Abstract This article aims to apply the fuzzy comprehensive evaluation method to evaluate the effectiveness of implementing sunshine sports in universities. This method is based on fuzzy mathematics and multivariate statistical theory, which can comprehensively consider multiple factors and achieve a comprehensive evaluation of the evaluation object through mathematical models. The article first introduces the background and significance of Sunshine Sports in universities and then elaborates on... This article aims to apply the fuzzy comprehensive evaluation method to evaluate the effectiveness of implementing sunshine sports in universities. This method is based on fuzzy mathematics and multivariate statistical theory, which can comprehensively consider multiple factors and achieve a comprehensive evaluation of the evaluation object through mathematical models. The article first introduces the background and significance of Sunshine Sports in universities and then elaborates on the basic principle and implementation steps of the fuzzy comprehensive evaluation method. On this basis, the article applies the fuzzy comprehensive evaluation method to analyze the implementation effect of Sunshine Sports in a certain university, including determining the weight of evaluation indicators, establishing a fuzzy evaluation matrix, conducting fuzzy operations, and obtaining comprehensive evaluation results. Finally, the article summarizes the advantages and existing problems of the fuzzy comprehensive evaluation method in evaluating the implementation effect of Sunshine Sports in universities and puts forward corresponding suggestions and prospects. Read More Read Less

Abstract Body part motion recognition is an important research direction in computer vision and artificial intelligence, widely used in motion analysis, rehabilitation medicine, and game interaction. Traditional methods for recognizing body part movements are usually based on image processing, machine learning, or deep learning techniques. This article proposes a body part motion recognition method based on fuzzy theory and a double-layer hidden Markov model (HMM). This... Body part motion recognition is an important research direction in computer vision and artificial intelligence, widely used in motion analysis, rehabilitation medicine, and game interaction. Traditional methods for recognizing body part movements are usually based on image processing, machine learning, or deep learning techniques. This article proposes a body part motion recognition method based on fuzzy theory and a double-layer hidden Markov model (HMM). This method aims to improve the accuracy and robustness of motion recognition, providing an effective solution for real-time motion capture and pose recognition applications. Read More Read Less

Abstract With the rapid development of information technology, computer talent training has become an indispensable part of various industries. In this context, the application of interactive school enterprise network computer talent cultivation management is gradually emerging, aiming to improve the efficiency and quality of computer talent cultivation. This article will analyze the application and explore its advantages, challenges, and solutions. The interactive application of computer talent cultivation... With the rapid development of information technology, computer talent training has become an indispensable part of various industries. In this context, the application of interactive school enterprise network computer talent cultivation management is gradually emerging, aiming to improve the efficiency and quality of computer talent cultivation. This article will analyze the application and explore its advantages, challenges, and solutions. The interactive application of computer talent cultivation and management in school-enterprise networks adopts various interactive methods, such as online forums, real-time chat, online testing, etc., to enhance the interaction between students and teachers, as well as between enterprises and schools, and improve teaching effectiveness. Read More Read Less

Abstract Food safety management is crucial for social stability and is an important component of the country’s long-term development strategy. Previous food safety management methods failed to achieve dynamic supervision of various links in the food production-to-sales process and needed more objectivity in food safety testing. Therefore, this paper introduces the Markov model into food safety management and optimizes it using the cuckoo search algorithm to... Food safety management is crucial for social stability and is an important component of the country’s long-term development strategy. Previous food safety management methods failed to achieve dynamic supervision of various links in the food production-to-sales process and needed more objectivity in food safety testing. Therefore, this paper introduces the Markov model into food safety management and optimizes it using the cuckoo search algorithm to improve parameter convergence speed and solve the global optimal solution problem. Experimental results demonstrate that based on the improved hidden Markov model, the food safety management model can effectively achieve dynamic food safety supervision and improve food safety risk assessment accuracy. In practical applications, it significantly enhances food management efficiency and improves technical and scale efficiency. Read More Read Less