bluuebunny/crossref_metadata_2025_split huggingface dataset:
Artificial Intelligence Technology Drives Intelligent Transformation of Music Education
Authors: Hou Chunbo 
Published: July 2024

Abstract
With the development of music education and artificial intelligence technology, it is increasingly common to assist teaching with the help of artificial intelligence technology in music education at present. This paper analyzes the role of intelligent transformation in music teaching, discusses its necessity, and proposes the direction of constructing an intelligent music teaching system accordingly. In the construction of the intelligent music teaching system, the short-time autocorrelation function method, the average amplitude difference function method, the inverted spectrum method, and the median smoothing and linear smoothing algorithms in the fundamental tone smoothing algorithm are introduced in the audio feature extraction algorithm. With the RBF algorithm as the core of the system design, the layers of the neural network structure are sequentially attributed to the implicit layer, the input layer, and the output layer to construct the RBF model for students to learn music knowledge. Taking first-year students majoring in music at Z University in Jiangsu province as research subjects, the use of an intelligent music teaching system is being carried out in teaching practice. The students’ sound sense and music sense improved by 15.33 and 14.25 compared to the pre-practice period, showing significant differences (P<0.05). A highly significant difference (P<0.01) was demonstrated in all dimensions of music literacy.
Exploration of Sports Film and Television Art and Youth Cultural Literacy in the Internet Era
Authors: Huang Qian 
Published: July 2024

Abstract
This paper starts from the connotation of the definition of sports, film art and youth cultural literacy, and after determining the corresponding independent variables and dependent variables, the quantile regression model is constructed using the least squares method. The research data is collected, and examples analyze the constructed regression model. The results showed that the multivariate correlation coefficient between the four performance types of sports film and television art and adolescent cultural awareness was 0.265, and the F-value of the overall test was 19.548 (P<0.001). In addition, documentaries (B=0.349, S.E=0.111, p=0.001) and variety shows (B=0.249, S.E=0.028, p<0.001,) had a significant positive predictive effect on adolescents’ cultural awareness, whereas sports event indicators (B=0.227, S.E=0.078, p=0.125,) and film and television dramas (B=0.259, S.E=0.056, p=0.244) have no significant correlation effect on adolescents’ cultural awareness. In conclusion, based on the results of regression analysis, it is revealed that film and television art have a relationship with the cultural literacy of adolescents, which facilitates the formation and development of cultural literacy.
A Study of the Impact of Internet Technology on Minority Languages and Cultures
Authors: Jia Furui 
Published: July 2024

Abstract
Network technology influences and transforms the language use, environment, and cultural practices of ethnic minorities. This paper designs a text classification model for minority languages and cultures, utilizing BERT for word vector modeling, and introduces LSTM and attention mechanisms to capture distant semantic information, solve the gradient vanishing problem, and learn contextual details. The BiLSTM multi-head attention mechanism is then used to filter important semantic features of the input sequence, and finally, all extracted features are linked to complete the text classification and output the categories of minority language and culture texts. The model is applied to text datasets from ethnic minority forums and their news video datasets. It is found that the proportion of traditional ethnic minority vocabulary in forums decreased from 14.6% in 2004 to 10.7% in 2024. Conversely, the ratios of vocabulary related to consumption, marriage, employment, and education increased, with the ratio of marriage-related vocabulary rising from 0.33 to 0.94. This suggests that, despite the influence of Internet technology, traditional cultural concepts of marriage among ethnic minorities remain widely observed. This study provides a feasible solution for categorizing texts in minority languages and offers a unique reflection on the influence of the Internet on the cultural changes of minority languages.
Contingent and Actual: The Realistic Dilemma and Path Reconstruction of “Dual Tutoring System” in Master of Education
Authors: Wu Dongcun , Li Huiwen 
Published: July 2024

