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.

The paper considers an important problem of the successful development of social qualities in an individual using machine learning methods. Social qualities play an important role in forming personal and professional lives, and their development is becoming relevant in modern society. The paper presents an overview of modern research in social psychology and machine learning; besides, it describes the data analysis method to identify factors influencing success in the development of social qualities. By analyzing large amounts of data collected from various sources, the authors of the paper use machine learning algorithms, such as Kohonen maps, decision tree and neural networks, to identify relationships between different variables, including education, environment, personal characteristics, and the development of social skills. Experiments were conducted to analyze the considered datasets, which included the introduction of methods to find dependencies between the input and output parameters. Machine learning introduction to find factors influencing the development of individual social qualities has varying dependence accuracy. The study results could be useful for both practical purposes and further scientific research in social psychology and machine learning. The paper represents an important contribution to understanding the factors that contribute to the successful development of individual social skills and could be useful in the development of programs and interventions in this area. The main objective of the research was to study the functionalities of the machine learning algorithms and various models to predict the students’s success in learning.

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.