bluuebunny/crossref_metadata_2025 huggingface dataset:
A study on the dynamics of regional economic differentiation in China under big data environment combined with neural network algorithm
Authors: Wang Jiangnan , Lu Yao , Pan Lina , Zeng Ye , Zhang Dexin
Published: October 2024

China’s economy is in a state of rapid development in today’s digital era, and big data technology has become a key force in promoting industrial upgrading and economic operation. The article first constructs 14 economic operation indexes in 7 aspects to establish the regional economic index system according to each type of regional economy. After researching BP neural networks, a TMBA-BP neural network prediction model based on adaptive t-distribution has been proposed. The prediction model is used to predict the economic development of Liaoning City, and the results show that the TMBABP prediction model is accurate. Finally, the Gini coefficient is combined with the TMBA-BP model to explore the causes of regional economic differentiation in China. In terms of the contribution rate of regional differences, the inter-regional contribution rate is higher than the intra-regional contribution rate. It indicates that in the big data environment, the main reasons for the obvious regional economic differentiation in China are inter-regional differences, followed by intra-regional differences.
Research on deep neural network-based anomaly detection technology in high-dimensional data environment
Authors: Wang Yan
Published: October 2024

With the popularization of information technology, the dramatic growth of data size, the significant rise in data dimensions, the increasing complexity of data types, and the diversity and complexity of the manifestations of anomalies all make anomaly detection more difficult. In this paper, we enhance the structure of the variational self-encoder in deep neural networks to maintain the benefits of anomaly detection technology, which relies on reconstruction error. Utilizing the high reliability of agent supervision to make up for the lack of detection performance of the deep self-encoder when the anomaly data dimension is high, a novel unsupervised anomaly detection model for high-dimensional and high anomaly rate data is proposed. Results from tests on several public datasets show that the UAD-ADC model does better than four other traditional anomaly detection methods in all of the datasets when looking at AUC values. On two datasets, Pendigits and Letter, the method improves by 0.3648 and 0.3004 over the lowest algorithm, and the experimental results confirm its effectiveness.
Information Technology Integration and Teaching Effectiveness Enhancement Strategies in Public Physical Education Programs
Authors: Wu Nengwei
Published: October 2024

By integrating a heart rate monitoring module and a step frequency monitoring module, this study aims to use informatization technology to monitor the exercise level of students in public physical education courses and to adjust the teaching methods of public physical education courses based on informatization feedback. A school had 332 students divided into an experimental and control group for comparative experiments. Based on the results of students’ exercise data monitoring by heart rate oximetry module and acceleration sensor, it was found that the exercise density of students in the experimental group (73.3%) was much higher than that of students in the control group (54.4%), which means that the students’ exercise status was better under the informatization teaching mode. During the experimental period, there were significant differences in the average heart rate and MVPA percentage time between the experimental group and the control group students (p<0.05). The results of the physical fitness test showed that the informatization teaching mode significantly improved the student’s performance in body weight, pull-up, and standing long jump events (p<0.05) and significantly improved the student’s performance in lung capacity, sitting and lying forward bends, 50-meter run, and 1000-meter run events (p<0.01).
Research on the Optimization of Enterprise Resource Economic Benefits and Management Costs in Cloud Computing Environment
Authors: Xue Qianqian
Published: October 2024

Based on cloud computing technology, this paper constructs a benefit-optimal enterprise resource scheduling model and an enterprise cost management prediction model to maximize the economic benefits of enterprise resources and optimize the management costs, respectively. Combining the improved greedy algorithm and the benefit function, a cloud resource scheduling algorithm based on benefit optimization is proposed, defining the benefit function about time and cost, and taking the highest user satisfaction as the optimal resource scheduling objective. A mathematical model for management cost prediction is constructed by using the fireworks algorithm to optimize the number of trees and the number of leaf nodes in the random forest, and the Informatica software is used to manage and integrate the enterprise source data. The performance of the company’s operating conditions after optimizing resource management and cost savings is explored as a case study of Company S. In 2023, the total asset turnover ratio of Company S increased to 21.45 from 0.48 in 2022, and the overall asset operating efficiency improved. Working capital rose to 262,852,200 yuan. The current ratio, quick ratio, and cash ratio improved, while the gearing ratio, equity ratio, and equity multiplier showed a downward trend. The net operating margin achieved the maximum profitability in the last three years, net total assets margin, and net equity margin, with an increase of 25.42%, 20.65%, and 31.49%, respectively.
A neural network-based model for cross-border e-commerce supply chain demand forecasting and inventory optimization
Authors: Yang Weimin
Published: October 2024

