bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploration and Improvement of Structural Imbalance Factors of Extramural Sports Competitions for Elementary and Middle School Students Based on Principal Component Analysis Methods
Authors: Du Fang , Shu Shengfang 
Published: May 2024

Abstract
With the continuous development of China’s sports competition business, the problem of structural imbalance in China’s sports competition has gradually appeared from the bottom. Starting from the extracurricular sports competitions of primary and secondary school students, this paper makes a preliminary sorting out of the structural problems of primary and secondary school students’ sports competitions. It puts forward a system reform method for the structural imbalance problem of sports competitions. In addition, the study randomly selects the teacher-student system of primary and secondary schools in District M as a research sample. It combines the principal component analysis model and the factor analysis model to conduct a more in-depth study of the factors affecting the structural imbalance of sports competitions. Among them, the cumulative explanatory rate of five factors, namely, policy support, environmental factors, sports industry, economic inputs, and competition activities, is 100%. The correlation coefficient values between the five factors are 0.632, 0.542, 0.371, and 0.675, respectively, with significant correlation. 7.3-15.5 points improve the scores of the indicators of the improved structure compared with those of the pre-improved structure. The structural imbalance problem was effectively resolved through system improvement in this study, resulting in a more sound and perfect sports competition system for primary and secondary school students.
Supply Side Reform of Tourism in Ethnic Areas Empowers Common Wealth--Based on the Perspective of Tourism Human Resources
Authors: Hu Xueqin 
Published: May 2024

Abstract
As part of the supply-side reform, tourism in ethnic areas is increasingly recognized as crucial for achieving shared prosperity. This paper introduces a model from the perspective of tourism human resources designed to predict the demand for such resources. The model aims to inform strategies that support supply-side reforms in tourism for ethnic areas. The GM(1,1) model is constructed with the gray algorithm model, and on the basis of the gray algorithm model, the gray prediction method is effectively combined with the BP neural network prediction method, and the prediction preferences are made according to the variance as well as the prediction method idea of the preferred combination, and the final prediction results are obtained. In the analysis of the tourism human resources profile and demand forecast in Xinjiang, the total number of tourism employment in 2022 accounts for 17.22% of the total number of jobs, and the total number of tourism students in school reaches 6,189. Only 11.66% of tourism human resources are highly educated talents with a bachelor’s degree or above, and the number of personnel with senior titles is only 8.42%, which is obviously low in high-education and high-level talents. Nearly 80% of the personnel in non-tourism-related categories are still there, and the specialization of tourism management personnel is low. The demand for tourism human resources in Xinjiang in 2027 is expected to reach 2.1179 million.
Effective paths and model innovations for social work-driven child protection in the context of the Internet
Authors: Li Xue , Yang Panpan 
Published: May 2024

Abstract
Children are the hope and future of the country, and doing an excellent job for children is of great importance to social development. Social work program efficiency assessment, can help service providers and program implementers understand the effectiveness of program implementation. For this reason, this study uses data envelopment analysis and the Tobit regression model to construct a child protection social work program efficiency assessment model. The input-output indicators of child protection program efficiency are selected. The model is used to analyze the input-output efficiency of social work child protection programs in City H from 2018-2021 as an example. The variables that affect the efficiency of child protection programs are explored in depth to explore the effective ways of child protection. The results show that the comprehensive technical efficiency, pure technical efficiency, and scale efficiency of the child protection program in 2018-2021 are all less than 1 and have not reached DEA efficiency. The comprehensive technical efficiency of the program is significantly affected by the scale efficiency, which necessitates an increase in resource investment in the child protection program. In addition, the six selected influencing factors are significant, at least at the 10% level, all of which positively affect the efficiency of child protection programs and need to be focused on to better improve the efficiency of social work services.
Artificial Intelligence Technology Helps Inform the Sports Industry
Authors: Shen Lin , Lyu Chen , Li Mingming 
Published: May 2024

