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27. Exploration and Reflection on the Development of Internationalized Industry-Education Integration of Vocational Education in the Context of Big Data

Author

Kong Ming, Kuang Yan, and Zhang Zhichao

Subjects
integration of industry and education, hierarchical analysis, fuzzy analysis, performance evaluation, vocational education, 97p10, Mathematics, QA1-939
Abstract

The integration of industry and education serves as a potent mechanism to enhance the educational quality of higher vocational colleges and universities while simultaneously fostering the innovative vitality of enterprises. This study delineates a framework for internationalized industry-education integration in vocational education, grounded in the tripartite relationship among government, enterprises, and educational institutions. Building on this framework, the research initially constructs a performance evaluation index system for internationalized industry-education integration, which encompasses three dimensions: the input, process, and outcomes of industry-education integration. Subsequently, the weights of these indices are determined through hierarchical analysis, and the integration performance of four sample institutions is assessed using fuzzy analysis. The findings reveal that all sampled institutions surpass a ‘good’ performance level, with Institution X1 achieving the highest comprehensive evaluation score of 86.3593. Further, the study conducts an empirical analysis comparing the implementation effects of two models of industry-education integration: the ‘group-run school’ model and the ‘industrial park’ model. The study indicates that the ‘industrial park’ model is marginally superior by 0.13 points in its evaluation compared to the ‘group-run school’ model; however, this difference is statistically insignificant (P>0.05), suggesting that both models exhibit distinct characteristics yet achieve comparable outcomes in integrating industry and education. The research offers actionable insights and practical guidance to advance the development of internationalized industry-education integration within vocational education contexts.

Published
2024
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28. Research on Artificial Intelligence Enabling High-Quality Development of Vocational Education

Author

Kong Ming, Yu Feilong, and Zhang Zhichao

Subjects
entropy weight method, fuzzy comprehensive evaluation method, relationship matrix, pearson chi-square test, vocational education, 97d10, Mathematics, QA1-939
Abstract

This paper studies the use of artificial intelligence technology in the field of education and the way of empowering vocational education and constructs a wisdom teaching model of vocational education based on artificial intelligence. It also applies entropy weight and a fuzzy comprehensive evaluation model to determine evaluation indexes and weights, constructs a fuzzy relationship matrix, and synthesizes a fuzzy comprehensive evaluation model. Based on the model, the teaching effect of vocational education with artificial intelligence is studied, and the advantages of wisdom teaching in the creation of a learning environment and the triggering of students’ interest in learning, creative thinking and problem-solving ability are analyzed by comparing with traditional teaching methods. The results show that there is a significant difference between the effect of AI teaching and traditional teaching, p

Published
2024
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29. Accurate recognition of the reproductive development status and prediction of oviposition fecundity in Spodoptera frugiperda (Lepidoptera: Noctuidae) based on computer vision

Author

Chun-yang LÜ, Shi-shuai GE, Wei HE, Hao-wen ZHANG, Xian-ming YANG, Bo CHU, and Kong-ming WU

Subjects
Spodoptera frugiperda, computer vision, ovary, testis, WeChat applet, Agriculture (General), S1-972
Abstract

Spodoptera frugiperda (Lepidoptera: Noctuidae) is an important migratory agricultural pest worldwide, which has invaded many countries in the Old World since 2016 and now poses a serious threat to world food security. The present monitoring and early warning strategies for the fall army worm (FAW) mainly focus on adult population density, but lack an information technology platform for precisely forecasting the reproductive dynamics of the adults. In this study, to identify the developmental status of the adults, we first utilized female ovarian images to extract and screen five features combined with the support vector machine (SVM) classifier and employed male testes images to obtain the testis circular features. Then, we established models for the relationship between oviposition dynamics and the developmental time of adult reproductive organs using laboratory tests. The results show that the accuracy of female ovary development stage determination reached 91%. The mean standard error (MSE) between the actual and predicted values of the ovarian developmental time was 0.2431, and the mean error rate between the actual and predicted values of the daily oviposition quantity was 12.38%. The error rate for the recognition of testis diameter was 3.25%, and the predicted and actual values of the testis developmental time in males had an MSE of 0.7734. A WeChat applet for identifying the reproductive developmental state and predicting reproduction of S. frugiperda was developed by integrating the above research results, and it is now available for use by anyone involved in plant protection. This study developed an automated method for accurately forecasting the reproductive dynamics of S. frugiperda populations, which can be helpful for the construction of a population monitoring and early warning system for use by both professional experts and local people at the county level.

Published
2023
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