https://ijitra.com/index.php/ijitra/issue/feed 2024-12-20T00:00:00+00:00 Editor editorial@prismapublications.com Open Journal Systems International Journal of Information Technology, Research and Applications https://ijitra.com/index.php/ijitra/article/view/111 2024-09-30T18:06:01+00:00 Zafar Iqbal zaffarkhan85@yahoo.com Ahthasham Sajid ahthasham.sajid@riphah.edu.pk Muhammad Nauman Zakki naumanzakki@gmail.com Adeel Zafar adeel.zafar@riphah.edu.pk Arshad Mehmood arshmail0808@gmail.com

<table width="590"> <tbody> <tr> <td width="385"> <p>In this study the authors have examines various machine learning algorithms that could be used in IDS for making secure IoT and Smart Cities. The study examines various deep learning architectures of supervised, unsupervised, and semi-supervised learning methods to improve security and resource usage. Federated learning, edge computing, explainable AI, adversarial machine learning defense, and transfer learning are also explored for smart farming and IoT challenges. Machine learning has the potential to improve security and agricultural sustainability, but it must be researched and developed.&nbsp;</p> <p>&nbsp;</p> </td> </tr> </tbody> </table>

2024-11-15T00:00:00+00:00 Copyright (c) 2024 Zafar Iqbal, Ahthasham Sajid, Muhammad Nauman Zakki, Adeel Zafar, Arshad Mehmood https://ijitra.com/index.php/ijitra/article/view/110 2024-09-14T22:03:05+00:00 Dave Sarran dave.sarran@uog.edu.gy Saeed Abdul Karim abdul.karim@uog.edu.gy

<p>Public sector organisations in Guyana recognise the need to handle and manage sensitive data properly. Proper data governance is the solution. Identifying the factors that would influence the design of data governance models helps to ensure the creation of a solid model and data quality management. This study accumulated factors from the literature and presented them to IT professionals in Guyana. The Contingency Model served as a base for the identified factors to work together to create a company-specific model for data quality management. Thematic analysis was employed to analyse nine (9) interview transcriptions from medium to high-level personnel across different public sector organisations in Guyana. The factors identified were refined to the Guyanese context. Culture emerged as an indigenous factor in this study. This research resulted in an emergent model that can now be used to design data governance models for public sector organisations in Guyana</p>

2024-11-15T00:00:00+00:00 Copyright (c) 2024 Dave Sarran, Abdul Karim