bluuebunny/crossref_metadata_2025_split huggingface dataset:
Interactive Multimedia Vocal Music Teaching System Based on Virtual Reality Technology
Authors: Guo Shanyu 
Published: December 2023

Abstract
Virtual teaching with the help of virtual reality technology to realize two-way interactive thinking and innovative teaching to create a good virtual learning environment for vocal learners. This paper combines the activity form and learning content of the virtual learning environment, designs the virtual scene, realizes the virtual display and virtual operation with the help of virtual reality technology, and completes the physical modeling of the virtual reality teaching environment. Combined with the objectives of vocal music teaching and the teaching needs of teachers and students, respectively, the teacher’s end, the student’s end of the functional design, the virtual simulation teaching and interactive multimedia vocal music teaching combined, using B/S architecture as the basis, follow the MVC design mode, virtual interactive multimedia vocal music teaching system design. The database design utilizes a top-down approach to demand analysis, using the teaching-centered E-R model and focusing on the three elements of the actual teaching curriculum. The vocal music teaching system underwent environment-building analysis, functional and performance testing, and real-world application testing. The practical application test shows that 92.5% of the students think that the virtual interactive multimedia vocal teaching system has a very strong degree of participation, and 90% of the students think that the virtual interactive multimedia vocal teaching system has a better learning efficiency compared with the traditional teaching mode.
The Application of Cognitive Linguistics Theory in Japanese Language Teaching in the Age of Artificial Intelligence
Authors: Shan Xiaoyan 
Published: December 2023

Abstract
This paper firstly summarizes the tense expressions in Japanese, Chinese and English according to the cognitive linguistics theory so as to derive the grammatical transformation law in the process of Japanese to Chinese or Japanese to English. Secondly, on the basis of artificial intelligence technology, a hierarchical Japanese phrase model based on maximum entropy tense classification features is proposed, and the extraction of Japanese phrase rules is realized through maximum entropy mathematical modeling to obtain the model feature function and decoding strategy, and the application of the model in Japanese language teaching is explained in the research. Then, the second-year students of Japanese language major in the School of Foreign Studies, Nanjing University of Posts and Telecommunications are selected as the research objects, research tools and experimental process are determined, and simulation analysis and statistical analysis are used to analyze the example of Japanese language teaching with the integration of artificial intelligence. The results show that on the model, compared with the baseline, the model in this paper improves the blue value by 0.64%, the comprehensibility by 4.39%, and the tense accuracy by 4.14% on the whole test set, which verifies the effectiveness of the hierarchical phrase model fused with the tense features proposed in this paper in Japanese-Chinese translation. In terms of Japanese language teaching, the independent samples t-test p-values were less than 0.05, and the students in class A outperformed the students in class B in the four question types: multiple choice, sentence ordering, Chinese-to-Japanese translation and composition. This study improves students’ language proficiency and achieves the objective of developing high-quality talents.
Power Mechanism and Practical Path of Agricultural Insurance to Help Rural Revitalization
Authors: He Tingting 
Published: December 2023

Abstract
This paper firstly explores the power mechanism of agricultural insurance to help rural revitalization from three aspects of agriculture, farmers and rural three farmers, respectively, and constructs the rural revitalization development index system by combining the entropy power method. Then, the three-stage DEA model and the three-stage Malmquist index model are used to measure the efficiency of agricultural insurance boosting rural revitalization by combining the selected agricultural insurance boosting indicators. Finally, taking province A as an example, after descriptive statistical analysis, the method of this paper is combined with empirical analysis, and the practical path of agricultural insurance to help farmers is proposed from the three aspects of the insurance system, publicity as well and supply. The results show that after the optimization of agricultural insurance, the value of technical efficiency is distributed in [0.600, 0.738], the value of pure technical efficiency is distributed in [0.716, 0.826], and the value of scale efficiency is distributed in [0.738, 0.833] from 2010 to 2019. The mean value of the agricultural technical efficiency index in each city is 1.091, the mean value of the progress index is 1.033, and the mean value of total factor productivity is 1.029, which is an upward trending technology, and all of them have a growth rate of more than 5%. Based on this study, agricultural insurance can help improve the efficiency of rural revitalization.
Research on Artificial Intelligence Enabling High-Quality Development of Vocational Education
Authors: Kong Ming , Yu Feilong , Zhang Zhichao 
Published: December 2023