Abstract
The dual tutorial system is a new educational model that involves two tutors, one from on-campus and one from off-campus, participating in the entire cultivation process of graduate students. Since the adoption of the dual tutor system in education to jointly cultivate professional degree students, it has achieved good results, but it has also created many problems. In this paper, we firstly clarified the reality of the dual tutor system of master of education through visiting and investigation, and then designed a questionnaire to investigate the understanding of master of education students about the dual tutor system, the guidance of internal and external tutors, and the communication between students and tutors, in order to understand the communication between master of education students and tutors. Then, we designed a questionnaire to understand the implementation status of the “dual tutoring system” of a master’s degree in education by investigating the understanding of the “dual tutoring system”, the guidance of internal and external tutors, and the communication between students and tutors. Finally, this paper puts forward the reform path of the “dual tutorial system” for masters of education. The results of the survey show that more than 70% of education master’s degree students support the “dual tutor system”, but nearly half of the students do not understand the specific content of the “dual tutor system”, internal and external tutors have basically accomplished their duties, and the student’s willingness to communicate with their tutors is not high overall. Suppose the reform path proposed in this paper can be realized in the actual operation of a “dual tutoring system” for a master of education. In that case, it can have a significant positive impact on the cultivation of a master of education.
Application of fuzzy neural network algorithm in the analysis of learning behavior of university users
Authors: Li Huishu , Ren Juanhui , Ren Bo 
Published: July 2024

Abstract
The rapid development of Internet technology and education informatization has accelerated people’s learning and changed their way of thinking and cognition. Colleges and universities have set up their cloud classroom learning platforms, and the mining and analysis of the platform’s learning data is, therefore, particularly important. In this study, the SOFM-based FCM algorithm is used to perform fuzzy clustering of user subjects with different learning behaviors, and then the FDMA algorithm is used to mine the association rules of users’ learning behaviors, and the fuzzy neural network algorithm is also used to predict the learning performance to achieve the fuzzy neural network algorithm based on the fuzzy neural network algorithm to analyze the learning behaviors of users in colleges and universities. On this basis, we are developing and implementing a system to monitor the learning behavior of college users to explore its practical value. Based on different user behaviors, college student users are divided into three categories: high motivation to study (29.8%), medium motivation to study (46.2%), and low motivation to study (24.0%). The confidence level of the mined fuzzy association rules takes the range of [0.84, 0.95], which has a high confidence level. The academic performance prediction model had an average relative error of 0.0278 and 0.0281, with better model fitting and higher accuracy of prediction. The success rate of user access to the system is high, and the system has been well-tested. This study provides a reference for the application of fuzzy neural network algorithms in the analysis of user learning behavior in universities.
Research and optimization of cross-border e-commerce marketing mode based on big data technology
Authors: Jiang Yuanyuan , Li Long 
Published: July 2024

Abstract
The development of mobile Internet promotes the updating of cross-border e-commerce models, and the precision marketing realized by relying on big data technology better meets the all-around demand of users for content, socialization, and transactions. The article establishes a cross-border e-commerce marketing process on the basis of STP marketing management and builds a cross-border e-commerce precision marketing model by combining the STP marketing model. The user behavior characteristics of cross-border e-commerce users are extracted based on the RFM model, and the user behavior model is established by combining the user’s interest in purchasing goods. Then, the K-Means clustering algorithm is used to process the subgroups of cross-border e-commerce customer samples so as to construct a precise portrait of users. The cross-border e-commerce enterprise Z is selected as the research object, and the impact of precision marketing strategy on its user growth, merchandise sales, click-to-purchase conversion rate, and marketing optimization effect is analyzed. The number of effective users grew from 10,516 in 2020 to 16,804 in 2022, and the click-to-purchase conversion rate of products improved by 20%~46%, and different types of customers have various degrees of improvement under the precision marketing strategy. Based on big data technology, cross-border e-commerce users can be accurately portrayed, marketing products can be provided to users with more accuracy, and cross-border e-commerce enterprises can effectively enhance their marketing capabilities.
Constructing the Teaching Classroom for Japanese Language Majors in Colleges and Universities from the Perspective of New Liberal Arts
Authors: Li Yanfen 
Published: July 2024

Abstract
The Japanese language major, a subset of foreign language disciplines at higher education institutions, is the focus of this study, which advocates a novel instructional pathway based on the new liberal arts perspective. This paper introduces the BRD teaching model for Japanese language majors in colleges and universities, detailing a six-faceted approach: task assignment, preparation stage, lecture delivery, report writing, report submission, and teacher grading. An evaluation system was established to measure students’ engagement and assess the effectiveness of the BRD model in Japanese language education. According to our findings, all students perceived the BRD method as beneficial for mastering politeness strategies, although only 4.75% found it marginally less effective for acquiring agreement and pleasantries strategies. Comparative experimental analysis revealed that students in experimental class C, under identical academic conditions, not only mastered polite language strategies as effectively as their peers but also achieved significantly higher average final grades compared to those in the traditional class B. The statistical significance of these outcomes, with a p-value of less than 0.05, underscores the efficacy of the proposed BRD teaching model in enhancing students’ proficiency in Japanese.
Research on Reconstruction of Practical Training System of Big Data and Accounting Professional Group Based on Virtual Simulation Technology
Authors: Li Ying , Li Junmei 
Published: July 2024

