bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on the precise pointing of college students’ career based on logistic regression classification algorithm
Authors: Xu Lin , Wei Yu 
Published: February 2024

Abstract
This study analyzes the career development direction of college students through logistic regression and gray theory to provide more accurate career planning guidance for college students. Logistic regression classification algorithm and gray theory are used to study career influencing factors and predict future career development trends. The significant influence of academic performance, English proficiency, and civic and political cultivation on career direction is identified by analyzing the sample data of S college students. The model’s accuracy is significantly higher than random guessing, up to 79.8%. The results show that the combination of logistic regression and gray theory can effectively predict the career direction of college students, provide data-supported career guidance services for colleges and universities, and help students make more reasonable career planning.
Study on the Positive Effects of Environmental Rule of Law Advancement on Environmental Governance in the Age of Artificial Intelligence
Authors: Wu Yingjia 
Published: February 2024

Abstract
In the era of artificial intelligence, the importance of environmental rule of law for ecological governance is becoming increasingly important. This study explores how artificial intelligence can contribute to environmental management, especially the prediction and analysis of ambient air quality through the random forest algorithm. The study aims to assess and predict the changes of ambient air quality in Chinese cities and provide a scientific basis for environmental governance. Methodologically, a random forest model was used to analyze the relationship between ambient air quality and multiple factors. The results showed that the random forest model was effective in predicting air quality, in which the level of urban economic development showed a significant correlation with air quality, and the PM2.5 concentration in cities with a high level of economic development was significantly higher than that in the towns with a low to medium level of economic growth, as the PM2.5 concentration decreased from 43.854 μg/m3 to 33.941 μg/m3. In addition, seasonal variations had a significant effect on air quality. It is concluded that the random forest model is an effective tool to provide accurate data support for environmental rule of law and governance, which helps to formulate more accurate ecological protection policies.
Analysis and optimization of industrial engineering and management operating environment based on human factors engineering
Authors: Ji Renzhou 
Published: February 2024

Abstract
In today’s society, which attaches great importance to humanization, human factors engineering has become a hot topic of research in industrial engineering to improve enterprises and factory sites. This paper aims to optimize the efficiency of industrial engineering by adopting industrial engineering (IE) methods, combing the methodological study of the production process and applying job measurement methods to improve engineering efficiency. The study results show that after the improvement of two-handed operation, the left and right-handed operation time is reduced to 25.78 seconds, which is 31.8% lower compared to the pre-improvement period. The overall process was optimized to minimize the bottleneck beat time from 1.379 seconds/piece to 1.333 seconds/piece, and the maximum production capacity increased from 51,308 pieces/day to 52,204 pieces/day. In addition, labor requirements in the industrial workflow were reduced by 20%, from 610 to 486 people. As for the improvement of the operating environment, the noise levels were kept below 73.9 dB(A), especially for the dust collector, which was significantly reduced from 86.4 dB(A) to 72.9 dB(A). This optimization of industrial engineering and its operating environment by applying human factors engineering principles ensures the production quality. It achieves the maximum output with minimum resource input, laying a solid foundation for the continuous optimization of industrial engineering.
Exploring the development of college students’ sports interests in physical education based on cluster analysis
Authors: Zheng Yegang 
Published: February 2024

Abstract
Good sports interest helps college students to actively participate in physical exercise, excellently complete sports tasks, form good sports habits and have a strong body. Given this, this paper establishes an innovative model of college physical education based on the 4R Theory, fully integrates physical education services with classroom teaching, and designs teaching experiments related to physical education services and sports education in colleges and universities. The subjects were Chengdu University of Technology students. The cluster analysis algorithm was used to cluster students’ sports interests, and the parameter estimation of the multiple linear regression model was carried out by the least squares method to deeply analyze the relevant factors affecting students’ sports interests in colleges and universities. The study found that: students’ sports interest clustering is divided into five categories, the number of students in cluster 1 sports awareness reached 542, and students’ sports interest increased by 0.627 percentage points for every 1 percentage point increase in sports skills, and students’ sports participation interest in the experimental class increased by 46.79% compared to that of the control class after the experiment. Adopting diversified physical education teaching methods and contents can effectively enhance college students’ interest in sports, thus providing guarantee for improving students’ physical fitness.
The Aesthetic Imagination of Chinese “Blockbuster” Movies under the Transformation of Digital Technology
Authors: Cui Mengdi 
Published: February 2024