Abstract
The continuous development and improvement of information technology and the arrival of the knowledge economy have injected new vitality into the development of the sports industry. In the context of artificial intelligence, this paper constructs a graph convolutional neural network model. It applies it to the field of sports teaching, creating an adjacency matrix based on image information to optimize the information processing speed of the neural network model. The standardized way is used to recognize and guide the various sports movements performed by students in the classroom. Through effectiveness analysis and FMS experiments, it was found that the graph convolutional neural network has a high recognition rate, and the matching rate for each section of the movement is above 70%. The mean values of angle features of students with very different body sizes remained at the same level with minimal differences under the same shooting angle. From the perspective of students’ sports performance, in the fourth week of the middle and late experimental period, the results of the experimental group and the control group students were 82.39±2.10 and 73.64±3.62, respectively, which was a difference of nearly 10 points. The results of the control group students had already lagged behind the experimental group students substantially from the perspective of the score, and the difference was significant at P=0.000<0.05. The convolutional neural network can effectively improve sports movement standardization, which in turn enhances the performance of students in physical education and promotes the information development of the sports industry.
Design of non-electrical protection device for 300Mvar-class large-scale phase-regulating units
Authors: Huang Jinjun , Wang Peng , Liu Zhiyuan , Han Jinsi 
Published: May 2024

Abstract
This study investigates the role of non-electrical protective devices in forecasting hazards for large 300Mvar class phase shifter units, which face overvoltage and overcurrent stresses under severe faults, distorting their internal magnetic fields. Utilizing migration learning, the research extracts target and auxiliary data to train autoencoders with sparse constraints. A deep learning-based DSAE-BP online recognition network is constructed using a backpropagation neural network. This network predicts potential safety hazards in large-scale phase-regulating units by analyzing data signals from connected sensors. Experimental results show delay time errors of less than 20ms and ripple rates between 1.40%-1.65% across varied current and voltage conditions, demonstrating the device’s accuracy and stability in fault prediction.
Exploring the Value, Risks and Its Path of Digital Transformation of Civics Teaching in Colleges and Universities
Authors: Li Mengyang 
Published: May 2024

Abstract
This paper uses deep learning algorithms to detect and extract student behavioral features in the Civics classroom. It first predicts and detects the target location and behavior of students in classroom images by FastR-CNN algorithm, extracts the detected student data features by MSResNet-50 algorithm, and then introduces the attention mechanism to screen the extracted behavioral features, and analyzes the accurate location information and channel information to get the student’s behavioral performance in the Civics classroom. The Civics element framework is used to construct a digital transformation path for Civics courses in this study. In order to reflect the value of the digital transformation of Civics teaching, the study conducted a teaching comparison practice. After a semester’s test, the Civics scores of the students in the five classes were above 80 (good or excellent). In contrast, the mean score of Civic Literacy in the post-test reached 3.863, which was significantly different from that before the practice (p=0.007<0.05). The value of “student-initiated speaking” behavior was higher than 45 in the practice class, and the student’s participation in the class was much higher than that in the control class. Analysis of the effect of teaching implementation found that the motivation score of students in class E increased from 3.511 to 4.957, with a significant difference (p=0.048<0.05). It was also found that the posttest score of “value concept” of students’ Civics literacy increased by 21.19%, and the score of “honesty and friendliness” also increased by 0.959 points. The massive amount of digital information generated by the implementation of the digital Civics teaching path in this paper may affect the student’s ability to think independently. However, the results achieved by the teaching path still provide reference ideas for the innovation of Civics teaching and reference data for the value and significance of the path’s implementation.
A study of key techniques in mathematical input-output modeling in the field of management accounting
Authors: Liu Shen 
Published: May 2024

Abstract
In this paper, we explore the integration of a stochastic input-output model based on uniform distribution into management accounting systems to enhance operational efficiency in enterprises. The model is formulated as the mathematical expression of an input-output table, focusing on the structure of the direct consumption coefficient matrix. By applying this model to the financial data of Y Iron and Steel Enterprise in W City, we evaluate the enterprise’s competitiveness and input-output performance. From 2019 to 2023, the company’s capital rate increased markedly from 0.0235 to 0.0868, reflecting a stronger resilience against lousy debt risks. Furthermore, we observed substantial growth in assets, deposits, and loans, with 2023 figures at 0.4965, 0.5839, and 0.3899, respectively. These metrics highlight the rapid development of the financial market and expansion opportunities. Our analysis demonstrates the utility of input-output models in management accounting to qualitatively assess and optimize product output and sales, thus ensuring greater overall operational efficiency.
Research on the Development of College English Pedagogy System in Cross-cultural Perspective
Authors: Jin Tiezhu 
Published: May 2024

