bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on Multiple Evaluation of English Teaching in Higher Vocational School-Enterprise Cooperation in the Era of Multimedia Informatization
Authors: Li Pei 
Published: January 2024

Abstract
With the progress of the information age, the evaluation of students in higher vocational colleges and universities is not single, and more and more colleges and universities pay more attention to the overall development of students and use diversified evaluation of students’ abilities. This paper constructs a multivariate evaluation model for English teaching in higher vocational school-enterprise cooperation based on deep learning networks and forest stochastic algorithms. By analyzing the application of convolutional neural networks in teaching quality evaluation, Sigmoid and Tanh functions are used to improve the efficiency of English teaching quality evaluation. The bagging method in integrated learning involves averaging the model prediction results of each subset to arrive at the final evaluation results. The multivariate evaluation model is utilized in English teaching evaluation to examine the impact of English teaching under multivariate evaluation. The results show that the evaluation accuracy of the pluralistic evaluation model for English teaching ideas, teaching objectives, teaching contents and teaching effects are 0.981, 0.893, 0.904, and 0.924, respectively, and the students’ liking degree of English is increased from 0.459 to 0.793 under the pluralistic evaluation, which is conducive to the improvement of the teaching effect of English in higher vocational colleges and universities, and provides a new reference for the teaching of English. Perspective.
Research on the Cultivation Mechanism of Innovation and Entrepreneurship Ability of Excellent Engineers
Authors: Chen Jinfei , Dong Xianwei , Yang Aixi , Hu Songyu 
Published: January 2024

Abstract
In this paper, after using PSO algorithm to encode the information on innovation and entrepreneurship education resources in universities, N particle is randomly generated to form the initial population, and it is also necessary to continuously update the particles to carry out the adjustment of the initial population size. The mathematical model of hard constraints of all courses of innovation and entrepreneurship teaching is obtained through the fitness function, on the basis of which, according to the objective function of innovation and entrepreneurship education resources in universities, each kind of resource is effectively allocated to the most adapted aspects, so as to realize the optimal allocation of innovation and entrepreneurship education resources in universities. Based on the current situation of innovation and entrepreneurship education at the Polytechnic Institute of Zhejiang University, the research hypothesis and research design are proposed, and the utilization efficiency and allocation efficiency of innovation and entrepreneurship education resources are confirmed and analyzed. The results show that before the experiment, there was a large difference in resource allocation efficiency between groups; the minimum value was 0.123, and the maximum value was 0.187. After optimization, the allocation efficiency is 0.188, with an average growth rate of 19.55%. That is, the PSO algorithm can achieve the optimization of innovation and entrepreneurship education resource allocation at the Polytechnic Institute of Zhejiang University. The four dimensions of innovation and entrepreneurship education: theoretical education, practical education, teacher quality, educational support and initiative personality of the three dimensions, motivation, change and resilience are in the presence of each other in the middle of the work, and the correlation coefficient is concentrated in the role of 0.5 on average. This study further stimulates the students passion for innovation and entrepreneurship, which is of great significance to the cultivation of students innovation and entrepreneurship abilities.
The Rationale of Physical Education and Aesthetics in the Context of Big Data and the Value and Significance of its Implementation in Colleges and Universities
Authors: Chen Bing , Liu Shuqiong , Chen Lihe , Zhang Fangping 
Published: January 2024

Abstract
This paper first takes the deep learning theory as the basis of the thesis of sports and aesthetic education, constructs the flipped classroom teaching model of sports and aesthetic education based on the theory, and introduces the Bayesian estimation theory and the structural equation model to apply it to sports and aesthetic education. Secondly, the research object and method are selected for the flipped classroom teaching model of physical education and aesthetic education, and the teaching process of the flipped classroom experiment and the assumptions related to students’ learning satisfaction are given. Finally, the application value of physical education and aesthetics in colleges and universities is analyzed through the convergence of path coefficients in Bayesian structural equation modeling and hypothesis testing. When the number of iterations reaches 100*103 times, the H6-H11 path coefficient convergence value interval is [-22.5, 14.2]. The convergence interval fluctuates a lot and shows a more unstable trend than the H1-H5 path coefficient. Students learning satisfaction will have a direct effect on their aesthetic ability and improve their aesthetic awareness, and the path coefficients are 0.629 and 0.524, respectively. Deep learning theory based on sports and aesthetics in colleges and universities under the background of big data can improve students’ learning satisfaction and then promote the enhancement of students’ aesthetic ability and aesthetic awareness.
The Value and Realization of Choral Conducting Talent Cultivation for Music Teachers in the Context of Deep Learning
Authors: Han Weiwei 
Published: January 2024