Abstract
This paper explores the aesthetic imagination of Chinese “blockbuster” films in the context of digital technological innovation, focusing on how virtual reality (VR) technology has reshaped the aesthetic experience of cinema and enhanced artistic expression and emotional interaction, thereby revealing the new position and value of Chinese cinema in the global cultural landscape. Using a combination of qualitative and quantitative approaches, this study deeply explores the multidimensional impact of this change through an in-depth analysis of the definition and characteristics of virtual reality technology and its application in cinema, combined with specific case studies of emotional expression in film. The study results show that VR technology significantly improves the immersion (21.01% growth rate) and interactivity (21.67% growth rate) of movies, and effectively enhances the audience’s emotional resonance and aesthetic awareness through the immersive experience. VR technology provides a new way of artistic expression for China’s “blockbuster” movies and brings a new way of creative expression for the Development of the film industry. VR technology not only provides a unique artistic expression for Chinese “blockbuster” movies, but also brings new possibilities for the Development of the movie industry, which helps to promote the critical position of Chinese movies in the global cultural map.
The Establishment of Chinese Culture Teaching Resources by Knowledge Graph Applied to Chinese International Education
Authors: Li Jing 
Published: February 2024

Abstract
With the development of Chinese international education, the construction of Chinese culture teaching resources has become a priority. This study uses knowledge mapping technology to optimize Chinese culture teaching resources in Chinese international education and improve the usability and efficiency of teaching resources. The study adopts a top-down approach to construct a knowledge graph of Chinese culture teaching resources, covering named entity identification, relationship extraction and knowledge meta-extraction. BERT and BiLSTM techniques are used for feature extraction, text encoding, and conditional random field algorithm for knowledge meta-extraction and relationship mining. The experimental results show that the information utilization rate of intelligent retrieval of teaching resources using this knowledge graph is 82.67% and shows good adaptability in applications between different geographical regions. In addition, through comparative experiments, the proposed method in this study performs better than the traditional method in improving the utilization efficiency of teaching resources. This study proves the effectiveness and practicality of knowledge mapping in constructing Chinese culture teaching resources in Chinese international education.
Analysis of law-based administrative law governance in the context of the sharing economy
Authors: Xu Juan 
Published: February 2024

Abstract
Driven by digitalization and Internet development, the sharing economy model challenges traditional government regulation and requires new rule of law concepts and methods. The article uses structural equation modeling (SEM) and multiple linear regression analysis, and we empirically analyze the data of A-share listed companies between 2012 and 2022. It is found that the development of the sharing economy has a significant positive impact on government regulation and public services. In particular, for every 1% increase in the level of sharing economy development, the government’s regulatory capacity increases by 0.854%, while the public service capacity increases by 0.636%. This indicates that the sharing economy enhances the government’s regulatory capacity and promotes the innovation and expansion of public services. In addition, the regional Analysis shows that the sharing economy has a more significant impact on administrative law governance in the eastern and northeastern regions. In contrast, the effect in the western region is not important. In summary, this study proves the sharing economy’s importance in enhancing administrative law governance and provides empirical evidence for policy makers.
Construction of a Knowledge Graph Based on the Study of English Translation of Traditional Chinese Medicine Terminology
Authors: Zhao Lingzhen 
Published: February 2024

Abstract
This study centers on the English translation of Chinese medicine terms and the construction of knowledge graph, to solve the problem of the accuracy of Chinese medicine terminology translation through scientific and technological means, and to improve the communication efficiency and accuracy of Chinese medicine in the international arena. First, we collected Chinese medicine-related data from websites such as “Seek Medical Help” and “Seek Medical Help” through crawler technology, then performed data cleaning and fusion processing to eliminate data redundancy and inconsistency. Then, we defined 17 types of concepts and 22 conceptual relationships related to TCM ancient books, as well as the corresponding attribute definitions, to ensure the accuracy and completeness of the knowledge graph. The Bi-LSTM model for text disambiguation and Labeling further improved data processing efficiency. Eventually, this study successfully constructed a knowledge graph of English translation of TCM terms containing 50051 nodes and 13521 relations. This knowledge graph improves the accuracy of TCM terminology translation and provides a powerful tool for international dissemination and academic research of TCM terminology.
Research on Indoor Digital Design and Experience Based on Perception and Behavioral Association
Authors: Ye Ping , Kweon Jihoon , Bai Di 
Published: February 2024

