Abstract
This paper proposes four open-end nine-phase conversion systems with a reduced number of controlled switches. For this to be achieved, a converter is shared among the three three-phase groups that compose the machine. In addition, in order to reduce the number of controlled switches even more, three of the studied topologies with a shared converter make use of diodes replacing some of the switches. Because of the shared converter, the configurations that make use of diodes are only applied for machines with no spatial shift between the machine three three-phase groups. Analysis of harmonic distortion for equal and unequal dc-link voltages is presented. It is shown that the harmonic distortion for configurations with diodes are higher when unequal dc-link voltages are used. Besides, study of machine torque ripple is performed and a pulse-width modulation strategy modification is made aiming torque ripple reduction for two of the proposed conversion systems. Simulation and experimental results are presented to validate the theoretical approach.

Abstract
There is a remarkable potential for implementing demand response (DR) strategies for several purposes, such as peak load reduction, frequency regulation, etc., by using thermostatically controllable appliances. In this paper, an enduser comfort violation minimization oriented DR strategy for residential heating, ventilation, and air conditioning (HVAC) units is proposed. The proposed approach manipulates the temperature set-point of HVAC thermostats aiming to minimize the average discomfort among end-users enrolled in an DR program, while satisfying the DR event related requirements of the load serving entity. Besides, the fairness of the allocation of the comfort violation among the enrolled end-users is also taken into account. Moreover, maintaining the load factor during the contracted DR period compared to a base case in order to reduce the load rebound effect due to shifting the use of HVAC units is also considered within the proposed strategy. Last but not least, the heat index that considers the impact of humidity is utilized instead of using ambient dry-bulb temperature through a spatio-temporal forecasting approach.

Abstract
The overall price of energy is gradually increasing as a result of a constant escalating demand and limited supply. Consequently, the idea of demand response is being entertained by researchers and policy makers as a viable solution to the challenges ahead. Thus, new methods that aim to reduce the energy consumption in the residential sector are required to face such challenges. However, in order to optimize the consumption of energy while guaranteeing a certain level of comfort in the interior of the building could generate several control challenges. The goal of this paper is to compare the performance of control methods such as the Model Predictive Control (MPC), ON/OFF, and proportional-integral-derivative (PID) of a domestic heating, ventilation and air conditioning (HVAC) system controlling the temperature of a room. The house with local solar microgeneration is modelled approximating a location in a Portuguese city - Evora - pilot in a demand response project. The residence of the case study is subject to the local solar irradiance, temperature and six Time-of-Use (ToU) electricity rates applied on an entire week of July 2016. The aim of this paper is to accomplish the best compromise between temperature comfort levels and energy costs given by the performance of the fittest control method under different ToU rate options.

Abstract
Clustering is one of the most popular data mining techniques. In this article, we review the relevant methods and algorithms for designing cluster algorithms under the data streams computational model, and discuss research directions in tracking evolving clusters. © Springer Science+Business Media New York 2011, 2017

Abstract
Knowledge Discovery in Databases (KDD) is a major innovation in knowledge extraction. This knowledge can be extracted to recognize patterns or behaviors. Board games playing patterns are a concise experiment on testing data mining methods in order to find such patterns and behaviors. In this work a Connect-4 game is simulated with several distinct players with different characteristics. Most of these distinct players have intelligent game playing abilities, whereas others are simpler and play by very simple rules. The work uses three different data-mining algorithms in order to classify the players and their moves. Analyzing the results achieved we can conclude that General Linear Model leads to better results in terms of accuracy, class precision and class recall

Abstract
Universities seek to promote entrepreneurship through effective education approaches, which need to be in permanent evolution. Nevertheless, the literature in entrepreneurship education lacks empirical evidence. This article discusses relevant issues related to promoting entrepreneurship in the software field, based on the experience of a 15-European Credit Transfer and Accumulation System course. This course seeks to instil in the students the recognition of the need to reconcile technical and business visions, organisational and commercial aspects, most of which have never been addressed previously. A series of semi-structured interviews made it possible to obtain relevant insights about the teaching-learning process underlying this course and its evolution over a seven-year period. Materials related with this course have been analysed, namely guidelines produced by the teachers and deliverables produced by the students. This article discusses the dimensions that were identified as fundamental for promoting entrepreneurship skills in the field of software, namely teamwork, project engagement, and contact with the market.