Dear Readers,

I am very pleased to announce today the tenth J.UCS issue of 2025. In this issue, various topical aspects of computer science are covered in 5 articles by 13 authors from 5 countries (Brazil, Croatia, Germany, India, Spain). As always, I would like to thank all the authors for their sound research and the editorial board for their highly valuable review effort and suggestions for improvement. These contributions sustain the quality of our journal. I would also like to express my sincere thanks to the KOALA Initiative and its team for their financial support, without which the J.UCS team would not be able to publish our journal.

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 receiving 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 5 accepted articles: Rodrigo Costa Camargos and Ismar Frango Silveira from Brazil explore in their research the application of Explainable Artificial Intelligence (XAI) techniques to mitigate cognitive biases in predicting student dropout comparing Explainable Boosting Machine (EBM), Logistic Regression and XGBoost models.

Sorav Kumar Singh, Alak Roy and Rajneesh Raushan from India focus their research on underwater wireless sensor networks and propose a Residual Energy-Aware Fuzzy-Based Clustering Algorithm (REAFCA), which presents an enhanced framework to improve network performance and addresses issues with energy usage.

Juan Morales-García, Fernando Terroso-Sáenz, Andrés Bueno-Crespo, and  José M. Cecilia from Spain discuss in their research the analysis of synthetic timeseries as an enabler to improve region-based human mobility forecasting by applying Generative adversarial network (GANs) to generate synthetic time-series mobility data.

Igor Tomičić,  Petra Grd, and Andrija Bernik from Croatia present in their research a comprehensive analysis of the integration of artificial intelligence into threat intelligence (TI) systems focusing on its potential to enhance cybersecurity operations by an extensive literature review including machine learning, deep learning, and natural language processing for automating threat detection, classification, and analysis.

And last but not least, Daniel Spiekermann from Germany investigates in his research the real-world behaviour of network traffic within virtualized environments to identify the key factors that impact packet dynamics, including VM operations, multi-tenancy, user customization, and hardware adjustments.

Enjoy Reading!

Best regards,

Christian Gütl, Managing Editor-in-Chief