The golden visa is a regulation designed to facilitate foreign nationals through a residence permit scheme with an emphasis on investment and citizenship. This research aims to look at the development of the golden visa as an innovation policy, and find out how its implications for the flow of foreign investment into Indonesia. This research uses online research methods (ORM) to discover new facts, information and conditions through technology and internet searches. The aspects used to conduct analysis in this descriptive qualitative research are using innovation policy instruments which include regulatory, economic, financial, and soft instruments. The research findings show that the golden visa as an innovation policy has great potential to support national development through investment in priority sectors. However, its implementation needs to be done carefully with strict supervision and inclusive regulations so as to mitigate risks such as money laundering and property price inflation. That way, golden visas can encourage sustainable and inclusive economic growth through the smooth flow of incoming foreign investment.

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 investigates the integration of sustainability principles into educational curricula, focusing on the gap between theoretical knowledge and practical application. Through a mixed-methods approach, the research identifies key institutional barriers, including outdated policies, insufficient teacher training, and limited resources. These barriers hinder the effective incorporation of sustainable development principles into education. The study reveals that while some educational systems struggle to adopt sustainability, examples from progressive institutions show that integrating these principles enhances student awareness and equips them with skills essential for sustainable development. The findings suggest that substantial changes are needed in existing educational frameworks to better support sustainability in curricula. Recommendations for future research include conducting longitudinal studies to assess the long-term impact of curriculum changes on sustainability outcomes and exploring the role of technology in advancing sustainable education. Policy recommendations emphasize the need for advocacy and the implementation of actionable strategies, such as industry collaborations for pilot projects and real-world applications. Furthermore, institutional support for teacher professional development is crucial, with structured programs that combine theoretical knowledge and practical skills in sustainability. Enhancing partnerships between educational institutions and industries, including co-designed curriculum modules and internship opportunities, is also essential for aligning education with the Sustainable Development Goals. This study highlights the importance of transforming educational practices to better address the challenges of sustainable infrastructure development, ultimately preparing students to contribute to a more sustainable future.

This longitudinal study is dedicated to the evaluation of the comprehensive impact of educational reforms through a mixed research methodology which is a combination of the quantitative- and qualitative-oriented research methods to check the students’ outcomes. Data was collected in the span of [mention the time frame] from various data sources for instance standardized test scores, school performance statistics, and through open-ended qualitative evaluation from both students and teachers. Data analysis carried on after the reforms had been put in place revealed that there was a considerable rise in mean test scores and success graduation rates. Therefore, formative evaluation demonstrates the need for implementing reforms that will eventually help the students in boosting academic performance. Besides, there is no difference among investor opinions on teachers, administrators, and students who are involved with the implementation of the reforms. Stakeholders manifest this new assistance as an outcome of lasting improvements in curriculum quality, methods of teaching, and student participation. The study approaches two main challenges that are confronted with education reform that is resourcelessness and to society the change of the educational system can be more suitable for the students to excel academically and it can have an impact on the whole community. Even though this study makes important advancements toward the realization of the complex education implementation process and its effect on student academics, there are elements in which it can be criticized. Both quantitative and qualitative performance improvement is important as well as all the important stakeholder participation. This way the transformation process becomes layered. In other words, these results point to the necessity of planning interventions for longer periods that target the challenges and the forces that maintain the low levels of education performance by the counties.

Physical sampling of water on site is necessary for various applications like drinking water quality checking in lakes and checking for contaminants in freshwater systems. The use of water surface vehicles is a promising technology for monitoring and sampling water bodies, and they offer several advantages over traditional monitoring methods. This project involved designing and integrating a drone controller, water collection sampling contraption unit, and a surveillance camera system into a water surface vehicle (WSV). The drone controller unit is used to operate the boat from the starting location until the location of interest and then back to the starting location. The drone controller has an autopilot system where the operator can set a course and be able to travel following the path set, whereas the WSV will fight the external forces to keep itself in the right position. The water collection sampling unit is mounted onto WSV so when it travels to the location, it can start collecting and holding water samples until it returns to the start location. The field of view (FOV) surveillance camera helps the operator to observe the surrounding location during the operation. Experiments were conducted to determine the operational capabilities of the robot boat at the Ayer Keroh Lake. The water collection sampling contraption unit collected samples from 44 targeted areas of the lake. The comprehensive examination of 14 different water quality parameters were tested from the collected water samples provides insights into the factors influencing the pollution and observation of water bodies. The successful design and development of a water surface surveillance and pollution tracking vehicle marks the key achievements of this study. The developed collection and surveillance unit holds the potential for further refinement and integration onto various other platforms. They are offering valuable assistance in water body management, coastal surveillance, and pollution tracking. This system opens up new possibilities for comprehensive water body assessments, contributing to the advancement of sustainable and efficient water testing. Through careful sampling efforts, a thorough overview of the substances presents in the water collected from Ayer Keroh Lake has been compiled. This in-depth analysis provides important insights into the lake’s current condition, offering valuable information about its ecological health.