bluuebunny/crossref_metadata_2025_split huggingface dataset:
Construction of a model for analyzing the trend of suicidal tendency among college students based on mental health monitoring
Authors: Gong Xun , Rao Zhouzhou 
Published: December 2024

Abstract
In recent years, college student suicide has become the second cause of death on campus after accidents. This project introduces machine learning methods to the mental health monitoring of college students and constructs a model for analyzing the trend of college students’ suicidal tendencies using the SVM algorithm. First, we researched the mental health problems of college students in several colleges and universities and constructed the SVM model by using screened mental health monitoring variables as input features. Its performance is analyzed through model evaluation and comparison, and it is used in the intervention of college students’ mental health problems. Experimental analysis reveals that the SVM model constructed in this paper presents a better performance in analyzing the trend of suicidal tendencies, with a prediction accuracy of 0.935 for different suicidal tendencies, and the results of different assessment indexes are better than the comparison model. After using the model to assist universities in providing mental health interventions for students, the suicidal ideation among sample students decreased by 42.41%. The use of the SVM model to predict college students’ suicidal ideation is effective, and it can be used as a convenient and efficient tool for screening and assessing the risk of suicide attempts to improve the efficiency of suicide prevention.
Research on the Innovation of Publicity Work in Colleges and Universities under the New Media Environment
Authors: Tang Yanhua 
Published: December 2024

Abstract
New media has become a new propaganda carrier of the development of the times, today’s society with the massive use of mobile devices, all kinds of new media content in the form of fragmentation of high-speed dissemination. How to use new media in colleges and universities has become a key issue that must be considered in publicity work. In this paper, based on the topology and characteristics of the complex network, the complex network data model is constructed, and on this basis, the SIS propagation dynamics model and sentiment analysis are added, and the final propagation density formula is derived through the derivation of the critical value. Through the convolution operation of a graph neural network, the various orders of propagation phenomena in social media networks are modeled, and a prediction model is proposed to predict user preferences in the social perspective of new media. The user and content vectors are used as inner products to predict user ratings for the public numbers advertised. The model is optimally adjusted using the loss function. The WeChat public number of the subject university, University B, showed high reading peaks in March, May, October, and November, with reading counts of 75107.95, 75575.95, 72767.99, and 107,821.3 per read, respectively. University B’s official public microblog keeps a steady reading count, and individual extremely excellent works produce reading peaks. The publicity sentiment of student users to the official WeChat public number of University B is mainly positive and reaches a maximum value of 4.248 after 13 days of the publicity video release, followed by sad and fearful sentiment release to keep in line with the positive sentiment, the University B handles the publicity of the graduation season better, and the students’ sentiment is more positive.
A Topological Mapping Study on the Enhancement of Students’ Career Prospects by the Industry-Education Integration Model in Local Universities
Authors: Wang Yuxi , Dou Liang , Jin Jienan 
Published: December 2024

Abstract
This paper proposes a container network mapping algorithm (MMigration) for career prospect enhancement for the integration of production and education in local colleges and universities and constructs a topology mapping model for the enhancement of college students’ career prospects. After testing the performance of the model, it analyzes the impact of the container network topology mapping model on the career prospects of college students under the mode of production-teaching integration. Finally, based on the experimental results, it points out the direction for the “internship-employment-culture” industry-education fusion linkage training model of local colleges and universities on the improvement of students’ employment quality. Compared with 2019, the number of internship training bases (14.17%), the number of teachers hired from enterprises (41.18%) and the number of in-service teachers exchanging and studying in cooperating enterprises (151.61%) in local colleges and universities are all on the rise. When local colleges and universities integrate industry and education with enterprises, the performance of each of the six tasks of school-enterprise cooperation shows a significant upward trend. In addition, the mean employment rate of the students’ professional counterparts in industry-education cooperation enterprises increased by 64.87%, 72.15%, 86.51%, and 94.51% from 2019 to 2022, respectively. This indicates that the locally efficiently explored schooling model of industry-teaching integration in local engineering colleges is extremely helpful for students’ career prospects enhancement.
Hierarchical analysis-based retrofitting of old residences for age-appropriate interior design
Authors: Zhang Weiwei 
Published: December 2024

