bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysis of the timeliness of multiple information on college students’ patriotism education in the all-media era
Authors: Meng Ying 
Published: January 2024

Abstract
This paper explores the process of patriotism knowledge mapping from three aspects: graph entropy definition, entropy2vec and topic knowledge, and constructs the overall framework of patriotism knowledge mapping. The multivariate information technology in the era of all media is used to summarize the educational knowledge of the patriotism theme, construct the entity-relationship extraction model based on the Bi-LSTM network, and propose the SFAJED fusion algorithm to carry out the knowledge fusion of the patriotism education theme. After exploring the relationship extraction effect, knowledge fusion effect, and overall effect of the constructed knowledge graph, the timeliness of patriotism education for college students is analyzed. The results show that the network density of the constructed patriotism knowledge map is concentrated at about 0.004, the aggregation coefficient is concentrated at about 0.45, and the average road strength length of the graph is about 20. It is divided into three stages in accordance with the time axis: 2015~2017 is the patriotism education with class as the main axis, 2017~2018 is the patriotism education with the country as the basis, and 2018~2020 is the patriotism education with the culture as the virtue, and at this time, the strength is respectively between 2.3~3.5, between 2.12~3.08 and between 1.08~2.88.
Digital transformation of college teacher education from the perspective of behaviorist psychology: initiatives, effectiveness and pitfalls
Authors: Liu Yanling , Shi Yujuan 
Published: January 2024

Abstract
Behaviorist psychology can deeply reflect the perception of digital technology in teacher education in colleges and universities, and the digital transformation of teacher education is an effective path to improve the quality of education. Based on the TAM model, this paper analyzes the factors affecting the digital transformation of teacher education in colleges and universities, selects the relevant variables for research hypotheses, and obtains the relevant data for empirical analysis through questionnaires. In order to deeply analyze the initiatives, effectiveness and hidden worries brought about by the digital transformation of college teacher education from the perspective of behaviorist psychology, the combination of factor analysis and principal component analysis is used to carry out the extraction of common factors, which provides the basis for analyzing the factor loading coefficients of the influencing factors of digital transformation. The validity of the method was assessed using various methods, including descriptive statistics, reliability and validity tests, and structural equation modeling path fitting. The results show that the absolute values of skewness and kurtosis of the survey data in this paper are less than 1, which is in line with normal distribution, and the value of Cronbach’s Alpha coefficient of the reliability test is basically above 0.9, and the standardized factor loading coefficients are greater than 0.6. The direct effect of behavioral imagery on the actual application is 0.448, resulting in a significant difference at the 1% level. The digital transformation of teacher education in higher education needs to pay attention to the relevant applications of external environment and media technology so as to realize the improvement of the quality of teacher education in higher education.
Characteristics and Development Achievements of Modern Painting Art Based on the Perspective of Fine Arts in the Context of Digitization
Authors: Feng Dakang , Feng Momo 
Published: January 2024

Abstract
Modernism has brought a new fine art vision to the art of painting, making it show aesthetic characteristics that distinguish it from classical painting. In this paper, based on the method of information theory, the indexes of order, complexity, and saliency of images are proposed to characterize the digital features of different aspects of the visual art of painting. The FisherScore selection mechanism is used to evaluate and screen the excellent features extracted. The final features are input into the Key Area Description Network (KADN) to complete the digital construction of the features of painting art through the KADN algorithm, and finally, based on the Wikiart dataset, we carry out the experiments of feature extraction and analysis of the images of fine art paintings, and summarize the achievements of the development of the art of painting through the results of the experiments. The results show that the improvement of KADN’s classification performance for the style subset is reflected in the whole. For example, the class Ukiyo-e only has a Top-1 classification error rate of about 12.2% under the key region description network, while the Top-1 classification error rate of the Realism class reaches more than 61.5%. Modern painting art can be analyzed effectively using the feature extraction method, which is a powerful tool for exploring the evolution of painting features.
Research on Aging Adaptation of Urban Residential Environment Design in the Era of Artificial Intelligence
Authors: Xu Yue 
Published: January 2024

