bluuebunny/crossref_metadata_2025_split huggingface dataset:
Interrelationship of Visual Elements of Digital Media Artworks Based on Spectral Graph Theory
Authors: Zhang Jian , Tan Yang 
Published: November 2023

Abstract
This paper first explores the composition of visual elements in modern digital media artworks, extracts the graphical element features of visual elements by improved SIFT algorithm, and classifies and recognizes the graphical elements using by SVM algorithm. Secondly, the extracted and categorized graphical elements are represented by Laplace feature vector correlation spectra in combination with spectral graph theory to study the mutual relationships between the graphical elements. Finally, some graphic elements in modern digital media artworks are used as examples to explore the performance and interrelationship of graphic feature extraction, recognition, and classification. The results show that the vector eigenvalues of spectral graph theory are categorized into [0], (0,100], (100,200], [200, ∞), and the corresponding interrelationships are one-to-one, one-to-many, many-to-one, many-to-many, respectively.
Adaptive models of digital government governance in smart shared services
Authors: Yan Jin , Yang Jing , Yin Chenghao , Hu Weiqiang 
Published: November 2023

Abstract
Based on the basic platform supporting the overall e-government framework, this paper builds an application system for the intelligent management of government departmental business and three major databases of basic, departmental and thematic categories. Secondly, under the collaborative information governance model of blockchain, the data are jointly managed by all the regional governments in the distributed network, plus the application of smart contracts makes each governance link respond intelligently. Finally, an empirical study is conducted on employees of three types of government departments to analyze the regularity of the influencing factors of smart shared services in digital government. The results show that the regression coefficient of the strategic policy of government agencies on the degree of realization of information sharing is 0.829. The regression coefficient of the platform organization of government agencies on the degree of realization is 0.705. To promote the construction of digital government in China, this paper utilizes blockchain technology in digital government governance.
Semantic pattern recognition of special English words based on data corpus technology
Authors: He Qingxia 
Published: November 2023

Abstract
This paper first researches special English vocabulary teaching defines special English vocabulary definitions and characteristics based on special English usage, and proposes strategies for learning special English vocabulary. The study involves studying the semantic recognition of special English using data corpus technology. Based on data corpus technology, the semantic structure of English vocabulary is analyzed according to Chinese analysis and word vectors, and to facilitate the extraction of English semantic features, IOB2 labeled training corpus is needed. Then, the CRFs network algorithm in the data corpus technology is used to construct the special English semantic recognition model, the lexical annotation set is refined on the preprocessing, and at the same time, the semantic features are added to the recognition model of CRFs mainly used to recognize the noun phrases of gerund class and the experimental analysis is carried out on the recognition of the semantic patterns of the special English vocabulary. The results show that among high school students with high English semantic recognition ability, the correlation coefficient between their aggregates and reading level is 0.753, the correlation coefficient between collocated phrases and reading level is 0.772, and there is a high correlation between the ability to recognize aggregates, collocated phrases, and sentence framing phrases and reading level. This study is designed to improve the efficiency of English reading and communication and has a facilitatory effect on recognizing English lexical semantic patterns.
Artificial intelligence technology drives brand image design and promotion strategies of cultural and creative products
Authors: Ding Bin 
Published: November 2023

Abstract
In this paper, relevant cultural materials were first collected and extracted using knowledge mapping and retrieval tools, and the co-occurrence analysis method was used to construct the co-occurrence relationship matrix between keywords. Combined with the method of graphic vectorization, the traditional cultural and creative product design patterns and motifs are directly scanned to extract the design prototype’s outer contour and polygonal path. Next, the recommendation process of cultural and creative products was realized by combining collaborative filtering and the TransD-CF algorithm. Finally, the influence of cognitive attitude and purchase behavior indicators on cultural and creative products was analyzed through correlation. The results show that the difference between genders using essay on hobby collection of cultural and creative products is 0.203, and the practicality requirement of cultural and creative products decreases by 0.09 for every 100 yuan increase in price. This paper presents a fresh perspective on cultural and creative promotion and plays a guiding role in design practice with the aid of artificial intelligence.
Comparative Analysis of Business English and Everyday English Translation Stylistic Features Based on Keras Neural Networks
Authors: Xing Jiawei , Rong Xiuli , Chen Guomin 
Published: November 2023