Abstract
This paper combines the synergistic development logic of the accounting professional group, modeling the virtual simulation accounting professional group practical training scene through 3DMAX software, followed by particle swarm algorithms for scheduling the practical training resources, accountants into the virtual workplace roles through the system guidelines to complete the practical training tasks, and solving the target position so as to realize the human-computer interaction. The results of the application of the practical training system in actual teaching show that the unemployment of accounting practitioners in 2023 is as high as 12.71%, and the high unemployment rate pushes the accounting profession to reform in the direction of virtual simulation and real training. In four system delay experiments, the practical training system generally has shorter delays and better performance compared to the traditional method. The virtual simulation training system has a significant effect on the student’s academic performance, especially the practical performance, learning attitude, and accounting literacy (Sig<0.05), and improves the theoretical knowledge and practical hands-on ability to account majors.60.7%-66.94% of the students are satisfied with the virtual simulation training system. The practical training system in this paper has obvious advantages, as shown.
Research on Collaborative Filtering Algorithm Based on Hadoop Architecture for Matrix Dimension Reduction in E-commerce Environment
Authors: Liang Bing 
Published: July 2024

Abstract
The rapid popularization and expansion of the Internet have catalyzed the growth of diverse e-commerce platforms. To mitigate information overload and enhance consumer shopping experiences, recommender systems have been developed. Our proposed algorithm, grounded in the Hadoop architecture, employs a refined cosine similarity method to calculate the average distance between users and rated items. This method involves the application of the Singular Value Decomposition (SVD) model to reduce the dimensionality of the user-item rating matrix, facilitating the extraction of item feature vectors. Subsequently, these vectors are clustered and segmented using the Matrix Factorization (MF) algorithm, addressing the challenge of data sparsity effectively. Experimental evaluations demonstrate that our enhanced algorithm outperforms five conventional collaborative filtering recommendation algorithms across varying matrix densities (from 0.05 to 0.25) on a public dataset. This results in a significant reduction in prediction error, thereby offering users more precise item recommendations.
Incorporating Textual Analysis for Genre Measurement of Narrative Discourse in Business English
Authors: Lin Mei 
Published: July 2024

Abstract
In recent years, business English narrative genre research has been characterized by ambiguous concepts, insufficient theoretical basis, and single-genre features, which have weakened the reliability of research conclusions. Accordingly, this paper examines the representative genre of business English narrative, “management discussion and analysis report”, and explores its genre characteristics and its mapping relationship with corporate performance. The measurement framework is based on the discourse level, genre level, professional practice level, and professional culture level and builds a textual analysis path. In order to observe the lexico-grammatical features highlighted in the four levels of discourse, this paper designs the linguistic feature extraction process and the keyword information extraction method involved in the process. This paper improves the LDA model by introducing the emotional information factor, and improves the keyword extraction algorithm in the model based on information theory. According to the designed method for extracting linguistic features, the representative genre text is analyzed in terms of intonation. Through empirical analysis, it is found that the positive tone and negative tone of the retrospective part of the text of the representative genre are correlated with the current year’s performance of the enterprise at a significant level of 1%, and the positive tone is positively correlated with the current year’s performance, while the negative tone is negatively correlated with the current year’s performance. The positive and negative tone of the outlook texts is not significantly related to the performance of enterprises in the next year. The association of genre characteristics with the current year’s performance of the enterprise is evident but not with the next year’s performance. This paper’s text analysis path can be explored in detail for business English narrative discourse genre measures.
The Current Situation of the Implementation of College Admission System and the Way of Reform in the Digital Age
Authors: Liu Yabin 
Published: July 2024

Abstract
With the progress of science and technology and social changes, higher education in China is experiencing unprecedented challenges and opportunities. The digital era has not only changed teaching methods but has also profoundly affected the enrollment system of colleges and universities. The study uses a decision tree-based enrollment information mining algorithm and a gray prediction model to construct a data mining model of the current status of enrollment system implementation. Through the data mining model, the data mining and analysis of the student source status of college enrollment are used to propose targeted reform proposals. The number of female students in School Z has been increasing each year, while the number of male students has decreased significantly. The number of students with grades A and B is much lower than that of students with grades B and C. Among the special types of enrollment sources, the enrollment of national defense students and high-level athletes has decreased year by year, while the enrollment of the poverty special program has shown a yearly increasing trend. During the four years, the enrollment of national defense students was 61, 54, 46, and 39, and the enrollment of high-level athletes was 15, 14, 12, and 10. The enrollment in special programs for people experiencing poverty increased from 9 to 47 during the four years. The reform of the college enrollment system should focus on reforming the content of the examination, and government departments to do a good job of coordinating planning, improving laws and regulations, and putting an end to malpractice and irregularities.
A Study on the Enhancement Strategies of Physical Education Teaching in Colleges and Universities Based on the Kano Model
Authors: Shi Wei , Yang Lin 
Published: July 2024

