bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on the Relationship between the Participation Degree and Experience of China’s Intangible cultural heritage Tourism Activation in the Information Age
Authors: Zhao Fengjun
Published: January 2024

With the development of the trend of cultural and tourism integration, intangible cultural heritage has become an important part of the development of experiential tourism. This paper combines information visualization technology to construct a framework for the design of non-heritage information visualization. By constructing a relevant spatio-temporal retrieval function to reduce the redundancy of non-heritage spatial data storage, combined with the base state correction model, the change process of non-heritage spatial features is retraced. GRU is applied as a unit of temporal feature correlation analysis to model the serial data of the degree of participation in non-heritage tourism revitalization. Two gating controls, the reset gate and the update gate, are used to regulate the flow of NRM information. The relationship between participation level in NRH tourism revitalization and experience was focused on in the information visualization design. The results show that the p-value of tourism experience and tourism revitalization is 0.521**, which is the most significant among all p-values, indicating that tourism experience has the closest relationship with tourism revitalization, and there is a significant positive correlation between both. Among the different groups of tourists, most of the experience scores of group C tourists are concentrated in the range of (80,90), while the advanced level of participation brings visual enjoyment to tourists while conveying the cultural spirit and emotional experience.
The Nature of Ideological and Political Education in Colleges and Universities Based on Deep Learning Models and Its Development
Authors: Wu Qiong
Published: January 2024

In this paper, first of all, after extracting the character sequence information, a certain scale of the corpus is obtained by using a crawler, and a corpus in the field of ideological and political education, as well as a participle system, is constructed. Then, the sequence decoding problem is solved by combining the idea of dynamic programming, based on the word level N-gram language algorithm, to design and implement an efficient solution method and calculate the final result of the participle. Finally, the keywords of related literature are classified, the essential dimensions of ideological and political education can be derived, and the essence of ideological and political education is explored and analyzed by using the word division algorithm. The results show that the most important essence of ideological and political education is “educating people’s feelings” with a weight value of 0.46, and among the 24 secondary nodes, there are 19 items with coefficients of variation less than or equal to 0.3, which shows that the degree of consistency is high, indicating that the degree of importance of the essence of ideological and political education is also high.
Exploring the Sustainable Development Path of College Volunteerism with Voluntarism in the Context of Deep Learning
Authors: Cao Yumei , Wang Yanbo
Published: January 2024

This paper first analyzes the pain points and needs of voluntary college student volunteering in conjunction with college volunteering program management. Combined with the logic of generating a sense of acquisition for college students’ volunteer service, it explores the types of motivation that drive their volunteer demand. Based on deep learning, we propose volunteer integrity neural network prediction, classify volunteer integrity, and select different data sources to compare the running time and effectiveness of four classification algorithms, namely artificial neural network, Bayesian network, decision tree and support vector machine. Volunteer portraits are established with two dimensions: natural attributes and interest attributes. Deep feature extraction is utilized to recommend college volunteer activities. Among the sources of volunteering accessibility, 72.2% of college students consider volunteering information sources to be highly important. It can be seen that college volunteer service can help strengthen the construction of volunteer service information channels.
Differential Analysis of Stylistic Features in Chinese-English Interpretation Based on Natural Language Processing
Authors: Sun Weina
Published: January 2024

In this paper, after researching the natural language processing model, we use the knowledge representation technology to construct a knowledge base and use the sequence comparison algorithm to compare the sequences of Chinese and English translations, analyze the similarities and differences between the two sequences, and analyze the entropy of information between English and Chinese translations through the probabilistic theory and mathematical statistics method. On this basis, we analyze the differences between Chinese and English translations in terms of lexical dimension, syntactic dimension and articulation dimension and explore the differences in lexical richness and thematic concentration between Chinese and English based on “entropy”. The results show that Chinese is significantly higher than English translations in terms of language output length, sentence complexity, subordinate structure and phrase structure (p<0.001), and Chinese is significantly higher than English translations in terms of articulation (p<0.05). This paper provides an important reference value for studying the differences in stylistic features in Chinese-English translation.
Research on the Digital Preservation of Intangible Cultural Heritage of Folk Dance Art Category
Authors: Wang Xiaoyi
Published: January 2024

