In the context of education informatization construction, the heavy responsibility of promoting the integration of new technologies into the classroom falls on the shoulders of educators. With the increasing maturity of virtual technology, a new classroom form gradually comes into our view. In this study, we use "Physics Lab" to carry out inquiry-based teaching, provide a virtual experiment platform, help students to construct knowledge through inquiry, and provide theoretical and practical references for teachers.

This bibliometric review evaluates the research progress and knowledge structure regarding the impact of supporting facilities on halal tourism development. Using the Scopus database and bibliometric analysis with the “bibliometrix” package in R, the study covers the period from 2016 to 2023. The search, employing keywords like “halal tourism,” “facilities,” “infrastructure,” and “local support,” identified 26 relevant publications. The findings highlight a limited body of research, with the Journal of Islamic Marketing being the most active publisher in this area, contributing six articles. Indonesia emerges as a leading contributor to halal tourism research, driven by its significant Muslim population and the economic potential of this niche market. Key facilities, such as mosques, musholla, and high-quality halal food options, are identified as crucial factors influencing Muslim travelers’ destination choices. This review provides a comprehensive overview of the current research landscape on supporting facilities in halal tourism and highlights opportunities for future investigation to further enrich the field.

The goal of this research is to determine whether hospital financial performance is impacted by particular management accounting techniques, such as departmental revenue budgeting, specific costing, and departmental costing. We analyzed several sets of performance indicators for 146 hospitals whose management accounting adoption status is available. An outlier test was used to determine which data were outliers at the 0.1% significance level, and the results were then eliminated in order to see if any extremely outlier values (hospitals) were present for each indicator. To determine whether there were any noteworthy variations in the average values of the several performance measures, we employed a t-test (two-tailed probability). The results suggest that departmental revenue budgeting and departmental and specific costing improve hospital financial performance.

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.

Amidst China’s burgeoning population and rapid technological strides, this study explores how elderly citizens navigate and embrace electronic governance (e-governance) platforms. Addressing a crucial gap in knowledge, we delve into their limited digital fluency and its impact on e-governance adoption. Our meticulously crafted online survey, distributed via WeChat across significant cities (Beijing, Shanghai, Tianjin, Changsha), yielded 396 responses (384 analyzable). Utilizing Structural Equation Modeling (SEM), we unearthed key influencers of subjective norms, including perceived ease and usefulness, trust, supportive conditions, and past tech exposure. These norms, in turn, positively shape attitudes. Crucially, educational background emerges as a moderator, amplifying the positive link between attitudes and e-governance engagement intent. This underscores the necessity of an inclusive, customized e-governance approach, offering valuable policy insights and advocating for holistic solutions for older adults. Our research yields empirical and theoretical contributions, paving the way for actionable Social Sustainability Marketing Technologies in China, particularly championing digital inclusivity for seniors.