Abstract & Overview
Dear Readers,At the end of this year, it gives me great pleasure to announce the tenth regular issue of 2022. In this issue, various topical aspects of computer science are covered in 4 articles by 10 authors from 4 countries in 4 articles. I would like to thank all the authors for their sound research papers and the editorial board for the highly valuable review effort and comments for improvement. These contributions, together with the generous support of the consortium members, sustain the quality of our journal. I am looking forward to continuing my work as Managing Editor-in-Chief with the J.UCS community.In an ongoing effort to further strengthen our journal, I would like to expand the editorial board: If you are a tenured associate professor or above with a strong publication record, you are welcome to apply to join our editorial board. We are also interested in high-quality proposals for special issues on new topics and trends. Please consider yourself and encourage your colleagues to submit high-quality articles or special issue proposals for our journal.In this regular issue, I am very pleased to introduce the following 4 accepted articles: Nibras Othman Abdulwahid, Sana Fakhfakh and Ikram Amous from Tunisia present their research and proposal for simulating and predicting students’ academic performance based on two models, the seven-subject, one-grade, one-output (SOO) and the seven-subject, twelve-year, seven-output (STS) model. Jorge R. Quiñones and Antonio J. Fernández-Leiva from Spain introduce their approach to automated video gaming parameter tuning based on an extension of XVGDL, a language for specifying video games. Jarashanth Selvarajah and Ruwan Nawarathna from Sri Lanka build an automated drug monitoring and surveillance system for social media based on embedding-level attention, convolutional neural networks (CNN), and bidirectional gated recurrent units (BiGRU). Marko Zekan, Igor Tomičić and Markus Schatten from Croatia discuss their research of an improved Network Intrusion Detection System (NIDS) applying a novel semi-supervised EC-GAN method for network flow classification.Season greetings to all of you, relaxing holidays and ‘Enjoy Reading’!