bluuebunny/crossref_metadata_2025_split huggingface dataset:
Regression analysis of the effect of party education and management on organizational cohesion
Authors: Xue Jun 
Published: May 2024

Abstract
This paper divides organizational cohesion into dimensions, establishes a model of the relationship between party-building work and organizational cohesion, carries out statistics on the overall situation of the party’s work, and also measures the three dimensions of organizational cohesion - emotion, goal, and behavior - respectively, and subdivides the specific dimensions of the influencing factors. Then, the Pearson correlation coefficient was used to explore the strength of the relationship between party education and management work and organizational cohesion sub-correlation and to analyze the differences of party work on the strength of different organizational cohesion from the three factors of gender, political appearance, and grade level of attendance. Finally, organizational resources, number of projects, and organizational autonomy are selected as independent variables, and organizational cohesion is the dependent variable to establish a multiple linear regression model to explore the relationship between each single factor and organizational cohesion. The standardized partial regression coefficients beta of the three variables “organizational size,” “number of projects,” and “organizational autonomy” have larger absolute values, respectively 0.236, −0.096, 0.127, which has a significant relationship with organizational cohesion, in line with the relationship model between party building education and management work and organizational cohesion, strengthening the autonomy management of party building organizations and building the scale of party building organizations can improve the cohesion of party building organizations.
An Innovative Exploration of Music Integration into Art Education Teaching in the Context of Big Data
Authors: Wang Yunlong , Zhang Qun , Chen Jianrong 
Published: May 2024

Abstract
The interdisciplinary integration of art and music into education majors is a significant reform effort that benefits students’ overall artistic literacy. This study focuses on integrating music into art education teaching, with the goal of teaching concepts and empowering music applications. It uses k-means clustering to analyze the group profile of art teachers’ integration literacy. Then, we selected the influencing factors for music integration in art teaching, explored the relationship between them and the effects of art teaching, and proposed an effective way to integrate music into art education teaching. The results show that the group of teachers’ integration literacy can be divided into four categories: conservative (27.19%), ambivalent (47.50%), balanced (10.31%), and transformational (15.00%), and transformational teachers have the most vital ability to teach music integration. There was a significant positive correlation between the five dimensions of music integration in art teaching and art teaching effectiveness. The most essential effects on teaching effectiveness were found in creating a teaching context (0.217) and guiding the learning of art knowledge (0.154). The study can provide a basis for teaching music and art integration and individualized development of teachers’ integration literacy.
Exploring the Role of Traditional Music Elements in Music Art Appreciation
Authors: Yang Jingzhou 
Published: May 2024

Abstract
Music appreciation class is to appreciate and evaluate musical works through listening, experiencing, exploring and evaluating, so as to cultivate students’ aesthetic perception ability and music cultural literacy. This paper examines the relationship between music emotion and music elements, selects traditional music elements that have a significant impact on people’s perception of music emotion for labeling, and creates a data set. Then, based on the emotional characteristics of music elements, the role mechanism of traditional music elements in music art appreciation was explored. Based on the coupling model, we also explored the law of time evolution of the coupling system of “traditional elements-music empathy level.” Traditional music elements have a significant positive correlation (P=0.0021) with students’ empathy in music appreciation, as demonstrated in the results. The results show that students’ music appreciation ability can be significantly enhanced through the synergy of excellent traditional Chinese music elements in music and art appreciation, which can help them to establish a correct worldview, outlook on life, and values.
The application of OBE fused with PDCA teaching model in teaching English applied language
Authors: Yang Xin 
Published: May 2024

Abstract
In order to improve the quality and level of English applied language teaching in colleges and universities, this paper proposes the OBE-PDCA English teaching model combined with the knowledge tracking model. Using an exploratory analysis, the in-depth knowledge tracking model and the OBE-PDCA teaching model are analyzed extensively, and a specific application of the OBE-PDCA teaching model is proposed for teaching English applied language. The knowledge tracking model is used to obtain students’ behavioral characteristics and knowledge levels. In contrast, the knowledge tracking model is trained so as to complete the OBE-PDCA English teaching design based on knowledge tracking, and the validation of the teaching model adopts a two-group comparative analysis. The data show that the mean value of the control group is 15.22, while the experimental group’s score is 16.57, which indicates that the OBE-PDCA English teaching model can improve students’ English writing performance more efficiently compared with the traditional English teaching method. This study maximizes the students’ English teaching achievement and expression ability, which has a positive effect on the cultivation of English professionals.
Classification and Informatization of Subject Resources for English Language Teaching in the Context of Data Theory
Authors: Yin Bin 
Published: May 2024