The development of the Internet makes the e-commerce transaction scale in the total global trade share grow year by year, and cross-border e-commerce has become an important growth point of global trade by virtue of its unique advantages. In this paper, the ARIMA model is used to obtain the time series demand change of a cross-border e-commerce supply chain, and the results are input into the LSTM model to realize the construction of a cross-border e-commerce supply chain demand forecasting model. The ABC inventory classification method and economic lot ordering model are used as the basis for the establishment of cross-border e-commerce supply chain inventory control strategies and multi-cycle inventory control models. Taking the sales data of WT enterprise from May 2022 to May 2023 as an example, the effectiveness of the ARIMA-LSTM model in cross-border e-commerce supply chain demand forecasting is analyzed, and the inventory control optimization results of the multi-period inventory control model are verified. The relative error fluctuation range of supply chain demand forecasting of the ARIMA-LSTM model is between [-0.1,0.2], and the cross-border e-commerce supply chain’s monthly demand forecast MAPE value is only 0.0135. After using the inventory control optimization model, the annual average inventory is reduced by 178.42 tons, and the total cost of inventory is reduced by 0.09*108 yuan. Relying on neural networks can achieve accurate prediction of cross-border e-commerce supply chain demand and optimize cross-border e-commerce supply chain inventory.
Research on Intelligent Equipment Procurement Strategy and Optimized Resource Allocation Based on Big Data
Authors: Yin Tiehong
Published: October 2024

The intelligent equipment manufacturing cycle is long, resource consumption is large, in the manufacturing process often needs for different production stages to take multiple batches of resource procurement strategy and resource optimization configuration. Based on this situation, this paper proposes an intelligent equipment procurement strategy and resource optimization design. The problem description is established, the variables and constraints are introduced, and the construction of the objective optimization model is completed. The corresponding optimization model is solved using the improved Gray Wolf algorithm and the improved differential evolution algorithm. After the training and optimization of the improved gray wolf algorithm, the total cost of intelligent equipment procurement is 180150 yuan, and the procurement strategy is to select the preferred supplier at the corresponding point in time, according to which the procurement strategy can be a realistic intelligent equipment procurement task. In addition, the average deviation of resource optimization allocation based on the improved differential algorithm is only 0.35%, which is better than the performance of the traditional differential algorithm and genetic algorithm, confirming the feasibility of this paper’s algorithm in intelligent equipment resource allocation optimization model aiming at cost optimization.
An assessment of the impact of the digital economy on the adaptive reform of the tax system based on data analysis
Authors: He Haidong
Published: October 2024

The digital economy is playing an increasingly important role in economic development and has a non-negligible impact on the innovative development of the tax system. The study measures two aspects of the digital economy and the effectiveness of tax system reform (tax governance capacity and tax administration efficiency) and constructs a benchmark model through a panel Tobit regression model and a spatial regression model. The impact of the digital economy on the effectiveness of tax system reform is empirically analyzed. The digital economy shows a significant correlation with the effectiveness of tax system reform. The regression coefficients of the digital economy on the effectiveness of tax system reform in the eastern, central, and western regions are 1.586, -1.762, and 2.153, respectively. The differences in the coefficients between the groups in the east and the center and the west and the center are 3.486 and 3.896, respectively, which indicates that the development of the digital economy has a more significant effect on the improvement of the effectiveness of tax system reform in the western region and the east. However, it is less beneficial to the effectiveness of the reform of the tax system in the central region than in the central region. The effect of tax system reform is less beneficial. The digital economy can play a significant role in promoting the reform of the tax system in both regions with high and low levels of human capital, but it has a greater effect on improving the effectiveness of the reform of the tax system in regions with high human capital.
Research and Practical Exploration of Innovative Pedagogy of Civic and Political Education Content in Colleges and Universities Facing the Digital Era
Authors: Cheng Beibei
Published: October 2024

