Abstract
An unidirectional single-phase three-wire rectifier is proposed in this paper. Such topology is composed of a noncontrolled leg, two controlled legs, and a capacitor bank. A suitable model, pulse-width modulation, and control strategies of the system are proposed as well. The control strategy includes the synchronization method, in which it imposes the grid currents with the same phase angle of the voltages generated by the rectifier. This method ensures sinusoidal grid currents and mitigates the zero-crossover distortions normally caused by the use of diodes. A comprehensive comparison with two conventional configurations is also presented in this paper. Simulation and experimental results are also presented for validation purposes.

Abstract
New achievements in information and communication technologies (ICT) are drastically influencing several industrial sectors. The provision of connectivity, networked entities, real-time data, and pervasive information is shifting paradigms in industries. However, this rapid evolution requires a proper comprehension and defmition by scholars and practitioners in order to achieve a broad dissemination of the technological progress. Today, the trend towards a digital revolution in manufacturing is known as "Industry 4.0". However, the footprint of these evolutions, the technological borders, and the application frameworks are not yet specified. Therefore, the adoption of this paradigm change still requires more research to further develop the knowledge about the drivers and accomplishments of Industry 4.0. Towards this goal, this paper reviews some major EU industrial guidelines, roadmaps, and scientific literature that led to the depiction of the term Industry 4.0, and explores how key technologies and concepts have been addressed over time. (C) 2017 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of the Manufacturing Engineering Society International Conference 2017.

Abstract
This study addresses the product-launch planning problem in the chemical-pharmaceutical industry under technical and market uncertainties, and considering resource limitations associated to the need of processing in the same plant products under development and products in commercialization. A novel approach is developed by combining a mixed integer linear programming (MILP) model and a Monte Carlo simulation (MCS) procedure, to deal with the integrated process design and production planning decisions during the New Product Development (NPD) phase. The Monte Carlo simulation framework was designed as a two-step sampling procedure based on Bernoulli and Normal distributions. Results show the unquestionable influence of the uncertainty parameters on the decision variables and objective function, thus highlighting the inherent risks associated to the deterministic models. Process designs and scale-ups that maximize expected profit were determined, providing a valuable knowledge frame to support the long-term decision-making process, and enabling earlier and better decisions during NPD.

Abstract
The information generated by a network monitoring system is overwhelming. Monitoring is imperative but very difficult to accomplish due to several reasons. More so for the case of non tech-savvy home users. Security Information Event Management applications generate alarms that correlate multiple occurrences on the network. These events are classified accordingly to their risk. An application that allows the sonification of events generated by a Security Information Event Management can facilitate the security monitoring of a home network by a less tech-savvy user by allowing him to just listen to the result of the sonification of such events.

Abstract
With the overwhelming volume of online multimedia content and increasing ubiquity of Internet-enabled mobile devices, pervasive use of the Web for content sharing and consumption has become our everyday routines. Consequently, people seeking online access to content of interest are becoming more and more frustrated. Thus, deciding which content to consume among the deluge of available alternatives becomes increasingly difficult. Context-aware personalization, having the capability to predict user's contextual preferences, has been proposed as an effective solution. However, some existing personalized systems, especially those based on collaborative filtering, rely on rating information explicitly obtained from users in consumption contexts. Therefore, these systems suffer from the so-called cold-start problem that occurs as a result of personalization systems' lack of adequate knowledge of either a new user's preferences or of a new item rating information. This happens because these new items and users have not received or provided adequate rating information respectively. In this paper, we present an analysis and design of a context-aware personalized system capable of minimizing new user cold-start problem in a mobile multimedia consumption scenario. The article emphasizes the importance of similarity between contexts of consumption based on the traditional k-nearest neighbor algorithm using Pearson Correlation model. Experimental validation, with respect to quality of personalized recommendations and user satisfaction in both contextual and non-contextual scenarios, shows that the proposed system can mitigate the effect of user-based cold-start problem.

Abstract