Abstract
This study examines interior digital design and experience based on perceptual-behavioral associations, focusing on how users’ perceptual cognition affects the internal design experience. This study collects data on users’ physiological and psychological responses when observing interior design by combining eye movement and electroencephalography techniques. Morphological analysis was used to deconstruct and reorganize the interior design elements, while the Mixed Integer Quadratic Programming (MIQP) method was used to design the interior space layout. The experimental results show that subjects’ average perceptual imagery ratings of interior schemes in the internal design perception and behavioral experiments differed significantly, and the EEG data and eye movement data exhibited specific behavioral characteristics. For example, there were statistically significant differences in perceptual imagery ratings and physiological data across interior design schemes within a particular time window. Combining eye-movement and EEG data can capture users’ perceptual perceptions and behavioral responses.
Artistic Characteristics and Innovative Application of Ink Animation in Animation Scenes in the Age of Artificial Intelligence
Authors: Hu Qiaohong 
Published: February 2024

Abstract
This paper discusses the artistic characteristics and innovative applications of ink animation in the era of artificial intelligence, mainly including the preprocessing of ink works, the Extraction of stylistic feature analysis, the internal haloing technique, and the simulation technique of ink painting features. The research methods include image segmentation, object contour and internal separation, and the application of ink stylization techniques. The results show that the improved CIE1976L*a*b* color space transformation and the “kernel-free” region growing method have successfully realized the efficient processing and stylistic feature extraction of ink works. The experiments use the gray scale co-production matrix for texture characterization, and the results show that the extracted stylistic features have a high degree of consistency with the traditional artistic features of ink animation. In addition, the practical expression of terrain ink style is realized by 3D ink rendering technology, which demonstrates the innovative application of ink animation in modern technology.
Adaptation and Creation of Psycho-Opera Scripts Based on Emotional Calculation - An Example from Verdi’s Opera Macbeth
Authors: Zhu Kai , Yang Dongdong 
Published: February 2024

Abstract
This study effectively associates the evaluation object tree with attribute nodes by constructing an innovative tree-structured emotion dictionary. Utilizing the TF-IDF algorithm, this paper meticulously classifies the emotional features in opera librettos and adds a list of inspirational word nodes. Further, a basic framework of weighted decision matrix is designed, and the data in the emotion score matrix is normalized by Softmax method, to derive the weight allocation coefficients, according to which the results of weight coefficient allocation of the opera libretto are calculated. In particular, for the adaptation of the famous opera Macbeth, this paper proposes three significant principles to ensure that the emotional Expression of the libretto matches the creative intent. The adapted libretto was subjected to emotion calculation and effect analysis, and the empirical study showed that in the first six minutes of the adaptation, there were two periods characterized by extremely significant emotional tension, in which the emotional tension exceeded 7.5 points in both cases. In the specific dynamic analysis, about 60% of the probability emotional value of clip 2 is located in the first quadrant, which coincides with the expected creative goal. In the correlation analysis of the script adaptation, the correlation between emotional attachment and the audience’s willingness to watch the play is as high as 0.8963, indicating that the adaptation is effective. This study not only innovates the method of emotion analysis of opera libretto in theory, but also provides practical guidance for opera libretto adaptation in practice, which helps to enhance the artistic infectivity of opera works and the audience’s viewing experience.
Theoretical Informational Inheritance of Xi Jinping’s Thought on Socialism with Chinese Characteristics in the New Era
Authors: Wang Jiyu 
Published: February 2024

Abstract
This article aims to study the theoretical informatization heritage of Xi Jinping’s socialist thought with Chinese characteristics in the new era. The article first uses web crawler technology to obtain data, followed by a multimodal fusion model based on the self-attention mechanism to analyze the data. The study results show that the Kinetics400 dataset processed by this method achieves 94.2% in top-1 video classification accuracy. In socialist core values textual content classification, the model has strong predictive ability, with most of the categories being on the diagonal, indicating high accuracy. The conclusion points out that the method proposed in this paper effectively promotes the digital dissemination of Xi Jinping’s socialist thought with Chinese characteristics in the new era, and provides new perspectives and technical support for the theory informatization inheritance.
Characterization of Red Civic Education in Colleges and Universities under Big Data Platform and Optimization of Teaching Methods
Authors: Pan Rong 
Published: February 2024

