Abstract
A mudança climática não pode ser desmentida. Desde que a humanidade adquiriu o conhecimento da eletricidade que tem transformado todo o seu modo de viver em seu redor. Para a produção de eletricidade recorre-se, em parte, à combustão de materiais que libertam CO2 e que, pela quantidade emitida, potencialmente degrada o ambiente. Noutra perspetiva, em certas zonas geográficas, o acesso à energia elétrica é escasso. É neste contexto que surge a profissão de Software Testing. Neste artigo procura-se quantificar o contributo dos testes de software no desenvolvimento de aplicações que tenham em conta um consumo energético mais reduzido. Para atingir esse objetivo é proposta e aplicada uma metodologia para a medição de consumo e é definida uma fórmula matemática para apuramento da viabilidade económica dos testes. As consequências de um software que consuma menos energia serão de três ordens: a ambiental – na redução da emissão de CO2; a humana – pela possibilidade de mais pessoas utilizarem a capacidade energética instalada; e a financeira – na redução direta do custo do consumo.;Climate change cannot be ignored any longer. Since humanity has developed the knowledge of electricity and has shaped his existence in a way that we are all dependent on it. The generation of electricity is linked to the combustion of products that release CO2 into the atmosphere which has the potential to degrade the environment. On the other hand, some countries have a restricted access to electricity. It is in this context that a new profession emerges – the software testing. This article aims at quantifying the contribution of Software Testing in the energy consumption of software. To achieve this goal it is proposed and applied a simplified methodology for measuring consumption of software and it is defined a mathematical formula to calculate the economic viability of the tests. The consequences of an optimized software in its energy consumption will be: environmental – by reducing CO2 emissions; human – by allowing more people to use the already installed power capacity; and financial – by reduction of economical expenditure.

Abstract
This paper applies optimal power flow (OPF) to evaluate and maximize network benefits of demand-side management (DSM). The benefits are quantified in terms of the ability of demand-responsive loads to relieve upstream network constraints and provide ancillary services, such as operating reserve. The study incorporates detailed information on the load structure and composition, and allows the potential network benefits, which could be obtained through management of different load types, to be quantified and compared. It is demonstrated that the actual network location of demand-manageable load has an important influence on the effectiveness of the applied DSM scheme, since the characteristics of the loads and their interconnecting networks vary from one location to another. Consequently, some network locations are more favorable for implementation of DSM, and OPF can be applied to determine the optimal allocation of demand-side resources. The effectiveness of the presented approach is assessed using a time-sequential OPF applied to typical radial and meshed U.K. distribution networks. The results of the analysis suggest that network operators could not just participate in, but also encourage and add value to the implementation of specific DSM schemes at the optimum network locations in order to maximize the total benefit from DSM. © 2014 IEEE.

Abstract
Traditionally, the Teacher-Student relationship is a close one. The student spends several hours of a day in the presence of the teacher and can talk, express doubts and pose questions. These doubts, or the general feeling towards the object of learning, are not only expressed explicitly but also implicitly. Indeed, the teacher is constantly, even if in an unconscious way, reading the state of the student in search for sings of doubt, frustration, stress or fatigue. This information is then used by the teacher to adapt their methods or to personalize their approach in function of each student. These aspects, intuitively central in education, become less efficient when learning takes place in a Virtual Environment. Indeed, the growth of online courses, in which the student and the teacher often never even meet, make learning more difficult for a number of reasons. In this paper we analyse these reasons and put forward an approach for inferring the student's state that aims to minimize the effects of the absence of the teacher.

Abstract
The energy sector in industrialized countries has been restructured in the last years, with the purpose of decreasing electricity prices through the increase in competition, and facilitating the integration of distributed energy resources. However, the restructuring process increased the complexity in market players' interactions and generated emerging problems and new issues to be addressed. In order to provide players with competitive advantage in the market, decision support tools that facilitate the study and understanding of these markets become extremely useful. In this context arises MASCEM (Multi-Agent Simulator of Competitive Electricity Markets), a multi-agent based simulator that models real electricity markets. To reinforce MASCEM with the capability of recreating the electricity markets reality in the fullest possible extent, it is crucial to make it able to simulate as many market models and player types as possible. This paper presents a new negotiation model implemented in MASCEM based on the negotiation model used in day-ahead market (Elspot) of Nord Pool. This is a key module to study competitive electricity markets, as it presents well defined and distinct characteristics from the already implemented markets, and it is a reference electricity market in Europe (the one with the larger amount of traded power).

Abstract
Microgrids have been explored as active cells capable of providing enhanced control schemes towards a more secure, reliable and efficient operation of LV distribution networks or MV networks when aggregated in a multi-microgrid. These structures, within the smart grid concept, rely on a communications infrastructure that introduces uncertainty in the data exchange process. In this paper such uncertainty is evaluated considering a multi-microgrid operating in isolated mode.

Abstract
We introduce an extension to Merton's famous continuous time model of optimal consumption and investment, in the spirit of previous works by Pliska and Ye, to allow for a wage earner to have a random lifetime and to use a portion of the income to purchase life insurance in order to provide for his estate, while investing his savings in a financial market comprised of one risk-free security and an arbitrary number of risky securities driven by multi-dimensional Brownian motion. We then provide a detailed analysis of the optimal consumption, investment and insurance purchase strategies for the wage earner whose goal is to maximize the expected utility obtained from his family consumption, from the size of the estate in the event of premature death, and from the size of the estate at the time of retirement. We use dynamic programming methods to obtain explicit solutions for the case of discounted constant relative risk aversion utility functions and describe new analytical results which are presented together with the corresponding economic interpretations.