bluuebunny/crossref_metadata_2025_split huggingface dataset:
Study on the Cluster of Coastal Cities in China under the Influence of Storm Surges
Authors: Zhu Li , Cui Shibai , Luo Tianyu 
Published: January 2024

Abstract
Coastal areas are the most developed areas in China’s economic society, but they are vulnerable to storm surges. The characteristics of coastal cities under the influence of storm surges can be targeted to adjust social and economic activities and promote sustainable development. Combining characteristics of 52 coastal cities and based on the indicator system method and data cluster analysis, this study explores the different indicators and future development strategies of 5 clusters of cities when facing storm surges, aiming to fill the research gap in this area. The indicators related to the economy, population, and environment of coastal cities were selected, and the characteristics and frequency of regional storm surges were considered. At the same time, the K-means clustering method and DBSCAN were used to select the most suitable clustering method. The clustering results of coastal cities caused by storm surge disasters were analyzed, and a series of specific strategies and suggestions were proposed. According to the research findings, the K-means clustering method is more appropriate for this study. A total of 52 cities are clustered into five categories, of which the number of the fourth category is the largest, and the number of the fifth category is the least. The findings can be used to scientifically determine and guide subsequent analyses related to the disaster-bearing abilities of different types of coastal cities in the face of storm surges, thereby greatly enhancing and strengthening refined storm surge disaster defense efforts.
Statistical method for clustering high-dimensional data based on fuzzy mathematical modeling
Authors: Wang Changhui 
Published: January 2024

Abstract
In this paper, firstly, the fuzzy mathematical model and its types and algorithms of fuzzy numbers are studied. Then, the concept of fuzzy mathematics is added to cluster analysis, and fuzzy cluster analysis is carried out on samples or objects after data standardization and the construction of a similarity matrix. Then, the fuzzy C-mean FCM algorithm is proposed, and the FCM algorithm is improved by introducing the point density of data objects, the maximum minimum distance method of point density sampling, and the reduction of computation to improve the statistical function of clustering high-dimensional data. Finally, the algorithm of this paper is compared with other algorithms by AC, PR, RE, convergence speed, running time, DBI index and other indexes in order to analyze the advantages of the FCM algorithm in high dimensional data clustering statistics. The results show that the F value of the FCM algorithm in the Zoo dataset reaches 0.976, which improves 61% compared to FKM and nearly 12.6% compared to the IIFKM0 algorithm, with the best clustering effect. The DBI index of the FCM algorithm is the lowest in the four datasets, which is basically stabilized in the range of 0.5-0.6. This is better than other algorithms.
Design of Online Intelligent Detection System for Power Quality and Fault Identification in Distribution Networks
Authors: He Wanru , He Chunhong , Zhang Zongjie , Ren Bin 
Published: January 2024

Abstract
This paper lays the foundation for the subsequent analysis of power quality in distribution networks by briefly describing the indicators of power quality. Utilizing the zero sequence voltage mutation detection fault of a small current routing algorithm, the instantaneous values of voltage and current of each phase of the three-phase circuit are quickly calculated based on the electrical parameters of instantaneous reactive power and the online intelligent detection system is established. The effectiveness and feasibility of the designed detection system and detection algorithm in detecting electrical energy parameters have been verified through experiments. The results show that the error of voltage measurement is within 0.0003-0.002, the frequency error of the system is up to 0.0117%, the measurement error of three-phase unbalance is distributed between 0.001 and 0.1, and the error of negative sequence and zero sequence is between ±0.003, which meet the system design requirements. It shows that the use of online intelligent detection systems can improve the quality of distribution network operation and fault identification accuracy, improve power quality, and effectively improve the reliability of power supply.
Vocational Education and Industry Integration and Symbiosis of Subjects and Digital Drivers
Authors: Guo Yi 
Published: January 2024

Abstract
Under the new round of scientific and technological revolution and industrial change, the integration of vocational education and industry is an important direction of educational development. In this paper, the structure of the learning path network of higher vocational professional courses is analyzed, and through the analysis of the elements of learning behaviors, the learning behaviors are mined by adopting sequence relations, and the behavioral structure model is established. The assessment of the learning path under the integration of industry and education courses was finished using uncertainty association coefficients and time association coefficients. After building the learning path network for vocational education, the subjective characteristics of students under vocational education were detected using isolated point analysis. The detection results show that the correlation coefficient between the first pair of typical variables is 0.488. The Wilks statistical test results for typical correlation coefficients show that the p-value of the first typical correlation coefficient is 0.098, which is less than 10%. The correlation study of the environment of integration of education and industry and the effect of integration can be simplified to study only the relationship between the first pair of typical variables. By analyzing the main characteristics, the main body for vocational education and industry integration is clarified, which creates a digital-driven impetus for the integration of industry and education.
Analysis of Challenges and Countermeasures for Higher Education Management in the Era of Big Data
Authors: Chen Feng 
Published: January 2024

