bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on the problems and reform strategies of government statistics based on big data technology
Authors: Zhang Xianwei , Zhang Yueyan 
Published: April 2023

Abstract
In the past two years, with the development of big data technology and the revolutionary innovations it has caused within various industries, there has been a boom in the use of big data to transform and optimize government workflow within the field of public administration. In this paper, we build a theoretical framework through government statistics, focusing on the four elements of government statistics. The decision tree algorithm is used to analyze the indicators of the government statistical work problem, mainly from three aspects: grassroots statistical institutions, government revenue, and government forestry construction statistics. The accuracy of the decision tree algorithm is controlled between 83% and 91%, with a variation range value of 8%, which is more accurate than the other two algorithms. The decision tree algorithm helps improve the efficiency and quality of government statistics, thus contributing to the processing of statistical work problems and reform strategies. This study is important for deepening the reform of the Chinese government administration system, improving the construction of a service-oriented government, ensuring the quality of statistical information, and guiding the benign development of statistical work.
A study on the aesthetic characteristics of ethnic music based on radial basis neural network model
Authors: Yang Saiyu , Dai Peng 
Published: April 2023

Abstract
To explore the aesthetic features of folk music, this paper takes the radial basis neural network model as the basis and takes the zither piece “Flowing Water” and “Spring River Flower and Moonlight Night” as the examples, and unearths and analyzes the examples to understand the harmonious beauty, unique beauty and contextual beauty under the aesthetic characteristics. The results show that among the harmonious beauty, the average percentage of the characteristic vocabulary tranquility of the zither piece “Flowing Water” is 80.34% after learning by the radial-based neural network model, and the remaining percentages are 69.56%, 85.35%, 80.27% and 86.30% respectively, which shows that the radial-based neural network-based model can well resolve the characteristic vocabulary in the music through training and learning This shows that the radial basis neural network-based model can, through training and learning, well parse out the characteristic words in the music, and then explore the aesthetic features of the music. From the viewpoint of unique beauty, the musicalization of poetry and the poetization of music have been the main themes from ancient times to the present, with changes of 838% increase and 74.91% decrease, respectively, which also shows that the current degree of our attention to national music is not as much as that of the Tang, Song and Yuan dynasties, and we should strengthen the excavation of national music and create a unique humanistic environment. From the perspective of the beauty of the context, 67.81% of those who listened to “Spring River Moon Night Song” thought that the rhythm and context were full, and 79.48% thought that the theme melody and performance method were eye-catching, but there were still voices of dissatisfaction. Therefore, with the radial basis neural network model, we can intuitively see the aesthetic characteristics of folk music, and we can improve folk music according to its shortcomings so that folk music can be further renewed through a new interpretation.
Analysis of news communication strategies in the era of full media based on big data mining
Authors: Jin Xin , Xu Zihang , Hua Yucheng 
Published: April 2023

Abstract
With the development of information technology, the news media industry has entered the all-media era. Today, everyone is a communicator, and the audience has more diversified channels to obtain news information, but it also leads to the truly useful news being easily overwhelmed. In order to analyze the strategy of news dissemination in the all-media era, this paper analyzes different types of news media platforms and audiences based on big data mining technology. The mining results show that cultural news has the largest share on radio, TV, and video sites, with 27.5% and 57.3%, respectively. Social news had the largest share on news sites, at 29.8%. Political news has the largest share of mobile clients at 27.9%. Economic news has the largest share on social media platforms, with 23.5%. In addition, the news is viewed much more on new media, such as video websites and social platforms, than on traditional media, such as newspapers, magazines, TV and radio. In terms of the exposure rates of different types of news audiences to media platforms, the average exposure rates of newspapers and magazines, TV and radio, news sites, mobile clients, social platforms and video sites are 8.83%, 28.30%, 44.49%, 59.57%, 71.03% and 90.46%, respectively. In the era of full media, news dissemination should focus on applying new communication technologies, enriching the presentation form of news, and selecting reasonable topics for the characteristics of audiences on different platforms. The analysis of news communication strategy based on big data mining can grasp the pain points in current news communication, which is of great guidance for transforming news communication in the era of full media.
Construction of an enterprise financial risk management system based on F-score model
Authors: Ge Xiaomeng 
Published: April 2023

