bluuebunny/crossref_metadata_2025_split huggingface dataset:
Coordinated Cultivation of Innovative and Entrepreneurial Knowledge and Ability of College Students Based on Markov Modeling
Authors: Yang Dan , Zheng Sisi , Cheng Si , Zhou Qi 
Published: February 2024

Abstract
Evaluating innovation and entrepreneurship ability measurement of college students is one of the critical areas of research on innovation ability cultivation in colleges and universities. In this study, based on the existing Bayesian knowledge tracking model, the parameter matrix of innovation and entrepreneurship knowledge point relationship is added to improve the standard knowledge tracking model. The CS-BKT model is proposed to provide college teachers with detailed mastery of students’ innovation and entrepreneurship knowledge. Then the corresponding state space is delineated according to the mastery situation, and the evaluation model of innovation and entrepreneurship ability measurement for college students based on polymorphic rewarded Markov chain is constructed. Combined with different transfer probabilities, the model operates on student data to measure students’ innovation and entrepreneurship ability. The results of the study showed that there was a significant difference between the acceptance and non-acceptance of innovation and entrepreneurship education in students’ innovation and entrepreneurship competence, and the level of innovation and entrepreneurship competence of students who had accepted it was 3.71, which was higher than that of students who had not taken it (3.53). There is a significant positive correlation between the social level of the place of origin, the individual level of entrepreneurial experience, and the rank of professional achievement and innovation and entrepreneurship ability, with p-values of 0.008, 0.003, and 0.001 respectively are less than 0.01. This study concludes the factors influencing the innovation and entrepreneurship ability of college students, which provides a reference value to the formation and development of the innovation and entrepreneurship ability of the students.
Research on the Quality Assessment Model of “Dual-Teacher” Teachers in Higher Vocational Colleges and Universities Based on Big Data Technology
Authors: Lou Yunjia , Xiao Huayi 
Published: February 2024

Abstract
To further analyze the content of “dual-teacher” teacher team construction in higher vocational colleges and universities, this paper focuses on teacher moral construction, teacher training, assessment and evaluation, and incentives for in-depth investigation. It is clear that higher vocational colleges and universities should distinguish between “dual-teacher” teacher quality assessment and ordinary teacher assessment, and put forward the gradient “dual-teacher” teacher quality team construction. Improve the support vector machine, use the binary tree to propose an evaluation model based on incomplete DBT-SVM, and combine multiple binary classifiers to solve the multi-classification problem of “dual-teacher” teacher quality evaluation. The optimal parameter combinations, i.e., C =28 and γ = 0.0534, are obtained using the kernel function and parameter tuning experiments, and the accuracy of the model prediction results reaches 94.325%, taking the “dual-teacher” teachers in a university in Y province as the specific evaluation object. This shows that the accuracy of this DBT-SVM-based evaluation method of “dual-teacher” teacher quality is good.
The Beauty of Context and Its Expression in Chinese Language Literature: Based on the Perspective of Semantic Contrastive Analysis
Authors: Chen Xiaojing 
Published: February 2024

Abstract
This paper conducts an in-depth study centering on the beauty of context and its expression in Chinese language literature, mainly from the perspective of semantic contrastive Analysis. Firstly, the study utilizes various natural language processing techniques including LSTM neural network and GRU model to acquire and process textual semantic information by constructing a specific Chinese language contextual model. Then, an empirical analysis of Chinese language literature was conducted, and accuracy and recall were used as evaluation criteria to compare different Chinese language contextual models. The results show that the LSTM-GRU-based Chinese language contextual model significantly improves accuracy and recall. In addition, the model’s effectiveness in improving the ability of contextual Analysis in Chinese language literature is demonstrated through the review and Analysis of Chinese language literary works. Finally, the article proposes strategies to improve the ability of contextual Analysis in Chinese language literature.
Research on Accurate Teaching Reform of Japanese Language Education in Colleges and Universities with the Help of Big Data Technology
Authors: Li Yin 
Published: February 2024

Abstract
The development of Japanese language education provides a solid foundation for the friendly relations between China and Japan. In this paper, we first constructed a framework for optimizing teaching in Japanese language education based on big data and intensive learning intervention decision-making. We designed an achievement prediction model based on deep learning for Japanese language teaching effectiveness. The achievement prediction model is applied to the teaching achievement prediction and compared with the actual achievement, and its relative error range is between 0~0.2, compared with the traditional prediction model error reduction of about 0.2 or so in the Japanese language teaching achievement prediction analysis, the confidence and validity of the learning law and class performance are more significant than 0.8, the association rule is superior, and the optimized student prediction of the Japanese language teaching course learning achievement is basically distributed between 80 and 100 points, and the achievement level was significantly improved. This study provides an effective method for the precise reform of Japanese language teaching and realizes the prediction of the effectiveness of educational reform.
Role Shaping and Character Recognition of Cultural Education in Higher Education in the Context of Digitization
Authors: Luo Bin 
Published: February 2024

