bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development of a Big Data Analysis and Management Decision Support System for Student Mental Health in Higher Education
Authors: Zheng Fenping 
Published: July 2024

Abstract
In recent years, the number of psychological problems occurring in college students has been increasing day by day, and timely, convenient, and accurate psychological warning is an important way to prevent college students from psychological crises. Starting from the basic needs of the system and aiming at realizing the embedding of data mining technology in the psychological management system, this paper elaborates on the design and implementation of the data mining technology module suitable for the psychological management system. The clustering algorithm-K mean algorithm of data mining is used to distinguish groups of students with different categories of psychological problems, which provides data support for the next decision-making. Through simulation experiments between the system designed in this paper and four other mental health management systems, the clustering performance and system evaluation performance of this paper’s system are better than those of the other systems. The result of mining the mental health of college students through this system shows that 82.2% of the student’s assessment results show normal, and 8.35% of the students need to focus on, and this result is not much different from that obtained from the statistical survey of a personality questionnaire, which indicates that the use of clustering analysis in the system can be an effective prediction of the mental health of college students.
The Utility of “Industry 4.0” for Economic Development and Industrial Structure Change in Germany
Authors: Yan Jie , Liu Qiannan 
Published: July 2024

Abstract
Germany’s “Industry 4.0” strategy is a technological revolution that accelerates full penetration into industrial fields such as manufacturing, mainly based on the Internet of Things and the rapidly developing new generation of Internet technology as a carrier. This paper examines the implementation of Germany’s “Industry 4.0” strategy, focusing on R&D expenditures, capacity utilization rates, and CNC rates of key processes in the manufacturing industry. It also lays the groundwork for Germany’s economic development and the effects of industrial restructuring. We construct a regression model to analyze the impact of “Industry 4.0” on the German economy, using economic growth as a measure of economic development. We use the automobile industry as a representative to study the industrial restructuring and upgrading of Germany under the “Industry 4.0” strategy. The results demonstrate a positive correlation between the estimated coefficients of economic growth variables in each year from 2020 to 2022 and the industry’s value-added, passing the significance test at the 0.05 level. In the industrial restructuring, Germany’s automobile industry has realized the transformation from traditional manufacturing mode to intelligent manufacturing mode, and the 1387.2 billion euros of Volkswagen’s R&D investment also shows that Germany is still pursuing the technological upgrading of the industry.
Research on Personalized English Language Learning Based on Artificial Intelligence
Authors: Yang Kunlun 
Published: July 2024

Abstract
Although AI technology has been widely utilized in many fields and has reaped good reviews. However, there is a vacancy in the education field for AI technology to achieve personalized recommendations for the English language. In this paper, based on the traditional cognitive diagnostic model, we propose optimizing two aspects, namely question type and mastery state. Combining the neighborhood recommendation algorithm, the English learning recommendation model is constructed using fuzzy cognitive diagnosis. Based on the theory of adaptive learning, we have designed a personalized bank of recommended English learning questions. The model is utilized in the real world of English learning, and a control experiment is designed to evaluate the student’s knowledge mastery and the impact of the model application. The experiment shows that student A has a better mastery of S1 and S3, with mastery levels of 0.856 and 0.815, respectively, but only 0.235 for S4, and needs to customize a more targeted personalized learning plan and strategy for S4-related content. The average scores of D1 and D2 before practice were 73.51 and 72.18, and after practicing through the personalized recommending English learning methods proposed in this paper, the English score of the D2 class was improved to 85.33, and the t-test result between the two groups was significant p-value of 0.002, which is less than 0.01, indicating that there is a significant difference between the two groups and that the model proposed in this paper has a significant enhancement on English learning.
Analysis of Teaching Capacity Building of College Teachers’ Innovation and Entrepreneurship Education under Comprehensive Multiple Fuzzy Evaluation System
Authors: Zhao Ruochen , Xiang Xiaomi , Deng Qiqi , Zhao Ruoxiu 
Published: July 2024