Abstract
Under the background of aging, how to make the elderly live comfortably and improve the quality of life have all become the main problems solved by the current society. Based on the relevant theoretical foundation, this paper constructs a aging adaptation design model of the urban residential environment. Principal component analysis and factor analysis are employed to simplify the data structure of living environment design and decrease the complexity of data analysis. Regression analysis and structural equations are combined to investigate the relationship between the living environment and age appropriateness. PLS regression analysis was used to solve the external weights or factor loadings to obtain the estimates of the latent variables and the path coefficients among the latent variables. To demonstrate the reasonableness of the factors influencing the quality of the environment, the reliability and validity of the perceived quality are analyzed. Combining the basic attributes and needs of the elderly is the basis of proposing an aging-friendly environment design strategy. The results show that In terms of architectural spatial perception, the master bedroom space scale exceeds 3.92m × 4.61m, which is a relatively optimal choice that can simultaneously meet the diversified needs of the family’s living behavior at different stages. In terms of road accessibility and greening perception, the width of the age-appropriate walkway can vary depending on different locations and the unit time flow of people. In the era of artificial intelligence, the design of the aging-adapted living environment should fully consider the physiological characteristics of the elderly and formulate more suitable living data for the elderly.
Exploring the research on the follow-up industrial development of relocation for poverty alleviation based on the background of big data
Authors: Wei Jian 
Published: January 2024

Abstract
Relocation for poverty alleviation is an important part of the implementation of the “five batches” project for poverty alleviation and has now entered the stage of consolidating the relocation results and promoting industrial development and economic growth. Based on this, this paper firstly explains the techniques related to the subsequent industrial development of relocation for poverty alleviation, including the double difference model, partial least squares regression algorithm and forward score matching algorithm, which provides the basis for the relevant analysis in the following paper. Secondly, the poverty reduction mechanism of industrial development in relocation for poverty alleviation is discussed, and the formation mechanism of poverty in relocation for poverty alleviation is explored. Finally, the impact of livelihood capital of relocated farmers was analyzed by using the double difference model, the partial least squares regression model analyzed the impact of industrial development, and the ATT effect of industrial development was analyzed by the PSM method. The results show that industrial development has a significant effect on reducing the multidimensional poverty index, multidimensional poverty order, income, education, health, and life-related poverty of relocated farmers, and their R2 test results are all above 0.6. The livelihood capital of relocated farmers is more affected by concentrated industrial development than decentralized development, and all of them have significant differences at the 5% level. The ATT effect based on PSM reflects that industrial development will increase the per capita total consumption level of relocated farmers, which can improve the living standard of relocated farmers to a certain extent. The subsequent industrial development of relocation for poverty alleviation should further optimize its industrial structure to provide an industrial foundation for the implementation of rural revitalization strategies.
Dynamic Coupling and Coordinated Evolution of Rural Tourism Development and Cultural Industry in the Information Age
Authors: Qin Puhong 
Published: January 2024

Abstract
This paper selects rural tourism development indicators and cultural industry development indicators, respectively, and constructs the evaluation system of comprehensive development level of rural tourism development and cultural industry. The dynamic coupling evolution algorithm is proposed, algorithm improvement is carried out, and the improved coupling model is used to substitute rural tourism development and cultural industry development to analyze the dynamic coordination evolution of the two. Use hierarchical analysis to calculate the weights of the indicator system. Combined with the comprehensive development level of rural tourism and the comprehensive development level of the cultural industry, the coupling and coordination level of the two are measured, and suggestions for the integrated development of rural culture and tourism are put forward. By 2020, the coupling coordination degree of the cultural industry and rural tourism industry in L city will develop to 0.734, and both the cultural industry and rural tourism industry will reach the intermediate level of coordination, but the development of the tourism industry is relatively lagging, and the comprehensive development level of the cultural industry will be 0.695, and the comprehensive development level of tourism industry will be 0.562.
Construction of Online Interactive Teaching Platform for College English Based on Multilayer Perceptual Machine Modeling
Authors: Cao Yuanyuan , Du Hongmei , Zheng Pinsu 
Published: January 2024