The advancement of information technology in the digital era has raised the standards for the content and methods of civic and political education in colleges and universities. This paper utilizes knowledge mapping technology as its foundation, integrates resources from civic and political education in colleges and universities, and builds a knowledge mapping system for civic and political courses. This system enables the digital and intelligent development of civic and political education in these institutions. The entities of Civics and Political Science courses are obtained through the Hidden Markov Model and BiLSTM-CRF model; semi-structured and unstructured data are crawled from web pages to constitute the entity relations of the Civics and Political Science domain, and the knowledge of Civics and Political Science courses is fused by using the double-layer filtering method. In addition, this paper constructs a Civics knowledge mapping system, which includes data modules and application modules, to visualize the complexity of the Civics knowledge system. This system is then applied to the practice of Civics teaching in colleges and universities. Based on the empirical analysis of the TAM model, it is concluded that the mean value of five potential variables (PEU, PUA, TU, BI, and SU) of the Civic Political Knowledge Mapping System constructed in this paper is high, and the acceptance of the system by students is long. The implementation of this paper’s system in actual teaching can significantly improve the overall civics learning objectives of the class.
Innovative Research on Illustration Design Integrating Color Science and Image Processing Technology
Authors: Zhou Guobao , Bai Guiwei
Published: October 2024

How to create intelligently and efficiently has become a hot research topic in the field of illustration design. In this paper, starting from the acceptance intention to satisfy users’ favorites and needs, we propose an intelligent analysis method of style based on a deep clustering model and use the categorized style attributes as a reference to disperse designers’ creative thinking. In addition, a semi-supervised semantic segmentation method is introduced to construct an automatic coloring model for sketches, and the automatic coloring function is realized by incorporating the color label recognition process, which further improves the efficiency of designers’ work. The results of clustering analysis of the STL dataset show that the ACC (78.39%), NMI (67.78%), and ARI (62.93%) metrics of the VIT+K-Means model have the largest results compared with other feature extraction methods. Results are superior to other feature extraction methods. Not only that, adding a pseudo-label retraining process for this model further improves the results of the three metrics by 9.13%, 9.97%, and 10.78%, and the visual analysis experiments of clustering clusters also verified the performance enhancement effect. In the comparative analysis of illustration coloring models, the AdvSSL scheme with semi-supervised strategy achieves the best performance in the semantic segmentation task, with an improvement of 4.31% and 2.29% over the SSAN scheme and the S4GCN scheme, respectively. The experts’ coloring evaluation shows that the improved sketch coloring model has the highest results in all four dimensions compared to the traditional Tag2Pix model.
Research on Augmented Reality Teaching Strategies for Civics Courses Oriented to History Education
Authors: Du Yunnan
Published: October 2024

In the context of comprehensively promoting information-based teaching, the construction of school classrooms is also developing in the direction of specialization, connotation as well as intelligence. The article designs a learning system for augmented technology in the context of augmented reality technology. The AR image-matching algorithm is proposed through the study of the system, and then the traditional KCF algorithm is improved, and a target tracking algorithm based on fusion matching is obtained by fusing the improved KCF algorithm with the image-matching algorithm. Then, the target is judged whether the target is lost or not by comparing the magnitude of the peak value (PSR) and the empirical value, and the test results show that the improved KCF has stronger target tracking utility. Subsequently, target tracking experiments were conducted using the fusion matching-based target tracking algorithm on students’ expressions in the classroom as well as head-up rate and concentration, while the accuracy of both experiments ranged from 83% to 95%. Thus, the algorithm performed better. Finally, a goal-tracking system was conducted for civics teaching with 75 students from University A. The results were based on the mean changes before and after the seven dimensions of the Civics course. It was found that after using the goal tracking system, the students’ post-test means all changed, of which the largest change in the score mean was historicism, with a difference of 21.04 between the before and after meals and the most obvious educational effect. It is favorable for teachers to conduct civics lessons to improve students’ learning status and performance.
Research on Clothing Brand Marketing Strategy Based on E-commerce Webcasting in the Internet Era
Authors: Chen Nuo
Published: October 2024

In recent years, with the rapid development of the Internet, e-commerce webcasting, as a new type of marketing method, has gradually been favored by clothing brands. The study constructed a model of factors influencing consumer purchase intention in live broadcasting e-commerce based on the SOR model, followed by hypotheses. An empirical study was conducted by distributing questionnaires to the consumer population watching live e-commerce streams. This paper recovered 388 valid questionnaires and used the PLS-SEM structural analysis method and factor analysis to conduct relevant test studies on each of the proposed variables. The empirical study of the five stimulus variables through structural equations concludes that all five stimulus variables are impacted by consumers’ purchase intention, with situational characteristics having the most significant impact on consumers’ perceived pleasure. Lastly, the derived influencing factors confirm the results. The proposal suggests a strategic approach to enhance the marketing of e-commerce clothing brands.
A qualitative study of undergraduate nursing students’ experience of clinical placement based on Nvivo software - a service learning theory perspective
Authors: Zhao Chong , Chen Juan , Li Linna , Gui Shuying , Zhou Qianqian
Published: October 2024

OBJECTIVE

To explore the experiences and feelings of undergraduate nursing students during their 4-month clinical placement through the lens of service learning theory.