Abstract
Current college English programs at universities suffer from an inadequate teaching system and poor practical results, which hinder the effective development of students’ intercultural communication abilities and reduce their interest in learning the subject. This study integrates the output-oriented approach with blended teaching techniques to develop a college English teaching model. Utilizing University A as the research subject, we designed questionnaires and conducted teaching comparison experiments to evaluate the model’s effectiveness. The entropy value method calculated the weights of formative evaluation indices, while the fuzzy comprehensive evaluation model assessed the teaching quality. The results of the data analysis show that the reading character of students in class A under the blended teaching mode shows significant differences. The total score of reading level score is 21.07 points higher than that of students in class B with traditional teaching, and the speaking score rises by 3.468 points. The quality of college English teaching in University A was rated good, with a comprehensive score of 90.32 points using the fuzzy comprehensive evaluation model. The POA-based college English blended teaching model and formative evaluation system provide a new reference for innovating the college English teaching model in colleges and universities and boosting the intercultural communicative competence of college and university students.
Research on Electromagnetic Sensing Detection Technology for Non-Destructive Testing Applications
Authors: Wang Dongdong , Cao Feng , Guo Shuzhi , Yu Yan 
Published: May 2024

Abstract
Nondestructive testing technology, as an indispensable part of modern industrial production, is of great significance for guaranteeing product quality, improving production efficiency, and ensuring production safety. This paper is based on nondestructive testing and electromagnetic sensing detection technology research. The study first adopts ACFM detection to analyze the sensitivity of the surface defect parameters of the material to be detected, and based on the analysis of the magnetic circuit of the electromagnetic sensing structure, to build a mathematical model of ACFM and electromagnetic coupling probe, and then through the magnetic method of non-destructive testing on the material cracks in the detection of the signal effect of the study. The results show that the amplitude of the response signal increases with the increase of the defect angle from 0 to 7 ms, reaching a maximum value of 0.24–0.26 around 6 ms. The amplitude of the response signal decreases with the decrease of the defect angle from 7 to 14 ms and reaches a minimum value of −0.16–0.18 around 14.5 ms. The amplitude of the detection signal is related to the depth of the crack and the length of the surface defect of the steel sheet specimen. The crack depth and surface defect length of the steel plate specimen influence the detection signal’s magnitude. When the defect depth and surface length of the steel plate specimen are 1.5 mm, the detection signal value is weak, and the noise on the surface of the steel plate specimen has a significant effect on the detection signal. Promoting the development and application of NDT technology is greatly aided by the results of this paper.
A Systematic Study on the Dilemma and Innovative Path of Rural Family Education Development in the Context of Deep Learning
Authors: Li Jun , Yang Qilin , Xia Feng 
Published: May 2024

Abstract
In order to better improve the level and quality of rural family education, this paper adopts text mining technology to interpret the relevant data of rural family education under the background of deep learning. On the basis of deep learning algorithms, web crawler technology is used to obtain rural family education research data. It is found that there are null values and repetitive values in the acquired research data, so it is necessary to further clean the research data. After washing, the combined Bi-LSTM-CRF algorithm is used to process the data for Chinese word segmentation, and at the same time, the stop word list is improved in order to achieve the best word segmentation effect. The LDA thematic model was used to determine the influencing factors of rural family education, and then the linear regression algorithm was used to analyze rural family education empirically. Rural teachers with different education levels were not significantly different in Q1 (1.608), Q2 (0.117), Q3 (2.019), Q4 (1.733), and Q5 (2.042), according to the results. The adjusted R2 is 0.133, indicating a fair fit between the model obtained from the regression analysis and the actual data, and the regression coefficient of family education is 0.411 after eliminating the confounding interference of grade and political appearance. This study purposefully proposes a path for the innovative development of rural family education, which can provide a theoretical reference program for the development and construction of modern rural family education.
Exploring the Path of Civic-Constitutional Construction of Civil Aviation Professional English Courses in the Information Age
Authors: Shen Weihua , Chen Hongyan , Zhang Yuanting 
Published: May 2024