Abstract
This paper analyzes the factors affecting the efficiency value of human resource management in higher education by using the Tobit regression model, puts forward the hypotheses of the influencing factors, constructs a model of the factors affecting the efficiency of human resource utilization in higher education, and derives the specific correlation coefficients of the influencing factors. After examining the correlation between each dimension of teacher management culture in higher education and teachers’ organizational commitment and its dimensions using Pearson’s product-difference correlation method, the correlation between educational management and teachers’ teaching commitment is verified through the quantitative measurement of correlation analysis and linear regression analysis. Based on the decision tree algorithm and multiple linear regression method to predict the resource allocation of teachers’ positions, we constructed a model of human resource optimization and allocation strategy for college teachers and carried out the actual analysis of the utilization rate of resources for teachers’ positions and teachers’ schedules by genetic algorithm. Analysis obtained shows that selecting different population sizes for test results in teacher positions and teacher scheduling programs results in higher algorithm efficiency for populations between 30-50. When the value of the population is taken in the range of 30-50, the average time of the experiment is 60380.4ms-153199.2ms.
Analysis of the effectiveness of virtual reality technology integration in landscape design
Authors: Li Fubin , Zhao Xia 
Published: January 2024

Abstract
In this paper, we first studied the 3D visual immersion technology of virtual reality, explored the stereoscopic display and multi-channel stereoscopic display method of virtual reality, and corrected the nonlinear distortion by grating alignment and deformation correction. After that, the model’s lighting technology is examined, and the model’s lighting coefficient is analyzed and calculated. Then, the advantages of landscape design based on virtual reality technology in terms of subjective evaluation, human perception, and promotion of work efficiency were analyzed by comparing traditional landscape design with virtual reality landscape design. The results show that the Sig value of the environmental adaptability of the two spatial designs is 0.037, which is less than 0.05, and there is a significant difference between the two in terms of subjective ratings. People’s attention was enhanced by 7%-10% in the virtual design scene, and the induced brain frequency was 8%-10% higher than that of the traditional landscape design, indicating that the virtual landscape design was more effective.
Research on the Design of Digital Teaching Resource Management and Sharing Platform in Colleges and Universities Based on Cloud Storage
Authors: Wang Yajie 
Published: January 2024

Abstract
In this paper, after analyzing the structural system of the digital resource sharing model in colleges and universities, a shared storage model based on cloud storage is designed, and a digital teaching resource management and sharing platform for colleges and universities based on cloud storage is constructed on this basis. In order to realize accurate sharing, the sharing behaviors of teaching resources are symbolically illustrated, double behavior aggregation is performed, and a multidimensional preference personalized recommendation algorithm, i.e., DB-CGAT model, is designed to construct the personalized sharing module of teaching resources that integrates the behavioral graph. In addition, three types of experiments are conducted on the personalized sharing module of the platform to test its sharing performance and overall performance. The results show that the accuracy of this model is reduced by 0.04 compared with the traditional algorithm; the 90 percent time of login transaction is 2.44, and the time of query transaction is 1.46, which is all up to the standard value. All the action actions are green, and the number of clicks and throughputs in 5~30ss are around 120. Universities can benefit from the digital teaching resource management and sharing platform designed in this paper, which can improve teaching efficiency.
A Study on the Development of Professional Training in Physical Education in Colleges and Universities under Information Technology
Authors: Zhang Zhihua , Li Songmei 
Published: January 2024