Abstract
With the development of socialist market economy, enterprises are faced with an increasingly complex development environment. In the context of socialist market economy, enterprises can only obtain better development if they continuously promote the improvement of internal control and management system, and effectively carry out financial risk control and management. This paper discusses the procedures and construction measures of the internal control and management system of the enterprise from the requirements and contents of the enterprise financial risk management, using the F-score model. We hope to strengthen the exploration of enterprise financial risk management measures by further improving the enterprise’s internal control system, so as to further enhance the quality of enterprise financial risk management, effectively predict, prevent, control and respond to the relevant financial risks of the enterprise, and build a stable development path for the enterprise.
Research on the operation and management mechanism of cross-border e-commerce shared practice training base
Authors: Meng Wenwen 
Published: April 2023

Abstract
For the third-party cross-border e-commerce sharing platform, due to the lack of management and operation mechanism, the current sharing platform has relatively high fees, insufficient publicity, and consumption methods are not conducive to Chinese consumers. There are obvious problems such as insufficient personnel training. In this article, we use the CGA-LSO-BP network to solve the problems of various systems disjoint, complicated department settings, confusing distribution of powers and responsibilities in the training base, as well as unclear division of team functions, technology mismatch, and the training base itself. The scale, social reputation and other factors lead to the difficulty of reducing financing channels and other related operation and management issues to study and analyze. The results show that the minimum error can reach 0.5% for CGA-LSO-BP, which is much smaller than the traditional algorithm. It is proved that the algorithm can help the BP neural network to jump out of the local optimal value to a certain extent, and play an active role in the regression task. In addition, the improved CGA-LSO-BP neural network based on this can provide a good reference for various problems in cross-border e-commerce, such as disjointed systems, complicated department settings, and chaotic distribution of rights and responsibilities, and propose optimal solutions.
Robust speech recognition based on deep learning for sports game review
Authors: Liu Min , Ying-Hao An , Fa-Li Liang 
Published: April 2023

Abstract
To verify the feasibility of robust speech recognition based on deep learning in sports game review. In this paper, a robust speech recognition model is built based on the generative adversarial network GAN algorithm according to the deep learning model. And the loss function, optimization function and noise reduction front-end are introduced in the model to achieve the optimization of speech extraction features through denoising process to ensure that accurate speech review data can be derived even in the game scene under noisy environment. Finally, the experiments are conducted to verify the four directions of the model algorithm by comparing the speech features MFCC, FBANK and WAVE. The experimental results show that the speech recognition model trained by the GSDNet model algorithm can reach 89% accuracy, 56.24% reduction of auxiliary speech recognition word error rate, 92.61% accuracy of speech feature extraction, about 62.19% reduction of training sample data volume, and 94.75% improvement of speech recognition performance in the speech recognition task under noisy environment. It shows that the robust speech recognition based on deep learning can be applied to sports game reviews, and also can provide accurate voice review information from the noisy sports game scene, and also broaden the application area for deep learning models.
Strategies for constructing mathematical models of nonlinear systems based on multiple linear regression models
Authors: Shao Yongcun , Qin Cong 
Published: April 2023

Abstract
Mathematical systems often have nonlinear, time-varying, time-lagged, and uncertain factors, which affect the experimental prediction accuracy. In order to improve the experimental prediction accuracy, this paper inputs the independent and dependent variable data sets as the original samples into a multiple linear regression function performs fitting calculations to obtain the nonlinear factors, and constructs a mathematical model of nonlinear systems based on a multiple linear regression model. In this model, the expected output value is calculated, and the input vector and output vector are continuously controlled for rolling operations to obtain the prediction results. A mathematical experiment of nonlinear system dynamics of vibration of deep water trap-test pipe system is set up to test the prediction ability of the model. The results show that the nonlinear system mathematical model based on the multiple linear regression model has a very high prediction accuracy. In the mathematical experiments of vibration nonlinear system dynamics of deep water trap-test pipe system, the error of the nonlinear system mathematical model based on multiple linear regression model in the transverse flow vibration frequency of the trap pipe column is 2%, which is lower than the single trap pipe calculation model by 4%. The prediction accuracy of the nonlinear system mathematical model based on the multiple linear regression model is higher than that of the single test tube model calculation by 78%. This shows that the nonlinear system mathematical model based on the multiple linear regression model can improve the experimental prediction accuracy.
A study on the influence of the spread of Yangming Studies in Japan on the psychology of the Japanese people based on big data analysis
Authors: Liu Hongyan 
Published: April 2023

