bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluating the Effectiveness of the Practical and Applied Integration Teaching System of College English Based on Decision Tree and Rule Association Analysis
Authors: Qian Wei 
Published: January 2024

Abstract
In this paper, the basic framework of data mining is first proposed, and the data mining model based on the ID3 algorithm decision tree is constructed by analyzing the information gain of the attributes to divide each subset recursively, and the model is utilized to mine the data related to the teaching of practical application of English in the university effectively. Then, the attributes of support, confidence, and interest from the Apriori rule association algorithm are utilized to measure students’ evaluation of English teaching. Finally, the applicability of this paper’s algorithm was evaluated by indicators such as classification accuracy and computing speed, and the effectiveness of the English practical application integrated teaching system was verified in terms of the dimensions of students’ English literacy, learning interest, and classroom problems. The results show that the mean values of students’ English basic knowledge, English application ability, English core skills, and English awareness attitude are 4.02, 4.15, 4.06, and 3.99, respectively, and the students’ learning interest has been improved by at least 50%, indicating that the teaching effect is good.
The Construction of Teaching Effect Indicator Management System for Wushu Courses in Colleges and Universities Oriented by “Internet+Education”
Authors: Liu Jianguo 
Published: January 2024

Abstract
In this paper, the simpler wavelet transform method is used to remove the Gaussian noise contained in the image, reconstruct the approximation signal and the final processed detail signal, and obtain the estimated value of the noise signal to complete the image preprocessing. In the process of human static feature extraction, due to the structural limitations of the human body shoulder joint activity angle is low. Therefore, the local spherical coordinates are used to represent the joint angle characteristics of the human body in the static posture and, through the completion of the calculation of the distribution function of the action features of the target, to be tested to realize the recognition of the martial arts action. After completing the judgment matrix and consistency test, we finally establish the teaching effect index system for college wushu courses and analyze the teaching of ‘Internet Education’ wushu courses. The results show that the accuracy of the results of the four algorithms test dataset is stably maintained between 0.8 and 0.9, DNN algorithm, CNN algorithm, RNN algorithm, this paper’s algorithm loss average value of 1.34, 1.58, 1.75, 1.23, respectively, the combined accuracy and loss value, this paper’s algorithm compared to DNN algorithm, CNN algorithm, RNN algorithm performs better. Namely, the algorithm in this paper can accomplish action recognition with high accuracy. In the analysis of the teaching effect index evaluation of wushu course, the experts think that the matter dimension wushu course design index weight (0.800) > wushu teaching system (0.200), and wushu lecturers should design the course key points before the class. In this study, through the digital construction of teaching wushu courses in colleges and universities, we can achieve long-term development.
Research on the Path of Civic-Political Construction of Music Appreciation Courses in Public Art Education in Colleges and Universities under the Perspective of the Internet
Authors: Ma Huawei , Zhang Ying 
Published: January 2024

Abstract
In this paper, the association rule algorithm is used to mine all the strong association rules in the public art education music appreciation course, and the course Civics, and the Inter-transaction algorithm is utilized to decompose the mining task into two parts of long and short itemsets according to the time-consuming time, so as to reduce the number of transactional intersection operations. A new pruning strategy has been adopted to effectively limit the number of candidate sets and improve the performance of the algorithm. Finally, based on the model of this paper, we analyzed the relevance of the music appreciation courses in public art education in colleges and universities to Civics and the change in students’ Civics literacy after integrated teaching. The results show that the mean value of students’ moral quality after teaching increased by 3.24 from 18.07±2.08, and the p-value of each index except music literacy is 0.000, which is significantly different. And sup=0.05, conf=0.622, lift=4.499 for Music Art A and Introduction to Basic Marxist Principles A. There is a strong correlation between teaching music and Civic and Political Science courses.
An Introduction to the Innovative Path and Exploration of the Teaching Reform of Ethnic Vocal Music
Authors: Jiang Ke 
Published: January 2024