Abstract
In the era of big data, the implementation of red ideological and political education has a positive and practical guide to the daily behavior habits of college students, and plays a positive guiding role. The lack of red ideological and political education is one of the main reasons for the abnormal behavior of college students. In this paper, the daily behavioral habits of college students are modeled, and according to the different distribution characteristics of individuals on campus activities, abnormal class determination and cluster analysis are carried out. The abnormality detection operator is used to detect the strange behavior of college students. In the study of abnormal behaviors of college students, the proportion of medium and low intensity of deviant behavior college students in sports behavior is as high as 73%, the proportion of high intensity in dietary behavior is 53%, and the proportion of high intensity in consumption behavior is also more than 50%. The psychological attention characteristic value of abnormal behavior college students is lower than that of average behavior college students, and the fluctuation is slightly more significant than that of intermediate behavior college students. Except for the forgiveness and modesty factors, the other 13 positive psychological quality factors of abnormal behavior college students are lower than those of average behavior college students, and the evaluation of the quality of political thinking is more inadequate than 80 points, which is in the range of poor and general assessment. Given the abnormal behavior of college students, the optimization direction of red Civics teaching method is proposed.
Research on the Creative Performance of Digital Film and Television Works Based on Virtual Reality Technology
Authors: Zhang Jicheng , Feng Yi 
Published: February 2024

Abstract
This study investigates the application of virtual reality technology in the creative expression of digital film and television productions, especially the role of EEG signal denoising and feature recognition methods in enhancing the audience experience. The study uses wavelet threshold denoising and parallel RLS adaptive filtering algorithms to process EEG signals to improve the accuracy and reliability of the data. Then, the EEG signals were feature extracted using a bihemispheric domain adversarial neural network (BiDANN) to more accurately recognize the user’s emotional responses. The experimental results show that in the virtual reality environment, the users’ concentration and emotional reactions are significantly improved, with the average concentration reaching 74.21 and the average value of the electrodermal test data being 6.19. In addition, the eye-movement interaction experiments show that different types of digital movie and television works can cause additional attention allocation of users in the VR environment, leading other creative performance effects. The study’s results prove that virtual reality technology can significantly enhance the innovative performance of digital movie and television works and improve the audience’s viewing experience.
Reform and Innovation of Chinese Language and Literature Teaching in the Perspective of Chinese Traditional Culture in the Internet Era
Authors: Zhang Mina 
Published: February 2024

Abstract
In the Internet era, the combination of traditional Chinese culture and the teaching of Chinese language and literature has become an important topic of education reform, and exploring its innovative mode is of great significance for the inheritance of culture and the enhancement of teaching effect. The study adopts the independent cooperation mode, builds a new cultural position based on the Internet, and adds classroom practice links to enhance the teaching effect. The teaching activities are designed based on the framework of self-study before class, interaction during class, and summarization after class. In addition, this study uses fuzzy C-mean clustering and multiple regression analysis to mathematically model educational data and deeply analyze the influencing factors of teaching quality. Teaching experiments showed that the reformed teaching model significantly improved students’ performance, and the average grade of students increased by 9.6130 points compared with the traditional teaching model. In addition, multiple regression analysis revealed that course completion, learning engagement and teaching interaction significantly affected students’ performance. The results of this study are of practical significance for promoting the innovative development of teaching Chinese language and literature.
Research on Face Attribute Recognition Technology Based on Fine-Grained Features
Authors: Gao Yizhuo 
Published: February 2024

Abstract
This study explores fine-grained feature-based face attribute recognition techniques to enhance the accuracy of face recognition in low-resolution and complex environments. The article proposes a global feature extraction method and a local texture feature extraction method to extract global and regional features by enhancing feature reuse and information flow through dense connectivity and ShuffleNet V2 framework. Then, a multiscale feature exchange method is used to fuse different scale features to enhance the capture of detail information. Finally, efficient feature integration is achieved by the multiscale feature fusion method. Experimental results on the CK+ and FER2013 datasets show that the accuracy of this method on face expression recognition reaches 97.24% and 95.93%, respectively, and the average recognition accuracy in the face attribute recognition experiments on the CelebA dataset is 97.11%, which is significantly better than the comparison algorithm. In addition, the analysis of the recognition effect on low-resolution faces shows that this paper’s method achieves a recognition accuracy of 54.03% at a resolution of 15 × 15 and a high accuracy of over 99% at resolutions of 70 × 70 and above. These results show that the face attribute recognition technique based on fine-grained features proposed in this paper significantly improves recognition accuracy.