Abstract
Nowadays, with the large-scale penetration of distributed and renewable energy resources, Electrical Energy Storage (EES) stands out for its ability of adding flexibility, controlling intermittence and providing back-up generation to electrical networks. It represents the critical link between the energy supply and demand chains and, moreover, a key element for increasing the role and attractiveness of renewable generation into the power grid, providing numerous technical and economic benefits to the power system stakeholders. On islanded systems and micro-grids, being updated about the state-of-the-art of EES systems and their benefits becomes even more relevant. Hence, in the present paper a comprehensive analysis of EES leading technologies' main assets, research issues, global market figures, economic benefits and technical applications is provided.

Abstract
This paper presents a comparative analysis of Free/Libre Open Source Software (FLOSS) Learning Management System (LMS). Following a selection process we analyze the functionalities and characteristics of 8 tools commonly used in formal and informal education. More specifically we focus on the availability of different tools concerning communication and assistance, such as, forum, email, calendar, portfolios, etc. Our analysis showed that despite their similarities, the appropriateness of different FLOSS LMSs can be greatly affected by the specific needs of students, instructors and institutions. © Springer-Verlag Berlin Heidelberg 2014.

Abstract
Software development is a knowledge-intensive activity. Software products usually start as a simple idea, or a vision, and then progress towards a final deliverable product. Along this evolution, there is a lot of knowledge that is captured, organized, and shared, leading to new knowledge, both as a whole and within specific development activities. The concept of "Ba" provides a foundation to advance individual and collective knowledge, which describes knowledge creation as a spiral involving tacit and explicit knowledge: the Socialization, Externalization, Combination, Internalization model (a.k.a. SECI model). By applying this foundation to software development, we found issues that may hinder the effective knowledge management cycle. In this paper, we present a vision and a set of requirements for tools to overcome such issues and therefore better support the whole process of software knowledge evolution.

Abstract
Environmental problems related to the conventional generators have motivated governmental policies all over the world in order to incorporate alternative power sources to reduce greenhouse gas (GHG) emissions and fossil-fuel consumption. On the one hand, wind power generation can increase GHG emissions of the others conventional generators connected to the system. On the other hand, wind energy is characterized by its variability that imposes challenges in the operation of the power system. In order to integrate GHG emissions estimation and the uncertainty related to the wind power generation, a probabilistic point of view is presented in this paper to estimate the probability distribution function (PDF) of the GHG emissions of a typical insular power system. The PDF of power production of each conventional generator is calculated, and then the expected value of the total GHG emissions is estimated.

Abstract
This paper analyzes the scientific literature produced recently about new product development (NPD) in order to identify and classify the major fields of knowledge, possible connections, as well as the nature of articles and analytics tools used. A review of the literature was implemented on 461 articles focused on NPD, published in three leading journals between 2000 and 2010. It was possible to create 13 main categories, in which innovation, research and development, NPD products and processes and NPD teams stand out. Results conclude that NPD is multifaceted, includes multiple concepts and interrelated categories. Moreover, future studies need to complement qualitative with quantitative research and to analyze how small and large firms differ.

Abstract
The massification of electric vehicles (EVs) can have a significant impact on the power system, requiring a new approach for the energy resource management. The energy resource management has the objective to obtain the optimal scheduling of the available resources considering distributed generators, storage units, demand response and EVs. The large number of resources causes more complexity in the energy resource management, taking several hours to reach the optimal solution which requires a quick solution for the next day. Therefore, it is necessary to use adequate optimization techniques to determine the best solution in a reasonable amount of time. This paper presents a hybrid artificial intelligence technique to solve a complex energy resource management problem with a large number of resources, including EVs, connected to the electric network. The hybrid approach combines simulated annealing (SA) and ant colony optimization (ACO) techniques. The case study concerns different EVs penetration levels. Comparisons with a previous SA approach and a deterministic technique are also presented. For 2000 EVs scenario, the proposed hybrid approach found a solution better than the previous SA version, resulting in a cost reduction of 1.94%. For this scenario, the proposed approach is approximately 94 times faster than the deterministic approach.