Abstract
At present, the aging of the population, the aging of buildings and environmental facilities and other problems are becoming more and more serious, and the aging renovation of old communities is an effective measure to solve the problem of population aging. Based on the demand analysis, this paper combines expert opinions to construct an index system for aging-appropriate interior design and renovation of old residences, including 1 target layer, 4 guideline layers, and 17 index layers. The AHP-fuzzy comprehensive evaluation model is created by combining the hierarchical analysis method with the fuzzy comprehensive evaluation method. The AHP-fuzzy comprehensive evaluation model is utilized to evaluate each index of the old residential interior design renovation that is age-appropriate. Finally, it is concluded that the weights of the indicators of the criterion layer (B) to the target layer (A) are spatial function (0.4495), mobility accessibility (0.2596), electrical equipment system (0.1707), and thermal environment (0.1202). The weights that were assigned to the indicators of the indicator layer (C) to the target layer (A) were most significant for bedrooms (0.1651) and least significant for temperature regulation and ventilation (0.0072). The overall quality of interior design for aging in older homes was “good” (0.796), with kitchen design (0.4) being the worst. Based on hierarchical analysis, the study proposes remodeling strategies for several important aspects that need improvement.
Applying Game Theory to Analyze the Development Path of School-Enterprise Cooperation in Vocational Education
Authors: Shen Jie , Zhang Silei 
Published: December 2024

Abstract
In the context of today’s rapid economic and social development, school-enterprise cooperation in vocational education has become increasingly important. The cooperation process can be challenging due to the differences in the interests of the cooperating parties. The study constructs a vocational education school-enterprise cooperation model based on the use of game theory in school-enterprise cooperation and combines it with the game model of the school-enterprise cooperation mechanism and the power mechanism of the school-enterprise cooperation game. Examine the impact of school-enterprise cooperation on the evolution strategy of school-enterprise parties in school-enterprise cooperation and propose recommendations for the development path of school-enterprise cooperation. In school-enterprise cooperation, the different initial willingness of school enterprises, cooperation benefits, extra costs of the university side, positive benefits of the university side, and betrayal benefits all have impacts on the strategy evolution process. Among them, the initial willingness of the school enterprise, cooperation gains, and positive gains of the university side are positively correlated with the strategy evolution process. When both the university and the enterprise value their initial willingness at (0.9), they tend to exhibit a positive cooperative tendency. When the cooperation gain (R) reaches a value of 50, the system evolves to (1,1). The system steadily transitions from the stability point (0,0) to (1,1) as the university side’s positive gain increases from 1 to 3. In contrast, as the extra costs and betrayal gains on the university side increase, university-enterprise cooperation shows a negative trend.
The linear programming model of the optimization configuration of education resource optimization for higher vocational students
Authors: Han Yushan 
Published: December 2024

Abstract
Promoting the optimal allocation of the ideological and political education resources for higher vocational students is the key to realizing the work of higher vocational ideological and political education. On the basis of analyzing the connotation characteristics and content framework of the ideological and political education resources, the article explores the optimization mechanism and configuration objectives of the ideological and political education resources. Based on the data envelopment model, a DEA-CCR pairwise planning model is constructed by combining the linear programming theory, and the Malmquist index is introduced to explore the dynamic optimization and allocation efficiency of the ideological and political education resources. The input redundancy and output of Civic and political education resources are not enough to obtain the specific measures for their optimal allocation, and the DEA-CCR model for optimal allocation of Civic and political education resources is also solved by using LINDO software. Panel data from 31 provinces in China were used as an example to quantitatively analyze the allocation efficiency of civic education resources for higher vocational students.The values of the allocation efficiency of civic education resources for higher vocational students during the period of 2017-2022 were all in the range of 0.78-0.85, with a 33.73% increase in purely technical efficiency, a 140% increase in the number of regions where the DEA was realized to be effective, and an increase in the Malmquist index of 0.375.In the linear programming model of civic education resources, based on input redundancy and output insufficiency it is possible to obtain targeted strategies for the optimal allocation of civic education resources for higher education students.
Tax Incentives, Innovative Development of Digital Economy Industries and Green Innovation Efficiency in Cities
Authors: Wang Hongyan , Peng Aimei , Xu Wenwen 
Published: December 2024