In this paper, based on the rapid head generation technique of the model library, we obtain a frontal 2D face photo, mark 13 feature points selected from 7 parts, such as both eyes, nose, mouth, etc., to determine the approximate position of the whole facial features, simulate the real color of the face according to the texture mapping of the face, and at the same time, we add the texture features of the target face in the to the matching model, to achieve the mapping of overlaying texture to the neutral texture and the fusion of skin color. Using HigherHRNet network extraction to obtain the coordinate information of the joint points of the intangible cultural heritage dance inheritors and their heat maps, the obtained key frames of the dance features are connected in a certain order to obtain the synthesized folk dance video with gesture estimation. Combining semantic segmentation of keyframes and style rendering, the visual image of the dance is designed, and the intangible cultural heritage of folk dance is analyzed through examples. The results show that this paper’s method achieves more than 90% recognition accuracy on all three datasets and more than 94.8% recognition accuracy on the folk dance movement dataset. On the evaluation of folk dance movements, the average distance calculated by this paper’s algorithm is the largest, 95.7, and the average score is the lowest, 43.6. The average distance and average score of this paper’s algorithm are in between the above two cases, i.e., the experimental results verify the effectiveness of this paper’s method. This study promotes the intelligent protection and creative inheritance of Chinese non-heritage dances through digital protection.
Research on art design and application of cognitively oriented thinking in the following creative products
Authors: Cui Ronghua , Chen Liyuan
Published: January 2024

At present, the knowledge of cultural relics in cultural creative design is fragmented and fragmented, and lacks the support of a unified system. In this paper, firstly, with the help of a topological model to characterize the creative process of image thinking, effective reasoning is carried out on the objects, things and relations of cultural and creative products according to the expansion analysis of primitives. Then, a conceptual network of art design for cultural and creative products is constructed based on semantic association, and an identification model of art design elements for cultural and creative products is built based on quantitative theory. Finally, through the experiment of art design for cultural and creative products, the perception of cultural and creative products was analyzed in multiple dimensions. The results show that the maximum factor influencing the value of art design of cultural and creative products is 0.951, among which the cultural characteristics have a strong correlation with the color characteristics of 0.642, and the functional characteristics have a strong correlation with the cultural characteristics of 0.837. The results of this paper provide new ideas and methods for the development and maturation of artistic design of cultural and creative products.
Personalized teaching of college psychology based on information fusion technology
Authors: Huang Tao
Published: January 2024

This paper explores the cognitive attention mechanism in mental activities, analyzes the learning emotion contained therein as well as the information of thinking activity that carries out the whole cognitive process of mental learning, and obtains the information construction data of the three-dimensional interest model after the estimation of the learner’s head gesture and the recognition of dynamic expression. A conditional random forest model is built using multimodal information fusion technology, and a natural smile detection method is proposed based on it. After training, it realizes the information estimation of the learner’s head pose data, generates the smiley face classifier based on conditional random forest, and determines the teaching decision boundary using K-Means clustering. To analyze the psychological personalized teaching results of the model, an empirical study is conducted through a controlled experiment. The experimental results show that the learning efficiency of the model on the CelebA dataset and SMILEsmileD dataset is improved, the accuracy rate is stabilized at 95% after the number of iterations 10, and the model’s performance is superior. The majority of the students in the experiment have a mastery of psychological knowledge that is around 0.85, and there is a significant positive correlation, and personalized teaching has a more significant effect.
Research on Curriculum Construction and Capacity Cultivation of Innovation and Entrepreneurship Education in Colleges and Universities in the Context of Digital Curriculum Civics and Politics
Authors: Wang Cong , Liu Yuening , Yin Huamin
Published: January 2024

When colleges and universities develop courses on innovation and entrepreneurship, they frequently concentrate on teaching theories related to these topics, which results in students having limited practical skills. Based on the complete assessment approach, this research develops a coordinated development model for innovation and entrepreneurship education in the context of civics and politics. It examines the components of education related to innovation and entrepreneurship, as well as the supporting role that the civics curriculum plays in these areas. Three factors, namely the objective, content, and development prospect, are considered when analyzing the applicability of the Civics and Politics course to teaching innovation and entrepreneurship. Establish the coordinated degree value of digital curriculum development and the creation of college entrepreneurial and innovative education curriculums. Determine the degree of link between civic and political matters by using them as a reference point. The current state of education in entrepreneurship and innovation in colleges and universities is analyzed using the coordinated development model, and corresponding solutions are put forth for the issues with curriculum development and entrepreneurial ability. The findings demonstrate that the range of [0.6,0.85] is often where the teaching impact of integrating curriculum and practice falls. After combining politics and ideology with innovation and entrepreneurship education, the percentage of students who said that their entrepreneurial aims were to gain money fell from 0.8751 to 0.2103. In order to allow students’ values and opinions to be reflected in the new curriculum for innovation and entrepreneurship education, this study combines the benefits and resources of politics and ideology with the study of innovation and entrepreneurship.
Research on Teaching Resource Management in Colleges and Universities Based on Multiple Data Chain Networks
Authors: Wang Kunpeng
Published: January 2024

