bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on the construction of sports statistics index system based on AMOS model
Authors: Chai Weiqi , Zhang Mingliang , Guo Wangda 
Published: September 2023

Abstract
With the rapid development of the AMOS model, it provides new ideas for the construction research of sports statistical index systems. This paper firstly measures the level of sports development based on the current situation of the construction of a sports statistical index system, and the sports statistical index system is scored by the comprehensive index method. Secondly, it identifies for SEM model and AMOS model and establishes the sports statistical index system based on the AMOS model. Finally, it was verified that the dimensional division of the PE model and variable indexes were reasonable, and the relationship between latent variables was defended on the basis of variable index calculation and utility analysis. The results show that student expectations have the greatest positive total impact on students’ perceived value with a value of 0.58274, that student expectations have the greatest indirect impact on students, and that the indirect impact is close to its direct effect impact with a value of 0.26845, that the total impact on students ranks second with a value of 0.66374, and that student expectations have an indirect impact on student complaints and student loyalty through one and more intermediate variables. Thus, it shows that the AMOS model can effectively solve the problem of constructing a sports statistical index system and promote the development and innovation of research on constructing a sports statistical index system.
Innovative Research on Synergistic Development of Digital Integrated Media and Visual Design Based on Kruskal Algorithm
Authors: Liu Ren 
Published: September 2023

Abstract
This paper aims to explore the innovative development of synergy between digital media and visual design and improve and optimize the Kruskal algorithm model. The WTC-Kruskal algorithm is used to study and analyze the data generated by the combination of digital-integrated media and visual design and find the resonance point between digital-integrated media and visual design data. By studying the changes in visual design under digital media integration, we explore the new trend of synergistic development of digital media integration and visual design and thus propose feasible suggestions. The survey results show that most of the users prefer visual design presentation in the form of images, with percentages of 70%, 80% and 90% respectively, and the percentages of users who prefer paper presentation are very low, with 10%, 5% and 3% respectively. The user’s love for 3D visual design works is the highest in the questionnaire of different people; the percentage of those who like 3D visual design is 60%, 80%, 70% and 75% respectively. This paper provides effective reference data for the development of visual design and promotes better integration of digital integrated media and visual design.
Exploring the path of reforming college mental health education curriculum based on big data technology
Authors: Chen Lingjing 
Published: September 2023

Abstract
Big data technology’s quick advancement and widespread use provide fresh perspectives on how to change the mental health education curriculum at colleges and institutions. This study builds a prediction model for the college mental health education curriculum using big data technology, examines the prediction model’s development process, and builds a model assessment index using the SVM support vector machine technique. Second, it assesses the development status of the mental health education course reform in colleges and universities by looking at three elements of the mental health education courses in colleges and universities: the teaching strategy, the learning environment, and the student’s learning habits. Finally, using big data technologies, we investigated how college students’ happiness with their learning in mental health education courses was influenced by the mediating role of these courses and evaluated regression analyses of both holistic and partial teaching approaches. According to the findings, a comprehensive teaching approach had an 86.5% negative impact on student’s mental health under the direct effect, with a standard effect value of −0.134. Under the indirect impact, the standardized effect value of a holistic teaching approach on students’ mental health was −0.019, and the effect proportion was 12.7%. This demonstrates the significance of big data technologies for the establishment of a new mental health education curriculum in universities.
Research on the effective way of mental health education based on artificial intelligence technology
Authors: Chen Lingjing 
Published: September 2023

Abstract
In response to the imperfect development of the mental health education enhancement system, this paper uses artificial intelligence technology to explore and innovate effective ways to enhance mental health education. This paper firstly constructs the MDP model, value function, strategy evaluation, and strategy enhancement based on artificial intelligence technology to build a feed-forward neural network model. Secondly, it analyzes three aspects of mental health education: the course offering or not, the frequency of the course offering, and the relevant content of the course. Finally, the MDP model with artificial intelligence technology and feed-forward neural network model was used to verify the enhancement path of mental health education, and four aspects of mental health education were analyzed in terms of the cognitive situation, arrangement of content, course offering, and educational teachers and training. The results showed that only 5.875% of the teachers knew a lot about mental health education in schools, 37.25% said they knew more, and 57% said they did not know much about mental health education, which indicates that most teachers do not pay much attention to mental health education. Thus, it is feasible to explore ways to improve mental health education based on the context of artificial intelligence.
Optimization of Teacher Incentive Mechanism and Policy Supply in Rural China Based on Judgment Matrix
Authors: Lv Tiantian 
Published: September 2023