Abstract
The analysis of the psychological impact of the spread of Yangming studies in Japan on the Japanese people is to enable Yangming studies to be better developed in Japan. Based on big data analysis technology, this paper constructs a hybrid data analysis model using the EM algorithm and proposes performance evaluation indexes for the model. Under the EM data analysis model constructed in this paper, the example indicators of the Japanese people’s psychological impact in disseminating Yangming studies by big data analysis are explored, i.e., the psychological acceptability of the dissemination method and the psychological and moral construction impact. Regarding the dissemination method, the Japanese people are more receptive to disseminating Yangming studies in Japan through “learning rules”, with an average percentage of 39.37%. Regarding psychological and moral construction, 90.22% of the Japanese people believe that disseminating Yangming studies can promote self-improvement of value standards and correct self-examination. Based on the big data analysis, we can effectively see from the data the impact of Yangming studies on the audience in the process of dissemination, and improve the scope of Yangming studies dissemination according to the data feedback, so that more people can recognize the idea of unity of knowledge and action.
Modeling Analysis of User Consumption Data of Internet Culture Industry in the Context of Emerging Technologies
Authors: Cao Fei 
Published: April 2023

Abstract
In the context of the prosperity of the Internet economy and the progress of the cultural industry, the Internet cultural industry is expanding in a big way based on the economic development of the cultural industry, supported by the Internet technology platform and serving the cultural and spiritual experience of consumers. The Internet cultural industry is gradually becoming the backbone of the country’s comprehensive strength for the amount. The Internet to boost the development of China’s cultural industry and cultural export to the outside has become a general trend. In 2018 China’s Internet cultural industry added value accounted for the first time exceeded 3 trillion of GDP, and the added value of the Internet cultural industry in 2021 further increased to 6.63% of GDP. Thus, it can be seen that the share of Wen Internet culture industry in China’s GDP is a steady upward trend and the future development is clear. This paper uses the vector autoregressive model to model and analyze the cultural consumption data of Internet users, and the analysis results show that in 2021, China’s Internet cultural consumption mainly tends to music and video, games, literature, animation, and online cultural content information services in five areas, among which games account for 36.52% of the total Internet cultural consumption. Due to the improvement of China’s comprehensive strength, the difference in CPI of Internet culture consumption between urban and rural groups in China is 11, and the gap is gradually narrowing, and the countryside will be a big new market in the future. The Internet group culture user group as a whole tends to be younger, with the student group accounting for 26% of the user group. Based on the analysis of this study, it is concluded that Internet cultural consumption tends to be young, cultural innovation is the main driving force to promote consumption, and future development is unstoppable.
Application of digital technology in environmental art design
Authors: Xu Xuanyin 
Published: April 2023

Abstract
In recent years, digital technology has rapidly penetrated various industries and brought various opportunities for developing these industries. Based on two digital technologies, BP neural network and the Gray Wolf algorithm, this article analyzes the application of digital technology in environmental art design at Xi’an Eurasian National University, taking environmental art design as an example. The article uses these two algorithms to analyze the site and design principles of the campus, followed by detailed design and consideration of the campus environment design, mainly from greenery design, groundscape and road pavement design, and campus landscape lighting design. The analysis of the collected data in this paper shows that students’ satisfaction with the central teaching area is generally low, at around 20%, and the satisfaction with the northwest teaching area is the highest, all above 40%, up to 61%. The students’ satisfaction with the plant landscape on the campus was generally at a medium level. However, the satisfaction level for loblolly pine is not very high, and overall is around 30%, while the satisfaction level for the cedar is high, and everyone’s satisfaction is higher than 60%. Therefore, this paper takes the students’ satisfaction with the campus landscape environment into consideration in the landscape design, which is conducive to achieving the perfect integration of landscape art design and ecological environment and achieving the realistic goal of both aesthetic and environmental protection.
Digital Regeneration and Database Construction of Hunan Embroidery Needlework under the Perspective of Artificial Intelligence
Authors: Sun Shunyao , Tang Yuxuan , Wang Wei , Xiao Ying 
Published: April 2023