In this paper, we first take the datalink network as the entry point and construct a university teaching resource management model based on a multivariate datalink network. A Link-22 data chain time synchronization algorithm with KF-RTPT is proposed to address the actual existence and unavoidable time deviation based on accuracy and timestamp acquisition errors. Meanwhile, a time slot allocation and optimization algorithm designed to maximize message transmission benefits is being developed to optimize the allocation of node time slot requirements. Finally, the constructed teaching resource management model is empirically analyzed from three perspectives: error optimization, dynamic time slot allocation, and model application effect. According to the findings, the KF-RTPT algorithm increases motion error efficiency by 3.83 in low-speed motion states and 8.16 in high-speed motion states when compared to the conventional RTT method. This effectively eliminates motion error and boosts the effectiveness of teaching and managing resources in colleges and universities.
Mining and Teaching Design of Civic and Political Elements in Digital Electronics Technology Course Based on Markov Modeling
Authors: Zhang Jie
Published: January 2024

This paper proposes a course knowledge resource extraction method based on the improved Hidden Markov Model and combines the method with hierarchical classification ideas. The improved Hidden Markov Model is used in the study of the text classification process of course knowledge resources, the expected cross entropy selects the feature words, and the semantic space composition is obtained by using the implicit semantic indexing method. When setting the observation output probability matrix for the HMM classifier model, the improved TFIDF method is introduced to reflect the semantic relations between feature words. An evaluation criterion such as macro-micro mean is used to analyze the performance of the whole text set classification and gradually improve the HMM model. Finally, the HMM resource information extraction model has been improved to mine the elements of civics in digital electronics technology courses. It is found that in the compulsory textbook knowledge of digital electronics technology, the trigger knowledge has the greatest integration degree with the Civic-Political elements with a percentage of 0.3382, followed by the analog-digital and digital-analog converter knowledge with a percentage of 0.2818. In the textbook column on digital electronics technology, the extended knowledge has the greatest integration degree with the Civic-Political elements with a percentage of 0.5043, followed by the strengthened category column with a percentage of 0.1712. The analysis of the students’ different Civic-Political dimensions after the instruction has been done. In the political identity category, national sentiment, scientific spirit and ecological environment topics improved by 7.23, 2.01, 3.2 and 2.14 points, respectively. It shows that students can improve their cultural knowledge in digital electronics and establish a correct worldview, life view, and values.
Exploring the Development, Dilemmas and Countermeasures of College English Teaching by Combining the Hierarchical Analysis Approach
Authors: Xu Jiayu
Published: January 2024

College English teaching has formed a long-term historical persistent problem in the process of higher education expansion, and it is urgent to explore its development dilemma and corresponding countermeasures. This study uses hierarchical analysis to analyze the connection between relevant factors in English teaching activities, constructs a judgment matrix for teaching evaluation, establishes the index ordering through a consistency test, and applies intuitive fuzzy logic to establish the index weights. At the same time, a genetic algorithm was applied to the weight optimization process to iterate the better matrix indicator weights. After verifying the optimization effect through experiments, the comprehensive assessment method was applied to specific teaching cases and analyzed. The comprehensive evaluation results of students, teachers, and experts were obtained respectively, the latter being [0.3459 0.2961 0.1848 0.1086 0.0636]. The final evaluation result of the university English teaching case is [0.3358 0.2790 0.1874 0.1272 0.0695], which corresponds to the grade of “general”. Through the evaluation of university English teaching, the difficulties of current English teaching are fed back, which lays the foundation for the countermeasures to be put forward.
Research on the Innovation of Piano Music Teaching in Colleges and Universities Based on the Characteristics of Music Culture
Authors: Hu Dongming , Zheng Ying
Published: January 2024

Starting from the communication characteristics of piano music culture in colleges and universities, this paper proposes a piano music signal detection technology that includes two parts: note onset and fundamental frequency detection. Based on the characteristics of the harmonic structure of the music signal, the degree of harmonic matching between the signal to be recognized and the standard note signal is calculated, and the task of multi-fundamental frequency estimation is accomplished by using the timbre characteristics and harmonic structure. The detection technology of piano music signals is applied to the recognition of teaching short notes, playing music and playing evaluation to get a new model of piano music teaching in colleges and universities. The results show that the algorithm in this paper can recognize piano music correctly by more than 91%, and the method has no obvious decrease in recognition rate in the process of gradually increasing noise, which is conducive to improving the effect of piano music teaching in colleges and universities.
Study on the Application in the Protection and Renewal of Ancient Architectural Cultural Heritage in the Age of Smart Media
Authors: Jiao Ziyun
Published: January 2024