Abstract
With the continuous development of artificial intelligence technology, rural education is crucial in Chinese education, and the problem of rural teachers’ incentive mechanisms directly affects the quality of rural education. Firstly, according to the incentive mechanism of rural teachers, quantitative and qualitative research on the incentive mechanism of teachers in rural areas using the fuzzy evaluation method is proposed. In the fuzzy judgment matrix, each level is determined based on the decomposition of the previous level, and the results of the previous level are determined based on the calculation results of the next level. Then, using the relevant motivation theory and questionnaires, the principal and teachers of the school were investigated to understand the current situation and main problems of the construction of teachers’ motivation mechanism in the junior high school of Un Dong Town, Duyun City. Using the fuzzy evaluation method to analyze the difference between the actual feeling and expected demand of teachers’ motivation, the result shows that the difference between salary and promotion is 1.22 and 1.19, which means that the difference between salary and promotion is bigger in the motivation mechanism of rural teachers, and we should focus on reforming the salary scheme and implementing the promotion training mechanism of rural teachers. This study confronts the problem of rural teachers’ incentive mechanism, which has good theoretical and practical guidance for improving education quality and so on.
Research on multimedia intelligent algorithm based on recognition and detection of table tennis ball striking action
Authors: Dong Xinjing 
Published: September 2023

Abstract
There are many different types of batting motions in table tennis, and the accurate identification of these motion patterns is of great importance for the analysis of batting motions. In this paper, firstly, we explore the efficient representation of the batting motion in the time domain by reasonably placing the sensors and processing the collected data with respect to the characteristics of the batting motion. Secondly, based on the SVM algorithm, in real-world applications, the issue of creating complicated hypersurfaces is resolved using the kernel function technique., so that the simple hypersurfaces in the original space can achieve satisfactory classification results. Finally, a table tennis batting action recognition algorithm based on the SVM algorithm is calculated. The algorithm can efficiently extract the features of batting actions in temporal order and finally accomplishes an average recognition correctness of 93.58%, which is 4.155% more accurate than decision trees, 5.255% more accurate than random forests, and 3.305% more accurate than integrated classifiers. The best performance among the four classifiers indicates that the model has the best performance. This study demonstrates that the SVM algorithm model can quickly and effectively classify and identify action signals for the batting action during table tennis training.
Analysis of the influence path of Marx’s thought in contemporary college students’ Civic Education based on regression analysis
Authors: Liu Bin 
Published: September 2023

Abstract
This paper aims to investigate the influence path of Marx’s thought on contemporary college students’ thinking education, establishes a regression analysis model, determines the direction of the regression curve, uses the general analysis model to calculate the data of Marx’s thought as well as college students’ thinking education, and explores the influence of Marx’s thought on college students’ attitude towards Marx’s thought by analyzing the data of the influence situation of Marx’s thought on educated people and the data of college students’ attitude towards Marx’s thought. The data showed that 30.59% of the students were educated. The data results show that 30.59% of college students think that they can better show the national culture, 8.59% of college students feel that their after-school life is enriched, and 17.39% of college students feel happy. Only 12.9% of the educators only use textbooks for teaching, 10.77% of the educators use images in the classroom of university Civic Education, and 9.74% of the educators use short videos in the classroom of university Civic Education as a supplement so as to achieve the state of “no sound is better than sound at this time “This paper is a study of the influence of Marx’s thought on university education. This paper provides effective reference data for studying the influence path of Marx’s thought on university Civic Education.
Reform and innovation of Civic Education combined with deep and intensive learning
Authors: Kou Yilei , Zhao Meng 
Published: September 2023

Abstract
In order to respond to the call for reform and innovation of Civic Education, this paper establishes a new teaching mode of Civic Education by combining a deep reinforcement learning model with a Civic Education platform. Firstly, the modules and functions of the platform are designed, in which the modules are divided into the pre-class module, in-class module, and after-class module, and the functions are divided into front and back office management system functions. Then the deep learning based on value function and strategy gradient combines the Civic Education platform with deep reinforcement learning and designs a deep reinforcement learning model for Civic Education, which meets the requirements of Civic Education reform and innovation. Finally, the teaching practice of Civic Education reform and innovation was carried out, and the average attendance rate of students was obtained, which was 92.7% in the first round and 95.3% in the second round. 79 students (72.5%) had an excellent attendance rate in the first round and 85.4% in the second round. At the beginning of the semester, 67.64% of the students’ thinking structure belonged to low-order thinking, only 7.65% of the students’ thinking reached the structure of the association and abstract expansion, at the end of the semester, 60.59% of the students’ thinking reached the structure of the association and abstract expansion. It is concluded that the reform and innovation of Civic Education can improve students’ attendance and improve their thinking ability.
Research on Tourism Environment Carrying Capacity Evaluation of Tourism Demonstration Area Based on Objective Optimization Method in the Perspective of Territorial Tourism
Authors: Lu Xueying , Wang Na , Wang Juan 
Published: September 2023