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<0.05. For problem-solving ability, the average score of AI teaching students (M=4.049) is higher than the average score of traditional teaching (M=3.153), where t=14.745, p=0<0.05. The study is crucial for the utilization of artificial intelligence in education and the modernization and reform of teaching.
Data Mining Technology Helps Digital Teaching and Learning of English Majors in Colleges and Universities
Authors: Li You , Shang Fengmei 
Published: December 2023

Abstract
The use of information technology in the teaching of English majors in colleges and universities enriches the teaching means, especially the data mining technology that optimizes the digital teaching method. In this paper, starting from English writing, based on the functional requirements of writing training, we constructed a writing training process and utilized the NMF method to mine and decompose the English news text topics. In conjunction with the writing training, the data mining technology centered on the Rete algorithm was used to carry out automatic diagnosis of English composition on the basis of natural language processing. On the basis of mining and analyzing the English news text, the effect of English writing scoring was compared, and its enhancement effect on English composition was verified through controlled tests. The average writing score of the experimental group was 19.62, of which the full score was 25. The mean writing score of the control group is 16.38, which is 3.24 points lower than that of the experimental group. Significance Sig.=0.0004<0.05, P=0.025<0.05, there is a significant difference in the English proficiency of the two groups of students. Data mining technology enhances the language proficiency of students in English writing.
Problem Analysis and Legal Protection of the Exercise of Teachers’ Educational Disciplinary Rights Based on the Background of Big Data
Authors: Liu Junchen 
Published: December 2023

Abstract
The right of education and discipline is an important way of school education and teaching management, teachers to fulfill the teaching and educating people, the implementation of the fundamental task of moral education. This paper firstly discusses the dilemma of exercising the right to discipline teachers in education, and also analyzes the legal nature of the right to discipline in education and the impact on the emotional performance of teachers and students in the process of exercising the right. Secondly, cochlear filtering combined with CNN and LSTM network is introduced to extract the speech characteristics of teachers in the process of exercising the right of education and discipline, and a hybrid neural network model is used to realize the recognition and prediction of students’ auditory emotions. Finally, in order to verify the effectiveness of the method of this paper, experimental test analysis was carried out, and a comprehensive rule of law guarantee proposal was given in the process of exercising the right of teachers’ educational discipline. The results show that the maximum value of the intensity of the teacher’s speech signal after processing using the cochlear filter is 78.28dB, and the difference with the original signal is only 0.32%. The accuracy of recognizing students’ auditory emotions reached 90.48% after over 50 iterations. Under the background of big data, the right to discipline teachers in education needs to be analyzed with the help of technology for the data analysis of the appropriateness of exercise, and it is united in a number of aspects, such as strengthening the legislation, standardizing the implementation, strengthening the supervision, and perfecting the relief, as a way to help the comprehensive rule of law operation of the right to discipline teachers in education.
Emergency Resource Layout Planning Methodology with Multiple Constraints
Authors: Li Jing , Zhao Lexin 
Published: December 2023

Abstract
This paper first analyzes the characteristics and principles of the layout planning of emergency resources, explores the problems of emergency resource layout and distribution planning, and mentions the multi-constraint conditions of layout planning. Then, by describing the layout planning problem of emergency resources under multi-constraints and the related variable symbols, we constructed a two-layer layout planning model of emergency resources under multi-constraints, and after analyzing the particle swarm algorithm, we designed the layout planning model solving process based on particle swarm optimization. Finally, by constructing an emergency resource layout case, the centrality of the emergency resource layout network is explored, and the shortest distance and the best site selection of each emergency resource point corresponding to the demand point are divided. The results show that the structural degree centrality is between [0,0.78], the mileage degree centrality is between [0,1], the flow degree centrality is between [0.1,1], the structural median is between [0,0.32], the mileage median is between [0,2], and the structural proximity centrality and the mileage proximity centrality scores are both within the range of [0,1]. The shortest distribution distance of A, B, C, D, and E is selected to be only 393886m, and the error with the actual is around 0.009, which is able to carry out the layout planning effectively.
Research on the construction of evaluation system for high-level scientific and technological talents based on big data analysis
Authors: Wu Xue 
Published: December 2023