Abstract
Effective role shaping of cultural education in colleges and universities is of tremendous and far-reaching strategic significance to the development of socialist modernization. This paper establishes 3DBP-TBR method based on the 3D CLBP method with higher granularity to identify and analyze the role behavioral characteristics of teachers in higher education. It uses the elbow method to determine the optimal number of clusters in the clustering analysis, extracting and identifying the characteristics of teachers’ role behavior. By analyzing the role shaping of teachers, it was found that Teachers have the highest teaching support role index of 0.9548 points, and there is a significant difference in the dimension of teaching support characteristics of teachers teaching different courses (P=0.047<0.05). The analysis results in this paper lay a foundation for the study of role modeling and characteristics of college teachers, and the proposed role modeling suggestions also provide a reference for the future improvement of cultural education in colleges and universities.
Research on educational applications based on diagnostic learning analytics in the context of big data analytics
Authors: Zhang Naimin , Zhang Linlin 
Published: February 2024

Abstract
In the context of the significant data era, this paper explores the educational applications based on diagnostic learning analytics technology to improve personalized learning and teaching effects in the educational process. The study adopts a multidimensional feature fusion approach to construct a cognitive diagnostic model to predict learners’ knowledge status and future learning performance. Through actual data testing, the model can effectively predict the students’ knowledge mastery state and analyze the students’ learning process in depth. The experimental results show that the diagnostic model exhibits high efficiency and accuracy in predicting students’ knowledge mastery status, with an accuracy rate of 92.97%, significantly better than traditional teaching methods. In addition, the study explores the encoding method of learners’ multidimensional features and constructs a dynamic diagnostic model of test factors and student factors based on graph attention network. The study provides a new learning analysis and diagnostic method in the education field, which helps improve the effect of personalized learning.
Research on the Teaching Reform of Art and Design Courses in Colleges and Universities Driven by Artificial Intelligence
Authors: Zhao Yanyun , Xue Yujia 
Published: February 2024

Abstract
This paper focuses on analyzing the critical technologies of artificial intelligence technology in the creation and display of art and design teaching in colleges and universities, respectively, using image processing technology, image geometric transformation, and image special effects processing to realize the basic image design of art design, and using head-eye synergistic eye-movement multi-channel interaction and gesture interaction to form an immersive interactive art and design display device. Combined with the radar chart of the acceptance of AI technology in the course teaching, the influencing factors of the three dimensions of cognition, interest and Practice are explored. The OBE concept is introduced to propose a teaching reform program for art and design courses under AI technology. Practical application of the teaching program can improve students’ visual literacy in art and design, and its numerical difference is 0.3254 at the most. Thus, the teaching reform program of art and design courses in colleges and universities based on the OBE concept proposed in this paper is feasible to a certain extent.
The Infiltration and Integration of the Concept of Ideological and Political Education in the Employment of College Students in the Era of Big Data
Authors: Wang Yu , Zhou Yu 
Published: February 2024

Abstract
This paper studies integrating and penetrating the concept of Civic and Political Education in the employment guidance of college students to improve the effect of employment education in the context of big data. This paper uses genetic algorithm and projection tracking method to construct a measurement and evaluation model of Civic and Political Education and employment integration level. It is found that the coupling degree between Civic and Political Education and student employment in college A has increased year by year from 2010 to 2023, showing the effective integration of Civic and Political Education and jobs. The coupling degree risen from 0.136 in 2010 to 0.987 in 2023, indicating that the penetration and integration of Civic and Political Education in employment increased significantly. Strengthening the integration of Civic and Political Education and Employment Guidance can help improve the quality of student employment and student employment satisfaction. This study provides empirical support for integrating civic and political education and employment guidance in colleges. It confirms the importance and effectiveness of civic and political education in employment guidance in colleges and universities in the era of big data.
Analysis of the innovation path of news dissemination based on the multivariate data chain network
Authors: Wu Bin 
Published: February 2024