Abstract
How can we effectively promote and improve the quality of innovation and entrepreneurship education in colleges and universities? The key lies in enhancing the capacity of teachers to impart innovative entrepreneurial education. The article takes the requirements of innovation and entrepreneurship education and the connotation of teaching ability as the orientation and establishes the evaluation index system of dual innovation education teaching ability of college teachers by combining the CIPP model. The IAHP method and the improved CRITIC method, respectively, calculate the subjective and objective weights of each index in the index system, and then they introduce the game theory idea to amalgamate and assign weights to the index system Based on the gray fuzzy mathematical theory, a fuzzy comprehensive evaluation model of the teaching ability of innovation and entrepreneurship education among college teachers was established. Using University Y as the research object, data analysis was carried out to determine the differences between teachers’ dual entrepreneurship teaching abilities, comprehensive evaluation, and the application effectiveness of the evaluation system. The maximum mean value for teachers’ innovative entrepreneurship education teaching ability is 4,085, and the minimum skewness coefficient is only −0.475, suggesting a trend towards correct skewness. Teachers’ mastery of dual-creation theory is proportionately weighted at 25.52%, and the fuzzy comprehensive evaluation score is 81.97, which is a good grade. The evaluation index system, combined with the fuzzy comprehensive evaluation model, can help college teachers clarify the problems of dual-creation education, which is conducive to improving their dual-creation teaching ability.
Integration Strategies of Sports Culture in Ethnic Areas and Volleyball Teaching in Colleges and Universities
Authors: Zhong Yuan 
Published: July 2024

Abstract
The integration of ethnic area sports culture and college sports teaching in the multicultural environment is the inevitable development of education and teaching in the new era. This paper combines the analysis of the impact of the school sports curriculum in a multicultural environment and the form of development of sports culture, combines the sports culture of ethnic areas with college volleyball teaching in order to promote the implementation of sports ideological and political education in colleges and universities and to realize the development of differences and unity in the context of multivariate evaluation of college volleyball teaching. Combine the objectives of college volleyball teaching with the national sports culture to construct the volleyball course content system. Propose methods for training teachers, create a knowledge map of college volleyball teaching materials, and use the enhanced TF-IDF algorithm to extract keywords and increase volleyball teaching resource allocation. Statistics of volleyball teaching in colleges and universities integrating national sports culture, analyzing the influence of learning atmosphere*teaching level, learning atmosphere*attention on the cultivation of national sports culture. Combine the improvement of volleyball skills, physical quality, and independent learning ability before and after teaching to analyze the advantages of college volleyball teaching that integrates ethnic sports culture. The overall mean value of “the current situation of volleyball teaching integrating ethnic sports culture” is 8.97, which is at a good level. In the three dimensions of learning motivation, learning process, and learning outcome, the P-value of the experimental class and the control class is less than or equal to 0.05, which indicates that the students in the experimental class are better than the students in the control class in the three dimensions of independent learning ability in sports. Volleyball teaching that integrates the sports culture of ethnic regions has the beneficial effect of promoting the development of sports culture as well as enhancing the development of students’ volleyball skills.
The Realistic Dilemmas and Possible Paths of Artificial Intelligence Enabling Teacher Education
Authors: Zhou Qin 
Published: July 2024

Abstract
This paper explains the dilemma of artificial intelligence in relation to the development of teacher education based on the functional structure of artificial intelligence and the activity characteristics of teacher education. Then, after designing a survey questionnaire on the factors affecting the development of teacher education empowered by artificial intelligence and completing the reliability test, the paper collects initial data in the form of distributing questionnaires and analyzes in detail the least squares estimation of mean, variance, standard deviation, correlation coefficient, and regression coefficient needed in the process of analyzing the data to carry out the analysis of instances. The correlation coefficients of teacher training, professional development, policy support, resource allocation, teacher literacy, educational information technology behaviors, and AI-enabled teacher education development are 0.674 (0.003), 0.496 (0.001), 0.259 (0.009), 0.371 (0.008), 0.639 (0.004), and 0.325 (0.007). Their corresponding regression coefficients were 0.616 (t=59.852, P=0.003), 0.021 (t=0.018, P=0.007), 0.078 (t=5.668, P=0.005), 0.032 (t=3.282, P=0.009), 0.239 (t=29.734, P=0.008), 0.137 (t=5.406, P=0.001), indicating that these factors have a significant impact relationship on AI-enabled teacher education.
Application of Artificial Intelligence in Computer Neural Network Algorithm Technology in the Age of Big Data
Authors: Zhou Sheng 
Published: July 2024