In this paper, the candidate region network in the Fast R-CNN algorithm is used to obtain the feature values of surface damage of ancient buildings, and the regression algorithm is applied to the target bounding box after the features are successfully obtained, which can more accurately complete the task of detecting and locating the damage on the surface of buildings. The three-dimensional laser scanner and total station are used to explore the surrounding environment of the buildings on the site, and the sketch is drawn according to the research and analysis results combined with the exploration to design a digital archive of the cultural heritage of the ancient buildings. Aiming at the ambiguity of the assessment system of the integrity of ancient buildings, we constructed the assessment system of the cultural heritage of ancient buildings with the fuzzy affiliation of the data of the integrity of ancient buildings and multilevel fusion assessment and carried out an example analysis of the research on the protection of the cultural heritage of ancient buildings in the era of smart media. The results show that when the number of iterations is 15000, the mAP value is 0.9411 (where 1 represents the maximum AP value), which is higher than the training results with the number of iterations of 20000 and 25000, i.e., the Faster R-CNN training model has good applicability for the autonomous visual detection of the damage on the surface of the ancient buildings. “Q9 I will not damage the ancient buildings in Zhuge Village” has the highest mean value of 4.71 and the highest approval rate of 99.1, and the standard deviation of each question item is small, i.e., it indicates that there is a high degree of consistency in the positive attitudes of residents towards the protection of the cultural heritage of ancient buildings. This study contributes new ideas to the protection of ancient architectural, cultural heritage and tourism development, which is crucial for advancing the research field.
An Analysis of the Impact of Insider Trading on Executive Compensation in Listed Companies Based on VAR Modeling
Authors: Jin Li
Published: January 2024

In this paper, we first establish a VAR model, screen the variables using the CSIS method so as to achieve fast dimensionality reduction, and use the cointegration theory to model non-stationary time variables to determine the pseudo-regression analysis between variables. Impulse response functions and variance decomposition are then used to analyze the dynamic effects of changes in random disturbance terms on the whole system and other variables. Finally, the effects of insider trading on executive compensation are explored using corporate performance and market-based executive pay entitlement as references, respectively. The results show that the regression coefficients of executive compensation level and cumulative excess turnover rate of the event announcement period are 0.805 and 0.018 for corporate performance and market-based compensation, respectively, and the higher the level of executive compensation based on corporate performance and market-based compensation, the lower the impact of insider trading on executive compensation. Equity incentives reduce the impact of insider trading on executive compensation, and the regression coefficient of excess turnover on executive compensation is less than 0 in firms with shareholding levels higher than 10%.
Measures for the Integration of Digital Media Art and Film and Animation Creation Based on Virtual Reality Technology
Authors: Liu Yongchun , Li Juan
Published: January 2024

In this paper, we propose a scene animation network (FSGAN) method that uses spectral features to perceive the deep style of an image, which uses three loss functions for perceiving the distribution of image style features in the same style domain to generate anime style-consistent images. The recurrent consistency adversarial network is supplemented with a local reinforcement module based on self-attention, adapted to the animalization of portrait scenes based on their characteristics and needs. This module guides the network to pay attention to the salient regions in the image and combines layer normalization and instance normalization methods through the weighting of the attention weight coefficients to construct a portrait animation network based on local reinforcement perception. Then, based on the digital media technology to complete the virtual reality scene construction, the constructed space for three-dimensional division, and the use of generative adversarial network training model, the proposed key events and random sampling technology combined with the control of virtual animation scene generation method, to achieve the controllability and diversity of the virtual animation scene generation. The first-stage design efficiency, the second-stage design efficiency and the overall design efficiency of the animation creation method in this paper are all basically stabilized between 0.8-1. Compared with the traditional method, they are higher by 0.3932, 0.3596, and 0.5635, respectively. The extreme pixel percentage, standard deviation and contrast of the animation images created by this paper’s method are 0.0349, 0.0037 and 0.3382, respectively, and the overall color performance is better. Thus, the method presented in this paper has the best overall effect on processing anime images using digital media art effects.
A Study on the Relationship between Human Resource Management and Firm Performance Based on VAR Modeling
Authors: Qin Yue , Lv Di
Published: January 2024

