bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on the Influencing Factors of Cross-border E-commerce Development of Fresh Agricultural Products under the Internet Environment
Authors: Chen Haifei 
Published: February 2024

Abstract
This paper analyzes the current situation of cross-border e-commerce of fresh agricultural products in China regarding import and export trade, e-commerce development and logistics services, and summarizes the existing problems and influencing factors. Through the establishment of AHP-fuzzy comprehensive evaluation model, according to the established index system, the weight of each index factor is determined by using hierarchical analysis, and the importance degree of the influencing factors is calculated using fuzzy comprehensive evaluation method. The results show that among the primary indicators, the supply of fresh agricultural products has the highest influence, with a score of 4.49. Among the secondary indicators, the quality of new farm products and cross-border e-commerce trading platforms have a very high degree of influence, with scores of 4.714 and 4.518, respectively. The study provides a vital decision-making support for optimizing the development of cross-border e-commerce for fresh agricultural products.
Research on Intelligent Development and Practice of Accounting Laboratory Courses in Colleges and Universities in the Context of Interdisciplinary Cooperation
Authors: He Yuanyuan 
Published: February 2024

Abstract
In this paper, an innovative solution is proposed to address the problems of single content design, lack of relevance and specialized training in traditional accounting laboratory courses. In interdisciplinary cooperation, an efficient intelligent assistance model for accounting laboratory courses is constructed by combining the collaborative filtering recommendation model and K-Means clustering algorithm. The model significantly improves the recommendation accuracy and computational efficiency by optimizing the cosine similarity calculation and introducing the similarity-weighted average, combined with the enhanced dichotomous K-means algorithm. After dataset testing and practical application verification in a university, the model effectively improves the quality of personalized recommendation of teaching resources. In particular, students’ mastery of knowledge points K2 and K3 is more adequate through the model recommendation, while their mastery of K8 is significantly improved. In addition, the model successfully identifies the similarity between students, which lays the foundation for providing more personalized learning resources. Overall, the model solves the traditional problem of accounting laboratory courses and provides a practical methodology for intelligent recommendation of teaching resources in universities.
Digital Health Oriented Quality Grading and Evolutionary Study of International Trade Development
Authors: Chen Kesheng , Chen Jianghao 
Published: February 2024

Abstract
This article explores the impact of digital technological advances on international trade exchanges, notably regarding trade costs and barriers. The article first constructs a trade development measurement model for global trade costs and barriers, and analyzes in detail the development quality of international trade using a threshold effect model. In addition, a model for the development potential of international trade is constructed, and the evolution of its spatial pattern is investigated through global and local Moran indices. The empirical Analysis shows that the regression coefficients of economic level, trade potential and trade barriers are 0.228, 0.661 and −0.110, respectively. Analyzing from a macro perspective, the development quality of China’s international trade shows an upward trend between 2012 and 2022, with an overall improvement of about 38 percentage points. This result indicates that improving economic level and trade potential helps to promote the improvement of the development quality of international trade. In contrast, trade barriers may have an inhibiting effect on the development of international trade. By scientifically calculating the quality of international trade development and data visualization of its development process, the article provides effective ways and methods for the Analysis and research of international trade development.
Digital Technology Drives Changes in the Communication Order of Hunan Sports and Culture
Authors: Ma Rui , Xia Dong 
Published: February 2024

Abstract
In the rapid development of digital technology, it has become urgent to explore the order change and development strategy of sports culture communication. This study extracts and analyzes the factors affecting the order change of sports culture communication through partial least squares regression and nearest neighbor component analysis. It was found that between 2016 and 2023, the communication channels, contents and audience order of sports culture in Hunan changed significantly, in which the traditional media communication accounted for 82.52% in 2016, while 81% of the residents accessed sports information through WeChat (26.22%), microblogs (27.73%), and computer webpages (26.78%) in 2023. In 2018 and 2019, the proportion of sportsmanship culture in the overall sports culture communication content is 40.77% and 38.87%, respectively. The development suggestion model in this paper provides an essential reference for the future order change of sports culture communication in Hunan region.
Research on the Integration Path and Practice of AI Intelligent Technology and English Teaching Reform in Higher Vocational Colleges and Universities
Authors: Yu Junli , Wang Lirong 
Published: February 2024

