bluuebunny/crossref_metadata_2025 huggingface dataset:
Regression analysis of the effect of party education and management on organizational cohesion
Authors: Xue Jun
Published: May 2024

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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.
Artificial Intelligence Technology Facilitates Model Innovation in Higher Education Management and Student Training Mechanisms
Authors: Liu Dangying
Published: May 2024

In order to promote the model innovation of higher education management and student training mechanisms, this paper proposes data mining technology to assist the research of education management and training mechanisms. Using web crawler technology to obtain the required initial data for the study, data cleaning and conversion are carried out to ensure the accuracy of the results of the research and analysis in response to the problems of missing data, intermingled noise, and attribute redundancy in the initial data. Aiming at the slow efficiency and collapse of the traditional association rule algorithm in the face of massive data, the whale optimization algorithm is used to optimize the association rule algorithm for multi-objective optimization, and the optimized association rule algorithm is used to analyze the data of higher education management. The data showed that the Confidence=77.82% for the association rule poor grades in introductory courses=>poor grades in major courses, which indicates that the probability of students whose average grades in introductory courses are outside the 75th percentile and those whose average grades in significant classes are outside the 60.00th percentile is 77.82%. This study aids teachers and administrators in making scientific decisions to enhance teaching management, enhance teaching quality, and reduce costs associated with school operations.
Dynamic Object Detection and Tracking in Vision SLAM
Authors: Liu Heng , Niu Lele , Deng Yufan
Published: May 2024

Addressing the trade-off between operational efficiency and localization accuracy in visual SLAM, this paper introduces a monocular visual-inertial SLAM algorithm that integrates point and line features. To construct the point-line reprojection error and optimize the observation volume in front-end vision initialization, the motion recovery structure method (SFM) is employed through 3D reconstruction with a sliding window. The marginalization method uses the removed keyframe information as a priori constraint for nonlinear optimization in the back-end. In addition, the loopback detection algorithm is optimized in combination with the bag-of-words model and four-degree-of-freedom global bitmap to improve the accuracy of dynamic object detection, and the performance of the algorithm is tested. The results show that in the case of no closed loop, the absolute root mean square error of the algorithm proposed in this paper is lower than that of VINS-Mono (0.0625), PL-VIO (0.0401), and PL-VINS (0.0554) for the majority of sequences. In the case of closed loops, the absolute root mean square error of the proposed algorithm in this paper is reduced by 0.0395 and 0.0139 on average over most sequences compared to VINS-Mono and PL-VINS. The proposed algorithm in this paper demonstrates higher accuracy and robustness for improved detection and tracking of dynamic objects.
Analysis of School-Enterprise Cooperation Talent Cultivation Mode and Its Problems in Agricultural Colleges and Universities Involving Agriculture in the Era of Melting Media
Authors: Qu Yanpeng , Li Heng
Published: May 2024

School-enterprise cooperation and innovation is an essential support for the implementation of an innovation-driven development strategy. This study examines the stages of school-enterprise cooperation and innovation, underpinned by integrated media, through the lens of deep coupling theory. It categorizes the process into pre-, mid-, and post-stages. The pre-stage involves analyzing university agricultural programs to develop a credit network database identifying optimal school-enterprise pairings. The mid-stage focuses on enhancing knowledge exchange mechanisms to tightly integrate participating entities. The post-stage assesses the impact of these integrations, revealing a coordination degree of 0.416 among agricultural majors, suggesting that effective interaction mechanisms are yet to be established, occasionally leading to mutual constraints. This research informs strategies to foster robust school-enterprise collaborations in agricultural education.
Construction of a Questionnaire System for College Students’ Consumption Views Based on Discrete Regression Algorithm in the Context of Ideological and Political Education
Authors: Su Dongmin , Li Yangfan
Published: May 2024

This paper constructs a questionnaire system for college students’ consumption views based on the discrete regression algorithm combined with the questionnaire method. The least squares staggered identification method is employed in the discrete regression algorithm to select the window width and reduce the integral square error of the estimation. On the basis of continuous and discrete data, the density function and regression function are estimated, and the parametric and nonparametric estimation methods are utilized to select the optimal smoothing parameters of the regression function by the method of least squares interleaved identification. In the survey of college students’ consumption outlook, the consumption outlook of college students in colleges and universities in the S province region is taken as the research object. In the questionnaire analysis, it is known that the first factor considered by college students is the sustainable use of products. The mean value of the sustainability dimension is 4.86, and the last factor considered is the ostentatiousness and extravagance of the consumption products, and the mean values are 2.65 and 2.71, respectively. Each basic situation of the college students and the social, family, personal, and influencing factors have a significant predictive effect on each dimension of the college students’ consumption outlook status.
Mechanism of grain refinement in FSW joints of 6063-T6 aluminum alloy under different rotational speeds
Authors: Sun Xuejiao , Ji Liangbo
Published: May 2024