Abstract
Based on the formal definition of semantic language and specific natural language, the research adopts the Word2vec model to map words into a low-dimensional dense space and performs semantic modeling by unsupervised learning through a large amount of unlabeled data to realize the vectorized representation of translated text. For the vectorized text, the text features are combined and filtered based on the TextCNN network, and the TextCNN network is implemented under the Keras framework. Based on the TextCNN network of Keras, the stylistic features of Business English and Daily English are compared at three levels: lexical, syntactic and discourse. Business English was rated 23.6 points higher in terms of conciseness of diction compared to everyday English, and 28.7 points improved the modesty of diction compared to everyday English. This study furthers the improvement of various English translation types.
Symbolic Graphic Emotion Design in Gift Packaging Based on Multimodal Emotion Fusion
Authors: Yang Chun 
Published: November 2023

Abstract
This paper firstly discusses the value significance of emotional packaging design, outlines its design principles and methods, and explains the thinking structure of emotional design. Secondly, the feature detection of symbolic graphics is realized using a mixture of regression and segmentation, and a multilevel cross-modal perceptual emotion recognition model is constructed based on the collaborative attention mechanism of the cross-modal Transformer and recurrent neural network. Finally, a dataset test and empirical analysis were conducted to verify the model’s effectiveness in this paper. The results show that the multimodal fusion model has better recognition performance than the unimodal and bimodal models, with F1 values of 0.914, 0.923, and 0.902 for neutral, positive, and negative emotions, respectively. Symbolic graphics in the emotional design of gift packages are mainly expressed in the form of intuition, vividness, and validity to emphasize the diversity of symbolic graphics in the emotional design of gift packages. This shows that multimodal emotional fusion can be realized to analyze the emotional design of symbolic graphics of gift packaging and promote the emotional innovation design of symbolic graphics of gift packaging.
Systematic integration of information big data and physics teaching based on deep learning algorithms
Authors: Tao Guanqi , Wang Yinshu , Fan Yina 
Published: November 2023

Abstract
This paper first investigates the main performance of the shackles of traditional physics teaching on students and its negative consequences and then designs a physics teaching process model based on the teaching environment of information big data and constructs a framework of the physics teaching system by utilizing data mining technology. Then, the physics teaching system is modeled based on the artificial neuron model and recurrent neural network, and the attention mechanism is used to improve the overall generalization performance of the model. Finally, the application effect of the physics teaching system is compared through empirical evidence. The results show that there is a deviation in the mean value of the two classes; the average score of the experimental class is 75.552 points, and the average score of the control class is 65.910 points, and there is a difference of 9.642 points between the two classes’ mean values. The data show that applying a physics teaching system can improve the learning status quo of students’ mechanical imitation, help students better master knowledge, enhance students’ ability to use information technology and achieve better teaching results than traditional teaching.
Research on the Path of Cultivating Socialist Core Values through Campus Sports Data Visualization in the Context of Healthy China
Authors: Xu Xiaoling 
Published: November 2023

Abstract
This paper firstly researches the role of sports in the cultivation of socialist core values in the context of healthy China, which is mainly embodied in the establishment of the correct goal to strive for in life and the establishment of a sense of fair and just social responsibility, and puts forward the path of socialist core values cultivation. Secondly, the socialist core values are studied by visualizing campus sports data. According to the LSTM neural network with good visualization and computational recognition ability, a campus sports data visualization model based on LSTM is constructed, and sensors are used to obtain the feature extraction of students’ sports. Based on the feature values, the feature state’s output value is computed using the LSTM neural network. Considering the extraction and feature loss problem in the calculation process, it is necessary to select a suitable loss function to optimize it and the example analysis of socialist core values based on LSTM data visualization. The results show that the higher the level of soccer skills, the higher the level of “self-confidence”, “strength”, “respect”, “responsibility”, “law-abiding” and “patriotism” indicators, the higher the level of “self-confidence” (t=3.736, p=0.005) indicators. The difference is significant. This study has contributed to socialist core values in the context of sports.
Strategies and Path Analysis of Choral Conducting Teaching in Colleges and Universities in the Context of Multimedia Era
Authors: Pu Ziyan 
Published: November 2023