Abstract
Most of the existing English online teaching platforms are just digital replicas of offline teaching, which cannot fully utilize the advantages of information technology. Based on the learning theory of constructivism, this paper builds the functional architecture of a personalized English interactive teaching platform and completes the design of the main functional modules. According to the quantitative results of the platform’s user proposition requirements, a matrix description method for English test papers is proposed, and an algorithm is designed to realize the automatic generation of test papers. Meanwhile, the resource recommendation mechanism of the English platform is optimized using a multilayer perceptual machine. Unstructured English learning resources are processed based on the word vector representation method, and for the problem of insufficient processing of nonlinear data in the DN-CBR model, multilayer training is carried out using the MLP to improve the perceptual degree of this part of the data, and the design goals are verified through the test of the teaching platform. The correlation coefficient between self-assessment difficulty and topic difficulty is 0.368, and the correlation coefficient between self-assessment difficulty and positive error is 0.163, indicating that there is a moderate correlation between learners’ self-assessment difficulty and the difficulty of the system topics and between learners’ self-assessment difficulty and positive error. The MLP-based pushed questions’ difficulty is adapted to the learner’s personalization level by dynamically revising it based on their learning process data.
Research on the integration and development of visual communication art and brand pattern design based on data envelopment analysis method
Authors: Yang Anyu 
Published: January 2024

Abstract
Brand pattern design is an important part of brand image building. This paper proposes a fractal method for visual communication and brand pattern design, combining fractal theory with a computer to generate Julia fractal graphics and apply them to brand pattern design. The grayscale covariance matrix is utilized for texture analysis to address the issue of difficult fractal processing. Meanwhile, the DEA method was applied to measure the economic efficiency of the brand design process based on visual communication art. Three input indicators and two output indicators were selected to construct the DEA performance measurement system, and based on the study of the fractal effect of pattern design, the brand design of hotel brand Group A was taken as the research object to compare and analyze the DEA efficiency and influence of similar brands. From the perspective of brand pattern design, the average value of the brand influence score of Group A from 2017 to 2020 is 0.4515, the overall average value of the brand influence score of the sample hotel group is 0.5154, and the brand influence score of A fails to reach the average level. The brand design of Group A is still insufficient to fully reflect the influence of the brand.
Research on the Evaluation of the Effectiveness of the Construction of First-Class Undergraduate Majors in Colleges and Universities Based on Student Input in the Context of Deep Learning
Authors: Zhao Qinqin , Chen Han 
Published: January 2024

Abstract
This paper uses triangular fuzzy numbers to solve the weights of the evaluation indexes and then applies the improved TOPSIS method to evaluate the effectiveness of the construction of first-class undergraduate majors in colleges and universities. Empirical data were collected through questionnaires and materials related to the declaration of first-class major construction to verify the factors affecting the effectiveness of first-class undergraduate major construction and the comprehensive evaluation. The results show that four indicators, namely student learning outcomes, effective teaching practices, teacher-student interaction levels, and professional curriculum plans, explain 57.52% of the effectiveness of first-class undergraduate major construction. Among the ten universities, the relative closeness of the first-class undergraduate major construction effectiveness to the optimal solution of University D is 0.75221, and the major construction effectiveness is the most significant. The combination of students’ inputs and the effectiveness of first-class undergraduate major construction in universities under the background of deep learning can further enhance the depth of students’ learning for the major and promote the effectiveness of major construction.
A Statistical Study of English Teaching Methods Incorporating Children’s Memory Characteristics
Authors: Zhao Fang , Li Mingxia , Feng Cheng 
Published: January 2024

Abstract
In this paper, a multivariate linear regression model of the English teaching method incorporating children’s memory characteristics is designed. The linear regression algorithm is utilized to reduce the error between the real and predicted data, and the multiple covariance problem is corrected through the principal component-ridge regression model to study in depth the effect of the implementation of the English teaching method that combines children’s memory characteristics. Taking students and teachers majoring in English as the research subjects, we designed a questionnaire survey to collect research data and reflect on the practice through classroom observation and interviews. The results showed that the regression coefficients of the variables of children’s memory characteristics, attention concentration, preference, memory repetition and association factor were ranked in the order of 0.290, 0.240, 0.182, 0.018, and the other three variables were significant at 0.5 significance level except for the variable memory repetition, which was significant at 0.1 significance level. This study shows that there is a causal relationship between children’s memory characteristics and English language teaching and that children’s memory characteristics can induce students to form positive preferences and improve their memory repetition in English language teaching.
Analysis of the Path of Improving English Listening and Speaking Ability Based on Big Data Technology
Authors: Tao Yingjie 
Published: January 2024

