The present study focuses on improving Cognitive Radio Networks (CRNs) based on applying machine learning to spectrum sensing in remote learning scenarios. Remote education requires connection dependability and continuity that can be affected by the scarcity of the amount of usable spectrum and suboptimal spectrum usage. The solution for the proposed problem utilizes deep learning approaches, namely CNN and LSTM networks, to enhance the spectrum detection probability (92% detection accuracy) and consequently reduce the number of false alarms (5% false alarm rate) to maximize spectrum utilization efficiency. By developing the cooperative spectrum sensing where many users share their data, the system makes detection more reliable and energy-saving (achieving 92% energy efficiency) which is crucial for sustaining stable connections in educational scenarios. This approach addresses critical challenges in remote education by ensuring scalability across diverse network conditions and maintaining performance on resource-constrained devices like tablets and IoT sensors. Combining CRNs with new technologies like IoT and 5G improves their capabilities and allows these networks to meet the constantly changing loads of distant educational systems. This approach presents another prospect to spectrum management dilemmas in that education delivery needs are met optimally from any STI irrespective of the availability of resources in the locale. The results show that together with machine learning, CRNs can be considered a viable path to improving the networks’ performance in the context of remote learning and advancing the future of education in the digital environment. This work also focuses on how machine learning has enabled the enhancement of CRNs for education and provides robust solutions that can meet the increasing needs of online learning.

This study aims to examine the impact of an innovative self-directed professional development (SDPD) model on fostering teachers’ professional development and improving their ability to manage this development independently. A quantitative research method was adopted, involving 60 participants from Almaty State Humanitarian and Pedagogical College No. 2, Almaty, Kazakhstan. Descriptive and inferential statistics were used to assess the SDPD model’s effectiveness, specifically in promoting teacher engagement, adoption of new pedagogical techniques, and improvement in reflective practices. The study findings reveal that teachers, particularly in developing regions, often face challenges in accessing formal professional development programs. The implementation of the SDPD model addresses these barriers by providing teachers with the tools and strategies required for self-improvement, regardless of geographic or economic constraints. The study participants in the pilot phase showed increased engagement with new pedagogical methods, improved reflective practices, and greater adaptability to emerging educational technologies. The algorithmic aspect of the model streamlined the professional development process, while the activity-based approach ensured that learning remained practical and relevant to teachers’ everyday needs. By offering a clear framework for continuous improvement, the model addresses the gaps in formal training access and cultivates a culture of lifelong learning. These findings suggest that the SDPD model can contribute to elevating teaching standards globally, particularly in regions with limited professional development resources.

The main purpose of this research is to investigate the cash holdings behaviour on sectoral level for South African firms listed on the Johannesburg Stock Exchange (JSE). The accounting cash ratio is used to identify abnormal (excess) cash holdings for the firms listed on the JSE. This informed the panel regression analysis to identify cash holdings determinants on a sectoral level. The sample data included 255 firms of which 102 represent Financial Firms and 153 represent Non-Financial Firms for 2005 to 2019. The findings show the significant internal and external determinants of cash holdings. Comparing coefficient sizes, this research finds that financial and non-financial sectors with abnormal (excess) cash holdings exhibit higher coefficient sizes as opposed to sectors without. As a result, the higher coefficient size shows that the internal and external determinants of cash holdings have a greater effect on the cash holding levels of these sectors. The implications of the findings of this study are that each sector operates differently and that each firm within each sector has differing cash management policies and procedures. Therefore, analyzing cash holdings behaviour on an aggregated level and assuming that all sectors and firms within the collective operate the same is an erroneous assumption, as shown by this study. This research firstly contributed by introducing the use of the accounting cash ratio to indicate the presence of abnormal (excess) cash holdings. Most research focus on cash holdings of Non-Financial Firms. Therefore, the second contribution of this research is that both Non-Financial and Financial Firms with and without abnormal (excess) cash holdings were included to identify determinants of cash holdings, this was also done on a sectoral level.

With the declaration of the Sustainable Development Goals (SDGs), the importance of localisation principles and, consequently, the local-level institutions in implementing development policies came to the forefront. India adopted a thematic approach by condensing the seventeen goals into nine themes, to be worked upon by the local administrative units, furthering that each Village Panchayat (constitutionally known as Grama Panchayats) should select a theme in a plan year and strive towards attaining it. For the South Indian state of Kerala, with its good trajectory of decentralised governance, this localisation process of SDGs was rather smooth. In this article, we discuss the case of the best-performing Grama Panchayat (GP) in Kerala, which has identified ‘Village with Self-Sufficient Infrastructure’ as the development theme. Through qualitative research methodology, we examine how the Panchayat included projects specific to this theme in the development plans and how the implementation helped produce effects on multidimensional aspects of SDGs using the SDG Impact Assessment Tool. The case studies of different infrastructure-based projects endorse that with proper planning and implementation of such projects, the lowest tier of administration can significantly contribute to the improvement of development goals. We have delineated full fund utilisation through convergence schemes, community participation, and strong monitoring mechanisms as the factors leading the selected Panchayat to be the champion of the cause. The accomplishment exhibited by the Panchayat by integrating SDGs into the Village Development Plan through the projects on the theme of self-sufficient infrastructure can be well emulated by other local bodies across the world.