Abstract
The arrival of the big data era makes the amount of data explosive growth, which puts forward new challenges and demands for computer network technology, and the integration of big data and network technology has become an important trend. This paper uses the optimization strategy and the elimination mechanism of the genetic algorithm to optimize the inertia weight and particle position speed updating mechanism of the particle swarm algorithm and combines the searching method of the Tennessee whisker algorithm with the sharing mechanism of the particle swarm algorithm to achieve the optimal data searching ability. Finally, the improved artificial intelligence algorithm and MapReduce are combined to improve the performance of the computer neural network algorithm in big data processing. The average data redundancy rate of this paper’s algorithm for big data processing is only 1.18%, and the resource integration checking rate always exceeds 85%, according to simulation experiments. In addition, the algorithm also shows good performance in practical applications, and it can achieve accurate classification of big data labels in big data label classification tasks while maintaining a low energy overhead. Meanwhile, it can accurately recognize electronic medical record data in large medical databases. Big data processing can benefit greatly from the proposed neural network algorithm in this paper.
Internal Logic, Path System and Practical Strategies of “Meteorology + Tourism” Integration and Empowerment
Authors: Huang Ping , Shi Peihua , An Junxiu , Qiao Shaojie , Jin Liya 
Published: July 2024

Abstract
Meteorological resources are not only fundamental but also strategic tourism resources, which are the important foundation for the integrated development of meteorology and tourism. With the intensification of global climate change, the urgent need for healthy tourism in China’s mass tourism market after the epidemic, and the rapid development of meteorological science and technology, the natural and inseparable relationship between meteorology and tourism activities and tourism economy has become more and more prominent, and “meteorology+tourism” has become a new field that is the most active and most directly perceivable by the people in the utilization of meteorological resources and innovation of meteorological services. Meteorology + Tourism” is becoming the most active and directly perceivable new field in the utilization of meteorological resources and innovation of meteorological services, and the fastest-growing and most energetic new development direction of the tourism economy in various places. Research shows that promoting “meteorology + tourism” can drive the positive coupling of the two; the deep integration and two-way empowerment of meteorology and tourism in “all-round, all-time, all-process, all-factor, all-field” is not only related to the high-quality development of tourism and meteorology but also related to the quality of tourism experience and life safety of tourists. Tourism experience quality and life safety, opportunities, and crises are surging; through seven major integration paths, “meteorology + tourism” can give rise to trillion yuan scale emerging industry clusters and should become the new focus of China’s meteorological services and tourism industry and economy synergistic and breakthroughs.
The Impact of Fiscal Support for Agriculture on the Revitalization of Rural Industries - A Case from China
Authors: Ge Linling , Kongruang Chuleerat 
Published: July 2024

Abstract
The low economic but high social benefits of rural industries necessitate increased fiscal investment for their development. This study looks at how fiscal support for agriculture affects the level of revitalization of rural industries. It does this by using panel data from 30 provinces from 2003 to 2021 and fixed effects, fixed effects instrumental variable models, and spatial econometric models. The study’s findings are outlined below: First, overall, fiscal support for agriculture has a positive effect on the revitalization of rural industries in China. Particularly since the Chinese government proposed the Rural Revitalization Strategy in 2017, this effect has strengthened. However, structurally, the impact is greater on the integration of agriculture > the quality of agriculture > the efficiency of agriculture > the technologization of agriculture. Second, the impact of fiscal support for agriculture varies across different regions. Fiscal investment in agriculture significantly promotes the revitalization of rural industries in major grain-producing areas, has no significant effect in major grain-selling areas, and has almost no effect in areas where production and sales are balanced. Third, fiscal support for agriculture exhibits spatial aggregation effects. However, this effect has diminished since 2012, when the Chinese government vigorously promoted industrial restructuring and accelerated the shift from labor-intensive to technology, capital, and knowledge-intensive industries. Fourth, local fiscal investment in agriculture has a stronger economic effect at the local level while reducing the agricultural production efficiency of surrounding areas. Therefore, it is necessary to adjust the structure of fiscal expenditures, adopt differentiated fiscal support policies, adjust expenditure structures, and innovate and optimize policy tools and funding methods for fiscal support of rural revitalization.
Research and Application of Knowledge Graph Design for Interactive Teaching Platform Based on Artificial Intelligence
Authors: Bai Yajuan , Liao Xinhai 
Published: July 2024

