The issue of quality of higher vocational education in China has become a common concern in all aspects of society, and promoting the improvement of the quality of education within higher vocational colleges is an important way to realize the high-quality development of higher vocational education. Based on the self-constructed five-dimensional model of factors influencing the improvement of the quality of education within higher vocational colleges, an empirical study was conducted using questionnaires and SPSS27.0 software on the teacher and student groups within 13 higher vocational colleges in Hainan Province, and the results showed that the teacher groups of different genders, titles, ages, academic qualifications and disciplines as well as the student groups of different genders and admission modes have different opinions on factors such as the level of governance, education and teaching, the integration of industry and education, student development and policy guarantees; and that there are different degrees of perception differences between teachers’ and students’ groups on the effect of internal education quality improvement. In order to promote the internal quality improvement of higher vocational colleges, it is necessary to improve the construction of modern university system to enhance the governance level, deepen the integration of production and teaching to innovate the education and training mode of talents, promote the development of the whole chain of education to improve the comprehensive quality of students, strengthen the construction of teaching staff to deepen the reform of education and teaching, and innovate the internal education policy and system to regulate the management order.

Smart electric meters play a pivotal role in making energy systems decarbonized and automating the energy system. Smart electric meters denote huge business opportunities for both public and private companies. Utility players can manage the electricity demand more efficiently whereas customers can monitor and control the electricity bill through the adoption of smart electric meters. The study examines the factors affecting the adoption intention of smart electric meters in Indian households. This study draws a roadmap that how utility providers and customers can improve the smart electric meters adoption. The study has five independent variables (performance expectancy, effort expectancy, social influence, environmentalism, and hedonic motivation) and one dependent variable (adoption intention). The sample size for the study is four hundred and sixty-two respondents from Delhi and the National Capital Region (NCR). The data was analysed using structural equation modelling (SEM). The results of this study have confirmed that performance expectancy, environmentalism, and social influence have a significant impact on the intention of adopting smart electric meters. Therefore, utility providers can improve their strategies to attract more customers to adopt smart electric meters by focusing more on the performance of smart electric meters and by making them environmentally friendly. This research offers meaningful insights to both customers and utility providers to make energy systems decarbonized and control energy consumption.

This research explores the relationship between the independent variables (need for achievement, risk-taking, family support, economic factors, and the dependent variable of women’s enterprises’ success) and examines the moderating influence of socio-cultural factors. A survey-based methodology was adopted. One hundred sixty-nine small and medium-sized enterprises (SMEs) in the Palestinian West Bank were surveyed using structured questionnaires. Structural equation modeling (SEM) was conducted by using the Smart-PLS program. The results indicate that women entrepreneurs’ success in SMEs is positively and significantly impacted by the need for achievement as an internal factor and economic factors and family support as external factors. Furthermore, sociocultural factors did not show any significant moderating influence. By gaining knowledge about the relationship between internal and external factors and the success of women-owned SMEs, this study adds to the body of literature already in existence. These factors can be considered in the success of these enterprises, particularly in an environment full of political and economic fluctuations. Furthermore, the research is said to be the first of its type in Palestine, particularly concerning SMEs run by women. It also supports entrepreneurs by providing them with resources that might aid in the growth and success of their businesses.

With the popularization of the Internet and the rapid development of computer network technology, human beings have entered a brand new era - the information age. This kind of network technology beyond space not only brings well-being to people, but also subtly affects the ideas and behaviors of teenagers. It not only changes their lifestyle and values, but also quietly makes them mentally ill, resulting in an endless series of problems of juvenile cybercrimes. For the purpose of promoting the governance of Internet crimes among young people effectively and avoiding crimes among special groups of young people, this paper plans to base on the concept of Internet crimes of teenagers, summarize the characteristics of youth crimes in our country, analyze its influence factors and propose the measures to deal with it.

This study examines the adoption and usability of lifestyle (LS) apps, considering demographic factors like age and education that influence adoption decisions. The study employed a mixed-methods design, combining an experiment (spanning 14 weeks of app use) with semi-structured interviews and periodic measurements. The researchers employed the Mobile Application Usability Questionnaire (MAUQ) to identify pivotal aspects of standalone app usability, interface satisfaction, and usefulness at various stages of use, with a particular emphasis on the experiences of Hungarian students (n = 36). The results demonstrate that health-related factors have a significant impact on students’ behavior and evaluation of lifestyle apps over the 14-week period. Overall, the analyzed LS apps demonstrated positive outcomes in terms of supporting subject health and significantly improving the perceived health state. The findings highlight both practical and theoretical contributions to the field of mobile health applications, suggesting avenues for further research to either confirm or challenge existing theories.

This study evaluated the performance of several machine learning classifiers—Decision Tree, Random Forest, Logistic Regression, Gradient Boosting, SVM, KNN, and Naive Bayes—for adaptability classification in online and onsite learning environments. Decision Tree and Random Forest models achieved the highest accuracy of 0.833, with balanced precision, recall, and F1-scores, indicating strong, overall performance. In contrast, Naive Bayes, while having the lowest accuracy (0.625), exhibited high recall, making it potentially useful for identifying adaptable students despite lower precision. SHAP (SHapley Additive exPlanations) analysis further identified the most influential features on adaptability classification. IT Resources at the University emerged as the primary factor affecting adaptability, followed by Digital Tools Exposure and Class Scheduling Flexibility. Additionally, Psychological Readiness for Change and Technical Support Availability were impactful, underscoring their importance in engaging students in online learning. These findings illustrate the significance of IT infrastructure and flexible scheduling in fostering adaptability, with implications for enhancing online learning experiences.