Abstract
The application of artificial intelligence technology in language learning, especially English teaching, is subverting the traditional learning mode. This paper discusses in depth the innovative strategies of English practical teaching in higher vocational colleges. It introduces an AI-assisted teaching system that synthesizes the reasoning mechanism, the student independent learning system and the mathematical model of knowledge forgetting. Through practical application, this study verifies the effectiveness of the system. The results showed that the grades of all students who used the AI system and had an average score of more than 60 did not decrease. There was a significant linear relationship between students’ engagement and grade improvement, indicating that the more serious the students were, the more influential the grade improvement was. In addition, there is a positive correlation between exam difficulty, passing rate and the number of high scores, and a negative correlation with the number of scores below 60, which verifies the reasonableness of the correlation coefficient. Students’ foreign language learning pleasure, burnout and self-efficacy have significant mean differences between the two classes, with p-values less than 0.05, indicating substantial differences. These findings confirm the effectiveness of the AI-assisted teaching system and provide valuable references for future teaching models.
Promoting Educational Reform to Enhance Talent Cultivation Quality of Civil Engineering Majors Based on Deep Learning Background
Authors: Zhu Meng , Zakaria Sharifah Akmam Syed , Wang Chenyu 
Published: February 2024

Abstract
This paper focuses on improving the quality of talent cultivation for civil engineering students through reforming teaching quality and course selection management. Regarding teaching quality management, the article proposes to use improved Apriori algorithm to generate high interest rules and utilize SQL for effective data manipulation. Regarding course selection management, the content-based recommendation algorithm is used to optimize the course selection mechanism. After the implementation of the reform, the proportion of low scores in the self-quality evaluation of college students was significantly reduced, and the evaluation indexes of teachers also showed significant differences. In addition, employers were satisfied with the competence of civil engineering graduates. These results indicate that data-driven teaching management and personalized course selection recommendation can effectively improve education quality and student satisfaction.
Research on Optimization Method for Fault-Tolerant Integration of Real-Time Dual-Computer Embedded Systems
Authors: Lu Borong , Yang Jianhao , Li Xiaolong 
Published: February 2024

Abstract
This paper addresses the fault-tolerant performance of real-time dual-computer embedded systems. The article first emphasizes the importance of real-time and reliability in various fields and points out that improving fault-tolerant performance is a crucial topic. Based on the Markov chain algorithm, the study optimizes the fault-tolerant integration method for real-time dual-computer embedded systems. By constructing a model of Markov algorithm and using the deadline of the task as a benchmark, the passage and transfer probabilities of faults are calculated. The article also provides algorithmic proofs of fault-tolerant control of Markovian jump systems and calculates their stability levels. The results show that the fault passage rate of the system increases as the number of complex tasks increases, e.g., when the number of complex tasks is 4, the passage rate can reach 90%. In addition, in the scheduling test, it was found that the schedulability of the system increases with the increase in the number of processors. When the number of processors reaches 5, the system's schedulability is 43%. In conclusion, the system fault tolerance optimization method based on Markov algorithm proposed in the article can effectively improve the reliability and fault tolerance of the system.
Mechanical Automation Design and Manufacturing of Production Equipment Combined with Artificial Intelligence Technology and Algorithm Implementation
Authors: Bai Jie , Zhang Shuling 
Published: February 2024

Abstract
This paper explores the impact of artificial intelligence and machine automation on productivity. It focuses on analyzing the production model of machinery automation based on Petri nets. Through the invariant analysis method, the article constructs a model and presents its structure as a correlation matrix. The study results show that the model has an error rate of only 2.26% and an accuracy of 90.14% in terms of operational performance. Regarding time performance, its training time is 3854 seconds and response time is 351 milliseconds, which are better than other algorithms. In the practical application of automotive parts production, the method significantly reduces the busy probability and blocking probability during order processing and material delivery, and also improves the equipment load rate, waiting rate and blocking rate in the production process. This indicates that the Petri net-based method of machine automation production has significant advantages in improving productivity and reducing costs.
An Intelligent Control Method for Industrial Equipment Based on Distributed Electrical and Electronic Architecture
Authors: Han Xiaodong 
Published: February 2024

