Addressing the worldwide crisis of inadequate physical education (PE) programs requires immediate attention. Despite the advocacy of international organizations like UNESCO and WHO, there still needs to be a significant gap in understanding the effectiveness of PE initiatives globally. Cultural, socio-economic, and policy differences further complicate evaluating and improving these programs. More comprehensive research is needed to promote academic achievement, well-being, and overall health. This is where Global Innovations in Physical Education and Health comes in, a groundbreaking solution poised to revolutionize PE on a global scale. This innovative book serves as a beacon of hope by exploring diverse teaching strategies and creative methods worldwide. Bridging critical research gaps empowers policymakers, educators, researchers, administrators, and health professionals with actionable insights to enhance the quality and inclusivity of PE programs. With its comprehensive coverage of topics such as adaptive PE, nutritional education, and global health initiatives, this book provides a roadmap for transforming PE into a catalyst for holistic health and lifelong well-being.

PE often finds itself overlooked in the broader discourse on educational innovation, despite its crucial role in fostering lifelong health and well-being. Unlike subjects that easily attract attention due to their academic prestige or technological allure, PE is sometimes seen as secondary, relegated to the sidelines of educational reform. Yet, in an age where global health challenges such as obesity, mental health disorders, and sedentary lifestyles are increasingly prevalent (World Health Organization, 2020), the significance of PE cannot be understated. The Global Innovations in Physical Education and Health book seeks to challenge this perception by highlighting the transformative potential of innovative approaches in PE and health education (Garcia, Lopez Cabrera, et al., 2023). It brings together 69 experts from nine countries—Indonesia, Philippines, China, Ireland, United Arab Emirates, Portugal, India, USA, and Canada—to explore how these innovations are reshaping the way we teach, experience, and benefit from PE, making it a field deserving of as much attention and innovation as any other educational domain. This book serves as a crucial resource in guiding the development of more effective, inclusive, and culturally aware health and PE programs. It sets the foundation for actionable teaching and learning models in various educational and cultural contexts. The coverage includes insights into how different countries approach PE, the integration of health education within these programs, and their impact on student health and academic achievement.

Power system protection is essential for maintaining the reliability and stability of electrical grids, ensuring continuous service, and preventing catastrophic failures. As power systems evolve to incorporate renewable energy and increasingly complex configurations, the role of Artificial Intelligence (AI) in enhancing protection mechanisms has become indispensable. This paper reviews the integration of AI in power system protection, highlighting its potential to improve fault detection, adaptive protection strategies, predictive maintenance, and real-time monitoring. AI techniques, including machine learning, deep learning, and expert systems, offer significant advancements in overcoming the limitations of traditional protection schemes. Furthermore, the integration of AI contributes to the development of resilient and sustainable infrastructure, supports innovation in intelligent urban systems, and enhances the reliability of modern power grids. Despite its promising potential, challenges such as data scarcity, model scalability, and real-time processing need to be addressed for effective implementation. This review synthesizes the current literature on AI applications in power system protection, comparing them with conventional methods, and provides information on future research directions and practical applications to improve energy reliability, sustainable urban development, and industrial innovation.

With the increasing popularity of Raspberry Pi (RPi) comes the increase in available use cases and projects that utilize this single-board computer. One of these uses cases is the RPi Cluster, where multiple nodes are connected to a local network to form one logical resource pool. Implementing this build, however, can be a tedious and needs manual intervention such that each node needs to be configured to the cluster, one-by-one. While easily implementable if the scale is relatively small, the task becomes complex if several nodes need to be configured all at once. To save time, as well as to automate the whole process, developers and hobbyists would use Docker Swarm as an alternative. This paper explores the possibility of going beyond the popular Docker Swarm by proposing the use of OpenStack, a Cloud Computing Platform, as an alternative. Document analysis and review of existing research were used to prove the build’s technical feasibility. After comparing five relevant use cases, it can be concluded that deploying OpenStack to the RPi Cluster, or OpenStack-on-RPi, is feasible, though further research and testing that will optimize this use case is recommended.

This study focuses on the evaluation of a faculty Performance Modeling System, recognizing the critical role of faculty performance in educational quality and institutional success. Although previous research has often concentrated on the technical development and predictive capabilities of such systems, this paper shifts the focus to user acceptance and system efficacy from the perspective end-users, the faculty. To achieve this, the researchers propose and apply a Modified Technology Acceptance Model (TAM) as the theoretical framework for evaluation. This modified TAM incorporates specific constructs relevant to the academic environment and faculty roles, such as perceived impact on teaching effectiveness and perceived relevance to professional development, alongside traditional TAM constructs like perceived usefulness and perceived ease of use. The evaluation methodology involves assessing faculty perceptions and attitudes towards the system, utilizing both quantitative and qualitative data to understand factors influencing its adoption and continued use. The findings are expected to provide valuable insights into the practical applicability and user acceptance of faculty modeling systems, guiding future design and implementation efforts to ensure these tools effectively support faculty growth and institutional objectives.