Abstract
The form of online teaching in the information age has become the mainstream of the construction of civil aviation professional English courses in Civics. In this paper, the digital resource module for the English course Civics for Civil Aviation Professionals is screened out by combining it with the teaching design of the Civics course for civil aviation English courses. With the help of the subtitle text selection method and the semi-supervised model of S4VM to label the teaching resources of the English course Civics, the CUMPF model is used to recommend the teaching resources of the English course Civics. Collecting and organizing the online learning behavior data of flipped classrooms to explore the influence of long and short-acting course resource design factors on the continuity of online learning, and recommending teaching resources based on the analysis results. The results of the effectiveness of the construction of the civil aviation professional English course’s Civic and political construction are analyzed from the degree of integration of the course’s Civic and political elements as well as from the four dimensions of course background, course guarantee, course implementation, and course effect, respectively. The integration degree of English course Civics resources for civil aviation majors is the best, which can reach up to 3.9315. The overall construction scores of the English course Civics are 0.907, 0.809, 0.744, and 0.768. The construction of the course implementation dimension needs to be improved, and the teaching materials of the English course Civics need to be improved in terms of writing and design. Civil aviation majors can benefit from the study’s ability to check and fill in the gaps in the Civics and Politics of English course construction.
Value, Dilemmas and Innovative Strategies of Educational Management Clustering in the Internet Era
Authors: Tan Binghua 
Published: May 2024

Abstract
With the continuous improvement of the national education system, the Internet brings new opportunities for educational development but also brings specific challenges to the educational management of colleges and universities. This paper aims to analyze the current situation of education management in colleges and universities and construct an innovation model for education management clustering based on PDCA, which will be explored for its development value and power. And then, using the partial least squares regression algorithm and its modeling steps, to construct the educational management clustering regression model. The influencing factors of the educational management clustering model are analyzed with 12 “double first-class” colleges and universities in five provinces in Northwest China as research objects. The results show that the average comprehensive efficiency and pure technical efficiency of the universities in Northwest China range from 0.6585 to 0.9987 and from 0.773 to 0.994, respectively, indicating that the efficiency of higher education resource allocation in Northwest China is constantly improving. Compared with the traditional education management model, the colleges and universities applying the education management clustering model constructed in this paper in 2022–2023 show a scale-invariant trend, indicating that the colleges and universities have sufficiently invested in education resources and realized the scale efficiency. Educational management clustering can improve the efficiency of school educational resource allocation, thus improving the level of educational management and providing a theoretical basis for the study of innovative strategies in educational management.
Music personalization imputation method based on deep transfer transfer learning
Authors: Wang Jing 
Published: May 2024

Abstract
The current music recommendation is less efficient and cannot meet the needs of most people. This paper combines deep learning and migration learning to research music recommendations. It mainly utilizes the hybrid recommendation method of label recommendation and noise reduction autoencoder to achieve accurate music recommendations after extracting the features of music and the user’s preference features. In addition, in order to explore the recommendation effect of the model in this paper, the deviation between the measured score and the actual score of this model is compared and analyzed as well as the similarity difference of music with different features is explored in terms of HR, Recall, and NDCG index performance. The results show that the number of songs with a deviation of 2 or less in the predicted scores of this recommender system all account for 88% of the total number of songs, which is better than other models. In terms of HR, Recall, and NDCG, this paper’s model has better recommendation performance than other models, and the similarity of music recommendation between the same album and different albums is more than 0.65. This study is of great significance for eliminating the information barriers to enhance and explore the value of music data information.
Intelligent Assessment of Teaching Quality of Computer Technology Courses in Colleges and Universities Based on ISSA-DRNN
Authors: Xie Pinzhang 
Published: May 2024

Abstract
With the continuous development of artificial intelligence technology, its application in the teaching of computer technology courses in colleges and universities is gradually deepened. In this study, the traditional sparrow search algorithm (SSA) is first processed to find the optimal solution, and then the ISSA algorithm is proposed and modeled. Training the deep recurrent neural network algorithm (DRNN) and combining it with the ISSA algorithm resulted in the construction of the teaching wisdom assessment model for the course. Finally, a teaching quality evaluation system for computer courses is constructed and applied to explore changes in teaching quality. The results show that in the assessment of the teaching quality of computer technology courses, the course structure and the teacher’s profile occupy the highest weight, and the weights occupied by these two items are more than 0.7. Secondly, the accuracy of the ISSADRNN model reaches more than 95%, and the maximum error is 0.0284. The average scores of each index system are more than 88. The overall performance is good and close to excellent. The model output’s actual value is within the expected range and has high accuracy. It can be seen that the intelligent assessment model of computer teaching quality proposed in this study has broad application potential and practical value.