Abstract
The construction of information resources based on the development needs of disciplines is the fundamental guarantee for carrying out disciplinary service work. An English teaching resource guarantee system is created by combining the OAI protocol with Open URL technology in this paper. Furthermore, the VIPS algorithm is used for style tree construction, combined with split bar weights and mixed text density for extracting web page body information. Then, the weight factor is introduced to improve the PageRank algorithm, and the critical resource selection strategy is combined to achieve the mining and classification of English teaching resources. In addition, the study introduces a knowledge graph for entity recognition and combines graph convolutional networks with user preference weights for optimizing teaching resource recommendations. Based on this basis, the performance of the constructed English teaching resources assurance system is verified for webpage information extraction, teaching resources classification, and personalized recommendations. It is found that the correct rate of English webpage information extraction is 96.42% when the text density of the preceding and following text is 0.334 and 0.527, respectively, and the personalized recommendation performance of English teaching resources is 4.12% higher than the best-performing KGCN model in terms of AUC index. The English teaching resources guarantee system can effectively ensure the precise classification of teaching resources in the English language and provide new guidance for furthering the automation of English teaching resources.
A Community Aesthetic Construction Based on Big Data Enabling the Integration of Chinese Traditional Culture into Ethnomusicology
Authors: Zhang Yu 
Published: May 2024

Abstract
Ethnomusicology, as an essential part of traditional music, is uniquely characterized by Chinese cultural connotations and national spirit and continues to progress with the development of modern information technology. In this paper, after determining the evaluation index system for Chinese traditional culture and ethnomusicology, respectively, the data of both systems are processed and analyzed. The coupling relationship between Chinese traditional culture and ethnomusicology is verified by integrating it through the coupling mechanism, and the evolution model of the community aesthetics coupling system is established. Relevant evaluation criteria are established based on the efficacy model. The aesthetics of the constructed community were used in practice, and the coupling between the systems was tested separately. The value-added of the coupling coordination degree reached 0.35797 during the 14 years of the test sites, and the coupling degree kept developing at a higher level above 0.99 after 2012. The grade was raised from level 6 to level 9, which has reached the level of coordinated development. There is a slight difference in the coupling condition between the two test sites, and the coupling coefficients are 3.414 and 3.455, respectively. However, the coupling condition is excellent.
Research on the Application of Music Technology in Modern Music Education in the Information Age
Authors: Wu Yuanhui , Kang Weijia 
Published: May 2024

Abstract
In the age of information technology, the way of music teaching as a whole has changed, and music technology has brought great impetus to modern music education. The purpose of this paper is to research music teaching and musicians’ paper-and-pencil music-making habits. Firstly, based on the joint hidden semantic model and convolutional neural network, we make full use of the decisive advantage of a deep neural network to extract features automatically, obtain higher-level music feature representation from audio content, meanwhile abstract the historical behavioral information of users’ interaction with music into scoring data and integrate it into the recommender system to generate reasonable music recommendation for target users, and realize note recognition through convolutional neural network. After verifying and analyzing the effects of note recognition and music recommendation models, they are used in music teaching. The results show that the model’s recognition of musical notes is more satisfactory, and the music recommendation accuracy is improved by 6.45%~10% compared with the comparison algorithm, and it still has a specific predictive recommendation ability in a cold-start environment. The music performance of the experimental class that uses the model presented in this paper to assist in music teaching has improved by 5.08%. The note recognition and music recommendation model can be introduced into music teaching to promote the innovation and development of music teaching concepts and teaching methods and improve the effectiveness of music teaching.
Application and Practice of Motion Capture Technology in Badminton Teaching
Authors: Yu Le , Feng Yu , Yu Lun 
Published: May 2024

Abstract
As Internet technology rapidly evolves, it significantly enhances the informationization of physical education. This paper proposes the implementation of the Openpose bone tracking algorithm to improve how students master movements in badminton training. By leveraging a convolutional neural network (VGG) to create skeleton maps, the algorithm accurately predicts body postures by examining the user’s center of gravity shifts and limb angle differences. These predictions allow for effective comparative correction of movements. To achieve multi-target action recognition, this paper introduces the SLIC algorithm, which is based on the Openpose algorithm and corrects and repairs action nodes that were incorrectly recognized to improve recognition accuracy. In the teaching experiment test for students of badminton elective class in S college, the retention rate of picking skills of the experimental group of students on the 35th day after the technical training was 101%, which indicated that the mastery of the movement skills was more solid. In terms of comprehensive scores, the average score of the experimental group’s attainment was 2.489 points higher than that of the control group, and the average score of the technical evaluation was 5.885 points higher than that of the control group.
Exploring the Teaching Reform of Computer Software Engineering Specialized Courses in Colleges and Universities under the Background of New Engineering Sciences
Authors: Zhao Hui 
Published: May 2024