Abstract
This paper analyzes the three-level inclusion relationship of high-level innovative talents and combs the structure of high-level scientific and technological talent evaluation models based on big data technology. Aiming at the evaluation problems of high-level scientific and technological talents, a fuzzy neural network model is constructed, and at the same time, the R&D middle school effect is utilized to evaluate the innovation achievements of high-level scientific and technological talents. Construct the evaluation index system of high-level scientific and technological innovative talents by utilizing 6 first-level indexes, 14 second-level indexes and 48 third-level indexes. Create a hierarchical analysis structure model, evaluate the indicator data through a judgment matrix and consistency test, and output the indicator weights. Analyze the relevance of the indicator model for different input layer neurons in fuzzy hierarchical analysis through comparative experiments. Use empirical analysis to analyze the innovative evaluation scores of high-level scientific and technological talents in Group A. The experimental results show that when the input layer contains 48 neurons, the loss value ranges from [0.132,1.765], the loss decreases the fastest, the stronger the indicator correlation, the stronger the generalization ability of the fuzzy neural network regression model. The overall scores of the evaluation of high-level scientific and technological talents of Group A for the first and second-level indicators are 3.54 and 3.869, respectively, and the overall view of Group A’s high-level scientific and technological talent innovative ability is better. Good.
Imbalance analysis of regional economic law laws incorporating improved PPO algorithms
Authors: Yi Yanwei , Lin Xiaohong 
Published: December 2023

Abstract
This paper first analyzes the status quo of regional economic law coordinated development and draws out the mechanism and characteristics of regional economic law legal imbalance under the perspective of game theory. Then, on the basis of the proximal strategy optimization algorithm, the generative adversarial network is introduced, and according to the auxiliary role of the subjective metric constituted by the generator in the generative adversarial network as the dominance function to provide the real metric, the GAN-PPO algorithm based on the generative adversarial network is constructed to improve the GAN-PPO algorithm. Finally, after evaluating the performance of the improved PPO algorithm, the mechanism and degree of imbalance in regional economic law laws are studied using the GAN-PPO algorithm. The results show that the GAN-PPO algorithm reaches the peak gain at 1,250,000 steps, the peak value of the average reward obtained is 885, and the speed of convergence is improved by 0.42 in the sensitive environment, which realizes the acceleration of the algorithm. In the regional economic law imbalance, the degree of regional economic imbalance is between [0.1,0.48], the degree of industrial imbalance is between [0.08,0.43], the degree of capacity imbalance is between [0.10,0.45], and the degree of information imbalance is between [0.05,0.38], and the regional economic law legal imbalance is obvious, and it needs to be reasonably regulated.
Research on the Reform of the Teaching Mode of Rural English Education Assistance Based on the Technical Support of Network Technology
Authors: Su Zinan 
Published: December 2023

Abstract
Under the background of the development of network technology, this paper aims to promote rural English teaching and constructs an English teaching model that combines English recognition technology and rural teaching. The main process of speech recognition is examined by analyzing different speech recognition technologies. Using a deep learning network, an English speech recognition model has been established. Combined with the English acoustic features in the network data, fluency of English speech is evaluated. Data embedding is performed on the English sequences in the network, combined with the sequence probability in the English data, so as to determine whether the English speech is correct or not. The Eval value for the English recognition model based on deep learning is 5.49%, while the test value is 5.89%, as per the results. As the English dataset increases, so does the English recognition technique proposed in this paper, and the accuracy remains above 0.6, and when the dataset is 500, the speech recognition accuracy is 0.8. The teaching model that combines speech recognition techniques with English teaching improves students’ English to a certain extent.
Analysis of mental health influencing factors and students’ psychological education countermeasures based on ID3 algorithm
Authors: Li Hongfeng 
Published: December 2023

Abstract
This paper utilizes the data mining decision tree ID3 algorithm to improve the traditional ID3 algorithm, exclude the influence of other factors, and realize the decision tree ID3 algorithm by using the data mining decision tree ID3 algorithm in the database of college students’ mental health assessment in the application of mental health assessment in colleges and universities as an example. Among them, the number of nodes, the number of rules, the classification accuracy and the time of constructing the decision tree of the algorithm are compared to verify the improvement effect of the ID3 algorithm. The target dataset consists of psychological assessment data of students, which includes their basic situation and nine-dimensional psychological symptoms. Analyze the recorded data of students’ mental health status, extract the information on personality, parental relationship, economic income, and psychological abnormality, set the decision tree analysis variables, assign the value of students’ health status, and derive the specific factors affecting students’ mental health by using the decision tree If-Then classification rules. The validation results show that the generated decision tree ID3 model cross-validation estimate is 0.261, the standard error is 0.016, and its obtained standard error is less than 0.018, which indicates that the model fits better.
Research based on the use of digital media art in garden landscape design
Authors: Hu Huazhong 
Published: December 2023