Abstract
Focusing on the value of green innovation efficiency in cities, this paper explores the intrinsic mechanisms of tax incentives and the innovative development of digital economy industries in promoting efficiency. This paper first proposes the principle of the regression algorithm required for the study as its theoretical foundation. In the principle, it focuses on the solution method of the LS method, proposes the univariate regression model and the multivariate regression model respectively, and determines the parameter estimates through the residual vector derived by the least squares method. Combined with the regression model, the mediation effect model is proposed to examine the impact of tax incentives on urban green innovation efficiency by taking government subsidies and tax incentives as the entry point of tax incentives. The results show that the regression coefficients of government subsidies and tax incentives are 1.769 and 1.838, respectively, which are positive, and the tax incentives can significantly improve urban green innovation efficiency and can realize the improvement of urban green innovation efficiency by promoting the innovative development of the digital economy industry. The effect size of tax incentives on urban green innovation efficiency in different regions of East, Central, and West China shows regional heterogeneity.
A study on the innovation of one-stop school registration management mode and the application of graph theory algorithm in the context of digitization
Authors: Che Yaqian , Liang Gaoyan 
Published: December 2024

Abstract
School registration management is an important part of the school management process, which is the basis of other work. This paper proposes an innovative school registration management system that integrates the school registration early warning system into the one-stop school registration management model. The data mining method is utilized to mine and process students’ school registration information to extract useful information. On this basis, the academic registry management system and the academic registry early warning system are constructed, and the graph theory-based subspace clustering algorithm is introduced to realize the innovative academic registry management model integrating academic registry early warning. Behavioral data provided by the information center of University A is used as the basis for the analysis of students’ campus card usage data. The subspace clustering algorithm proposed in this paper can obtain accurate results for clustering students’ usage behaviors, and the accuracy of the algorithm is consistently maintained between 80% and 90%. Then the academic data of the 2018 to 2021 graduates in University A is used as an experimental analysis object to predict the clusters to which the performance points belong, and the clusters generated by clustering are mined to find out the common characteristics of outstanding students and the relationship between the student data and the academic data. Finally, feature data clustering is performed on students’ academic characteristics to obtain information on students with abnormal academic status, and the implementation of dynamic monitoring of academic status reveals that 95% of students do have abnormal academic characteristics.
Research on Content Innovation Path of Journalism and Communication Education Driven by AI Technology
Authors: Chen Feijing 
Published: December 2024

Abstract
Under the background of the big model of artificial intelligence, the cultivation of journalism professionals in colleges and universities is facing major challenges, and this paper explores the content innovation path of news communication education empowered by AI technology with the help of the structural equation model. By summarizing the development history of “AI+Education”, it extends the impact of AI technology on journalism and communication education. Combined with the principles of questionnaire design and the actual situation of journalism and communication education in colleges and universities, the questions in the questionnaire are designed, and a structural equation model is constructed for the content innovation of journalism and communication education empowered by AI technology, and the model in this paper is used to analyze the examples. The 20 items in the questionnaire satisfy the condition that the absolute value of skewness and kurtosis is less than 3, its sample data based on the questionnaire conforms to normal distribution, and all the paths have passed the significance test with a significance level of 0.05. This study demonstrates the interaction mechanism and linkage between the paths of content innovation in journalism and communication education, empowered by AI technology, using a questionnaire and structural equation modeling.
Pattern Recognition and Algorithm Improvement for Error Analysis in Voltage Transformer Low Voltage Testers
Authors: Chen Xu , Zhang Haomiao , Zhang Chao , Cheng Zhiqiang , Xu Yinzhe , Yan Yu , Zhang Xinrui 
Published: December 2024

Abstract
To ensure the fairness and accuracy of electric energy measurement, it is necessary to carry out on-site calibration of voltage transformers in operation according to the cycle, and due to a large amount of measurement workload and many dangerous factors, a low-voltage tester is used at this stage to carry out the measurement work. This paper explores the basic method of low-voltage testing, sorting out the steps for the use of low-voltage testers in voltage transformers and proposing a resonance-based CVT analysis method to assist in the voltage transformer measurement operation of low-voltage measuring instruments. When performing the calculation of the error on the low-voltage side, the low-voltage extrapolation method is used to extrapolate the measurement error on the high-voltage side of the voltage transformer, and on this basis, a neural network architecture is proposed to suggest an improvement strategy for the existing algorithm. Using the method proposed in this paper, the voltage transformer low voltage test error analysis, the method proposed in this paper is consistent with the error trend measured by the overall error test method, and the maximum value of the error deviation is 0.0436%, which is not more than 0.05%, and is smaller than the error limit of the test article. At the same time, in different modes of voltage transformer error characterization, with the ambient temperature from -35 ° C to +22 ° C in the process of change, the ratio difference of voltage transformer from 0.183% change to 0.152%, phase difference from 4.18′ change to 4.68′, the whole process, the ratio, phase difference is not exceeded, the error measurement effect is good.
A Study on the Reform Direction of Virtual Reality Teaching Tools on Traditional Chinese Literature Teaching Methods
Authors: Cheng Xirong , Pan Tingting , Wang Mulan 
Published: December 2024