Abstract
Focusing on virtual chorus, this paper analyzes the training process of VR technology and music choral conductor talents. After the construction of the online data platform, the image splicing, image alignment and image fusion algorithms of VR technology are integrated with the Harris corner detection improvement algorithm to realize the virtual chorus in the context of deep learning. The influence of family support and school aesthetic education on various dimensions of psychological needs for talent cultivation was modeled using structural equation modeling. Based on the data of music teachers using VR technology, mediated effect analysis and total effect analysis were conducted to analyze the factors influencing the use of imagery with VR technology. ANOVA was utilized to compare the data on the four dimensions of rhythmic memory, pitch, melodic memory, and listening ability to verify the effectiveness of VR technology on music teachers’ talent cultivation. The total effect analysis showed that the order of the influence of each influencing factor on the intention to use was 0.361>social influence 0.263>perceived usefulness 0.263>perceived ease of use 0.251>computer self-efficacy 0.169>convenience conditions 0.162>job relevance 0.134>simulation 0.075.
Application of Sustainable Education in Chinese Language Education in the Context of Big Data
Authors: Nan Yunfan 
Published: January 2024

Abstract
This paper explores all student related data using educational data mining techniques to draw conclusions about their performance and behavior. The main idea and theoretical basis of Random Forest is described, the importance of each feature is calculated using Random Forest based Important Feature Selection Algorithm, and each feature is ranked and the best feature is selected as the effective feature for constructing the performance prediction model. By Light GBM is to further improve the GBDT algorithm and XGBoost algorithm to construct the Light GBM grade prediction model in order to improve the training speed and the prediction ability of the model. In order to verify the feasibility of the constructed model, the application of sustainable education in Chinese language education is tested from various aspects such as model testing as well as learning behavior. The results show that the accuracy of the Ligth GBM grade prediction model increases from 0.68 to 0.918 when the course progress is raised from 10 to 100, i.e., the accuracy of the Ligth GBM grade prediction model in predicting students’ grades gradually increases as the course progresses, so that it can effectively analyze the application of sustainable education in Chinese education.
Innovation of Administrative Management System of Universities Based on Cloud Computing
Authors: Wang Li 
Published: January 2024

Abstract
In the traditional administrative management mode of higher education institutions, different departments work separately, and it is difficult to realize the sharing of information. This paper follows the hierarchical design of J2EE multilayer architecture to build an administrative management platform for colleges and universities. Through cloud computing technology college management information through Hibernate mapping to the object table to achieve data storage and sharing. Simulated annealing algorithms and genetic algorithms are introduced into the system to realize the optimal scheduling of administrative tasks and promote the overall collaborative efficiency of the task process. Finally, the workflow analysis is carried out on the practical cases of administrative management in colleges and universities, and the optimal scheduling of administrative tasks t
1 ~ t
9 in colleges and universities is completed. The results show that the platform 400Vuser under the integrated response time of 2.833 seconds less than the expected 3 seconds, the maximum number of concurrency in the maximum response time constraints can reach 4500 or so, to meet the performance requirements of university administrative management. And task t
1 ~ t
9 completes the optimal scheduling in the experiment, saving a total of 2 resource types. This system is of great practical significance in improving the efficiency of administrative offices in universities, reducing human errors and saving labor costs.
Research on the Impact of Elective Subjects of College Entrance Examination on Talent Cultivation of Higher Vocational Colleges Based on Students’ Cognitive Behavioral Characteristics
Authors: Liu Xiaoyong 
Published: January 2024

Abstract
The reform of the optional subjects of the college entrance examination under the new situation puts forward higher challenges to the talent cultivation of higher vocational colleges. In this paper, for students entering higher vocational colleges and universities after the new college entrance examination, the random forest framework is improved by mining students’ homework and quiz data with PCA dimensionality reduction. Behavioral feature extraction using Random Forest and coding definitions are proposed after feature screening. Based on general feature coding, the behavioral group differentiation extraction of higher education students was constructed, which finally provided label classification of students’ cognitive-behavioral features. After analyzing the impact of the optional subjects on the quality of higher vocational students, the learning behaviors of higher vocational students were dissected. The probability density distribution plots of students’ entry rates show that the overall probability density distribution curves of entry for different students are significantly different. The wave heights of the first, second, third and fourth academic years were 10.25, 16.48, 13.24 and 12.61, respectively, and the study behavior of senior students after the selection of subjects in the college entrance examination showed a unique pattern. In response to the behavioral performance of higher vocational students, institutions need to scientifically use assessment reports to launch talent development work.
Research on the Promotion and Teaching Methods of Uyghur Dance in Colleges and Universities
Authors: Tian Xue 
Published: January 2024

