bluuebunny/crossref_metadata_2025_split huggingface dataset:
Reflections on Rhythm Control in the Stage Performance Process of Dancers
Authors: Zhong Shu 
Published: June 2024

Abstract
The article proposes a dance score generation model based on the graph attention model and Transformer, which first preprocesses the stage motion capture data of dancers, utilizes a multi-scale attention network to realize motion feature aggregation, and introduces the gated loop unit in the Transformer model to enhance the recognition accuracy of dance movements. Based on the recognition of the dancer’s stage movements, the skeleton size normalization is performed on the joints of the dancer’s gestures, and the skeleton replacement method is combined to realize the correction of the dance movements. Next, we test the model’s dance score generation effect, the matching accuracy of dance movements and music rhythm, and evaluate and analyze the quality of dance movement correction. The results show that the Former model in this paper scores 8.33% higher in beat consistency than the traditional dance generation model Bailando, and the matching coefficient of the rhythmic intensity of the generated dance is basically the same as that of the original dance, with a difference of only 0.02-0.06. It shows that the rhythmic control of the stage performance of dancers carried out by the Transformer model can enhance the stage performance power of dancers and strengthen their stage performance. It shows that using the Transformer model to control the rhythm of dancers’ stage performances can improve the stage performance of dancers and enhance the viewability of stage performances.
Artificial Intelligence Technology Enabling the Construction of Employment Nurturing System in Colleges and Universities
Authors: Zhou Fengjin 
Published: June 2024

Abstract
Employment forms the cornerstone of societal welfare. Within the rapidly evolving landscape of artificial intelligence technology, the challenge for higher education institutions is to leverage these advancements to forge a robust employment and educational framework. This study integrates personalized recommendation algorithms to address the prevalent issue of accuracy deficits in the employment education systems of colleges and universities. Utilizing both content-based and collaborative filtering algorithms predicated on latent factor decomposition, this approach enables the precise tailoring of job recommendations that align closely with individual student preferences. This targeted recommendation process not only enhances the quality of student employment outcomes but also addresses the enduring challenge of sustaining effectiveness in the employment education systems within academic institutions. Furthermore, this paper examines the contributory factors to the efficacy of these systems through the structural equation modeling (SEM) of student satisfaction with university employment education systems. The analysis reveals that in the perceived quality of these systems, as assessed by the SEM, the factor loading for the precision of employment recommendation approaches reaches a value of one. This underscores the critical importance of aligning job recommendations with the student’s circumstances and preferences, highlighting it as a central concern among students.
Research on the Integration and Development of Intangible Cultural Heritage and Tourism Management Industry in the Context of Digitization
Authors: Zhou Wei 
Published: June 2024

Abstract
This study employs the entropy power method to disaggregate the development potential of intangible cultural tourism resources in Area Z, further analyzing these resources via the RMP model. This model comprehensively evaluates the quantity and categorical structure of Area Z’s intangible tourism resources. Additionally, this research explores the dynamics of intangible tourism product design, focusing on the interplay between intangible tourism resources and products, herein referred to as the R-P relationship. The Herfindahl index serves as the primary analytical tool in this paper to assess and quantify the degree of integration between the tourism and cultural industries in Area Z. The findings reveal that the most significant developmental potential lies in the appeal of non-heritage resources and products, which score 50.8 in terms of development value. Intangible tourism resources in Area Z are abundant and diverse, with skill-based resources constituting 50% of the total. From 2014 to 2023, tourism revenue in Area Z surged from 28.046 billion yuan to 69.915 billion yuan, indicating substantial market potential. The design of non-heritage tourism products should, therefore, prioritize items with significant collectible and cultural heritage value. The integration index between the cultural industry and the tourism management industry in Area Z is measured at HI=0.6058, while the core product index for non-heritage and tourism stands at HI=0.2604. This paper underscores the critical role of strategic resource allocation and product design in maximizing the economic impact and cultural preservation of intangible tourism resources.
The Innovative Path of Patriotism Education for College Students in the New Era under the Environment of Intelligent Education
Authors: Li Anqi 
Published: June 2024