Abstract
Based on the analysis of the influence of core subjects on the carrying capacity of the tourism environment, this paper constructs the “PSR” mechanism and builds the urban tourism environmental carrying capacity index system from three perspectives of natural, economic and social components of the tourism environmental system. The article researches the tourism environmental carrying capacity from three perspectives: economic benefit, social benefit, and environmental benefit, and constructs the objective function from three perspectives: maximizing the average tourism economic income, minimizing the emission of pollutants, and maximizing the number of accommodated subjects. Taking the state of the tourism environmental carrying capacity index as the constraint, the multi-objective optimization model of tourism environmental carrying capacity is constructed, and the optimization model is simulated and solved with the help of NSGA-II to provide a reference for the choice of decision-makers scheme. According to the evaluation of the tourism environment carrying capacity by the formula, the tourism environment carrying capacity coefficient increased from 0.1118 in 2012 to 0.8434 in 2021. The natural tourism environment carrying capacity coefficient increased from 0.2686 to 0.7893, the economic tourism environment carrying capacity coefficient increased from 0.064 to 0.8183, and the social tourism environment carrying capacity coefficient increased from 0.0925 to 0.9248. The evaluation and optimization of tourism environment carrying capacity conducted in this paper are of practical research value for guiding the sustainable development of tourism destinations.
Design of WeChat Public Service System for Toilets in Tourist Attractions Based on Adaptive Recommendation Algorithm
Authors: Yao Qifang , Zhang Li 
Published: September 2023

Abstract
This paper aims to design a microsoft public service system for toilets in tourist attractions. Through the research and analysis of the adaptive recommendation algorithm, an adaptive recommendation algorithm model based on deep reinforcement is constructed. Using the algorithm model to analyze tourists’ demand data for the scenic toilet service system and tourists’ expectations of the system functions, a WeChat public service system with finding toilets as the core was established. The results show that the most important channel for tourists aged 13-17 to obtain toilet information is through the scenic spot staff and the information column, accounting for 40% and 42%, respectively, while tourists aged 66 and above mainly obtain toilet information through the scenic spot toilet slogan, accounting for 52%, and the older stage considers more the distance of the toilet from the departure place the number of visits in 200, and the middle-aged and young tourists consider more the function of toilet finding. The number of visits is 200, 180 times. This paper provides an effective reference for the design of the public service system of Wechat for toilets in tourist attractions, which is conducive to promoting the update and improvement of the system.
Effect of low-intensity exercise therapy combined with health education on quality of life and blood pressure in hypertensive patients
Authors: Qin Liu , Safwan Bin Samsir Md. 
Published: September 2023

Abstract
In this paper, starting from exercise prescription and health promotion of hypertension, the hyperparameters of the XGBoost model are optimized using the Bayesian optimization algorithm, and then the BO-XGBoost blood pressure detection model is constructed. The model can estimate blood pressure from the ECG pulse wave signal of hypertensive patients and understand the patient’s blood pressure by PPG signal and ECG signal. For the effect of low-intensity exercise therapy combined with health education on the quality of life and blood pressure of hypertensive patients, experiments of the model and comparative test analysis of quality of life scores were conducted in this paper. From the model detection, the systolic and diastolic blood pressure detected by the BO-XGBoost blood pressure detection model was 118.6 mmHg and 65.2 mmHg, respectively, with an error of 3.03% and 3.83%, respectively, compared with the standard value of blood pressure. In terms of quality of life, the quality of life scores of the control and experimental groups improved by about 14% to 20% after the intervention compared with those before the intervention. This indicates that low-intensity exercise therapy combined with health education can help hypertensive patients improve their blood pressure control and quality of life.
Research on the construction of enterprise financial management information based on feature set
Authors: Jin Yingying 
Published: September 2023