The inherent properties of aluminum alloys often result in defects like deformation and porosity in joints and welds created through conventional fusion welding. Our paper investigates the impact of varying rotational speeds in the friction stir welding of 4mm thick 6063-T6 aluminum alloy, focusing on microscopic grain refinement and mechanical property alterations in T-joints. Using mechanical stretching and numerical simulation methods, we observed that the initial weld joint is robust, with minimal flying edges and a distinct fish-scale pattern on the surface. Moreover, the grain sizes in the weld’s core area are notably smaller than those in the region affected by the upper axial shoulder. The mechanical properties of the joint experienced a first increase and then a decrease in mechanical properties when the friction stir welding rotational speed, was increased from 600r/min to 1500r/min. Moreover, in 1000r/min rotational speed, the material welded tensile strength and yield strength of the best tensile strength compared to the raw material to enhance the 21MPa, yield strength of 30MPa, elongation close to the raw material of 89.86%.
The Impact of International Trade Development on China’s Free Trade and the Value of the Agricultural Industry Chain
Authors: Yin Zhiwei
Published: May 2024

The development of international trade is both a challenge and an opportunity for China’s free trade and agricultural industry chain. Linear regression modeling is employed in this paper to examine how international trade development affects the value of China’s free trade and agricultural industry chain. The variables in the linear regression model are set, and the correlation coefficient is calculated to obtain the correlation coefficient between them. This basis is used to test the regression coefficients for significance and multicollinearity using the least squares method. The data show that the difference between the minimum value and the mean value of the free trade economy index is significant, about 0.3-0.6, while the difference between the maximum value and the mean value is slight, about 0.1-0.4, which indicates that the free trade economy of the provinces with poor free trade economy in China is much lower than the average free trade economy level in China. The degree of international trade development shows the most apparent upward fluctuation from the five quantile regressions of 0.2, 0.4, 0.6, 0.8, and 1.0, gradually increasing from a regression coefficient of 0.2428 to 1.149, which suggests that the international trade development has a significant positive effect on the change of the positional situation of the value chain of the agricultural industry. This study not only enriches the connotation of the theory of free trade and the agricultural industry chain in China but also provides reference and information for enhancing the resilience and sustainability of the development of the agricultural industry.
Analysis of Diversification of Intelligent Teaching in English Literacy Integrated Classroom Empowered by Artificial Intelligence Technology in Colleges and Universities
Authors: Yuan Chunhui , Zhang Xiaoli
Published: May 2024

In recent years, an increasing number of English teachers have recognized the importance of reading and writing skills. Traditional English teaching methods often overlook the essential link between these skills, which hinders the improvement of students’ overall English proficiency. This paper introduces an adaptive Huber growth curve model to represent cognitive abilities in English reading. It develops an English reading ability detection model using a function-based approach. The model involves word feature extraction, fine-grained learning, and establishing information channels. These processes collectively contribute to a sequence annotation model that not only identifies but also automatically corrects errors in English writing samples. This facilitates integrated intelligent teaching of reading and writing skills. Analysis of English reading and writing capabilities among students at various colleges and universities reveals that the most notable improvement is in students’ critical thinking abilities during English reading, with most scores ranging between 3.5 and 4 and a total of 52 students participating. The difference in writing scores of the subject classes was 1.4186, of which the T value was 3.7855, the DF value was 112.3, and the P value was 0.000, which was significant, and the magnitude of the English writing scores of the subject class A was greater than that of the class B, which indicated that the integration of literacy and writing effectively improved the overall writing skills of the students.
A Study on the Development Trend and Mechanism Perfection of Cultural Industry in Western China Based on Variable Model
Authors: Luo Jing , Su Jiafu , Aumeboonsuke Vesarach , Yu Xin , Li Yuan
Published: May 2024

As an emerging industry with high growth, the cultural industry plays an increasingly prominent role in boosting national economic construction and enriching people’s lives. This paper utilizes the relevant statistical data of the culture industry in 2022, selects the indicators of input-output variables, and adopts the three-stage DEA method to measure the efficiency level of the culture industry in Western China and explore the development trend of the culture industry in western China after eliminating the influence of external environment and random variables on the analysis results. In addition, the level of cultural industry efficiency in West China is taken as an explanatory variable. Relevant explanatory variables are selected to derive the influence of each variable on cultural industry efficiency by the partial least squares method, and regional heterogeneity is detected. The overall cultural industry efficiency in the western region is low; more than 30% of the inputs do not create value, and 50% of the provinces and municipalities have a low level of cultural industry operation and management and low development of industry scale. Except for Chongqing and Shaanxi, all other provinces and cities are in the stage of increasing returns to scale. The selected explanatory variables all positively contribute to the comprehensive technical efficiency of the cultural industry, with the most significant effect of the urbanization level, with a regression effect of 0.387. Focusing on improving the operation and management levels and the scale of the cultural industry is the key to enhancing the efficiency of the overall cultural industry in the West.
Innovative Application of Modularized Virtual Interaction Design Technology in Clothing Design
Authors: Sun Ning , Sun Tao , Cao Botao , Mu Xichan
Published: May 2024