Abstract
This paper combines modern information technology with the design of mobile Internet smart classrooms and its realization. Using the structural equation model to summarize and refine the key elements of college smart patriotic teaching, the college smart patriotic teaching practice model is proposed, and the quantitative information of each influence path is explored through empirical evidence. After analysis, it can be seen that in the first and second standardized regression coefficient tests, the path coefficient of the wisdom patriotic teaching method on the environment of wisdom patriotic teaching in colleges and universities is 1.138, P=0.262. In addition to this, the other nine influence path hypotheses passed the significance test (P<0.05). In terms of the path coefficient of each path, the highest value reaches 0.58, and the lowest value to -0.14, revealing that the main development of college students’ patriotism is also affected by the diversified and rich influence of various other complex factors. The wisdom patriotic teaching model is highly rated by college students and has a significant difference in satisfaction between different academic degrees (P=0.008). Data support for the innovative path of patriotic education in a smart environment is provided by the findings of this paper.
Study on the Development Trends and Strategies of International Economy and Trade under the New Situation
Authors: Zhai Yu , Song Meijing 
Published: June 2024

Abstract
In today’s increasingly globalized world, trade between countries has become more interconnected, and international trade has emerged as the primary driver of economic development for all nations. This paper proposes a standard trade model for the new situation using the Dixit-Stiglitz model. Starting from the consumer’s point of view, the two-stage maximum method is adopted. Using the Lagrange function, the demand utility function of consumer preferences is processed, and the model optimization scheme is deduced. The ARMA model is used to predict the volume of merchandise foreign trade, and the prediction range includes autoregressive and moving average processes. The indicators are used to evaluate the smoothness of the series within the sample period. A suitable sample of international trade data is selected. The results of the analysis are as follows: in the logistic autoregressive analysis test, the significance of all factors, except for the language and religion factors, passes the significance test of 0.001, and at the same time, the model goodness-of-fit is greater than 0.1, ranging from 0.115 to 0.175. In the analysis of the spatial evolution pattern of international economic trade and trade dynamic development, the spatial Gini coefficients of the first category of goods in 2000, 2014, and 2019 and the third category in 2000 are 0.4306, 0.4717, 0.4956, and 0.4673, respectively, which are lower than 0.5, showing a more balanced evolution pattern.
Modeling Student Management and Civic Education Strategies from an Interdisciplinary Perspective
Authors: Zhao Xinying , Zhang Chengming , Wang Zisong , Yu Shuaiyi 
Published: June 2024

Abstract
This paper issues from an interdisciplinary perspective, combining computer technology, principles of management and other multi-disciplinary knowledge to build a model of student management and civic education strategy. Two modules are part of the student management model: student behavior analysis and prediction. In student behavior analysis, the fuzzy C-means clustering algorithm is improved, and the Gaussian density function is used to determine the initial clustering center. In student behavior prediction, the convolutional network is used to input raw data, and the extracted features are inputted into the CABLSTM model for training and prediction of student behavior. The Civic Education Strategy Model is built on the principle of feedback control and is constructed at the school, family, and individual levels. In the analysis of student management and Civic and Political Education practice, teaching practice was conducted at University C in Lanzhou City, Gansu Province, China. After the practice, the number of students who are very satisfied and satisfied with the overall student management is 2, 356, accounting for 65.81%, and the comprehensive quality of students is in the middle to high range. The students’ life values, family and national sentiment, and thought level dimensions in Civic and political literacy have significant differences (P<0.05), and the level of mastery of Civic and political knowledge is good.
The impact of digital trade rule networks on the advancement of global value chains in the Internet era
Authors: Wang Jingbu , Chu Xiwei 
Published: June 2024

Abstract
In the context of the digital era, global value chains are facing unprecedented reconstruction and upgrading. The development of global trade is influenced by the importance of digital trade in upgrading the status of global value chains. Based on the research of digital trade and global value chain theory, we construct a mechanism model of digital trade to enhance the status of the global value chain and measure digital trade and global value chain by combining the multi-indicator panel hierarchical factor analysis method and the trade value-added accounting method, respectively. Benchmark regression analysis of digital trade and global value chain status indices of major economies is used to explore the impact of digital trade on the status of global value chains. There is a positive correlation between the level of digital trade and the GVC status index, with the GVC status index increasing by 1.6 percentage points for every 1 percentage point increase in the level of digital trade. The level of digital trade has a positive impact on the GVC position of both developed and developing economies. For every 1% increase in the level of digital trade, the GVC position index of developed and developing economies increases by 2.5% and 1.7%, respectively.
A Study of Output Vocabulary Knowledge in the English Writing Process
Authors: Ning Yan 
Published: June 2024