Abstract
The article establishes the objective function of distributed electronic and electrical architecture from three dimensions of economy, quantization and loadability, and constructs a mathematical model for multi-objective optimization based on the satisfaction of constraints. The model was applied and tested in the intelligent control system of automotive industrial equipment. In practical applications, the intelligent control system can automatically reduce the speed to 16km/h to maintain a safe distance and prevent collision when the target vehicle is monitored to enter the lane it is in and the distance between the two cars is less than 30 meters. Under 1500 pcu/h traffic flow conditions, the average delays of vehicles at the intersection through intelligent control were only 8.06 seconds and 8.02 seconds, compared to 20.58 seconds and 23.29 seconds for vehicles under conventional control. Vehicle intelligent control systems based on distributed electronic and electrical architectures have great potential for development and significant safety performance improvement in automotive industrial equipment manufacturing. The research in this paper provides a new perspective and adequate technical support for the intelligent control of future industrial equipment.
Research on automation control technology of electrical and electronic equipment combined with integrated wireless module
Authors: Han Xiaodong 
Published: February 2024

Abstract
This paper discusses the critical impact of informatization automation on plant automation, and takes a water plant’s coagulation dosing automation control system as an example to explore the value of integrated wireless modules in the automation of electrical equipment. Algorithms for directly identifying the parameters of the second-order continuous model by regression model and based on the step response data are investigated, as well as the selection of the DMC algorithm for mathematical modeling of the coagulation dosing automation control. Finally, the effectiveness of the automated dosing system was verified by comparing its effectiveness in improving the qualified rate of precipitation water quality, reducing drug consumption and effluent turbidity, and improving stability. The study’s results showed that after using the coagulation dosing automation system, the water plant’s sedimentation water quality pass rate was increased from the original 85%~95% to 95%~100%. The drug consumption and effluent turbidity were reduced by 20.3% and 33.09% respectively, while the stability was also improved to different degrees. The coagulation dosing automated control system can dosage chemicals more accurately, safely and stably, which has specific reference value for developing the water purification industry.
Construction of Online Course Resource Library Based on MEA-BP Neural Networks
Authors: Li Juan 
Published: February 2024

Abstract
In this paper, the MEA algorithm is applied to the initial optimization of the weight threshold of BP neural network, which improves the stability of the classification of course resources through a two-stage optimization search process. Secondly, the effective recognition of knowledge point entities of teaching resources is realized by combining the LSTM-CRF entity recognition model, the BERT pre-trained language model and the text data enhancement technique based on the maximum bi-directional matching algorithm. In addition, the article proposes a candidate knowledge point entity generation method based on Levenshtein Distance and an entity characterization method based on BERT-TextCNN, which helps to alleviate the noise problem of the text data of curriculum resources and enhance the entity linking effect. The results of the study show that this newly constructed online course resource repository can significantly improve the allocation level of educational resources and reduce the variability of resource allocation among colleges and universities. The coefficient of educational resource allocation variation for SN217 in the university district was reduced from 0.764 to 0.518.In addition, the mean values of this repository in terms of learning path, perceived usefulness, course resources, and intention to use ranged from 1.45 to 1.66.The study in this paper provides valuable methods and insights for optimizing online educational resources.
Analysis of English Classroom Teaching Evaluation in Colleges and Universities Based on the Hierarchical Analysis Method
Authors: Guo Jingshuai 
Published: February 2024

Abstract
With the advancement of the new curriculum reform, English teaching in secondary schools has become increasingly important, and it is especially crucial for establishing a scientific evaluation system for English classroom teaching to adapt to the development of social needs and students’ law of language learning. This study aims to construct the evaluation standard of English classroom teaching in colleges and universities and quantitatively analyze English teaching. First, the English classroom teaching evaluation data are preprocessed by text feature analysis and the data feature weights are calculated. Then, the random forest algorithm was applied to categorize the processed data and construct a hierarchical evaluation analysis matrix. The hierarchical evaluation system was then used to English classroom teaching in colleges and universities to investigate its teaching effectiveness. The results of the study show that the difference between teachers’ and students’ evaluations of the evaluation system is tiny, with a difference of only 0.0149, proving the system’s rationality. Three months after the implementation of the English teaching evaluation system, students’ recognition of the system increased in all four classes, with increases of 0.733, 0.5625, 0.5882, and 0.5. This study provides an effective evaluation method for English classroom teaching in colleges and universities, which can help improve teaching quality and effectiveness.
Construction of a Comprehensive Evaluation System for the Core Literacy of Physical Education and Health Courses in Colleges and Universities
Authors: He Xin 
Published: February 2024