METHODS

A semi-structured questionnaire survey was conducted on 233 undergraduate nursing students who had completed their internships, and the content of the questionnaire was analyzed according to the rootedness theory using Nvivo 12.0 software.

RESULTS

The interns thought that internship could appreciate the insufficiency of their knowledge and ability, and through the tutoring teachers’ counseling and their self-study could be of obvious help to the consolidation of knowledge and skills, especially to the enhancement of communication and collaboration ability, clinical practice ability, and professional and related knowledge; humanistic care and nurse-patient relationship in the internship process were the main factors for the development of emotion, and successful humanistic care could enhance the nurse-patient relationship, and the failed operation and ineffective communication can also experience verbal violence; internship experience can form professional confusion and professional identity.

CONCLUSION

The use of learning and reflection promotes clinical nursing competence; both humanistic care competence and timely care for interns should be assessed, and career counseling promotes the formation of professional identity.
Application of composite materials in aircraft power engineering and their optimized design
Authors: Feng Xuqin
Published: October 2024

The aeroelastic flutter characteristics of composite wall plate structures of aircraft are investigated, the equations of motion of the structures are established by Hamilton’s principle and assumed modal method, and the aerodynamic forces of the aircraft are simulated by using piston theory. Physical quantities such as the intrinsic frequency and damping ratio of the structure can be obtained by solving the eigenvalue problem. The variation curves of the dimensionless intrinsic frequency of the structure with the aerodynamic pressure are numerically calculated to determine the critical aerodynamic pressure for flutter vibration, and the time response history curves of the structure for forced vibration are computed to analyze and compare the effects of graphene and carbon nanotube materials on the aerodynamic-elastic stability of the composite wall plate structure. It is found that the critical aerodynamic pressure of the FGM wall plate composed of carbon nano-(Si3N4) and graphene (SUS304) composites is 762 KPa at the temperature of 0°C. The calculated results show that the critical flutter dynamic pressure of the composite wall plate is increased from 375.6 Kpa to 433.1 Kpa, with an improvement in performance of 57.5 Kpa. The results of this paper are useful for the application of composites in the flight vehicle. The results of this paper are of theoretical reference value for the application of composites in power engineering and the optimization of the aeroelastic stability of the wall plate structure of the aircraft.
Study on the Path to Improve the Sustainability Responsibility of Biomedical Enterprises Driven by Data
Authors: Shen Xi
Published: October 2024

In today’s complex, changing, and competitive market environment, active and serious fulfillment of social responsibility is one of the important strategies for enterprises to gain competitive advantage. This paper combines relevant literature to construct the performance index system of sustainable development responsibility of biomedical enterprises, and then determines the weights of the evaluation index system based on game theory by jointly applying the Gl method and the CRITIC method, and constructs a fuzzy comprehensive evaluation model for the evaluation of sustainable development responsibility of biomedical enterprises. Based on this, relevant sample data of biomedical enterprises are crawled through data-driven technology to measure the fulfillment of sustainable development responsibility of the sample enterprises and further combined with structural equation modeling to explore the improvement path of sustainable development responsibility. The sample biopharmaceutical enterprises are affiliated with either poor or poor, except for the overall responsibility of the sample biopharmaceutical enterprises in 2017, 2019, and 2022, which are in the middle. Responsibility to employees (ER), responsibility to consumers (CR), responsibility to society and government (GR), responsibility to the environment (IR), and responsibility to suppliers (SR) all significantly and positively affect the sustainability responsibility of biopharmaceutical companies (all p < 0.01). Biopharmaceutical enterprises should serve society with more scientific concepts, leaner management, and safer and more reliable pharmaceutical products to achieve sustainable development and gain wider social recognition.
Synergistic optimization of rural green eco-tourism industry chain under the support of information technology
Authors: Li Jiao
Published: October 2024

