Editorial

Abstract

It gives me great pleasure to announce the sixth regular issue of 2021. All this is only possible thanks to the great support of the J.UCS community. Therefore, I would like to thank all the authors for their sound research and the editorial board for the highly valuable reviews and suggestions for improvement. These contributions together with the generous support of the consortium members sustain the quality of our journal. We are always interested in receiving high quality proposals for special issues on new topics and emerging trends. Please consider yourself and encourage your colleagues to submit high quality articles to our journal. I am also still looking to expand our editorial board: If you are a tenured associate professor or higher and have a good publication record, please feel free to apply to join our editorial board. In this regular issue, I am very pleased to introduce six accepted papers contributed by 17 authors from six different countries. Rochdi Boudjehem and Yacine Lafifi from Algeria outline their research on how to identify and assist struggling learners by monitoring and analyzing their behavior within the e-learning environment. Abdelouafi Ikidid, Abdelaziz El Fazziki and Mohammed Sadgal from Morocco introduce a fuzzy logic-based multi-agent system for traffic light control at a signalized intersection by acting on the length and sequence of traffic light phases to favor priority flows and make traffic flow more smoothly at an isolated intersection and for the entire network with multiple intersections. Andrea Lezcano Airaldi, Jorge Andrés Diaz-Pace and Emanuel Irrazábal from Argentina conducted a case study to evaluate the benefits of incorporating data-driven storytelling into the development of a software system to support decision-making in crisis settings. José Monteiro, Maria Bernardo, Mafalda Ferreira, and Tânia Rocha from Portugal discuss their study of quality aspects of e-government information with the goal of better understanding which of these attributes are most valued from the users’ perspective when evaluating content provided by government websites. Ricardo Pérez- Castillo and Mario Piattini from Spain outline their study on how the evolution of the development effort influences the code quality, which was analyzed on 13 open source projects. Hamda Slimi, Ibrahim Bounhas and Yahya Slimani from Tunisia discuss their approach, which aims to detect emerging and unseen rumors on Twitter by adapting a pre-trained language model, namely RoBERTa, to the task of rumor detection.