Abstract
This study actively explores the importance of the joint construction of physical education and health courses in colleges and universities. It emphasizes its positive impact on students’ physical and mental health, talent cultivation and social development. Based on the PDCA model, the article establishes a comprehensive evaluation system, determines the weights of the indicators through the coefficient of variation method, and analyzes the cultivation of core literacy and the influencing factors using fuzzy comprehensive evaluation and structural equation modeling. The validity of the evaluation system is examined and verified with ten colleges and universities in Province L as an example, showing that the comprehensive evaluation score is as high as 95.16 points. This complete evaluation system not only helps colleges and universities to improve the quality of education, but also points out the direction for improving students’ core literacy in physical education and health.
Study on the Integration Path of “Photovoltaic + Rural Revitalization” under the Perspective of “Dual Carbon”
Authors: Liang Yan , Chen Shuqiang , Zhang Hailin , Yu Lin , Hu Xiao 
Published: February 2024

Abstract
This study combines photovoltaic (PV) technology with rural revitalization, constructs a new long-term mechanism by using a BOT model, and applies fuzzy number processing to the model of the real option method to dig out the potential value of the project. Based on the field research of X county, the article comprehensively analyzes the PV power generation project in terms of economic and social benefits and its impact on poverty alleviation. The results show that the total benefit of X county can reach 3720.34 million yuan in 30 years, and the average annual benefit is about 124.011 million yuan. The full power generation capacity of the project is 4,987 MWh, and the total income from electricity sales reaches 471,985,000 yuan. The PV power project has contributed significantly to environmental protection, with reductions in carbon dust, carbon dioxide, sulfur dioxide, and nitrogen oxides of 12.12 billion tons, 44.61 billion tons, 13.77 billion tons, and 750 million tons, respectively. The study also found that villages with larger administrative territory and suitable topographic conditions are more ideal for establishing large-scale PV ground power plants to help alleviate poverty. Meanwhile, villages with good grid quality are more efficient in reducing poverty when implementing PV poverty alleviation programs. This study provides an innovative perspective for village revitalization strategies and demonstrates the great potential of PV technology in promoting village economic development and environmental protection.
Research on Digital Distribution Network Micro-application and Precise Control of Distribution Operations Based on Grid Resource Business Center
Authors: Xu Yi , Zhou Wei , Xu Kaiwen , Qian Zhongmin 
Published: February 2024

Abstract
This paper discusses the design and implementation of the grid intelligent micro-application, involving two core aspects: technical architecture and data architecture. First, the article successfully constructs the basic framework of grid intelligent micro-application, which realizes distribution network equipment’s inspection, operation, and maintenance control functions. It further establishes a collaborative regulation model for digital distribution network micro-applications, focuses on calculating and analyzing distribution banding operations, and proposes a precise specification for the methods easily confused in actual operations. The focus of the study includes comparative analysis of voltage and current overrun probabilities before and after regulation to assess the effectiveness of micro-applications in load forecasting and anomaly warning. The results show that using digital distribution micro-applications significantly reduced the likelihood of overruns at most weak points of the grid by an average of 68%, while the year-on-year reduction of anomalies reached 35%. In addition, the micro-application achieved over 90% accuracy in charge prediction, an impressive performance. By simplifying the distribution operation process, this study significantly improves the feedback speed and efficiency of field operation information, which is of great practical significance and application value for the digital construction of power grid distribution network.
Research on Reading Habits of College Students Based on Fuzzy Set Theory and Intelligent Transformation of Libraries
Authors: Kong Ji 
Published: February 2024

Abstract
This article analyzes the impact of the Internet on college students’ reading habits and preferences, emphasizing that short reading, micro-reading, and miscellaneous reading have become trends. The article discusses the intelligent transformation of libraries, proposes strategies such as enhancing resource publicity, strengthening academic resource construction and providing personalized services, and analyzes the effect of brilliant reading promotion assessed by WeChat Communication Index (WCI). The results show that reading speed in the virtual reality environment is significantly faster than in the traditional environment, but deep comprehension takes longer. The time spent by mobile college students on entertaining videos, WeChat public numbers, etc. reached a ratio of 0.6740 and 0.5637. PC students spent more time on professional academic journals, academic MOOC videos, etc. The results of the WCI index for March-September 2022 showed that the WCI before the beginning of the school year was 176.23, and the highest in the middle of the semester reached 387.63, which proved the effectiveness of the intelligent transformation of the Library. The article demonstrates college students’ new trend of reading behavior in the Internet era and the effectiveness of Library coping strategies.