CAD-based clothing design is known for its ease and flexibility, yet it often lacks intuitiveness and requires extensive experience for successful garment creation. To address these limitations, this paper presents a novel modular virtual interactive clothing design system using OpenGL and 3D modeling technologies. This system employs virtual reality to enable three-dimensional interactions, creating 3D garments that are then mapped onto a 2D plane for further evaluation. The evaluation module assesses the garment’s balance, line coherence, looseness, and wrinkle aesthetics to finalize the design. The research demonstrates that design discrepancies are kept below 1% in this virtual setting. The system’s modular nature also ensures satisfactory garment fit and appearance, underscoring its practical significance and potential impact.
Exploration of Cultural Change of Film and Television Art Media Formation and Digital Cultivation Path of Media Talents
Authors: Wang Yi
Published: May 2024

The ongoing evolution of digital technology significantly transforms the format of film and television media, simultaneously diversifying the training modes and requirements for media professionals. In this paper, the comprehensive characteristics of film and television art media are analyzed, and specific manifestations of cultural change in the form of film and television art media are identified. At the same time, combined with the cultural change manifestations, it helps media talents to find their role positioning, clarifies the digital literacy structure of media talents, and establishes a double-loop digital cultivation model of the connotation and form change of film and television art media. To further explore the digital cultivation of media talents, a quantitative analysis of data was conducted on the market development trend and the cultivation of media talents. It was found that the overall market demand for media talents increased by 65.67% between 2015 and 2023, but the employment rate of media talents decreased by 3.85 percentage points between 2016 and 2020. The χ2 -test value of digital training of media talents is 26.317, which has a very significant difference at the 1% level. The digital cultivation mode of media talents based on digital technology can effectively enhance the satisfaction of media talents, better meet the demand for talents in the film and television art media market, and help the media industry develop with high quality.
Research on the Innovation of Smart Teaching Mode of University Physical Education Driven by Digital Technology
Authors: Cao Li , Cui Pengtao
Published: May 2024

Physical education teaching mode is the link between physical education teaching theory and physical education teaching practice, which has a direct impact on the quality and teaching effect of physical education teaching. In this paper, the recognition algorithm is applied to physical education, and a graph-convolutional neural network is constructed. In order to solve the problem that a graph convolutional neural network can only deal with non-motion graphs, using the Masked Attention mechanism, assigning different weights to neighboring nodes, extracting node features and features between neighboring nodes, thus the graph attention neural network, and introducing the YOLO model to predict the single and multiple postures and correct the students’ technical movements. Through the comparative experimental study in this paper, it was found that the p-values of the four dimensions of students’ attention to athletics, adverse interest in athletics learning, positive interest in athletics learning, and daily athletics exercise were all 0.000<0.05. In the two dimensions of positive interest in athletic learning and daily athletic exercise, the mean values of the students in the experimental group reached 29.11 and 32.89, respectively. In terms of comparing the results of the students in the two groups, the 50-meter Run p=0.021<0.05, Vertical Long Jump p=0.002<0.05, Seated Body Flexion and Sit-ups for girls p=0.000<0.05. Therefore, the data-intelligent physical education teaching model constructed in this paper can increase the degree of students’ interest in physical education, improve students’ participation in physical education classrooms, and optimize students’ physical education achievement and performance.
Exploring the Practice of Enterprise education in Higher education institutions in Information Age
Authors: Zhai Wenqiu
Published: May 2024

With the advent of information technology, higher education institutions are urged to elevate the role of enterprise education. This includes a focus on the strategic use of information technology and the platforms that support IT practices, alongside refining the educational and assessment frameworks for enterprise studies. This paper advances enterprise education in higher education institutions by leveraging information technology to enhance the evaluation framework for entrepreneurship and innovation skills. We construct an enterprise education assessment index system and optimize the BP neural network with the ABC algorithm. Additionally, empirical quantitative research utilizing the ABC-BP model explores the effects of enterprise instruction and execution in these institutions. The results of the quantitative analysis show that overall, creativity and enterprise environment are the main factors affecting the implementation of creativity and enterprise (weight 0.722), and there is also a significant correlation between the three aspects of creativity and enterprise awareness (0.134), practice (0.111), and ability. In the percentage of each type of option in the statistics of the effect of the implementation of enterprise education in University X, the percentages of “agree with The total proportion of “agree” and “somewhat agree” is more than half of 70%, indicating that the main body of the survey is more satisfied with the current implementation effect of enterprise education in University X. The effect of the implementation of the University of X is influenced by the degree of knowledge (0.475), the degree of recognition (0.234), etc. which is significant in general. In conclusion, the assessment system for enterprise education in this paper can improve the degree of automation and the teaching effect of creativity and enterprise.
The Construction of Physical instruction Teaching Reform and Innovation Guarantee System in the Information Age
Authors: Dong Bo
Published: May 2024