Abstract
Uyghur dance has a long history and needs to rely on education to inherit. However, the Uyghur dance education in local colleges and universities does not follow the development of the times. Aiming at the situation of Uyghur dance education in colleges and universities, a Uyghur dance pose generation network is constructed. By analyzing the main components and tasks of the autoencoder, the process of extracting music and dance movement features is explored. Combine LSTM to retain the information of dance action features and solve the problem of disappearing dance gradients. Extract the dance video as a sequence of skeletal key points and replace each joint point position with a number accordingly to improve the representation of dance action. The Uyghur dance pose generation network is used to analyze the features of Uyghur dance and propose promotion strategies based on the dance features. The results show that the amplitude and power of female Uyghur dance movements are relatively small, and the distance between joints and points is only [10,90] cm, while the amplitude of male Uyghur dance movements is much larger, and the distance between joints of the point rubbing step is [-10,100] cm. in the promotion of the dance, the degree of validity of the promotion of the combination of modern technology and Uyghur dance is 0.8546. The present study has promoted the reform of Uyghur dance education to some extent. The reform of Uyghur dance education is conducive to the preservation of national traditional dance.
The construction of fine management system of library library materials under the background of informationization
Authors: Ma Lingyun 
Published: January 2024

Abstract
The growth in the number of books leads to the increasing inefficiency and cost of traditional library data management methods for book verification and classification. To solve the problems of book classification, this paper proposes an automatic classification model, ERBERT-HMATT, for book data features. Firstly, the pre-training of BERT is improved by adding masking at the word and entity level. Then, the network structure of the model is designed based on HMCN. Finally, a multi-label attention mechanism is introduced in the initial feature extraction module, which gives different weights to the words of the input text to increase the attention to the text features, and the model is subjected to recurrent learning, which enhances the robustness of the model by adding fine-grained knowledge. Finally, the classification performance of the three algorithms, KNN, SVM, and ERBERT-HMATT, is tested on the same dataset. The accuracy of the ERBERT-HMATT classification algorithm is 0.1% higher than that of the KNN according to the results. Classifying 300 book information takes less than 100ms, which is significantly less than the processing time for SVM and KNN. This paper also found that the subject word field in the book information has a large positive effect on the model classification, which can improve the classification accuracy by 0.09 compared with the model with only the title field. The test results indicate that the method enhances the classification of book data to a certain extent.
Research on the Construction of University Cultural Brand IP Driven by Network Cloud Platform Technology
Authors: Gao Shan 
Published: January 2024

Abstract
Campus culture brand IP, as the soft power in the construction of university brand culture, has become an important material carrier for the inheritance and dissemination of university brand culture. In the cloud platform technology, we are using an information diffusion model to explore the diffusion degree and influence of college culture brand IP information on the network platform. The dissemination process of cultural brand IP information is examined from the point of view of sharing information resources in colleges and universities. Construct a competitive information dissemination system based on the user nodes of online social networks and the interrelationship between users. Promote the dissemination and diffusion of university cultural brand IP information on online social networks using a data-driven approach. The results show that: k value is 0.12, the promotion effect of college culture brand IP is 2.59621e+04, and the relative risk index is 0.354264. Within 0-6 hours, the maximum number of IP views reaches 34,000 times, which indicates that the authority of the college platform and the information diffusion model can improve the diffusion of college culture brand IP.
Research on Network Security Situation Assessment Model in Decentralized Computing Environment
Authors: Zhu Ye 
Published: January 2024