Abstract
This paper first presents the O2O teaching strategy for choral conducting and analyzes specific methods and processes for teaching choral conducting using the O2O model. Then, the TFAHP choral conducting teaching evaluation model was constructed, and the judgment matrix was used to calculate the comprehensive degree of fuzzy value of the evaluation criteria and to compare the importance value between the indicators. Lastly, the impact of teaching was evaluated using indicators such as grades, comprehensive performance, and learning emotions. The mean value of the achievement of all knowledge modules is much higher than the mean value before teaching, and the average value of the achievement of each knowledge module is between 0.6-0.85, and the P value of each knowledge module is lower than 0.01, which is an extremely significant difference, indicating that the teaching effect is significant. The innovative development of music education is promoted, and this study greatly impacts choral conducting education.
Influence of Professional Mindset on Job Performance of College Teachers Based on the Background of Educational Psychology
Authors: Chen Jiebin , Jiang Yongzhi 
Published: November 2023

Abstract
This paper constructs a PLS structural equation model based on structural equation modeling and PLS computational methods. The focus is on the expression of the measurement model and the application steps while analyzing the general measurement model of structural equations. The PLS method is applied to solve the structural equation model to achieve the best summary of information in the system of independent variables. Combining the structural equation modeling of two simple variables, the structural equation modeling based on PLS was designed to analyze the path of influence of professional mindset on job performance. The results show that a positive teaching mindset can somewhat improve job performance. The z-value of the total effect of professional mindset on innovative performance was 7.798, and the upper and lower limits of the Boolstrap’s bias-corrected 95% confidence interval and percentile 95% confidence interval ranged from (0.751,1.229) and (0.745,1.237), respectively.
Data Mining Technology Oriented Integration Strategies for Habitat Improvement and Rural Tourism Development in China’s Agricultural and Rural Villages
Authors: Jian Zhengqing , Ren Zhengshi 
Published: November 2023

Abstract
This paper firstly calculates the weights of each system and indicator in the index system through the gray correlation method and comprehensively evaluates the status of the regional rural tourism development and the level of human habitat environment as well as the characteristics of temporal and spatial evolution. Constructing the spatio-temporal coupling and coordination relationship between rural tourism and the human habitat environment reveals the obstacle factors of rural tourism development and human habitat environment development level and the coupling mechanism of the two. Finally, the development process of the rural tourism industry in Kaili, Xingyi, and Zunyi, as well as the improvement and optimization process of the rural habitat environment, are empirically studied. The results show that the coupling coordination degree between the rural tourism development level and the optimization level of human habitat environment in the three regions increased from 0.06 in 2012 to about 0.48 in 2021, indicating that the overall coordination level between the rural tourism development and the optimization of the human habitat environment is continuously improving during the period. This paper is significant for the new path of economic development and habitat-environment coordination in rural areas.
The effect of emotional labour on professional well-being among early childhood teachers based on structural equation modelling
Authors: Ren Ting , Li Xianyin 
Published: November 2023

Abstract
This paper strategically classifies the emotional labor of early childhood teachers and explores the relationship between emotional labor, emotional exhaustion, occupational well-being, and occupational self-efficacy based on a five-dimensional model of teachers’ occupational well-being. A structural equation model was developed to explore the mediating effects of early childhood teachers’ psychological capital between surface behavior, passive depth behavior, and occupational well-being, using psychological capital as a mediating variable. Based on the mediation analysis of the structural equation model, parameter identification and parameter design were performed to conduct descriptive statistics, correlation and regression analyses of emotional labor and occupational well-being of kindergarten teachers occupational well-being, and to test the moderating effect of social support in the multimedia context. Deep play significantly and positively predicted the dimensions of emotional well-being, professional well-being, interpersonal harmony, environmental satisfaction, and total occupational well-being scores, i.e., β= 0.35, 0.42, 0.40, 0.21, 0.36, P<0.01.
Linkage between strategic human resource management and organisational effectiveness in enterprises combining multivariate statistical analysis methods
Authors: Zhou Lina 
Published: November 2023

Abstract
This paper first proposes strategic human resource management based on the competing value architecture, discusses the dimensions and measurement system of strategic human resource management, and carries out the K-mean clustering analysis on the contents of strategic human resource management. Secondly, constructs a relationship model of strategic human resource management that affects organizational effectiveness. Finally, organizational effectiveness was examined using various multivariate statistical analysis methods, such as stepwise regression. The results show that the path coefficients of strategic human resource management on organizational effectiveness are 0.43, 0.33, 0.51 and 0.60, respectively, and the standardized values of these path coefficients range from 0.33 to 0.60, which further confirms the positive impact of strategic human resource management on organizational effectiveness. The paper’s research provides a guide for promoting the healthy development of enterprises and enhancing the overall level of human resource management.
Evaluation Indicator System and Theoretical Model of Ice-Snow Tourism Destination Suitability Applying Time Series Data--Taking Jilin Province as an Example
Authors: He Rui , Liu Hongyan 
Published: November 2023