Abstract
With the continuous development of literature and art, vocal education, as an important part of aesthetic education, has also been developed unprecedentedly. This paper constructs a music emotion recognition model based on deep learning and the Lstm network. The preprocessing of music is accomplished through the methods of pre-emphasis, frame-splitting, and windowing so as to improve the purity of the music signal. Using the Mel frequency cepstrum coefficient and cochlear frequency, the music analog signal is converted into frequency features so as to better distinguish the acoustic features and combined with Word2vec to realize the extraction of music emotion features. By comparing the Lstm music emotion recognition model with other models, the performance of this paper’s model is verified in terms of classification accuracy. To understand the role of its embodiment, the music recognition model is applied to the teaching of ethnic music. The results show that the average fitness of Lstm music recognition is 75%-90% with the increase of the number of evolutions, and the average fitness of Lstm objective function reaches the peak at the number of iterations of 40, with a fitness of 95%. Under the music recognition model, the students’ spectrum is elevated to 0db above the reference line, and the amplitude mostly floats in the interval in (-3, -15), and the teacher can formulate appropriate ethnic vocal music teaching for the students’ spectrum.
Optimization of network flows for rural extension of fruit and vegetable agricultural technologies
Authors: Zhou Qiang 
Published: January 2024

Abstract
This paper focuses on the rural promotion of fruit and vegetable agricultural technology and proposes a network flow optimization model based on linear programming for the diffusion of fruit and vegetable agricultural technology. Based on the Bass model, it describes the process of natural growth of network users and the word-of-mouth effect among them. Fruit and vegetable agricultural technology diffusion in real social networks is fitted and predicted by the social network information dissemination model, and the network flow problem of fruit and vegetable agricultural technology promotion is optimized using linear programming equations. Based on this basis, the algorithm designed in this paper and the effect of rural promotion of fruit and vegetable agricultural technology are analyzed with relevant data. The results show that the coefficient of the variable of the number of promotion times in the behavior of agrotechnology promotion is 0.064, which has a significant positive effect on the evaluation of the rural promotion performance of fruit and vegetable agricultural technology, indicating that increasing the number of agricultural technology training and enriching the content of agricultural technology promotion will help to improve the evaluation of the rural promotion performance of fruit and vegetable agricultural technology by farmers. The network flow optimization model constructed in this paper can enable farmers to master more modern fruit and vegetable agricultural technology to meet the needs of modern production of fruit and vegetable agriculture so as to improve the level of local fruit and vegetable agricultural development.
Corporate Utilization of Bank Credit Financing Advantages under Supply Chain Finance and Industrial Policy Paths
Authors: Zhao Xiaolu 
Published: January 2024

Abstract
Bank credit financing is an effective method to promote the development of enterprises, and this paper discusses the use of enterprises in the credit financing advantage supported by supply chain financial networks and industrial policy in the new era. In the paper, the strategic choice of enterprises using bank credit financing is analyzed, the Nash equilibrium point of the bank and the enterprise is modeled by calculus, and the game evolution model of enterprise use of credit financing advantage is constructed to explore the equilibrium distribution of bank credit financing. On this basis, the regression model of bank credit financing and enterprise reputation is established, and it is combined with relevant data for empirical analysis. The results show that under the initial conditions, there are two evolutionary stable strategies of (0,0,0) and (1,1,1) in the enterprise bank credit financing game system, which verifies the analysis for the stability of equilibrium point under the dual mechanism of supply chain finance and industrial policy. The regression coefficient of bank credit financing of enterprises with greater corporate reputation is 1.26, and when the explanatory variable is the indicator of short-term lending and long-term investment, the coefficient of long-term borrowing ratio is -0.003, with a significance level of 1%, and the increase of long-term borrowing ratio can significantly reduce the behavior of short-term lending and long-term investment of enterprises.
Research on the Integration Mechanism of Cultural Industry and Tourism Industry Based on the Coupling Coordination Degree Model
Authors: Shen Hongtao 
Published: January 2024

Abstract
This research constructs an index system and uses the entropy weight technique to calculate index weights in order to assess the growth level of the culture and tourist industries based on panel data of 31 Chinese provinces and cities from 2012 to 2022. A specific grade of coupling coordination level is provided, and the coupling coordination degree model for cultural and tourist industries is developed. The worldwide autocorrelation of the culture and tourism sector is investigated using the Moran index, and the industry’s overall development level is assessed using the entropy weight approach. A relevant empirical study was conducted to investigate the mechanism that encourages the deep integration of the tourist and cultural industries. The findings indicate that the global comprehensive development level of the national culture and tourism industry has tended to increase annually from 2012 to 2019. From 2012 to 2019, the development level of the tourism industry has almost doubled, while the cultural industry’s comprehensive development level has increased by 68.88%. The overall country’s province and city-specific spatial and temporal evolution traits related to the coupling coordination level are not high, and the global autocorrelation analysis Moran index is greater than 0 and less than 0.3, indicating a strong correlation between the integration of culture and the tourism industry across regions. The level of overall coupling and coordination between the tourism and cultural industries is trending upward, but in order to achieve high-quality, coordinated development and encourage the in-depth integration of these two sectors, more capital investment and policy support are required.
Research on the Innovation of Physical Education and Physical Education Teaching Based on Big Data Analysis
Authors: Sun Mingyi , Gu Zhiyong 
Published: January 2024

