topology for an EDS, while satisfying all technical constraints at every demand level and minimizing the cost of energy losses in a given operation period. Both algorithms were implemented in C++ and test systems with 33, 84, and 136 nodes, as well as a real system with 417 nodes, in order to validate the proposed methods. The obtained results were compared with results available in the literature in order to verify the efficiency of the proposed approaches.

Abstract

Abstract
This paper proposes an oligopolistic model for a wind power producer (WPP) with a market power to compete with other Gencos and take part in day-ahead, intraday and balancing markets. In order to model the mentioned oligopoly markets from WPP's viewpoint, a bi-level optimization framework is proposed based on multi-agent system and incomplete information game theory. In this context, the WPP participates in the intraday market where demand response resources are incorporated, to update its day-ahead offers. The problem uncertainties, i.e., wind power and market prices, are considered using a multi-stage stochastic programming approach. Because of these uncertainties, a well-known risk measurement, CVaR, is considered for problem optimization. Several numerical studies are accomplished and various aspects of the problem are analyzed. According to the obtained results, the proposed WPP model reveals that the prices of day-ahead and balancing markets could be increased due to the market power of WPP.

Abstract
Monitoring an individual's performance in a task, especially in the workplace context, is becoming an increasingly interesting and controversial topic in a time in which workers are expected to produce more, better and faster. The tension caused by this competitiveness, together with the pressure of monitoring, may not work in favour of the organization's objectives. In this paper, we present an innovative approach on the problem of performance management. We build on the fact that computers are nowadays used as major work tools in many workplaces to devise a non-invasive method for distributed performance monitoring based on the observation of the worker's interaction with the computer. We then look at musical selection both as a pleasant and as an effective method for improving performance in the workplace. The proposed approach will allow team coordinators to assess and manage their co-workers' performance continuously and in real-time, using a distributed service-based architecture. Copyright (c) 2015 John Wiley & Sons, Ltd.

Abstract
State estimation (SE) has been considered the fulcrum of advanced computer-aided tools used to monitor, control, and optimise the performance of power grids. It is destined for the provision of a consistent real-time dataset, free of compromising errors. To the SE eye, observability is the faculty of seeing the actual system operating state. As such, it is vital to evaluate this faculty, especially in quantitative terms. Drawing a parallel between the financial market (in which investment grades - intended to signal the suitability of an investment - are assigned by credit rating agencies) and SE arena, this study proposes the establishment of observation grades. With a view to performing a reliable SE, these are defined as ratings capable of indicating that a measurement system (devoted to observing the state of a power grid under many different conditions), has a seal of approval, i.e. relatively low risk of being unsuccessful. The methodology proposed to express observation grades is based on the Monte Carlo simulation approach. The availability of measurement units and grid branches are adequately considered. Numerical results of a proof of concept study performed on the 24- and 118-bus benchmark systems illustrate the application and expected benefits of the proposed methodology.

Abstract
Equipment such as head-mounted displays are now available for the average consumer at affordable prices. This promotes the usage of this equipment for content consumption and demonstrations, thus it becomes important to establish the best practices for using this technology, namely guidelines in what concerns the recommended exposure time. Therefore, the purpose of this work is to study the impact of the exposure time on the feeling of presence while watching 360 degrees video using an head-mounted display. The independent variables of the study are the exposure time to the stimuli and gender of participants. There were tested four different exposure times: 1 minute, 3 minutes, 5 minutes and 7 minutes. For measuring presence, it was a Portuguese version of the Igroup Presence Questionnaire (IPQ) which considers also 3 presence subscales: spatial presence, realism and involvement. The results have revealed that there are few statistically significant differences for the given exposure times at the level of the sense of presence, apart from spatial presence and realism subscales, which consistently increased with exposure time for male participants and slightly decreased for female ones. Men always needed longer exposure times (> 1 minute) to report the highest scores, while women had the opposite behaviour, frequently reporting maximum scores for the shortest experiences.