Abstract
This paper explores the innovative path of news dissemination based on multivariate data chain network, through the design and implementation of a multivariate data chain integrated planning system, to improve the transmission efficiency and accessibility of the data chain network, and then optimize the effect of news dissemination. The study designs a multivariate data chain integrated planning system, considering the constraints of delay and transmission, and uses Poisson distribution and queuing theory to analyze the access delay of the data chain. It is found that the access delay can be effectively reduced by controlling the generation and transmission process of data packets. Secondly, the C-RTT algorithm is proposed to optimize the synchronous time slot allocation in Link16 network, which is experimentally demonstrated to improve the time slot utilization by 1.64% to 6.57% and significantly increase the network capacity. Further, the multivariate datalink dissemination model outperforms the traditional news dissemination method regarding news content perception, environmental awareness, news reliability, and environmental behavioral intention. The application of multivariate data chain network has significant advantages in news dissemination and has substantial impacts on the development of news industry.
Exploring the Digital Innovation Development Mode of Chinese Sports Intangible Cultural Heritage
Authors: Zhang Zuqiang , Li Zhiqiang 
Published: February 2024

Abstract
This paper explores the innovative development of digitization of Chinese sports intangible cultural heritage, focusing on applying advanced technologies such as three-dimensional reconstruction and movement recognition to protect and pass on this unique cultural heritage. The article digitally captures and analyzes traditional sports movements through 3D reconstruction and movement recognition techniques. Subsequently, a feature extraction method is applied to capture the critical features of the movements and Bessel curves are utilized to enhance the realism of the virtual character model. The experimental results show that this method can effectively recognize and reproduce traditional sports movements, with a recognition success rate as high as 97.05%, and accurately determine the standard degree of the movements. In addition, this technique helps to reduce training costs and improve training efficiency. Through these techniques, not only can the intangible cultural heritage of sports be preserved and inherited, but also promote its integration with modern science and technology and open up new ways for its development.
Research on the Path of High-Quality Development of Sports Industry Driven by Digital Economy Based on Big Data Analysis
Authors: Bai Hongzhou 
Published: February 2024

Abstract
This paper focuses on how the digital economy drives the high-quality development of the sports industry, explores the new path of development using extensive data analysis, and provides theoretical basis and practical guidance for the innovative development of the sports industry in the digital era. The DEA-Malmquist model and comprehensive data analysis methods are used to measure the development efficiency of the sports industry. The results of the study show that the digital economy has a significant impact on the efficiency improvement of the sports industry, in which the effect on the efficiency improvement of the sports industry is the largest, and the regression coefficient reaches 1.153. In addition, the study also finds that the digital economy can significantly reduce the cost of the sports tourism enterprises, improve the cost profitability, and effectively promote the expansion of consumption. The study’s conclusion shows that the development of digital economy provides new development power for the sports industry, and can effectively promote the optimization of the structure and high-quality development of the sports industry. In this regard, it is recommended to strengthen the application of digital technology in the sports industry and enhance the digitalization level of the sports industry.
Research on Intelligent Management System of Gas Pipeline with Multi-source Data Fusion
Authors: Cao Xin , Tan Jianxin , Li Hao , Li Rui , Wang Yifan , Zhang Junfeng 
Published: February 2024

Abstract
Aiming at the current challenges of enormous scale, complex structure, difficult control and frequent accidents of city gas high-pressure pipeline network, there are still three aspects of difficulties in the risk monitoring and control of China’s city gas high-pressure pipeline network, namely, rough data, shallow assessment, and lack of power. This paper proposes an intelligent management system for gas pipelines based on C/S model and J2EE enterprise-level framework, in which the failure warning models of gas leakage, Gaussian plume diffusion, and fire and explosion are established. And the Kalman filter algorithm improved by DS evidence theory is used for intelligent fusion of Multi-source data, analyzing and screening the unified adequate information on data types, extracting state characteristics, classifying warning levels, and developing an integrated and visualized pipeline remote diagnosis and warning platform. In the simulation of the intelligent management system of gas pipeline, when the wind speed is 1.5m/s in winter, the ground surface is a safe area within 12.15m of the gas pipeline. When the maximum wind speed is 10m/s, the upper limit distance of the gas leading to fire and explosion is only 2.43m, and the hazardous range of the gas pipeline jet fire is within 12.69m. Relying on the gas high-pressure pipeline network in L city for practical experiments and applications, it provides technical support and decision-making basis for the construction of intelligent pipeline network, comprehensively improves the risk control capability of city gas high-pressure pipeline network, and has reference significance for the risk control of national city gas high-pressure pipeline network.
Study on the Strategy of Red Literature and Tourism Brand Communication Helping Study Tourism Economic Development in Liaoning Province under the Background of Internet
Authors: Cao Xue 
Published: February 2024