At present, the full development of tourism and other tertiary industries has gradually become the economic driving force of the countryside, but the negative impact on the countryside environment is becoming more and more prominent. Therefore, achieving the synergy optimization of rural green ecology and the tourism industry is a problem that needs to be solved. In this paper, starting from the rural green ecological tourism information, through the analysis of the basic elements of tourism information and the sampling of tourism information data, we construct a data feature extraction sampling model based on distributed detection, which is used for the reconstruction of the collection of tourism information data to ensure the effectiveness of information processing. Utilizing the method of fuzzy clustering, mining tourism information data, establishing the data distribution function, and collecting tourism information data features. The model is applied in practice to predict the level of tourist consumption and the daily flow of tourists in tourist attractions, and the results show that the monthly consumption of tourists in the year of the study area is 44.08 yuan less than that of the previous year, so it is necessary to adjust the tourism policy to stimulate consumption. In the coupling coordination degree of informationization and tourism industry development, it is found that the index of informationization application level has a faster rate of improvement than other indexes, with an increase of 546.09% between 2017-2018, and the index data of industrial benefits basically achieve an annual increment, reaching 0.4215 in 2021.
Research on Supply Chain Network Optimization under Cross-border Industrial Cooperation Model Based on Dual Carbon Objectives
Authors: Miao Yang , Yang Le , Tian Yule
Published: October 2024

Under the background of economic globalization, green supply chain management has become a key strategic management tool for enterprises to improve their competitiveness as well as sustainable development. This paper proposes the objective function and constraints in supply chain network optimization based on the policies related to the dual-carbon target and the requirements in the cross-border industrial cooperation model and uses the robust model to solve and realize the establishment of the supply chain network optimization model. The simulation test found that the solving efficiency of this model and the control of carbon emissions are better than the traditional genetic algorithm. Meanwhile, after the optimization of this model, the supplier delivery rate of cross-border enterprise Y can reach 91.28%, which is far beyond the target expectation, and the carbon emission of the enterprise is far below the carbon emission limit, so the green cross-border supply chain network can be realized. The model in this paper can improve the weak link in the green management decision of cross-border supply chain network, strengthen the application of a robust model in the design and optimization of cross-border supply chain network, and provide auxiliary decision-making support for the construction of cross-border supply chain network scientifically and effectively.
Research on Physical Training Helping College Students’ Physical Fitness and Health Quality Development in the Context of “Healthy China”
Authors: Ren Limin , Zhang Liang
Published: October 2024

In the face of the current dilemma and predicament of students’ physical health, it has become inevitable to incorporate health education into the national education system, with the help of physical training to reshape cognition, establish beliefs, guide behavior, and other effective means, so as to achieve the fundamental purpose of improving the physical health of students. This paper takes college students’ physical health as the research object, carries out the research on efficient association rule mining algorithm for BMI index, uses Apriori association rule algorithm in R language data mining to carry out in-depth mining of physical health test data, and carries out in-depth comparative analysis and exploration of intrinsic information of physical test data of two academic years of 2022 grade in a school in a more detailed and in-depth way. A scientific guidance program for physical training is created using the collaborative filtering algorithm to support the high-quality development of college students’ physical fitness and health. The results of the study found that the correlation coefficient between physical training behavior and BMI index r = -0.753, confidence test value P = 0.0004 < 0.05, indicating that there is a significant negative correlation between students’ physical training behavior and BMI. That is, physical education and sports can significantly promote the physical health of college students, and ultimately, their BMI should fall within the normal range.
Research on innovative methods of virtual reality course content for tourism education
Authors: Zhu Zhu
Published: October 2024

Tourism practice teaching is an important means to cultivate high-quality skilled tourism talents. When virtual reality is in tourism practice, teaching undoubtedly shows a beautiful blueprint for modern tourism education. The article demonstrates the advantages of the application of VR technology, designs a VR practical training system for tourism education, and develops VR resources and interface interaction design for tourism education. Based on the binocular stereo imaging model to obtain maximum and minimum parallax, and combined with the adaptive weight PSO algorithm for optimizing tourism virtual scene viewpoints. Then, a comparison test for teaching was designed using the VR training system for tourism education. By analyzing students’ eye movement data to understand the viewpoint optimization effect of the AW-PSO algorithm, we also verified their learning performance, learning experience, and academic mood changes. The edge strength and clarity of the virtual scene obtained by the AW-PSO algorithm were 67.06 and 14.71, respectively, and the theoretical score of the experimental class students was 83.15, which was 9.06% higher than that of the control class students. Based on tourism education, VR practical training systems can effectively enhance students’ learning interest and academic mood for tourism education courses and help develop high-quality tourism education courses in colleges and universities.
A model for the application of big data analytics in cost prediction and control in construction projects
Authors: Sun Wenbo
Published: October 2024