Abstract
Vocabulary acquisition is pivotal in enhancing English writing proficiency. Effective integration of output vocabulary into written English is essential for improving students’ compositional skills. This study proposes a methodology for extracting vocabulary from English textual materials and subsequently applying it to student writing endeavors. To ensure the integrity and accuracy of the text materials utilized, this research employs a Long Short-Term Memory (LSTM) algorithm to perform a comprehensive spelling check on the English writing corpus prior to vocabulary extraction. Further, this paper adopts the high-frequency word list and Term Frequency-Inverse Document Frequency (TF-IDF) techniques to identify and evaluate the significance of vocabulary within the texts. Key vocabulary that significantly impacts word importance classification is preliminarily identified using the Graph Convolutional Network-K Nearest Neighbor (GCKN) algorithm. These pivotal words, termed ‘key nodes, ’ form the basis for constructing a network within the English texts. Utilizing the message-passing mechanism, information from associated nodes is aggregated at the central node, facilitating the acquisition of output vocabulary. The study findings indicate that students, after learning and applying the acquired vocabulary, demonstrate considerable improvements in their English writing capabilities. They exhibit a broader and more sophisticated use of vocabulary, leading to marked enhancements in their writing performance and overall English proficiency.
Research on Enterprise Management Process Reengineering Strategies for Integrating Innovation Ecosystems in the Age of Artificial Intelligence
Authors: Huang Yamin 
Published: June 2024

Abstract
Innovation is the inexhaustible driving force for an enterprise to realize sustainable development, and enterprise management process reengineering within the innovation ecosystem is the key know-how for the growth of enterprise benefits. This paper focuses on the realization of enterprise management process reengineering within the innovation ecosystem. The study starts with the construction of an embedded innovation ecosystem model, and it is then analyzed for threshold effects. The hexadecimal structure of fuzzy Petri nets is used to establish a diagnostic model of enterprise management processes, and problems in enterprise management processes are supervised through fault tree analysis so as to improve and optimize the management processes and process reengineering of the enterprise. The research on enterprise management process reengineering in this paper employs F-cluster analysis and fuzzy C-mean cluster analysis to fully demonstrate the relationship between the activities of every management process in the enterprise. Through the study, it is concluded that the open innovation and shared cognitive capital variables designed in this paper in constructing the embedded innovation ecosystem model have successfully passed the reliability and validity test and play an important role in enterprise innovation. In the case study of enterprise management process reengineering, the management process of enterprise A that implemented process reengineering realized intelligent transformation. The resulting total share of production cost of enterprise A decreased to 91.2%, and the overall cost of energy saving was about 10% or so.
Study on the Development Trend of Ideological and Political Education Discourse in Colleges and Universities in the Age of Network Media
Authors: Qiu Wenting 
Published: June 2024

Abstract
Network virtual information is complex and ever-changing, and people’s value orientation and way of thinking are unknowingly assimilated into multiple network scenarios. In order to fully analyze the discourse evolution of ideological and political education, this paper proposes a methodology for early warning and assessment of public opinion on the Internet in colleges and universities. Firstly, the risk assessment index system for university network public opinion is constructed, and different types of events related to university network public opinion are selected for analysis. The risk assessment index weights are calculated using the entropy weight method. The closeness was computed using the TOPSIS method, and the gray correlation coefficient and degree were calculated according to the gray correlation theory. The risk assessment level is classified using the k-means clustering algorithm. Among the risk assessment indexes of university online public opinion, the most influential index on the risk of university online public opinion is the amount of original participation of public opinion, and the weight of this index is 0.12. The second index is the attention of the public opinion publisher and the index of the publisher’s attention, and the weights are 0.114 and 0.11, respectively. Among the six university online public opinion events, the closeness is the highest one of event 6, which is 0.5872, and the grey correlation coefficients are 0.4395, 0.4072, 0.4952, 0.3864, 0.5321, and 0.6412. The results of the events evaluated through the college’s online public opinion early warning match the degree of influence of the actual public opinion, which indicates that the method can accurately predict public opinion. Colleges and universities can formulate targeted strategies according to the risk level and the factors that have an important impact on the development of public opinion to prevent the discourse of ideological education in colleges and universities from developing in a negative direction.
Research on the Innovative Model of Artificial Intelligence Technology Facilitating Sports Management in Colleges and Universities
Authors: Yan Bingcai , Xing Xuanshuo 
Published: June 2024

