https://geniusjournals.org/index.php/ejmc <p><strong>Eurasian Journal of Media and Communications (EJMC</strong><strong>)</strong> is an Open Access, Peer Reviewed, International, Refereed, Scientific Journal that publishes original research and review articles related to diverse research in Media and Communications.</p> <p>The main objective of <strong>Eurasian Journal of Media and Communications (EJMC) </strong>is to offer an intellectual platform to the international scholars and it aims to promote interdisciplinary studies in areas of Media and Communications. All manuscripts must be prepared in English language and subject to a rigorous peer-review process. The scope of the journal is not limited to-</p> <p>Communication studies, media studies, cultural studies, anthropology, telecommunications, sociology, politics, public policy, migration studies, economics, geography/urban studies, transnational security and international relations.</p> <p> </p> <p><strong>ISSN (E):</strong> 2795-7632</p> <p><strong>Journal Impact Factor:</strong> 7.760</p> Genius Journals en-US Eurasian Journal of Media and Communications 2795-7632 https://geniusjournals.org/index.php/ejmc/article/view/6447 <p>At the academic and scientific levels, the subject of "Enhancing Cognitive Knowledge in Television Programs: An Analytical Study of a Program "Red Cat Program"" is quite important. By improving the way information is presented and how viewers engage with it, cognitive expertise is essential to television show design. At the academic and scientific levels, the subject of "Enhancing Cognitive Knowledge in Television Programs: An Analytical Study of a Program "Red Cat Program"" is quite important. By improving the way information is presented and how viewers engage with it, cognitive expertise is essential to television show design. Designers may produce more captivating visual and aural experiences by utilizing principles of perception, such as how viewers interpret colors and sounds. Designers may produce more captivating visual and aural experiences by utilizing principles of perception, such as how viewers interpret colors and sounds. Programs can, for instance, highlight dramatic features or draw viewers' attention to crucial information by using particular visual strategies. Furthermore, knowing how the brain processes information aids in creating powerful stories that increase the audience's psychological involvement and concentrate on comprehending the messages being presented, thereby boosting the programs' emotional effect. Programs can, for instance, highlight dramatic features or draw viewers' attention to crucial information by using particular visual strategies. Furthermore, knowing how the brain processes information aids in creating powerful stories that increase the audience's psychological involvement and concentrate on comprehending the messages being presented, thereby boosting the programs' emotional effect. Between April 10, 2024, and May 9, 2024, during Ramadan, the UTV channel's "Red Cat" program was the subject of the study. The study comprised a thorough analysis of all 30 episodes of the show from the Ramadan season of 2024. Between April 10, 2024, and May 9, 2024, during Ramadan, the UTV channel's "Red Cat" program was the subject of the study. The study comprised a thorough analysis of all 30 episodes of the show from the Ramadan season of 2024</p> Rasha Mohammed Naji Copyright (c) 2024 https://creativecommons.org/licenses/by-nc/4.0 2024-11-06 2024-11-06 32 1 12 https://geniusjournals.org/index.php/ejmc/article/view/6465 <p>The expansion of distance education systems, especially during the COVID-19 pandemic, has played a crucial role in ensuring uninterrupted learning at educational institutions. However, ensuring the security of these systems and monitoring academic integrity remain pressing issues. Traditional authentication methods (such as login and password) are not sufficiently reliable for authenticating the identity of users. Consequently, the need for biometric authentication, particularly facial recognition technologies, is increasing. This study presents an advanced information model for verifying the authenticity of a user’s face in distance education through video footage. The model is based on convolutional neural networks (CNN) and employs robust tools such as dlib for facial detection and verification algorithms. The collected video data is analyzed under various conditions (lighting, angle changes, and facial expressions), ensuring the model’s stability and accuracy. The scientific foundation of the model lies in the deep learning methods, which are highly effective for in-depth analysis of images and extracting biometric facial features. The process of assessing facial authenticity incorporates algorithms that consider the 3D structure of the face, thereby providing protection against spoofing attacks (such as using photos or videos for forgery). The model’s efficiency was demonstrated in comprehensive testing, achieving a facial authenticity detection accuracy of 95%. The proposed information model has significant practical importance for making distance education systems more secure and reliable. In the future, integrating this approach with other biometric authentication methods could further enhance the security of distance learning environments</p> Mardiyev Muslimbek G‘ulom o‘g‘li Copyright (c) 2024 https://creativecommons.org/licenses/by-nc/4.0 2024-11-08 2024-11-08 32 13 16