Dear Readers,

I am very happy to announce the fourth regular issue of 2025. In this issue, 4 articles by 14 authors from 4 countries (Brazil, Egypt, India, Indonesia) cover a variety of topical research aspects in computer science. Allow me to express my appreciation to all the authors for their sound research work and to thank the editorial board and guest reviewers for their extremely valuable reviews and suggestions for improvement. This continuous stream of relevant and novel contributions, along with the generous support of the KOALA initiative, helps to maintain the quality of our journal.

In the 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 issues for our journal.

In the fourth regular issue, I am very pleased to introduce the following four accepted articles: In their paper, Carlos Goetz, Rodrigo Simon Bavaresco, Wesllei Felipe Heckler, Gustavo Lazarotto Schroeder,  Rafael Kunst, and Jorge Luis Victória Barbosa from Brazil propose an ontology to identify stressors, considering personal and environmental data, which makes it possible to generate knowledge about work stressors in order to mitigate the problem utilizing a methodology consisting of seven stages and two evaluation phases. In their research, Manpreet Singh and Jitender Kumar Chhabra from India deal with fault prediction of multimedia software which integrates various multimedia heterogeneous components by a GA-based technique to combine multiple features using conjunction (AND) and disjunction (OR) operators while finding threshold values. Sarah Khater, Magda B. Fayek, and Mayada Hadhoud from Egypt present their research on human activity recognition (HAR) and discuss a GA-based approach to automatically generate ConvLSTM architectures for human activity recognition. And last but not least, Hendrik Hendrik, Silmi Fauziati, and Adhistya Erna Permanasari from Indonesia introduce an enhancing knowledge graph construction with automated source evaluation utilizing large language models.

Enjoy Reading!

Best regards,

hristian Gütl, Managing Editor-in-Chief