Abstract
This paper uses virtual reality technology, augmented reality technology and other means to combine the virtualization design with traditional Chinese literature, interpreting a “virtual realm” in the future world from a new perspective and reforming the teaching of traditional Chinese literature through three aspects of literary imagery, scene and cultural display. This is a reform of traditional Chinese literature teaching, focusing on the three aspects of literary imagery, scene, and cultural display. The results of applying VR technology to the teaching practice of traditional Chinese literature show that on a natural level, the imagery of smoky rain and willow is mainly used. At the level of humanistic architectural landscape, temples, Rainflower Terrace, and Phoenix Terrace are the main imagery. At the level of social and cultural activities, the frequency of the Six Dynasties is the highest (40). Classical garden art and culture can be demonstrated in the scenes constructed throughout traditional Chinese literature, including poetry and literature. Compared to traditional teaching methods, the satisfaction rate for cultural display in VR teaching of traditional Chinese literature is as high as 92.5%. In the comparative analysis of teaching feedback, the experimental class mainly focuses on the score range of 60-80, while the distribution of the control class mainly focuses on the range of 30-60 points. The use of VR technology, on the other hand, allows students to devote themselves to the course and improves the learning process.
Exploring the Potential Application of Big Data in the Digital Transformation Practice of English Education
Authors: Ding Lingling 
Published: December 2024

Abstract
With the increasing development of the digital economy and Internet technology, in order to adapt to the demand for teaching, many colleges and universities are changing their education mode through digital transformation. Starting from English teaching, this paper seeks to uncover a suitable way for the digital transformation of English education. Based on a collaborative filtering recommendation algorithm, this paper constructs an English teaching model that integrates personality recommendations. The model can use clustering algorithms to classify learners into different groups, which facilitates the subsequent implementation of personalized recommendations. The performance comparison and examples of English teaching in colleges and universities are used in this paper to analyze the efficient performance of the recommendation model and evaluate its usefulness in the smart classroom. The recommendation model designed in this paper divides learners into five clusters, which provides strong support for us to provide personalized recommendations of English learning resources in the future. This paper’s system, for example, in basic English, has a recommendation accuracy rate of 10% and 21% higher than reference systems 1 and 2, according to performance comparison. Applying this paper’s recommendation model in an efficient and intelligent English teaching classroom, after the experiment, the performance of class T improved by 4.29 points compared to class CK. To conclude, the recommendation system of this paper is very adaptable to the smart classroom and has a greater role in promoting the digital transformation of English teaching mode in colleges and universities.
Analysis of the Deepening Path of Cognitive Logic in Chinese Philosophy Based on Knowledge Mapping
Authors: Dong Xiaoli 
Published: December 2024

Abstract
Existing knowledge graph representation learning models do not utilize the semantic information of philosophical entities and philosophical relationships sufficiently, which makes it difficult for the models to obtain optimal representation performance. Therefore, this paper constructs a knowledge graph-based philosophical knowledge base and a text-enhanced knowledge graph representation learning model based on semantic propagation. Firstly, the ontology representation of the Chinese philosophy discipline was completed through six steps, and the ontology was generated by loop iteration. The modeling of the Chinese philosophy knowledge system was finished after the completion of semantic annotation. Then, the knowledge was stored and the ontology-based knowledge base of the Chinese philosophy discipline was created. The constructed philosophical knowledge base is used to identify entity texts and connect them with corresponding entities to create an enhanced knowledge map of Chinese philosophy-related texts. Attempting to use a graph convolutional network to propagate semantic information among nodes of the enhanced knowledge graph, the semantic information of text semantics and the ternary group is deeply fused, and the construction of the knowledge graph representation learning model is completed. Finally, experiments were conducted on the WN18RR dataset and the Chinese philosophy knowledge base constructed in this paper. The MRR value of this model on the Chinese philosophy knowledge base constructed in this paper is 0.046 more than that on the WN18RR dataset, and the majority of the “agree” and “strongly agree” on all indicators, with only one exception, indicating the validity and sophistication of the philosophical knowledge base and model constructed in this paper, which is conducive to the deepening of the cognitive logic of Chinese philosophy.