Enhancing the technical methods of teaching physical instruction in the information age and building an ideal guarantee system for teaching physical instruction reform and innovation are essential components of higher education development. The construction path of the physical literacy teaching reform guarantee system is presented in this paper, along with the development of an evaluation model for the effects of physical instruction reform teaching. This model serves as the basis for evaluating the impact following the implementation of the physical instruction teaching reform. The assessment model relies on the hierarchy analysis approach, which also establishes the second-level fuzzy complete judgment matrix, creates the rubric set for the assessment of the teaching reform effect, and demonstrates the weight value of each indicator in the evaluation model. With respect to the research object in the case analysis of the CA University physical instruction teaching reformation effect, the evaluation’s overall rating is 0.693, and it receives a “good” grade. The 50-meter run, seated forward bending test, and BMI endurance test items showed significant differences (P<0.05). Significant differences (P<0.05) were also presented in the dimensions of athletic ability, athletic participation, athletic awareness, athletic character, and learning interest in physical instruction learning outcomes, except for the dimension of athletic participation interest.
Constructing a Multimodal Music Teaching Model in College by Integrating Emotions
Authors: Song Jia
Published: May 2024

In this study, we enhanced the CaffeNet network for recognizing students’ facial expressions in a music classroom and extracted emotional features from their expressions. Additionally, students’ speech signals were processed through filters to identify emotional characteristics. Using the LRLR fusion strategy, these expression and speech-based emotional features were combined to derive multimodal fusion emotion results. Subsequently, a music teaching model incorporating this multimodal emotion recognition was developed. Our analysis indicates a mere 6.03% discrepancy between the model’s emotion recognition results and manual emotional assessments, underscoring its effectiveness. Implementation of this model in a music teaching context led to a noticeable increase in positive emotional responses—happy and surprised emotions peaked at 30.04% and 27.36%, respectively, during the fourth week. Furthermore, 70% of students displayed a positive learning status, demonstrating a significant boost in engagement and motivation for music learning. This approach markedly enhances student interest in learning and provides a solid basis for improving educational outcomes in music classes.
Exploration of Talent Cultivation Strategies for Higher Vocational Industry-Teaching Integration under the Orientation of Career Trajectory Portrait
Authors: Fan Junyan
Published: May 2024

The fusion of industry and education plays a pivotal role in optimizing talent training structures, facilitating the conversion of scientific and technological achievements, and driving the upgrade and high-quality growth of the economy. This study applies a clustering algorithm, a form of data mining, to categorize students based on personality traits, learning capabilities, and career preferences. This categorization aids vocational institutions in selecting suitable corporate partners for training programs. Furthermore, we introduce a collaborative filtering algorithm to establish a bipartite graph that matches the attributes of students and companies. This approach enhances the practical skills of students and supports the strategic integration of industry and education in talent development. After the experimental research, it was found that after the implementation of the senior industry-teaching integration talent cultivation measurement rate, the average score of the higher vocational education improvement status is 4.20, the average score of the industry’s satisfaction with the higher vocational is 3.35, and the average score of the higher vocational talent cultivation characteristics is 4.41, which indicates that the industry-teaching integration education model constructed in this paper can effectively promote the formation of the characteristics of the higher vocational schooling and talent cultivation. By integrating industry teaching, this paper’s parenting model can help change the vocational faculty structure and improve student employment rates.
Research on the Application of Multidimensional Collaborative Landscape Design Course Teaching in Revolutionary Historical and Cultural Landscape Design--Taking Zhuhai as an Example
Authors: Yang Bixiang
Published: May 2024

This study explores a multidimensional collaborative landscape design course, detailing its unique collaborative teaching framework within the context of Zhuhai’s transformative historical and cultural landscape. It employs a comprehensive set of metrics, including teaching objectives and methodologies, to assess the course’s effectiveness. The relevance of variations among elements was evaluated through statistical analyses, including T-tests, F-tests, and correlation studies. Further, the study examined participant satisfaction, visual appeal, and aesthetic impact of the “red cultural” landscape design. Results indicated that the average teaching evaluation scores surpassed 4 points, and satisfaction levels with the red cultural landscape design approached 80%, reflecting a beneficial influence on educational outcomes. This research contributes novel insights to the development of landscape evaluation systems in cultural tourism settings and offers theoretical advancements for implementing multidimensional collaborative teaching strategies in landscape design.