dc.contributor.author | Kozachenko, M. R. | en |
dc.contributor.author | Chekhmestruk, R. Y. | en |
dc.contributor.author | Чехместрук, Р. Ю. | uk |
dc.date.accessioned | 2025-04-04T11:02:14Z | |
dc.date.available | 2025-04-04T11:02:14Z | |
dc.date.issued | 2025 | |
dc.identifier.citation | Kozachenko M. R., Chekhmestruk R. Y. Intelligent software application for adaptive control of screen modes based on user activity analysis // Матеріали LIV науково-технічної конференції підрозділів ВНТУ, Вінниця, 24-27 березня 2025 р. Електрон. текст. дані. 2025. URI: https://conferences.vntu.edu.ua/index.php/all-fitki/all-fitki-2025/paper/view/23297. | uk |
dc.identifier.uri | https://ir.lib.vntu.edu.ua//handle/123456789/46241 | |
dc.description.abstract | This paper discusses the problem of the long-term effects of screen use on vision and overall user wellbeing. The concept of an intelligent software application is proposed, which analyzes user activity and automatically adjusts screen parameters according to the working conditions. Methods such as computer vision, machine learning, and behavior monitoring are employed. This approach allows for dynamic changes in brightness, contrast, and color temperature, reducing visual strain and improving user comfort. The architecture of the application is outlined, along with the prospects for its further development, including integration with operating systems and enhancement of adaptation algorithms. | en |
dc.language.iso | uk_UA | uk_UA |
dc.publisher | ВНТУ | uk |
dc.relation.ispartof | Матеріали LIV Всеукраїнської науково-технічної конференції підрозділів ВНТУ, Вінниця, 24-27 березня 2025 р. | uk |
dc.relation.uri | https://conferences.vntu.edu.ua/index.php/all-fitki/all-fitki-2025/paper/view/23297 | |
dc.subject | adaptive control | en |
dc.subject | screen parameters | en |
dc.subject | user activity analysis | en |
dc.subject | machine learning | en |
dc.subject | intelligent systems | en |
dc.title | Intelligent software application for adaptive control of screen modes based on user activity analysis | en |
dc.type | Thesis | |
dc.identifier.udc | 681.004.58 | |
dc.relation.references | Singh, S., McGuinness, M. B., Anderson, A. J., & Downie, L. E; Digital eye strain – A comprehensive
review. Clinical and Experimental Optometry. – 2022. 140p | en |
dc.relation.references | Sen A., Richardson S. Computer Vision Syndrome: A Worldwide Health Concern // Journal of Clinical
and Diagnostic Research. – 2015. Vol. 9, Issue 10. – P. 1–3. | en |
dc.relation.references | Filatov, D., & Filatov: Evolutionary algorithm based adaptive navigation in information retrieval
interfaces. – 2015, 10p | en |
dc.relation.references | Charu C. Aggarwal; Neural networks and deep learning. – 2023, 529p. | en |
dc.identifier.orcid | https://orcid.org/0000-0002-5362-8796 | |