Abstract
In this paper, Openpose is used to process the sports teaching video to get the coordinates data of the human body joint point positions in each frame of the video, and Kalman filter data fusion is used to establish the human skeleton model. According to the results of the division of the five major parts of the human body, after establishing the limb vectors of the human body’s torso, left arm, right arm, left leg, and right leg in three-dimensional spatial coordinates, the distances between the joints of the five human body skeletons based on the DTW posture matching algorithm were used to extract the characteristics of the sports error technical movements. From the demand of sports digital teaching, the design and implementation of sports basic movement teaching evaluation system based on the DTW posture matching algorithm, and the research and analysis of sports teaching under the background of big data. The results show that the IoU values of batting action localization in 6 segments of physical education teaching are 85.6%, 91.6%, 77.7%, 75.1%, 87.4% and 77.7%, respectively, and the average reach 82.5%, i.e., it shows that the research on action localization and recognition based on the DTW posture matching algorithm has a good performance. In the assessment of movement standardization in physical education, the maximum moment of stretching angle corresponds to the moment of hitting the ball, and its value reaches 3.79, i.e., it reflects that the evaluation system of physical education basic movement teaching can accurately determine whether the students’ movements are accurate or not, and make timely feedbacks to carry out the corrections of physical education movements. This study has the potential to enhance students’ interest and performance in sports and contribute to the advancement of digital sports teaching.
Research on the Innovation of Business English Teaching Mode in Colleges and Universities under the Background of Artificial Intelligence
Authors: Liu Shengming 
Published: January 2024

Abstract
This paper examines the application of artificial intelligence technology in business English teaching and artificial intelligence in natural language processing and recognition to receive good results. These two technologies are suitable for business English teaching innovation. At this time, the introduction of the concept of ADDIE is the process of integrating artificial intelligence technology into the business English teaching innovation model. The business English teaching model is designed to utilize the conditional random field expansion model to address the label bias limitations of the entropy model. Add the LSTM model to this basis to handle speech recognition and translation tasks to complete the construction of a business English teaching model based on LSTM-CRF. After speech recognition, detect the existence of grammatical errors in the sentence through the multi-task model, deform the LSTM model, and use the deformed Bi-LSTM to construct the multi-task learning model framework. The objective of controlled experiments and empirical analyses is to investigate the students’ willingness to learn AI Business English and their learning effects. The experiment shows that among the seven items of students’ willingness survey, only the mean value of the hedonic motivation variable is 3.93, and the mean value of the remaining six items is above 4. Students’ willingness to learn AI is high. In the comprehensive learning engagement degree, the mean value of the engagement is 1.457, and the highest value reaches 1.83278, and the students have a high degree of engagement in AI English learning.
Quality development of vocational education in the context of big data
Authors: Xuan Hui 
Published: January 2024

Abstract
Taking vocational education as an entry point, this paper utilizes factor analysis to deal with the problem of multicollinearity of vocational education indicators so that the synthesized factors are no longer correlated and lay a good foundation for vocational education cluster analysis. The distance measure and similarity coefficient describe the relationship between vocational education indicators. To increase computational efficiency and handle large and multidimensional data sets more effectively, the advantages of K-mean and grid clustering algorithms are combined to create the GBKM cluster analysis algorithm. Higher education institutions in Province H are chosen as representative samples in order to examine the variables influencing the development of high-quality vocational education, categorize the degree of that development, and forecast the trend of that development. The findings demonstrate that the GBKM cluster analysis algorithm’s accuracy difference between the predicted and actual data on the development trend of vocational education ranges from [0,0.1]. The algorithm’s absolute error value is 0.182, which falls within an acceptable error range and suggests that the algorithm proposed in this paper is capable of more accurately predicting the development trend of vocational education and may have some theoretical and practical implications for fostering high-quality development of vocational education. It has theoretical and practical implications for advancing the development of vocational education to a high standard.
Muscle Strength Enhancement and Metabolic Acceleration of College Students in Traditional Archery Programs Based on Functional Training
Authors: Zhang Dongsheng 
Published: January 2024

