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

Abstract
This paper investigates the utilization of two different six-leg configurations of single-phase to three-phase converters. One of the topologies is transformerless and the other is transformer based. The studied converters allow feeding the load voltage with sinusoidal voltages with constant amplitude and frequency, and to operate with sinusoidal grid current with high power factor. The system model and pulse-width modulation techniques for one of the topologies are given. Control strategies for both topologies are provided. The studied topologies are compared with the conventional in terms of dc-link specification, voltages harmonic distortions, semiconductor losses, and other characteristics. Simulation and experimental results are provided to illustrate the operation of the systems.

Abstract
Plenty of literature exists about how to model liberalized electricity generation markets for the medium and long terms, contributing to the analyze and understanding of those markets, helping companies to plan cost-efficient shortterm market strategies and/or long-term generation capacity investments, and supporting regulators and policymakers in policy decisions and market designs. However, those models do not explicitly consider the impact on investment decisions, mix of technologies and wholesale market prices; of policy decisions but as an external passive input to the model. This paper reviews existing approaches to model policy decisions in such a context, and provides a theoretical modeling framework that explicitly considers the interaction of policymakers' decisions with the generation investment and operation, and customers' response in a liberalized power system. Such kind of model, based on bi-level optimization, contributes to the longterm assessment of some policy decisions in the electricity sector. © 2017 IEEE.

Abstract
We present a case study of quality evaluation of online health information. Two participants were selected from a health information search (HIS) study, in which we are investigating consumers' evaluation of the quality of online health information. The selected cases offered a rare example of two almost exactly opposite eye-movement patterns on the same webpage. To better understand the differences in these patterns, we investigated participants' cognitive evaluation processes by examining their textual explanations collected in post-task questionnaires and verbal explanations collected in the retrospective think-aloud (RTA) sessions. We discuss how eHealth literacy and personality scores may be related to the behavioral differences. The findings of this case study inform the formulation of hypotheses for full data analysis of the HIS study, as well as future research addressing behavior patterns and factors affecting consumers' quality evaluation of online health information. Copyright © 2017 by Association for Information Science and Technology

Abstract
Carsharing is a model of renting vehicles for short periods of time, where the payment is made according to the time and distance effectively traveled. Carsharing offers a simple, economical and smart alternative to urban mobility, that is already being adopted in the major cities in the world. The proposed methodology consisted in the development of a decision support system that simplifies the process of choosing carsharing services. Adopting the AHP method, the user can indicate their preferences in the choice of vehicles, and the system returns an ordered list of the most suitable available vehicles based on their geographic location. The findings of the project indicate that the use of this system encourage and simplify the use of carsharing services, which will allow to enhance the financial, mobility and environment advantages inherent to their use.