Abstract
This paper presents REQCAP, an implementation of a new method that articulates hierarchical requirements modeling and test generation to assist in the process of capturing requirements for PLC-based control systems. REQCAP is based on a semi-formal graphical model that supports hierarchical modeling, thus enabling compositional specifications. The tool supports automated generation of test cases according to different coverage criteria. It can also import requirements directly from REQIF files and automatically generate Sequential Function Charts (SFCs). We use a real-world case study to show how REQCAP can be used to model realistic system requirements. We show how the automated generation of SFCs and test cases can support engineers (and clients) in visualizing and reviewing requirements. Moreover, all the tests listed in the original test document of the case study are also generated automatically by REQCAP, demonstrating that the tool can be used to effectively capture requirements and generate valid and useful test cases.

Abstract
In this paper, the effect of renewable energy resources (RERs), demand response (DR) programs and electric vehicles (EVs) is evaluated on the optimal operation of a smart distribution company (SDISCO) in the form of a new bi-level model. According to the existence of private electric vehicle parking lots (PLs) in the network, the aim of both levels is to maximize the profits of SDISCO and the PL owners. Furthermore, due to the uncertainty of RERs and EVs, the conditional value-at-risk (CVaR) method is applied in order to limit the risk of expected profit. The model is transformed into a linear single-level model by the Karush-Kuhn-Tucker (KKT) conditions and tested on the IEEE 33-bus distribution system over a 24-h period. The results show that by using a proper charging/discharging schedule, as well as a time of use program, SDISCO gains more profit. Furthermore, by increasing the risk aversion parameter, this profit is reduced.

Abstract
Because of various developments in communications and technologies, each residential consumer has been enabled to contribute in Demand Response Programs (DRPs), manage its electrical usage and reduce its cost by using a Household Energy Management (HEM) system. An operational HEM model is investigated to find the minimum consumer's cost in every DRP and to guarantee the end-user's satisfaction, as well as to ensure the practical constraints of every battery and residential appliance. The numerical studies show that the presented method considerably affects the operational patterns of the HEM system in each DRP. According to the obtained results, by employing the presented method the consumer's cost is decreased up to 40%. © 2017 IEEE.

Abstract
This paper presents a new proposal for sensor fusion in power system state estimation, analyzing the case of data sets composed of conventional measurements and phasor measurements from PMUs. The approach is based on multiple criteria decision-making concepts. The equivalence of an L-1 metric in the attribute space to the results from a Bar-Shalom-Campo fusion model is established. The paper shows that the new fusion proposal allows understanding the consequences of attributing different levels of confidence or trust to both systems. A case study provides insight into the new model.

Abstract
Distribution automation systems in terms of automatic and remote-controlled sectionalizing switches allows distribution utilities to implement flexible control of distribution networks, which is a successful strategy to enhance efficiency, reliability, and quality of service. The sectionalizing switches play a significant role in an automated distribution network, hence optimizing the allocation of switches can improve the quality of supply and reliability indices. This paper presents a mixed-integer nonlinear programming aiming to model the optimal placement of manual and automatic sectionalizing switches and protective devices in distribution networks. A value-based reliability optimization formulation is derived from the proposed model to take into consideration customer interruption cost and related costs of sectionalizing switches and protective devices. A probability distribution cost model is developed based on a cascade correlation neural network to have a more accurate reliability assessment. To ensure the effectiveness of the proposed formulation both technical and economic constraints are considered. Furthermore, introducing distributed generation into distribution networks is also considered subject to the island operation of DG units. The performance of the proposed approach is assessed and illustrated by studying on the bus 4 of the RBTS standard test system. The simulation results verify the capability and accuracy of the proposed approach.

Abstract
Research management promotes an integrated approach to identifying, capturing, evaluating, retrieving, and sharing all of a higher education institutions' research information assets. These assets may include databases, documents, policies and procedures. Conceptually linked, knowledge and research assume critical relevance as an essential tool to insuring Higher Education institutions quality. Institutions are challenged to develop robust (internal) quality assurance systems in which information about scientific production, research projects, staff curricula are considered as relevant indicators. This commitment with science and research is also visible by the opportunities promoted by institutions for the academic development of their staff. Accordingly, the assessment of research and science indicators becomes an essential step for the definition of research development programmes in HE institutions. Based on this framework, it was developed an online questionnaire to be answered by academic staff, trying to assess some science and research indicators. Trying to measure the research potential of all faculty staff, this assessment tool is organized in distinctive four dimensions, namely researcher's (i) biographic data, (ii) scientific identification, scientific outputs (books, Books' chapters, scientific paper indexed and proceedings), (iii) research project with competitive funding and (iv) suggestions to improve research production. In what concerns to the application, all faculty staff members (teachers and researchers) were invited to contribute. The results were presented and discussed personally and collectively with all academic community. These results also provide relevant Key Performance Indicators, also known as KPIs or Key Success Indicators (KSIs), that could help managers and researchers gauge the effectiveness of various functions and processes important to achieving organizational goals. If scientific research is a strategic priority to higher education institutions, this kind of KPIs could be used to help academic managers to assess whether they or their faculty/research staff are on or off target towards those goals.