Abstract
This paper uses time series data to evaluate the suitability of ice-snow tourism destinations in Jilin Province. Firstly, based on the relevant data of snow and ice tourism development in Jilin Province, 5 dimensions, 15 indicators and 20 factors were selected to construct the model, and AHP and entropy method determined the combined weight value of each factor. Then, the evaluation model of the ice-snow tourism destination in Jilin Province was studied by using single-factor niche suitability and comprehensive niche suitability. Finally, the single-factor niche suitability and comprehensive niche suitability of ice-snow tourism destinations in Jilin Province were analyzed, respectively. Changchun has 6 ski resorts, receiving 41% of the total number of tourists in the province. Changchun’s GDP accounts for 50.3% of the province, and the road density reaches 1.182 kilometers/square kilometers. The proportion of grade 1-4 area in Jilin Province is 24.25%, 29.36%, 28.63% and 17.76%, respectively.
Transformation of Numerical Efficacy of Civic Building in College Physical Education Courses Combined with Matrix Modeling
Authors: Ju Linlin 
Published: November 2023

Abstract
This paper firstly analyzes the developmental problems of the construction of the sports course ideology and politics in colleges and universities, starting from the value function of the construction of the sports course ideology and politics. Secondly, it constructs the evaluation index system for the construction of college sports course ideology and politics, utilizes the subordinate criterion function of the subordinate matrix model for the weight calculation of the index subordinate coefficients, and calculates the positive and negative ideal solutions and relative posting progress of each index through the TOPSIS method. Finally, in order to analyze the transformation of the number-based effectiveness of the construction of the college sports course ideology and politics, an example verification analysis was carried out. The results show that the transformation of digital effectiveness in the construction of the ideology and politics of sports courses in colleges and universities is mainly carried out through the shaping of students’ values, the cultivation of ideals and beliefs, and the analysis of the weights of the indexes points out the direction of the development of the construction of ideology and politics of sports courses. This shows that the transformation of the digital effectiveness of the ideological and political construction of physical education courses needs to start from the spirit of sports, which in turn promotes the ideological and political construction of physical education courses to boost the quality of physical education disciplines.
Realization and Application of Knowledge Sharing Recommendation System for Power Grid Enterprises
Authors: Lin Zhengping , Zhou Yuzhong , Yang Yuliang , Shi Jiahao 
Published: November 2023

Abstract
Facing the complex knowledge of power grid enterprises, this paper builds and designs a system for sharing project knowledge. The design pattern of MVC is adopted as the business logic architecture of the system, and a large-scale distributed application based on JavaEE architecture is used. In the knowledge recommendation method, a recommendation algorithm based on knowledge context is proposed, and the similarity between different entities is calculated by matching the knowledge ontology, thus realizing the recommendation of enterprise knowledge based on entity similarity. Meanwhile, the recommendation effect is analyzed by stress testing the recommendation service interface as a performance test characterization of the system and combined with the hit rate. The hit rate of recommendation based on knowledge context is 0.124 higher than that of BPRMF, 0.104 higher than that of NeuMF, and 0.083 higher than that of CKE. This system is able to effectively improve the knowledge-sharing efficiency of power grid enterprises.
Utilizing Knowledge Graph to Build a Scientific and Technological Knowledge Management System for Grid Industry
Authors: Zhou Yuzhong , Lin Zhengping , Wang Qinghong , Shi Jiahao , Yang Yuliang 
Published: November 2023

Abstract
Based on knowledge mapping, this paper designs the application architecture of the scientific and technological knowledge management system for the power grid industry and proposes the design of key modules such as knowledge extraction, knowledge fusion and cross-checking. In terms of knowledge fusion, this paper proposes the functional design of conflict detection, entity alignment based on deep learning, data fusion based on linking and cross-validation based on confidence assessment. In terms of cross-truth, this paper investigates the credibility calculation of candidate message sets, the representation of candidate message sets, and the construction of logic rules for cross-truth models. Finally, this paper evaluates the system’s term extraction, concept recognition, and performance. The results show that the average elapsed time for each function of graph visualization, keyword search, keyword search, advanced search, and advanced search in the knowledge management system to be executed 20 times is 1.33s, 1.27s, 3.14s, 1.47s, and 3.26s, respectively, and the average response time is only 2.1s. Therefore, the knowledge management system for grid industry science and technology presented in this paper is effective.