Abstract
With the rapid development of education digitization, artificial intelligence (AI) and knowledge graph, their application in the field of education has received extensive attention and research by many scholars. In this paper, the design of knowledge graphs for AI teaching platforms is studied. Based on the construction process of a general knowledge graph, teaching resources’ text is processed through the steps of knowledge entity recognition and relationship extraction, which is applied to the intelligent interactive teaching platform. On this basis, the article designs a method for teaching resource retrieval based on semantic analysis to provide a path for further teaching applications of knowledge graphs. After completing its design, application and testing are carried out to test its feasibility and effectiveness. The score of the experimental class that used the knowledge graph increased by 17.68, which is about 22.47% year-on-year compared to the pre-class period; the score of the control class also rose, with a rise of 9.41, which is about 11.53% year-on-year. The results indicate that a knowledge graph-equipped teaching platform can better meet the needs of interactive teaching and enhance students’ learning abilities.
Exploration of the Path to Improve the Quality of Physical Education Teaching in Colleges and Universities with the Help of VR Technology
Authors: Dong Zhonglei , Sha Nu 
Published: July 2024

Abstract
VR technology, as an emerging frontier technology in recent years, has been applied in many fields, in which in the field of education, the technology has gradually entered the education classroom and played a great advantage. In order to promote VR technology comprehensively and help develop college education, this study explores the path to improve the quality of college physical education teaching using VR technology. Firstly, we review the relevant research data, select the relevant factors affecting the quality of physical education teaching, and explore the path to improving the quality of physical education teaching in colleges and universities through correlation analysis and structural equation modeling. On this basis, a VR-based innovation model of college physical education teaching is developed, and a comparison experiment is designed to study the effect of VR technology in helping to improve the quality of college physical education teaching. The five dimensions of the five factors: knowledge skills, teaching content, interest fit, VR input experience, and teaching method all have a significant positive correlation (p<0.01) to the quality of VR sports teaching in colleges and universities. The highest correlation coefficient is interest fit (r=0.345), followed by VR input experience (r=0.308). At the same time, through the teaching comparison experiment, it can be seen that the class based on the VR sports teaching of this paper is better than the traditional sports teaching mode in terms of physical quality and sports teaching effect, and P is less than 0.05. The VR sports teaching mode constructed in this paper can effectively improve the physical quality of the students, improve the level of sports teaching, achieve the effect of auxiliary teaching, and provide an effective path for the enhancement of the quality of sports teaching in colleges and universities.
Research on the method of predicting the trend of criminal activities based on time series analysis from the perspective of criminal procedure law
Authors: Liu Yiwen , Zou Mingzhu 
Published: July 2024

Abstract
Criminal activity has always been a problem that seriously affects people’s sense of security and well-being in life, and it is also the focus of public security departments in terms of security prevention and control. This study aims to use scientific methods to analyze the time series of existing historical data related to criminal activities and to advance inference or determination of the future trend of criminal activities. In this paper, after mining the spatiotemporal pattern of criminal activities using the centered moving average method, the spatiotemporal cycle characteristics and time distribution characteristics of criminal activities are analyzed. Based on the conclusions drawn, an improved LSTNet algorithm is proposed by combining deep learning spatio-temporal network, convolutional neural network CNN, recurrent neural network RNN, autoregressive AR, and specially designed Skip-RNN, and a GRU-gated recurrent unit structure is used to realize the optimization of the prediction accuracy of the criminal activities, to solve the problems related to the spatio-temporal dependencies, and to establish an improved ST- Res Net crime prediction model. Finally, the prediction performance of the model is examined. The RMSE, MSE, and MAPE values of this paper’s prediction model are 0.88, 5.12, and 5.12%, respectively, which are better than other models. The experiments demonstrate that the prediction model presented in this paper can enhance the accuracy of criminal activity prediction to a certain extent and can be employed in the prevention and management of criminal activities.
Optimization of Artificial Intelligence-based Dynamic Scene Generation and Perception Mechanism in Virtual Reality
Authors: Zhang Songlin , Xun Wei 
Published: July 2024

Abstract
Virtual reality, as a computer simulation system that can create virtual environments, is a fusion of multiple key technologies that are applied in different fields with important practical value and significance. This paper focuses on optimizing the artificial intelligence-based dynamic scene generation and perception mechanism in virtual reality. Firstly, a virtual dynamic scene generation method combining scene management technology and image rendering technology is proposed. In order to optimize the dynamic scene perception mechanism in virtual reality, a perception model based on spatial interaction perception and based on the analysis of user dynamic interaction is proposed. A two-layer perception management strategy is proposed. The paper finally uses the virtual reality technology proposed in this paper to create a Chinese classical garden attraction in a scenic spot. It carries out modeling accuracy assessment and comparison experiments and invites garden professionals and tourists to evaluate the overall effect of the virtual scene. The survey results show that more than 80% of the tourists are satisfied with the generation of the dynamic scene and think that it has spatial continuity and immersive experience.