Abstract
The issue of teaching quality in colleges and universities has received widespread attention, and teaching reform using information technology has become a way to improve the quality of university teaching. In this paper, an improvement method is proposed that combines the CBE competency education assessment model and improved C-ADDIE to create a teaching reform model for software engineering courses. After quantitatively assessing students’ professional competence using the IAHP-BP model, students with different competencies are divided by clustering and grouping to analyze the professional competence of software engineering students in terms of the whole and specialty. The professional competence score of the reformed students is 82.103 for the A class students, and the worse performing B class students, the professional competence score is only 72.639, and the gap between the two classes is close to 10 points. After the education of competency assessment with the model proposed in this paper, the student’s professional performance was improved with 11 points in the high score band, and the number of low score bands was gradually reduced. The model developed by the research is a valuable resource for computer software engineering students.
Motion Capture Sensor-Based Pose Estimation for Dance Canonical Movements
Authors: Zhou Xueting , Huang Juan 
Published: May 2024

Abstract
Motion capture technology, a developing technique for the quantification of human movement, is progressively revealing its unique significance within the realm of dance. This study introduces a motion capture approach using Kinect sensors to estimate normative dance postures. The sensors capture depth data, allowing for real-time, precise recording of a dancer’s posture. We propose a new method of similarity matching between feature planes to enhance the analysis of human movement postures. Evaluation trials have shown that this method, which focuses on feature plane similarity matching, yields more accurate assessments of movement complexity than traditional 3D model matching techniques. The feature plane matching-based similarity technique achieved the highest pairwise ranking precision, at 80.25%, using the Urban Dance Motion Quality Evaluation dataset. Additionally, it recorded the highest average bilateral ranking accuracy of 78.68% on the BEST dataset. This method has been proven to enhance the stability and efficiency of human posture analysis through its application of feature plane matching.
The Historical Requirements and Epochal Characteristics Analysis of the Chinese Periodization of Marxist Ethnic Theory Integrating Multimodal Information
Authors: Cai Fangchun 
Published: May 2024

Abstract
In order to continuously explore the new realm of Chineseization and modernization of Marxism’s ethnic theory, this paper proposes the study of Marxism’s ethnic theory based on multimodal information. Using LXMERT to initially encode the multimodal corpus of Marxist Ethnic Theory, the encoded multimodal features of Marxist Ethnic Theory are inputted into the noise filtering layer for training, which can more accurately determine the relationship between images and texts. In order to fuse the information of text and image in Marxist national theory multimodal, the multimodal attention mechanism is used to fuse the text and image context vectors, and the quality and efficiency of Marxist national theory multimodal features are improved by decoding. The specific types of manifestations of Marxist national theory that combine multimodal information are analyzed, and the research on the Chineseization of Marxist theory is also examined. According to the data, Marxist national theory has a multimodal sentiment recognition rate of 81.6%. Compared to the better performance of unimodal emotion recognition. The correct rate of students’ cognition of the era characteristics of Marxist national theory reaches 69.27%, which indicates that the students’ knowledge of the era characteristics of the Chineseization of Marxist national theory is mainly considered to be in general agreement and has not yet reached a perfect state.
Constructing and Empirical Research on Personalized Assessment of English instructors’ instruction quality in Higher Vocational Colleges and Universities
Authors: Cui Yan , Yu Xiuhua 
Published: May 2024

Abstract
Personalized assessment of English instructors’ instruction quality is one of the key initiatives to improve the quality of English teaching. This paper proposes an EM-AGA-BP model for English teachers to assess instruction quality. The entropy value method is used for the initial evaluation of English teachers’ teaching quality. The BP neural network is optimized for evaluation learning based on the genetic algorithm of adaptive mutation so as to put forward a more comprehensive and scientific English teachers’ assessment of instruction quality model. At the same time, the English teachers’ instruction quality evaluation index system is constructed. In the empirical analysis, English teachers in colleges and universities are taken as the research object to verify that the assessment of the instruction quality index system by English teachers has better reliability and validity. In the assessment of teaching evaluation quality, English teachers’ evaluation skills are high, with the largest mean value of 4.12, followed by evaluation attitude and evaluation awareness, with mean values of 3.8 and 3.71, respectively, and the overall evaluation score of English teachers’ personalized teaching quality is 3.02, with the evaluation grade level of “medium,” and the evaluation scores of the five evaluation criteria levels are all in the same range. The evaluation scores of the five evaluation criteria layers are all within the score range, and the evaluation level is also “medium.”
Analysis of transverse constraint force mechanics of anchor rods based on higher order theory
Authors: Jin Shenyi , Sun Xiaoyun , Zheng Haiqing , Zhang Wenlian 
Published: May 2024