Abstract
This paper takes garden landscape as the research object, discusses the application of digital media art in assisting garden landscape design, and obtains the optimization probability of various types of garden landscape types in landscape spatial layout through patch generation using the change simulation (PLUS) model. And after using the multi-scale Retinex algorithm to make image enhancement, a fusion of single-scale enhancement results in achieving the initial optimization of the image, after a dynamic interception and stretching operation to restore the enhancement effect to achieve the optimization of the landscape image. Finally, a group of landscape design images are selected as experimental objects to test the effectiveness of digital media art-assisted landscape design. The results show that with the assistance of digital media art, the modulus of the change distance of neighboring units is between 2.21 and 10.89, and the relative change rate takes the value between 0.45 and 5.21. The method is capable of balancing the ups and downs and repetitive rhythms in the design, ensuring that the landscape has good brightness and visual effects.
Economic Policy Uncertainty, Accounting Robustness and Commercial Credit Supply - A Big Data Analysis Based on Accounts Receivable
Authors: Guo Lei , Guo Xujie 
Published: December 2023

Abstract
In this paper, a two-dimensional panel data model of economic policy uncertainty is investigated based on the individual fixed effects of panel quantile regression, and a nonparametric panel model with individual fixed effects is established. The unfolding of nonparametric penalized spline and the introduction of Bayesian in stratified quantile are utilized to construct regression models applicable to accounting robustness, respectively. In the empirical study, the economic policy uncertainty index, accounting robustness and commercial credit supply are measured respectively. The annual data of China’s Shenzhen and Shanghai A-share listed companies during the period from 2012 to 2021 were selected as the research basis, and Bayesian quantile regression was made on the basis of correlation analysis. The coefficient of commercial credit supply is found to be -0.0821, and the variable RD1 is negatively correlated with economic policy uncertainty. This regression result confirms hypothesis H1 of this paper, suggesting that private firms invest less in innovation when economic policy uncertainty is higher. In the test of economic policy uncertainty by type, the regression coefficients of RD2, EPU, and SIZE are negative, respectively -0.0368, −0.2124, and -0.1458, which indicates that fiscal policy, monetary policy, and exchange rate and capital account policy uncertainty are negatively correlated with the supply of business credit to enterprises. Based on this correlation, this study provides guidance for the development of business credit for enterprises.
On the Traveling-Creativity Relationship: Effects of Openness to Experience, Cultural Distance, and Creative Self-Efficacy
Authors: Wojtycka Lidia 
Published: December 2023

AbstractIt is a common belief that travel allows us to grow, get inspired, and reach fulfillment. Travels offer a highly conducive combination of cognitive resource maximization, positive emotions, and, most importantly, new, out-of-ordinary experiences, enabling creativity to flourish. However, for travel to affect creativity in any way, some conditions must be met. Of key importance are characteristics of travel destinations and travelers’ Openness to experience. This study explores the creativity-traveling relationship by analyzing occurring interactive, mediating, and correlational effects. Also, it compares how traveling and living abroad predict creativity to address the ongoing debate. The analysis comprising 136 participants demonstrated that the traveling-creativity link is stronger among people low on the Openness trait. Further, an indirect effect of creative self-efficacy in the relationship between traveling and creativity was observed. These findings suggest the potential of facilitating creativity through traveling experiences among some groups, but at the same time, they call for more in-depth research on the topic.
Who are Lead users?
Authors: Boisadan Andréa , Buisine Stéphanie 
Published: December 2023

Abstract
Lead users are invaluable resources to generate user-centric radical innovation, but they remain difficult to detect and recruit in the general population. Lead userness, which draws both on the ability to identify unstated customer needs and find creative solutions to those needs, has been conceptualized as domain-dependent: this means that a lead user may generate innovation only in a specific domain for which they are an expert. In the present study, we aim to better understand the extent to which lead userness is a domain-dependent state (as elaborated in the literature) or a domain-independent trait. Following a questionnaire survey with 126 participants, we managed to reliably assess the empathetic side of lead userness (ability to identify needs) and showed that it was related both to domain-dependent characteristics (competences) and domain-independent trait (emotional intelligence). These results open up new avenues for implementing the lead user method in innovation projects.