Construction project cost control is an important aspect of project management. This paper aims to provide an effective cost control management mode for the construction industry by studying the application of big data technology in cost prediction and control management of construction projects. The standard particle swarm algorithm is optimized by establishing a particle object element model, performing iterative and hierarchical updating of particles, and introducing the Tent mapping strategy. Then it is used in the optimization of the Extreme Learning Machine algorithm to design a construction project cost prediction and control model based on APSO-LLM. The index system of the construction project cost prediction and control model is constructed, and the convergence effect, prediction effect, and case application of the model are analyzed. The APSO-LLM model enhances the convergence speed and search accuracy, boosts the optimal fitness by 0.037, and maintains a construction cost prediction error below 3%. The study proves the APSO-LLM model’s applicability, accuracy, and good prediction effect in cost prediction and construction project control.
A Study on Personalized Digital Marketing Content Creation Based on Consumer Psychoanalysis
Authors: Zhan Huina
Published: October 2024

At present, personalized recommendation technology is widely used in digital marketing. In this paper, on the basis of the existing personalized recommendation algorithm based on commodity characteristics, from the perspective of consumer psychology, we propose a multiple attitude recommendation algorithm under the apparent awareness of the customer. In this recommendation algorithm, the user’s recent and historical interest weights are added, and personalized digital marketing content recommendations are made based on consumer psychology. The MT algorithm designed in this paper has a higher recommendation accuracy when compared to other recommendation algorithms. A questionnaire survey is conducted to examine the influence of marketing content on consumers’ purchase intentions on shopping websites using the personalized recommendation system designed in this paper. The correlation analysis results indicate that the variables and the willingness to buy have a positive correlation at a significance level of 0.01. The final regression equation: willingness to buy = 0.065+0.126*information orchestration+0.113*pop-up ads+0.109*social channel recommendation+0.158*web system recommendation+0.152*user trust, which indicates that the variable of web system recommendation has the greatest effect on willingness to buy.
A Language Modeling-Based Approach to Real-Time Language Translation Quality Enhancement in ESL Education
Authors: Zhou Hong
Published: October 2024

With the development of ESL education in recent years, real-time language translation has gradually become a research hotspot in the field of natural language communication. In this paper, the data processing technology of real-time translation is introduced, and then a Transducer (RNN-T) model based on real-time language translation is constructed based on the BPE subword segmentation method under the condition of probability gradient calculation algorithm and transcription network. Secondly, this model determines and tests the content involved in the process of real-time language translation and finally obtains results to improve the quality of real-time language translation. The experimental results show that the accuracy of character translation among the six language models is 85.8%, 86.2%, 88%, 93.4%, 94.03%, and 94.36%, respectively. In addition, the error rate of inserting, deleting, and replacing characters is < 20%. Compared with the other four models, the word error rate of the RNN-Transducer algorithm is reduced by 1.59%, 3.94%, 3.86%, and 9.01%, and the RTF is reduced by 3.91%, 10.96%, 10.09%, and 7.94%, respectively, which reflects the superiority of the RNN-Transducer method proposed in this paper.
A Practical Study on the Teaching Reform of Civic and Political Integration of Economics Courses in Colleges and Universities Supported by Information Technology
Authors: Li Xiaolu , Wu Yuchuan
Published: October 2024

The issue of strengthening the construction of economics courses, enhancing the moral development of economics professionals, and cultivating professionals with firm and lofty economics ideals is of utmost urgency. In this paper, we model the potential relationship prediction and global correspondence of economics curriculum civics in colleges and universities and then use the sequence markers specific to the subset of relationships to deal with the overlap between entities and entities to complete the ternary extraction work and to realize the joint curriculum civics element entity relationship extraction. Fusion of entity attributes and structural features can be achieved by utilizing the dual attention mechanism, and hyperbolic spatial embedding in graph structure feature extraction can be utilized for entity alignment. The economics program at a university in Guangzhou implements classroom civics integration teaching reform after completing the named entity recognition task test on the dataset. It was found that compared to LEBRT, the current state-of-the-art method for incorporating lexicon information, the model in this paper achieved a performance improvement of 2.53%, 2.26%, and 3.47% in the three metrics, respectively. After one semester of teaching reform and model application, the four scores of Economics Interest, Economics Habit, Economics Confidence, and Economics Autonomous Learning Ability increased by 28.13, 28.65, 18.39, and 26.68 points, respectively, compared with the pre-test, and professionalism also improved by more than 10 points in all cases. This paper provides a useful exploration for optimizing classroom civics teaching methods and efficiency, as well as combining implicit civics with cutting-edge information technology.
Exploring Innovative Practices and Challenges in the Ecological Development of Art Industry Driven by Digital Technology
Authors: Chen Liyan
Published: October 2024