Abstract
Physical education (PE) within higher education plays a crucial role in fostering moral integrity among students. However, traditional approaches in PE have often struggled to align with student needs, leading to suboptimal educational outcomes. To address these challenges, this study employs and refines the Kano model to better analyze and categorize student needs in PE classrooms. By adopting mixed class analysis, the ambiguity typically associated with classifying needs in the conventional Kano model is significantly reduced. This refinement allows for a more nuanced consideration of various demand elements. Utilizing the Better-Worse coefficient, the study evaluates the influence of distinct educational needs on student satisfaction within courses. This analysis facilitates the identification of specific types of needs. For instance, in a controlled study focusing on basketball training, the application of the revised Kano model yielded notable improvements in students’ basketball skills. Specifically, scores for the 5-step backward shot increased from 12.55 to 15.97, and scores for the marching shot rose from 8.64 to 11.04. Additional enhancements were observed in the marching pass and half-court folding dribble, improving by 2 and 4 points, respectively. Furthermore, the basketball theory scores of students in the experimental group surpassed those of the control group by 7.92 points, with classroom satisfaction ratings also averaging 2.2 points higher. These findings underscore the substantial impact of the enhanced Kano model on improving basketball skills, theoretical understanding, and overall classroom satisfaction, highlighting its efficacy in tailoring PE curricula to meet student needs more effectively.
Model Construction and Path Exploration of Integrating Traditional Culture into College English Teaching in the New Media Era
Authors: Hao Jingdong , Sun Shanhui 
Published: July 2024

AbstractBased on the current situation of English teaching in colleges and universities, this paper proposes a path for the integration of traditional Chinese culture into English teaching in colleges and universities, which mainly covers teaching content, information technology, and practical activities combined with the principle of deep integration. In order to explore the desirability of the path of integrating traditional culture into English teaching in colleges and universities, a structural equation model oriented to the integration of traditional culture into English teaching is constructed, the latent and explicit variables of the model are defined, and set, and an example analysis of the integration of traditional culture into English teaching in colleges and universities under the perspective of new media is carried out by combining the data of the study. After analysis, it can be obtained that the evaluation indexes of the fit of the structural equation model are 1.728, 0.048, 0.884, 0.896, and 0.697, respectively. Moreover, the experimental group and the control group are significantly different in the aspects of accuracy (P=0.0292<0.05), fluency (P=0.0314<0.05), and logic (P=0.0253<0.05). And there is no significant difference in flexibility (P=0.612<0.05). This study can not only help students to have a more in-depth understanding of traditional Chinese culture but also cultivate their hands-on practice and thinking ability so that English knowledge can be put into practice.
The Embodiment of the Elements of Thinking and Politics in Digital Art Design in the Internet Era
Authors: Song Xiaojing 
Published: July 2024

Abstract
Civic and political elements play an indispensable role in the process of national cultural development. In the context of the era of booming Internet technology, this paper proposes the extraction technology of the Civic and Political elements of digital art design and explores the effective way of disseminating the Civic and Political elements in the Internet. The mean drift clustering algorithm is introduced to the image to segment the source image into multiple independent and disconnected image sub-blocks to achieve the segmentation pre-processing of the image. Subsequently, the density peak clustering algorithm is used to design the main color extraction algorithm, separate the image from the background by Otsu threshold segmentation and hole filling algorithm, and perform color clustering on the image to achieve the feature extraction of Civic and Political elements. This algorithm’s extraction time efficiency is superior to that of Grabcut, LazySnapping, and RepSnapping algorithms, and the correct extraction rate is over 85%. Taking the digital artworks published on the Internet as of December 2023 as the main research body, the implication of ideological and political elements is analyzed. The number of occurrences and extractions of each Civic and Political element is in the interval of 400~900, and the concentration of Civic and Political embodiment has been improved, but there is still much room for improvement.