Abstract
Research on the mechanical properties of transverse constraint force of anchor support under different loads can help to improve work safety. In this paper, based on the higher-order shear deformation theory, the higher-order whole-local theory of anchor rods is established with full consideration of the transverse normal strain. The geometric and physical equations in the intrinsic relationship are given for the wet thermodynamic behavior of anchor rods’ transverse restraining force. The equilibrium equations of the whole-local are constructed by combining them with the principle of virtual displacement. The analytical solution of the anchor core material was calculated by applying Navier’s method. The boundary displacement conditions of the anchor core material were solved. The anchor core material was modeled by combining it with ABAQUS finite element software. The mechanical analysis was carried out from the two perspectives of the buckling problem under thermal load and the parameter change of the transverse restraining force, respectively. It was found that when the thickness of the anchor bar increased from 20 mm to 50 mm, the radial displacement of the upper layer decreased by 52.95%, and there was no significant change in the positive stress at the upper and lower interfaces. The peak value of the upper interface shear stress decreases significantly from 0.55MPa to −1.41MPa when the anchor laying method is changed from a single layer to four layers. The combination of higher-order theory with ABAQUS software can effectively analyze the change of transverse constraint force of the anchor support, which can help improve its safety.
The Contribution of Ethnic Instrumental Art Education in Colleges and Universities to the Promotion of Multicultural Exchange
Authors: Li Jie 
Published: May 2024

Abstract
As a carrier of art and culture, the inheritance and development of ethnic instrumental music is of great significance to multicultural communication. This paper proposes a framework for teaching ethnic instrumental music in colleges and universities and selects evaluation criteria for teaching the art of ethnic instrumental music. On this basis, combined with the IPA model and related data, it analyzes the importance of the dimensions of ethnic instrumental music art teaching in colleges and universities and student satisfaction and thus obtains the strategic improvement path of the IPA model of ethnic instrumental music teaching. The dimensions of ethnic instrumental music teaching are taken as latent variables, and their contribution to multicultural communication is studied by constructing structural equations. It was concluded that students were most content with how teaching content was organized (3.775) and most minor content with how teaching evaluation was implemented (3.428) in teaching ethnic instrumental music. All dimensions of teaching ethnic instrumental art positively affect multicultural communication, with the highest contribution being teaching content organization (0.503). Colleges and universities need to maintain the strengths of teaching ethnic instrumental music in terms of teaching goals, content understanding, content selection, and thematic content representation strategies, and improve methods for conducting teaching activities to promote multicultural communication.
Code Clone Detection Based on Bytecode and Twin Neural Networks
Authors: Li Zhenhao , Lei Hang 
Published: May 2024

Abstract
In order to perform code clone detection in missing source code scenarios while ensuring the code clone detection effect, this paper proposes a code clone detection method based on bytecode and twin neural networks. The process begins by extracting the function’s opcode sequence from the bytecode instruction file. Then, the opcodes are vectorized using a neural network pre-training model to ensure that they contain semantic information. Then, a twin neural network is constructed based on GRU to compute the similarity between the vector sequences. The Opcode21K dataset dedicated to bytecode is used to test the constructed model. A total of 5818611 real clone pairs and 279112 fake clone pairs are detected, and the clone pairs that have been labeled by Opcode21K are plotted on the ROC curve so as to select the distance value of 0.7 as the code clone detection threshold. The number of clone pairs detected by SJBCD, the accuracy, and the recall rate are much higher than those of most existing methods. The number of large-difference code clones detected ranges from about 20% to 50% of the total clones. Additionally, the method’s runtime is the shortest for datasets with code lines ranging from 1M to 30M in size, and the detection time for a 250M dataset is approximately 54.5 hours. Therefore, the algorithm constructed in this study can take into account the detection of code clones in a variety of situations so that the efficiency of software development can be effectively improved.