The essence of the ecological development of the art industry, when viewed through the lens of digital technology, is precisely the development of regional economies within the framework of sustainable development strategies. This paper determines the first-level and second-level indicators of the three subsystems of industrial economy, ecology, and society according to relevant references and experts’ suggestions. Using the entropy weight method to calculate the weights of evaluation indicators, combining the weight values and normalized data, we construct the economic-ecological-social composite system evaluation model and make a detailed expression of the coupling degree and the coupling coordination degree calculation formula and process. This paper utilizes the model of this paper to evaluate and analyze the ecological development of the art industry influenced by digital technology by selecting the research object. The weight values of the ecosystem, social system, and economic system are 0.4277, 3064, and 0.2659, respectively. The index of the coupling coordination degree of the ecological-economic-social system falls between 0.6 and 0.7 in the years 2013 to 2015, indicating that the composite system is currently in the primary coordination stage. By evaluating and analyzing the results, we summarize the challenges that need to be faced by the ecological development of the art industry in the context of digitization, and for this reason, we propose innovative practices for the art industry.
Research on Cultural and Creative Design Based on Modal Theory and AIGC Technology
Authors: Xie Xueying , Tang Boyun
Published: October 2024

Modal theory is an important basis for studying cultural inheritance and dissemination. This paper combines modal theory and AIGC technology to innovate the cultural and creative design method. Through the calculation and analysis of modal recognition degree and other indicators, the modal factors that should be applied or innovated in cultural and creative design are identified. Using this paper’s cultural and creative design method, the analysis of Liangzhu culture and Shu brocade patterns is conducted separately. In the Liangzhu culture modal recognition, the higher recognition is pattern representation, morphological representation, and artifact function, and the lower recognition is color representation, aesthetic concept, material representation, and philosophical thought. The order of the popularity of the modal elements of pattern representations is from high to low: abstract pattern > animal pattern > geometric pattern. The traditional patterns of Shu brocade are in the order of color expression: A (0.209) > subject matter content, D (0.206) > surface features, C (0.162) > organization, B (0.148) > aesthetic meaning, F (0.138) > symbolic meaning E (0.137). When using AIGC to assist cultural and creative design, it is necessary to take into account the modal factors with smaller weight values to ensure that the final design can be loved by the public and achieve the dual goals of cultural heritage and economic benefits.
Comparison of Digital Literacy Education Strategies for Chinese and Foreign Youth in the Digital Media Era
Authors: Zhang Qian , Yang Di , Bai Ben
Published: October 2024

In order to realize the quantitative analysis of the digital literacy education strategies of Chinese and foreign youth, this paper constructs the evaluation index system with the help of a hierarchical analysis algorithm and comprehensive fuzzy evaluation to explore the differences between the digital literacy of Chinese and foreign youth, and to compare the differences between the digital literacy education strategies of Chinese and foreign youth. After analyzing and discussing, this paper identifies 10 expert panelists, conducts two rounds of the Delphi method survey on the preliminary expert consultation questionnaire, and finally determines the evaluation index system based on the standard of arithmetic mean and coefficient of variation. The evaluation indexes are divided into a hierarchical analysis structure. The judgment matrix of evaluation indexes is constructed according to the 1-9 scale method. The hierarchical single sorting and consistency tests are carried out to derive the weight value of each evaluation index. Based on the system of evaluation indexes, the evaluation factors are composed into a collection of factors, and the semi-trapezoidal distribution function is used to determine the subordination degree of the indexes. The principle of calculation of fuzzy comprehensive evaluation is given to realize the fuzzy comprehensive evaluation model. Construction. Using the above model to evaluate the digital literacy of Chinese and foreign youths, the evaluation result of the digital literacy of youths in country M is strong, with an affiliation degree of 3.9444, and the evaluation result of the digital literacy of youths in China is medium, with an affiliation degree of 3.1581. The difference between the digital literacy of Chinese youths and that of youths in country M is large. The education strategy determines the digital literacy of youths to a large extent. The results of the analysis of the evaluation are summarized in terms of three dimensions of distance education, feedback and communication, and evaluation system to explore the difference between Chinese and foreign youth digital literacy education strategies.
A study on eye movement test and visuospatial optimization of wayfinding perception in large-scale comprehensive transportation hubs
Authors: Zhai Leilei , Xia Haishan , Xu Ran , Shao Jinyan , Zhai Jianye , Nie Jiamin
Published: October 2024

