The quest for quality postgraduate research productivity through education is on the increase. However, in the context of the African society, governance structures and policies seem to be impacting on the quality level of the provided education. Hence, this conceptual study explored the roles of governance structures and policies in enhancing and ensuring quality postgraduate education programmers in African institutions of higher learning. To this end, various relevant literature was reviewed. The findings showed amongst others that governance structures and policies affect the quality of education provided. Meanwhile, other factors such as curriculum, foreign influence, lack of resources, training, amongst others contribute to the quality of education provided. The study concludes that there is need for the current structures of governance and the designed and implemented policies for postgraduate education to be reviewed and adjusted towards ensuring the desired transformation.

The objective of this study was to examine the impact of utilizing smart algorithms on enhancing the operational performance of sports facilities in the Kingdom of Saudi Arabia. These algorithms, based on principles and concepts of artificial intelligence, aim to achieve functions such as learning, decision-making, data analysis, pattern recognition, planning, and problem-solving. The study aimed to identify the extent to which smart algorithms are utilized in sports facilities, assess the level of operational performance, explore the correlation between the use of smart algorithms and operational performance, and predict the level of operational performance based on the use of smart algorithms. The study employed a descriptive approach, specifically utilizing a survey study method. Participants included chairmen and members of boards of directors, executive directors, sports directors, administrators, specialists, and members of various committees. The study sample was intentionally selected from different categories within the study population. Two questionnaires were used to collect data from 325 participants. The findings revealed a lack of utilization of smart algorithms in sports facilities in the Kingdom of Saudi Arabia, indicating a low level of operational performance. Additionally, a correlation was observed between the use of smart algorithms and operational performance, suggesting that the level of operational performance can be predicted based on the utilization of smart algorithms. The study concludes that the implementation of intelligent algorithms can enhance the operational performance of sports facilities in the Kingdom of Saudi Arabia. It provides valuable insights into the effects of utilizing smart algorithms on improving operational performance.

The Mass Rapid Transit (MRT) Purple Line project is part of the Thai government’s energy- and transportation-related greenhouse gas reduction plan. The number of passengers estimated during the feasibility study period was used to calculate the greenhouse gas reduction effect of project implementation. Most of the estimated numbers exceed the actual number of passengers, resulting in errors in estimating greenhouse gas emissions. This study employed a direct demand ridership model (DDRM) to accurately predict MRT Purple Line ridership. The variables affecting the number of passengers were the population in the vicinity of stations, offices, and shopping malls, the number of bus lines that serve the area, and the length of the road. The DDRM accurately predicted the number of passengers within 10% of the observed change and, therefore, the project can help reduce greenhouse gas emissions by 1289 tCO₂ in 2023 and 2059 tCO₂ in 2030.

This study explores the impact of technology effectiveness, social development, and opportunities on higher education accessibility in Myanmar, focusing on private higher education institutions. Utilizing a sample of 199 respondents, with an average age of X (SD = Y), the research employs standardized questionnaires and descriptive statistics, correlation analysis, and multiple regression analysis to examine the relationships between these variables. The findings indicate that technology effectiveness significantly enhances higher education accessibility, with strong positive correlations (r = 0.752, p < 0.001) and substantial impacts on educational outcomes (β = 0.334, p = 0.001). Social development also plays a crucial role, demonstrating that supportive social norms and community engagement significantly improve accessibility (β = 0.405, p < 0.001). Opportunities provided by technological advancements further contribute to enhanced accessibility (β = 0.356, p < 0.001), although socio-political and economic challenges pose significant barriers. The study highlights the interconnectedness of these factors and their collective influence on educational accessibility. Practical implications include the need for strategic investments in technological infrastructure, promotion of supportive social environments, and innovative solutions to leverage opportunities. Future research directions suggest longitudinal studies, broader demographic scopes, and in-depth analyses of specific technological and infrastructural challenges. By addressing these areas, stakeholders can develop effective strategies to improve higher education accessibility, ultimately contributing to the socio-economic development of Myanmar.