Abstract
This study suggests a PSO-SVM financial crisis early warning model aid organizations in developing an efficient financial crisis early warning model for early financial crisis avoidance. For feature set selection, a wrapper method is utilized, in which the classifier’s learning algorithm and feature set selection are combined. The SVM is utilized as the classifier, and its feature set and kernel function parameters (C and δ
2) are employed as the placements of the particles in the PSO, with the SVM’s classification results being used as the adaption values. By achieving the near-optimal feature subset and kernel function parameters, the results are close to the model’s ideal predictions. The PSO technique is used to concurrently optimize the feature set and the kernel function parameters to remove unnecessary or redundant features. According to the findings of the model comparison, the SVM’s accuracy is 80.31%, which is less than the accuracy of the PSO-SVM model, which is 94.55%. The accuracy and recall of the PSO-SVM training set are 71.39% and 81.87%, respectively, while the accuracy and recall of the test set are both 70.53% and 72.29%, respectively. In comparison, the SVM model’s test set accuracy rate is just 34.57%, while its training set accuracy rate is only 44.01%. This suggests that the PSO-SVM model put forward in this research has seen significant improvements in both the accuracy of indicator selection and indicator interpretability.
Exploring the Construction and Practice of College English Blended Teaching Model Based on Fuzzy Comprehensive Teaching Evaluation Model
Authors: Lan Lan 
Published: September 2023

Abstract
In order to explore a new English teaching mode, this paper constructs a hybrid teaching model of English in colleges and universities combined with multimedia to respond to the call for reform and innovation of teaching mode. Firstly, through analyzing three hybrid modes of teaching: complementary mode, flipped mode and cooperative mode, a multimedia-based hybrid English teaching model is constructed in combination with current multimedia technology. Secondly, the fuzzy comprehensive teaching evaluation model based on EWM-AHP-DEMATEL and the teaching quality and learning quality evaluation index system of the hybrid English teaching mode in the multimedia context were constructed. Then in the teaching evaluation system, it was found that the satisfaction of teaching materials construction after the improvement was only 85%. There is still a lot of room for improvement, but overall, all have more than 5% satisfaction improvement. In the learning evaluation system, the number of outstanding students in English class participation, English accompanying test, innovation challenge, and English practice all increased by more than 5, and the number of those needing efforts decreased by more than 3. The overall grade improved by about 12% compared to the previous semester. Finally, the conclusion found that this new teaching model can improve teaching ability and students’ English learning ability and is worth implementing in colleges and universities.
Correlation analysis between the quality of physical activity and public health based on artificial intelligence technology
Authors: Wang Yong 
Published: September 2023

Abstract
In the context of artificial intelligence technology, the declining physical fitness of Chinese college students is still a serious social problem, and it is urgent to improve the physical health of college students. In this paper, the K-menns algorithm and decision tree CART algorithm are selected to be applied to the analysis and evaluation of college students’ physical health data based on the actual range of attributes of college students’ physical health data, the specific ideas of big data mining algorithm, and the characteristics and application fields of the algorithm are fully considered. Then, in the analysis of the physical health test data of class students, the percentage of the specific index amount to the total index amount is calculated, and the superior and inferior indexes are derived so as to realize the diagnosis of physical health posture. In order to investigate the correlation between physical exercise behavior and the health level of college teachers, a correlation analysis was conducted between the scores of 5 dimensions of physical exercise quality of college teachers and the scores of 8 dimensions of health level. The results showed that among the 5 dimensions, except for the behavioral intention and behavioral control dimensions, which did not have a statistically significant correlation with the physiological function dimension of health level, each of the remaining dimensions had a highly significant positive correlation with each dimension of health level P<0.01. This study promotes the modernization of physical fitness assessment of college students, which is important for maintaining health.
A deep learning model-based approach to financial risk assessment and prediction
Authors: Li Xin , Li Lin 
Published: September 2023

Abstract
This paper proposes a split-lending network model for bank credit risk, calculates whether a bank fails by simulating the changes in bank assets and liabilities over time, and adds the default rate calculation considering the characteristics of the default rate when a bank borrows. Meanwhile, the XGBoost-based classifier is used instead of random forest to improve the accuracy of classification, and the grcForest_XGB model is established. The activation function Sigmoid, the error function mean square error function, and the adam optimization function with the best effect at present are used to predict the accuracy of the grcForest_XGB model, and the different models are compared with the grcForest model for comparison experiments. The experiments show that the grcForest model has higher AUC and KS metrics of 0.8224 and 0.6368, respectively. The recall value is 0.8319, which ranks first among the six models. The Acc value is 0.9732, which is only 0.05 lower than LSTM, and is at a higher level. This study shows that the model is more accurate for risk assessment, can predict financial risks in advance, and make an effective assessment of financial risks.