In this paper, after analyzing the VAR model, we design the Gram causality test between human resource management and enterprise performance and establish a structural equation combining multiple regression and factor analysis to explore the interrelationship between the two, in addition to evaluating enterprise performance based on mutation theory. In order to study the relationship between human resource management and enterprise performance, assumptions are made about the relationship between the two, a conceptual model of the role path relationship between human resource management and enterprise performance is established, and the proposed assumptions are empirically analyzed based on the existing literature and actual data. The results show that the coefficient of HR practices is 10.048343, which is significant at the 0.0031 level, and the goodness of fit is 0.403881, and HR practices do have a relatively significant impact on business performance, and the marginal impact is 10.048343, which indicates that HR practices significantly amplify business performance. This study confirms that human resource management is positively correlated with firm performance and that firms can optimize their human resource management strategies, which in turn will enhance their performance and provide impetus for their progress and development.
Research on action recognition for college dance teaching based on deep learning
Authors: Wang Rui
Published: January 2024

In this paper, Gaussian modeling is established to perform background subtraction of action feature images of dancers and combined with median filtering to denoise the background of feature images. The cumulative edge feature algorithm extracts relevant features from the dance dataset using the dance itself. Based on this, the directional gradient is introduced to output the extracted dance histogram features and cascade the optical flow histogram feature vectors in all blocks to form the HOF features of the image. The deep learning model is used to design the dance teaching model, and the teaching objectives are determined. The effect of dance teaching is tested through the method of simulation experiments and empirical analysis. The loss value of the model without deep learning is very high, reaching 1.25, and the loss values after convergence of the parametric model using deep learning are 0.85 and 0.95, and the deep learning algorithm has a better optimization effect on the model. The scores of the seven measures of teaching effectiveness are all above 12, and the significance p-value of each indicator is <0.05. The dance teaching effect is significant.
Innovation of Civic Education Path in Colleges and Universities under the Integration of Big Data Technology
Authors: Chen Xinjie , Liu Zhiqin
Published: January 2024

In the era of big data, different countries and regions use big data in the field of education. This paper constructs a personalized teaching model for Civics based on big data text-mining technology. Combined with the DIKW pyramid composition structure analysis, it shows how the data can be used to guide the process of teaching decisions. The frequency of Civics keywords in the teaching classroom and the key teaching content in the Civics classroom are determined using the word frequency analysis method. Similarity and KNN calculations are used to classify the students’ civics knowledge level, and personalized teaching plans are developed for their level of knowledge. The application of personalized teaching in Civics is practiced from the aspects of tracking students’ knowledge status and enhancing personalized teaching effects. The results show that the average final grade of class A in the experimental group is 102.37, and the average grade of class B in the control group is 97.37 in the final exam. Class A students have an average grade that is 5 points higher than that of class B. The average grade of students in class A is 5 points higher than that of class B. The two groups are tested using independent t-tests. The results of the two groups were subjected to independent t-test, F=7.047, p=0.00, 8<0.05, variance is not uniform. The t-test results show Sig=0.048<0.05, which indicates that there is a significant difference between the final grades of the experimental and control groups.
Digital Information Technology Enabling Computational Thinking C Language Blended Teaching
Authors: Cao Jingxin
Published: January 2024

Digital information technology provides an innovative way for the obsolete and inefficient C language classroom. This paper applies computational thinking to the design of C language hybrid teaching and builds a task-driven model for teaching C language using a driven teaching approach. Digital information technology is applied to TDT teaching; test questions are dynamically extracted in the process of students’ tests, intelligently analyzed according to the student’s answers to the test questions, and a genetic algorithm is used to adjust the difficulty, differentiation and knowledge points of the group paper. Based on the hybrid similarity model, we optimize the mutation operation in the genetic algorithm and verify the effect of similarity calculation through the practice of grouping papers for C language teaching. Hybrid similarity yields weighted average similarity scores of test questions that are 0.14 and 0.16 higher than edit distance and cosine similarity, respectively. On the basis of similarity calculation, the time taken to improve the GA to generate the test paper is no more than 1 second, and the difficulty coefficient obtained does not differ from the expected coefficient by more than 0.05. The intelligent paper grouping method can maximize the coverage of the needs of more students and improve the investigation of C language teaching. The way of teaching C language.
Analysis of the timeliness of multiple information on college students’ patriotism education in the all-media era
Authors: Meng Ying
Published: January 2024

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

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

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

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

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

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

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

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

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

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

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.