Abstract
In order to explore the development path of Hunan embroidery under the vision of artificial intelligence, promote the digital regeneration and database construction of Hunan embroidery stitches, the communication, and interaction between Hunan embroidery brands and the public, and create more possibilities for revitalizing the culture and industrial development of non-heritage Hunan embroidery. In this paper, a mechanics model of Hunan embroidery stitch is established based on the finite element idea under the view of artificial intelligence. The single yarn in the yarn is regarded as a frictionless articulation of some rows of elastic rods with a circular cross-section. The elastic rod can only be subjected to axial force without a moment, and it is a uniform, continuous, and completely elastic isotropic body. Using the displacement method, the displacement of the unit node is taken as the basic unknown quantity, the displacement in the unit is assumed to be linearly distributed, and the displacement of any node in the unit is obtained by linear interpolation. The strain, stress, and stiffness matrices of the elastic rod unit are derived, the equilibrium equations are given, and a database is established. The results of the study showed that consumers of all age levels thought that the patterns representing Hunan embroidery mainly include Hunan characteristic landscapes, portraits of Hunan great men, traditional flowers, birds and animals, and totems of Chu culture, etc., among which Hunan characteristic landscape accounted for 54% of the largest proportion. It provides a development direction for the inheritance and protection of Hunan embroidery skills.
Research on the practice of innovation and entrepreneurship education in universities under the environment of big data
Authors: Wang Haijun 
Published: April 2023

Abstract
Entrepreneurship education is an educational concept and teaching mode which is formed in socio-economic development. Universal entrepreneurship education has both the long-term value of realizing the transformation and upgrading of industrial structure and the practical value of alleviating the employment problem of college students. Therefore, how establishing the innovation and entrepreneurship education model in higher education under the environment of big data analysis is a major issue at present and also a key element to achieving the construction goal of modern higher education. In this paper, the entrepreneurship data of colleges and universities are deeply mined by association rules of the Apriori algorithm and clustering analysis of the FCM algorithm. As a result, an entrepreneurship education model is established and practiced in university classrooms. According to the results of the survey after the practice of the entrepreneurship education model, it can be seen that the number of students’ participation in innovation and entrepreneurship lectures has increased, and the proportion reached 50%. Innovation and entrepreneurship clubs formed on campus and discipline competitions accounted for 16.00% and 18.00%, respectively. College students’ motivations for learning innovation and entrepreneurship education courses are mainly ability enhancement, interest-driven, credit demand, future planning, and influence of others, and they account for 34.00%, 26.00%, 21.00%, 14.00%, and 5.00%, in that order. These indicate that the current group of college students considers the pursuit of knowledge and the improvement of their abilities as the main reasons for undertaking entrepreneurial learning activities. After practicing the entrepreneurship education model, people have increased their knowledge of entrepreneurship theory and are more willing to participate in various entrepreneurial activities.
Research on the innovation of model based on the cultivation of talents in higher vocational art and design
Authors: Liu Junhua 
Published: April 2023

Abstract
Art and design are creative activities humans engage in to achieve certain purposes. The multiple characteristics of art and design also put forward more requirements for developing higher education art and design education. In this paper, starting from the problem that the multiple characteristics of art and design make it difficult to evaluate the teaching quality, the FAHP-FCE evaluation system is proposed to score the quality of art and design talents training. Firstly, fuzzy hierarchical analysis (FAHP) is used to construct a judgment matrix to filter out evaluation indexes. Secondly, multi-level fuzzy comprehensive evaluation (FCE) is used to evaluate the evaluation indexes to obtain the score. Finally, conclusions were drawn by comparing the effectiveness of the two teaching models. The research results show that the effectiveness of the FAHP-FCE evaluation system-based art and design talent training teaching model is assessed as 83.47 points, which is 34.11% more effective, 23% more design ability, 31% more learning ability and 26% more hands-on ability than the traditional teaching model. The talent cultivation model in this paper enables students to master abstract design ability, helps to expand the field of creative thinking, enriches the language of modeling and artistic imagination, and improves comprehensive design ability and learning ability.
MATLAB-based simulation of industrial robots in water environment monitoring
Authors: Si Guobin , Jin Ying , Jin Xiaofeng 
Published: April 2023

Abstract
The use of industrial robots based on MATLAB simulation for water environment monitoring is to monitor the water environment better, improve monitoring efficiency and reduce monitoring costs. The robot can better collect data and can engage in deeper water-specific information. In this paper, based on the discussion of the water environment monitoring robots used in countries around the world for water environment monitoring, we introduce a MATLAB-based simulation of industrial robots in a wide range of water environments to simulate the autonomous data acquisition system. The main advantages are: compared with other robots, it can realize the “wide range” of water environment data collection; compared with fixed buoys, it can realize the “autonomous” collection of water environment monitoring data and gives the autonomous collection process and hierarchical software progression. The autonomous acquisition process and hierarchical software architecture are presented. The simulation results analysis shows no difference between the simulated data and the predicted data from the historical data using MATLAB-based industrial robots for water environment monitoring. This shows that the development of industrial robot simulation in water environment monitoring is promising and feasible.