Abstract
At the present stage, the evaluation of human motor function is mainly semi-quantitative, which only evaluates the overall motor function from the degree of joint mobility and muscle status, but the size of muscle strength cannot be obtained by direct measurement. In this paper, we take the muscle activation degree and joint angle of college students in traditional archery programs based on “functional training” as the experimental objects and establish a muscle strength prediction model based on a generalized dynamic fuzzy neural network (GD-FNN). By analyzing the relationship between the surface electromyographic signals and muscle strength under elbow flexion and extension, we selected suitable parameters as the sample data of the fuzzy neural network and proposed a learning algorithm based on the variable sliding window of the GD-FNN. The predicted muscle force was compared with the desired muscle force of the main flexion and extension muscles through the subjects’ elbow flexion exercise and extension exercise. The normalized root-mean-square error between the predicted and actual muscle strength of the algorithm in this paper is less than 0.2. Compared with the maximal strength test, the peak extensor moments (right) and peak extensor moments (left) of the college athletes before and after the functional training, the mean values increased by 30.6 N.m and 42.39 N.m, respectively. Compared with the metabolism of the students during the ordinary training of 2.74 met based on the “functional training” of traditional archery increased, students’ metabolism to 5.03 met. It shows that functional training is favorable to the muscle strength of traditional archery college students and has a positive effect on the metabolic capacity of the body.
Innovation and Application of English Teaching Mode in Colleges and Universities by Integrating Entropy Power-Cloud Modeling
Authors: Du Hongmei , Zheng Pinsu , Cao Yuanyuan 
Published: January 2024

Abstract
This study divides eight indexes from three dimensions—the outer layer, middle layer, and inner layer—in order to evaluate the English teaching modes in colleges and universities. The evaluation is focused on the traditional English teaching method, the flipped classroom, and the blended English teaching method. An English teaching model assessment framework based on the entropy weight-cloud model is created by applying the cloud model to the English teaching model and using the entropy weight technique to establish the weights of each evaluation index. The comprehensive grade of each sample is computed using the subordination degree of each assessment index. A new teaching model is suggested based on the evaluation results, and the model is examined in terms of learners’ attitudes and learning effects in order to confirm the flexibility and benefits of the cloud model for the assessment of English teaching models. According to the data analysis, the three teaching modes’ values in the excellent grade are 0.001, 0.1502, and 0.3020. The comprehensive grade in the traditional teaching mode is poor, the comprehensive grade in the flipped teaching mode is medium, and the comprehensive grade in the blended teaching mode is good.
Diversified Teaching Strategies for College Swimming Courses in the Context of Artificial Intelligence
Authors: Sun Jiayi , Wang Siming 
Published: January 2024

Abstract
Swimming is a sport with a very significant exercise effect, so swimming courses in colleges and universities can promote the overall development of students’ physical fitness. In this paper, students’ swimming data are collected using intelligent sensors, and the collected data are noise-reduced and normalized by a low-pass filter. After the completion of data preprocessing, the swimming posture data features are extracted. The features are dimensionality reduced by the PCA method, combined with the BP neural network for training and accurate swimming posture recognition, and on this basis, a diversified teaching system for swimming courses in smart colleges and universities is constructed. After the students’ swimming data set was collected, the recognition effect of each swimming stroke was analyzed, and a comparison experiment was set up to investigate the practical effect and strategy of this teaching mode. The results show that the average accuracy of recognizing each stroke in this study can reach more than 0.988, and in the teaching test, the average difference between the performance of the experimental group and the control group is 7.6, and the P-value of the technical evaluation performance of the two groups of students in this project is 0.002<0.05, which significantly improves the swimming performance. This study can be combined with artificial intelligence technology to diversify the teaching of swimming courses in colleges and universities.
The Practice of Healthy Elderly Service Innovation Model Based on Data Analytics
Authors: Jing Meng 
Published: January 2024

Abstract
With the gradual deepening of China’s aging population, the status quo of “getting old before getting rich” has brought great challenges to the problem of elderly care. In this paper, we take the supply chain management of elderly services as the core and optimize the service cost and service quality through a two-layer planning model to obtain the best decision-making scheme. A particle Swarm Algorithm (PSO) is proposed to solve the model with intelligent evolution, and an incentive mechanism is established on the basis of the senior care supply chain, which maximizes its revenue by relying on the contract. Finally, by improving the SCORE model, data analysis and dynamic simulation of the senior care service supply chain can be carried out. The results show that the supply chain of senior care service reaches the optimization when the ratio of the capital input of community, institution and home is 0.2:0.2:0.6, and its equilibrium ratio stabilizes at about 96.0%:4%, which effectively alleviates the current pressure of senior care service. This study realizes the coordination of information and interests in the supply chain of community senior care service, which is of great practical significance for the innovation of healthy senior care service.