Abstract
Liaoning Province has a deep red cultural background and rich red tourism resources, and has an enormous potential for the development of red study tour. This paper establishes the evaluation system of the competitiveness of study tour development in Liaoning Province based on the explanatory structural model, solves the index weights through the coefficient of variation method, and gives the calculation of the competitiveness of study tour economic development. The regional differences in the competitiveness of research and study tourism economic development were measured by using the Thiel index, the spatial autocorrelation Moran index verified the regional correlation, and the TF-IDF algorithm was introduced to improve the LDA theme model thereby analyzing the emotional expression of the research and study tourism network text. Taking the tourism data of Liaoning Province from 2015 to 2019 as the research object, the data were quantitatively analyzed regarding development competitiveness evaluation, regional differences, spatial autocorrelation and emotional expression. The results of the study found that the weight of the red culture tourism market size in the economic development competitiveness of study tourism reached 29.64%, the peak and valley values of the regional differences in competitiveness from 2015 to 2019 differed by 0.0587, and significant differences were presented at the 1% level between cities. The frequency of red characteristic words reached 2,536 times. This indicates that the effective integration of red culture and study tourism in Liaoning Province effectively reduces the development differences between cities, and enhances the satisfaction of study students with red culture study tourism bases.
Linear regression analysis of the correlation between students’ physical education performance and academic achievement in the context of smart physical education in colleges and universities
Authors: Chen Jin 
Published: February 2024

Abstract
In this paper, the principles, algorithms and different linear regression models are sorted out and finalized to determine the multiple linear regression model suitable for this study. The different types of regression are synthesized through the elastic net algorithm. Based on the multiple linear regression model, students’ performance in language, mathematics and English was used as the dependent variable Y on behalf of academic performance, and five sports such as physical education and hygiene were used as the independent variable X, to carry out an empirical study on 3,800 students. From this, it was concluded that the contribution rates affecting language achievement were sports attitude, environment, and hygiene in the order of coefficients of 0.548, 0.312, and −0.266. In contrast, exercise habit [B=−0.032, t=−1.574, P=0.116] and sports knowledge [B=0.027, t=1.561, P=0.119] did not pass the test of significance. The contribution of influencing math achievement was in the order of sports environment and attitude with coefficients of 0.402 and 0.327, which were positively correlated with math achievement Y2. The contribution rate affecting English achievement is in the order of sports hygiene, sports attitude and exercise habit, and their coefficients are 0.398, 0.295 and 0.124, all of which are positively correlated with English achievement Y3.
Shaanxi Red Cultural Resources into Party Building Education in Colleges and Universities under New Media Environment
Authors: Duan Zhaohui 
Published: February 2024

Abstract
Under the new media environment, exploring how Shaanxi red cultural resources can be integrated into party building education in colleges and universities significantly improves students’ political literacy and cultural cognition. The study adopts new media technology, combines K-means clustering algorithm and fuzzy cluster analysis method to extract students’ personalized characteristics, and uses them to optimize the content of party building education. The experimental data show that the intra-class average error of the K-means algorithm in the classification of excellent students is 2.56, while the overall average intra-class mistake of the fuzzy clustering algorithm is 10.28, indicating that the latter is more scientific and accurate in party assessment. Through the research and analysis of the student groups in 30 universities, it was found that 80% of the students believed that the universities paid attention to the development of intelligent party building, and 0.9198 of the students thought that the red cultural resources in Shaanxi could meet the needs of party building education. The study’s conclusion shows that combining technical means in the new media environment and Shaanxi red cultural resources can effectively improve the effect of party building education work in colleges and universities, and enhance students’ political literacy and cultural cognition.
Research on the Teacher Team Construction of Innovation and Entrepreneurship Education in Higher Vocational Colleges and Universities under the Background of “Double Creation” Upgrading
Authors: Hu Fenglin 
Published: February 2024

Abstract
With the promotion of “dual-creation” education, higher vocational colleges and universities face the challenge of building faculty. This study explores the strategies for making the faculty of innovation and entrepreneurship education in the context of “dual-creation”. The study adopts the evaluation model based on Backpropagation neural network. It proposes targeted construction strategies by analyzing the teaching process, teacher conditions and teaching effect of innovation and entrepreneurship courses. The results show that by optimizing the construction path of the faculty team, the teaching effect of innovation and entrepreneurship courses is significantly improved, the proportion of students participating in entrepreneurial practice has increased by 40%, and the number of declared innovation patents has increased by 47.6%. In addition, the percentage of rejuvenation of the teacher team grew by 10%, and the professional ability of teachers was significantly improved. Artificial intelligence technology such as neural network optimizes the path of teacher team construction for innovation and entrepreneurship education in higher vocational colleges and universities, which can effectively improve the quality of teaching and the professional ability of the teacher team.