The integration of rail transit stations and the surrounding underground space presents volume scale and functional complexity, and it has gradually formed a complex integrated transportation hub. Wayfinding inside its space is also more difficult, and the behavioral phenomena of passengers stopping, wandering, and getting lost are common. This paper uses station A of a large transportation hub as an example. It combines target detection technology and the optical flow method, designs the traffic space guidance system, tests how well passengers can find their way by moving their eyes, and then looks at how the visual space can be improved in terms of color, comfort, and subjective comfort after getting feedback. The data from the passenger eye-movement test reveals that during the sub-processes of information perception and elevator path selection, the logo is the primary focus, with attention ratios of 72.35% and 61.28%. Orange, yellow, and green were the three colors that received the highest ratings for subjective spatial comfort from passengers, with ratings of 0.58, 0.55, and 0.35, respectively, which are data-supported for visuospatial optimization.
A study of strong convergence of differential equations based on Euler’s algorithm
Authors: Ji Tianfu
Published: October 2024

Differential equations have important applications in many fields, such as chemistry, biology, epidemiology, and finance. Most analytic solutions of differential equations are difficult to obtain. Therefore numerical solutions of differential equations become an important tool. The truncated Euler method is proposed in this paper, and we investigate how the truncated EM solution of the derived SDDE converges strongly under the local Lipschitz condition and the one-sided linear growth condition after relaxation. The basic strong convergence theorem is set up and the new notation X(t,x;s) is introduced as an analytic solution of the stochastic differential equation. Establish the assumption that the coefficients of the drift term and the coefficients of the diffusion term of the stochastic differential equation satisfy a contractionary monotonicity condition in order to prove, by induction, that the exact solution of this stochastic differential equation is bounded for a long time. Different examples are given to compare the simulated deviations between the numerical and analytical solutions of Euler’s algorithm and the modified Euler’s algorithm for the initial value problem of fractional order differential equations and to analyze the convergence of the two numerical solutions. The truncated Euler method is applied to highly nonlinear time-transformed stochastic differential equations by means of the dyadic principle, and it is proved that the order of convergence of the strong convergence of the truncated Euler-Maruyama method for time-transformed stochastic differential equations is

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\min \left( {\alpha ,\gamma ,{1 \over 2} - \varepsilon } \right)

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Application of Artificial Intelligence-based Visual Arts Pedagogy in Traditional Painting Education
Authors: Wu Qiang
Published: October 2024

Traditional art has a deep cultural heritage and rich connotation, combining artificial intelligence technology with traditional aesthetics as a way to realize the innovation of traditional painting education mode. In this paper, starting from the performance of traditional painting’s aesthetic value, a personalized intelligent painting teaching mode is constructed based on the visual art teaching method and combined with artificial intelligence. The CCME-GAN model is introduced for the construction of a personalized painting learning generation model, and the BERT-LDA model is established by combining the BERT model and the LDA model for the intelligent evaluation of personalized painting works. Xinjiang folk artworks were selected as the research data source to carry out the validation of personalized painting work generation and assessment, and teaching comparison experiments were designed to analyze the teaching effect of the personalized intelligent teaching mode. The subjective evaluation score of Xinjiang folk art paintings generated by the CCME-GAN model was 9.11, and among the nine clustering results of painting work assessment, the eigenvalues of the theme of painting evaluation of Cluster 1 range between [0,5.5]. At the end of the teaching experiment, students’ creativity scores increased from 2.74±0.37 before the experiment to 4.63±0.26. Relying on artificial intelligence technology can enhance the teaching effect of traditional painting methods and improve students’ painting levels.
Research on Key Technologies and Eco-Innovation Strategies for Digital Transformation of Art Industry
Authors: Chen Liyan
Published: October 2024

The development of digital technology has brought unprecedented opportunities and challenges for the art industry, and seeking transformation and upgrading has become the preferred choice for the development of the art industry in the wave of digitalization that keeps rushing forward. This paper constructs an art design system using image processing technology to provide strong technical support for the core design of the art industry. The method of sparse feature expression and visual communication is used to extract the edge features of artworks, and the chunked feature matching technology is used for spatial sampling of artworks to realize the three-dimensional display of artworks based on virtual reality technology. The application effect of the image processing algorithm used in the art design system of this paper is significantly better than that of the original processing technology and digital signal-based processing technology. At the same time, the feature extraction and matching algorithms in the three-dimensional display of this paper are also significantly better than other algorithms, and the matching and fusion of artworks can realize the effect of high similarity with the original works. Based on the Kano model of display demand research, this paper finally calculated that the SI value is located between 0.1943~0.8120, the DSI value is located between -0.7053~-0.1004, and according to the calculation of the various demand items affecting user satisfaction, which provides a directional guideline for the upgrading and transformation of the display of works of art and the art industry.