Abstract
The training of college students’ English listening and speaking skills needs to be individualized scientifically and strategically in order to get a qualitative improvement. In this paper, we first analyze the correlation between students’ listening and speaking skill levels by using the improved maximum information coefficient (MIC) with the aid of an online platform. The students’ listening ability is assessed by the plain Bayesian algorithm, trained by the neural network to reduce the error, and the similarity between the feature vector and each pattern is calculated so that the element that obtains the highest value is used as the candidate mapping. Next, the schema mapping of data distribution (SMDD) method is combined to obtain the best matching schema. Finally, the effectiveness of English listening and speaking training with the Smart Teaching Platform was investigated through controlled experiments. The results show that in the post-test speech scores, the experimental group’s increase in speech scores was 2.322, while the control group’s increase was only 0.652. The effectiveness of the English listening and speaking ability training strategy is evident due to the obvious difference. This study proposes rational suggestions for improving college students’ English listening and speaking abilities.
Metaphorical Expression of Emotions in Modern Music Composition Based on Emotional Calculations
Authors: Zhu Lin 
Published: January 2024

Abstract
In this paper, audio and lyrics features of music are fused from the audio and lyrics attributes of modern music tracks to obtain a joint representation of music. The features such as tempo, directionality, average value of intensity, beat, and change of rhythm of each musical segment are extracted from the main audio track to form the music feature vector. Subsequently, the music was separated into multiple segments with distinct emotions, and the emotional expression of modern music was evaluated using the Hevner emotion model. Finally, the note extraction performance of this paper’s model is analyzed, and the spectral contrast features of different music pieces and the emotional expression of music pieces under different features are explored. The results show that the pitch patterns of sad emotions are mostly distributed in the range of 0.5-0.55, and the values of the pitch patterns of angry music are basically larger than 0.55. The mean values of the spectral entropy of joy and calmness are mostly distributed in the range of 0.5-0.7, and the sad emotions are mostly in the vicinity of 0.7, while the mean values of the spectral entropy of angry emotions are larger than 0.8.
Artificial Intelligence Technology Enabling Innovation in Museum Public Cultural Service Models
Authors: Yang Zhenyuan , Xia Mingming , Wan Xinxin , Wang Miaobei , Tang Wenrui 
Published: January 2024

Abstract
In this paper, we constructed an artificial intelligence model of environment perception and human body perception, and after filtering the irrelevant information in the environment, we collected and analyzed the three-dimensional information of the environment to realize the intelligent perception of the environment. Aiming at the transient noise that may occur in the robot’s operating environment, a time threshold is added on the basis of the traditional double threshold endpoint detection algorithm, which effectively eliminates the influence of transient noise on endpoint detection and realizes non-contact continuous speech recognition. Then the data of the perceived human body was analyzed to understand the perception of the human body by artificial intelligence. Finally, a model for museum public cultural innovation services was constructed based on AI, and the effects of AI on public cultural services were analyzed. The results show that people’s overall perception of intelligent services is 4.305 points, and the perceived functionality, perceived ease of use, perceived pleasantness, and level of intelligence have a significant positive correlation with the quality of public cultural services, with β-values of 0.286, 0.206, 0.068, and 0.378, respectively, and p<0.05.
Study on the Development Path of Rural Cultural Industry under the Perspective of Rural Revitalization
Authors: Ni Jiaojiao , Kuchinskaya Tatiana Nickolayevna 
Published: January 2024

Abstract
Based on the theory of systematics and synergy, this paper measures the degree of coordination within the system by measuring the system order parameters that determine the phase transition characteristics and laws of the system and establishes a model of the coordination degree of the composite system that can be realistically calculated. This paper sorts out the main constraints on the coordinated development of rural cultural industries, constructs an index system to evaluate the level of coordinated development of regional cultural industries, and introduces it into the composite system coordination model to measure the synergy degree of rural cultural industries. Starting from the interaction effect between the digital cultural industry and rural revitalization, this paper designs the research on the digital cultural industry from the perspective of rural revitalization and uses data analysis software to analyze the development path of the rural cultural industry. The results show that the iterative scheduling strategy achieves the best scheduling objective function in each test set, with values of 154.62, 287.074, 360.262 and 348.408, respectively. That is, the iterative scheduling strategy can better complete the passenger flow scheduling. In 2012 and 2019, the ‘ Moran sI values of rural cultural industry efficiency were 0.1752 and 0.3094, respectively. That is, the technical efficiency of rural cultural industries from the perspective of rural revitalization has a significant spatial dependence on geographical space and has a positive autocorrelation relationship. This study analyzes the dilemmas faced by the development of rural cultural industries and proposes practical ways to solve these issues.