Abstract
The challenge of managing information in collegiate physical education has progressively escalated, thereby amplifying the complexities inherent in the sports management domains at higher education institutions. The advent of artificial intelligence technology heralds a promising avenue for the evolution of sports management frameworks within these settings. This study delineates the development of a specialized cloud platform tailored for the management of collegiate sports, encompassing aspects such as teaching and research management, quality assurance in education, general teaching affairs, practical instruction, and support for auxiliary teaching processes. This platform is engineered using the OpenStack cloud architecture, and it meticulously explores advanced scheduling algorithms for virtual machines to enhance platform efficiency. Systematic testing of the platform reveals critical performance metrics; notably, prior to optimization, the CPU utilization of the educational system spikes to 100% with a Time to First Byte (TTFB) reaching indefinite timeouts when concurrent accesses surpass 9, 000, leading to a system shutdown and cessation of service availability. Post-optimization, the platform robustly sustains business accessibility even under similar stress conditions. Furthermore, the empirical usage data of the sports management systems indicate predominant utilization for fulfilling work-related needs (0.796), psychological requirements (0.74), and the pursuit of enhanced operational efficiency (0.732).
Traditional Cultural and Creative Product Design Methods Combining Digital Art Elements
Authors: Xu Xiaoqing , Chen Jingxin 
Published: June 2024

Abstract
As a mode of perpetuating and revitalizing traditional culture, cultural and creative products have garnered widespread affection and recognition from the public. In the context of evolving societal trends and advancements in science and technology, the digitization of traditional cultural and creative products has emerged as a prominent trend. This study undertakes the digital design of these products, primarily focusing on the innovative application of a style transfer algorithm to traditional motifs, supplemented by their visualization through digital platforms such as augmented reality (AR) and virtual reality (VR). Furthermore, it facilitates intelligent consumer interaction via gesture recognition algorithms, thereby enhancing user engagement and experience. During the implementation phase, this research conducts comparative analyses of style transfer and gesture recognition within digital cultural and creative products. It also employs the Kano questionnaire to categorize and analyze user needs effectively. Notably, while the recall rate of the style transfer algorithm documented in this study remains below 0.9, it consistently achieves high precision, significantly enhances feature extraction capabilities, and improves the quality of the style transfer effects produced. Moreover, the static gesture recognition algorithm achieves an impressive average recognition rate of 98.2%. The dynamic gesture recognition algorithm, meanwhile, maintains an average recognition rate of 94% with a processing time of 3.2 seconds, balancing the demands of real-time interaction and accuracy effectively. This study systematically analyzes the significance of each requirement element across six dimensions, classifying customer needs for digital cultural and creative products into four distinct categories. Additionally, it delineates a viable pathway for the integration of digital art elements into the design of artistic and innovative products, setting a foundation for future innovations in this field.
Research on the Application of Deep Learning Algorithm Based Design Technology in Lacquer Art Teaching
Authors: Yang Xionghui , Fan Hui , Zhou Linzhi 
Published: June 2024

Abstract
In the era of big data, analyzing students’ classroom behavioral status is an effective means of enhancing teaching quality and performance. This paper proposes algorithmic research on student behavior recognition and detection, researches the related algorithms of convolutional neural network’s target detection, further improves the student behavior recognition algorithm of YOLOv5, and tests the optimization program of lacquer art teaching as a real-world test research in terms of students’ behaviors and teaching effects. After using the behavior recognition algorithm proposed in this paper, the students achieved certain results in the creative learning of lacquer artworks. The student’s final grades in lacquer art have a good improvement; the mean value of the final grades of the experimental class is 89.43, the mean value of the final grades of the control class is 85.32, and the mean value of the final grades of the experimental class is higher than that of the control class by 4.11. It can be concluded that the use of learning behavioral recognition algorithms in the teaching of lacquer art has a good effect on enhancement.
An analysis of the cultivating mode and its existing problems of university-enterprise cooperation for engineering majors in college in the information technology age
Authors: Liu Lingna 
Published: June 2024

Abstract
School-enterprise cooperation in talent cultivation enhances the quality of talent training, enriches and updates enterprise production resources, and promotes stable and healthy societal development. This paper, after reviewing relevant research materials, designs an evaluation index system for the university-enterprise cooperation talent training model for engineering majors in colleges and universities and employs the combination assignment method to calculate the weight value of each index. The comprehensive evaluation index method is used to assess the development level of the university-enterprise cooperation talent cultivation model. The cluster analysis is conducted for each college and university according to their measurement levels. The study results show that colleges and universities are classified into four types. Type A colleges and universities have the highest level of talent cultivation, though they only constitute 7.14% of the total. Type D colleges and universities are the least advanced in developing the school-enterprise cooperation talent cultivation model for engineering majors, with a score of 2.14 points. The correlation between the proportion of schools uniformly equipped with teachers’ terminals (0.493) and the development level of the university-enterprise cooperation talent cultivation model is the strongest. The optimization suggestions presented in this paper, in response to the research findings, provide an innovative and breakthrough direction for the university-enterprise cooperation talent cultivation model in colleges and universities.