Editorial - Christian Gütl (Journal of Universal Computer Science)
Dear Readers,It gives me great pleasure to announce the sixth regular issue of 2025. In this issue, 4 papers by 11 authors from 3 countries - Brazil, Italy, Republic of Korea - cover various topical aspects of computer science. In a continuous 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.As always, I would like to thank all the authors for their sound research and the editorial board members and guest reviewers for their extremely valuable review effort and suggestions for improvement. I also want to thank the readers for their interest in our articles, which is reflected in the consistently high number of user accesses and PDF downloads. These contributions, together with the generous support of the KOALA initiative, maintain the quality of our journal.In the sixth regular issue, I am very pleased to present the following 4 accepted articles: Michele Berti, Matheus Camilo da Silva, Sebastiano Saccani, and Sylvio Barbon from Italy focus their research on synthetic data generation as an alternative to traditional data anonymization based on variational autoencoders to generate high-quality synthetic tabular datasets.Roger Vieira and Kleinner Farias from Brazil introduce in their research CognIDE, a tool-supported methodology that aims to seamlessly integrate psychophysiological data linked to cognitive indicators into VS Code by offering actionable contextual cues alongside dynamic source code.Pedro Henrique Dias Valle and Elisa Yumi Nakagawa from Brazil discuss in their research a catalog of the main interoperability architectural solutions for addressing the four levels of interoperability - namely technical, syntactic, semantic, and organizational – for solving interoperability issues in software systems by analyzing 65 studies from the scientific literature.Ji Woong Yoo, Kyoung Jun Lee and Arum Park from the Republic of Korea explore the potential of deep learning techniques - Long Short-Term Memory (LSTM) algorithm and Word2Vec model – for cleansing malicious comments from users, and enhancing the ethical nature of AI systems.Enjoy Reading!Christian Gütl, ManagingEditor-in-Chief