Abstract
In this paper, decentralized computing is used as an entry point to review the latest research results on network security issues through two methods, namely task assignment and hierarchical analysis, and construct a network security posture assessment model based on decentralized computing. A control framework is constructed by utilizing the functional complementarity of continuous authentication and security threat assessment in order to facilitate real-time observation of the security situation of the network and timely elimination of malicious nodes. A quantitative network security threat posture assessment model is constructed through hierarchical analysis to observe the extent of the breach of confidentiality and integrity of network information based on the security threat posture index. The effectiveness of the network security posture assessment model and method proposed in this paper was verified by empirical analysis in a simulated environment. The results show that after the simulated attack lasts for 12 minutes, the network security risk index measured by the assessment model in the test cascade case becomes larger with the intensification of the network attack, and the risk index value is up to 5.5. In summary, the network security posture assessment model based on decentralized computing designed in this paper can quickly reflect the changes in the security status of the underlying network and provide administrators with the current security status of the network in a macroscopic way.
Exploration and Practice of College Students’ Career Guidance Program in the Perspective of Green China
Authors: Liu Wenneng 
Published: January 2024

Abstract
The employment of vocational college graduates is a matter of social stability. In this paper, we first introduce modularized teaching in vocational college students’ employment guidance courses to unify the teaching of vocational college students’ career development and employment guidance courses. Secondly, in the preference analysis module, the WOA algorithm is used to optimize the selection of LSSVM parameters, and the WOA-LSSVM model adapted to the regression prediction of vocational college students’ employment preferences is proposed. Then, in the module of employment optimal matching, the Lagrangian conditional function extreme value is found in the discrete job data through the residual optimization algorithm, and the results of the optimal matching of vocational college students’ employment supply and demand are obtained. Finally, the overall situation and group differences in the intensity of employment pressure felt by vocational college students are analyzed. The results show that the maximum value of students’ employment pressure in the modular teaching of employment guidance is 128.28, the mean value is 0.02283, and the Std.Dev is 0.90383. The multivariate kurtosis coefficient decreases from 6.385 to 0.874, which is the critical value (c.r.). Decreases to 1.983<1.95, and the data are normally distributed. This study provides some references to enhance the career planning function of vocational college students’ career guidance courses.
Exploring the Emotional Characteristics of Chinese Language Literature Based on the Thinking Operation Model
Authors: Li Xiaoyan 
Published: January 2024

Abstract
In this paper, each text is mapped as a point in a multidimensional vector space in a thought operation model to represent the emotion feature vocabulary in Chinese language literary works in the form of word embedding. The bootstrapping technique is utilized to collect initial seed set vocabulary and target vocabulary, and a corpus of literary works with six basic emotion categories is established. Based on the emotional features of Chinese language literary works, the memory network model for textual emotion analysis based on multiple attention is constructed, and the textual emotion features of Chinese language literary works are empirically analyzed. The results show that the precision is 82.19%, 93.12%, and 94.1%, and the F1Score is 81.93%, 93.4%, and 93.76%, respectively, and the precision and F1Score are better than the effect of the control group model, i.e., it indicates that the effect of sentiment analysis is more excellent. The ratio values of positive emotion, negative emotion, and neutral emotion are, respectively, 63.16%, 15.49%, and 21.35%, i.e., the expression of emotion in Chinese language literary works is more rational. This study provides new perspectives and theoretical references for the study of traditional literary works and has the potential to expand the study in depth.
Coordinated Development of Civic Education and Student Management in Colleges and Universities Incorporating Principal Component Analysis Approach
Authors: Xu Mei 
Published: January 2024

Abstract
This paper observes the relationship between variables that cannot be explained through the structure of variable explanatory variance-covariance and explores the method of applying the theoretical model of principal component analysis and factor analysis by using the method of hypothesis. After studying the scope of application of the principal component analysis method and factor analysis method, both of which can be used in the general model of comprehensive evaluation of variables, the scientific management approach of planned behavior for student management in the classroom of college and university civic education is proposed. By empirically analyzing the Civics learning management and education evaluation of students and teachers in L colleges and universities, the experimental results show that the cumulative contribution rate of the three principal components, namely, high moral character, perfect personality and good communication, is 87.4% as the main observed variables. In the cluster analysis of the Civics performance, the best Civics performance was found in the category 2 and category 1 students in college L, with a total of 9 students conforming to it. The four principal component factors of the first-ranked teachers did not differ much, respectively 1.6485, 0.4653, 1.7463, −0.645, except for the teacher numbered 1, who had a big difference in the ranking place under the two evaluation methods, and the rest of the teachers did not have any difference, and on the whole, the quality of Civic and Political education in College L was better, and the harmonization with the student management was good.