Abstract
The deep integration of technology and college sports professional training can effectively stimulate the enthusiasm of students for sports training and, to a certain extent, reduce the danger of professional training. This paper first introduces the virtual reality technology under information technology to build a virtual sports training framework, and through virtual sports training, can effectively realize the immersive training of participants. Secondly, we use LiDAR to obtain point cloud data for the virtual scene of college sports professional training and reconstruct the virtual scene using the Poisson surface 3D reconstruction algorithm. Based on the OpenPose human posture estimation algorithm, the training movements of students in the virtual scene are identified, which helps coaches to better formulate standardized training movements. Finally, to verify the effectiveness of the method given in this paper in college physical education training, a series of quantitative analyses was carried out. The results show that the training loss of the Poisson surface 3D reconstruction algorithm is about 0.087 after 180 rounds of iteration, the verification accuracy is about 87.62%, and the training loss of the OpenPose algorithm is about 0.04% when the number of iterations reaches about 130 times. After using VR technology to carry out professional training in sports, the score of students in the experimental group in terms of active learning interest is 4.487±0.324 points, which is about 1 point higher than that of the control group. Virtual reality technology can effectively promote the innovation and reform of sports professional training in colleges and universities, enhance the student’s interest in learning sports training, and provide a guarantee for improving students’ physical quality.
Research on Grading and Evolution of International Trade Development Quality of City Clusters Based on Logit-ISM Modeling
Authors: Ye Baiqian 
Published: January 2024

Abstract
In order to further accelerate the realization of high-quality development of international trade and enhance the discourse power in international trade activities, this paper explores the grading and evolution of the quality of international trade development of city clusters. After analyzing the DEA static model and DEA-Malmquist dynamic evaluation model, combined with the entropy value method, the entropy value-DEA model is constructed to measure the comprehensive evaluation of the quality of international trade development of the city cluster, and the results are comprehensively analyzed. In addition, combined with the Logit-ISM model to analyze the factors affecting the development quality of international trade of city cluster and explore the grading and evolution of the development quality of international trade of city cluster from two perspectives of global statistics and global spatial trend. The results show that the fluctuation of the trade structure score is smaller than the trade scale, with an average growth rate of 0.165, and the trade competitiveness score basically stays in a state of growth except for 2008 and 2009, with an average annual growth rate of 0.972. The urban agglomerations in the eastern region account for a total of 0.38 of the city agglomerations in the city agglomerations synthesis, and the number of prefectural-level cities included is 106, which accounts for a total of 0.52 of the number of prefectural-level cities included in the city agglomerations. The quality of international trade development in city clusters in the eastern and northeastern regions stands out as the most significant. Based on the research in this paper, we advocate for the balanced development of the quality rating and evolution of each city cluster in international trade development.
Research and Practice of Digital Training Model Based on Artificial Intelligence Technology
Authors: Duan Haipeng 
Published: January 2024

Abstract
There are fatal defects in both the simulation practical training model and the actual combat practical training model. This paper firstly takes artificial intelligence technology as the basis for the construction of digital wisdom training classrooms and constructs the artificial intelligence digital wisdom training model. Secondly, it combines multi-factor reasoning and integrated clustering ideas to portray the vocational ability portrait of the learner group in the model and realizes the recommendation of students’ personalized training teaching resources with the learner’s portrait. Finally, the effectiveness is verified through the application practice of the digital training model for AI in higher vocational colleges. The results show that the use of multi-factor reasoning and integrated clustering can realize the accurate portrayal of the learner portrait of the digital intelligent training students and the difference between the loss value of the training and validation of the personalized recommendation model based on the learner portrait is about 0.01, and the average time consumed is about 1.05s. The digital training model supported by artificial intelligence technology can help students establish higher-order scientific thinking, promote students’ mastery of skills, and fully compensate for the shortcomings of the existing practical training model.
A Study of Minority Culture Outreach Translation Based on Cognitive Mapping Construction
Authors: Jin Ling 
Published: January 2024

Abstract
In this paper, we first construct a cognitive neural network and use the knowledge representation learning technique for knowledge complementation and relation extraction to semantically match head-tail entity pairs with relations and accurately model the semantic relationships between entities and relations. Then, the vectors of each entity are mapped onto the hyperplane of a given relation by the cognitive mapping translation model, and vector translation operations are performed on the hyperplane. Finally, this paper’s translation model is compared with other models to compare the semantic representation translation, task processing function, and model complexity of each model so as to verify the superiority of this paper’s model for minority culture outreach translation. The results show that this paper’s method increases 3.4 and 1.2 BLEU values on average in the four translation tasks compared to the Imagination model and VAG model, respectively. When the number of iterations is 40, the MRR value of this paper’s model is 0.345, which is at least 0.1-0.5 more than the other models, thus indicating that this paper’s model has a better performance in outreach translation.
The Construction of Online Interactive Teaching Mode of Cross-border E-commerce English in Colleges and Universities under the Background of Internet
Authors: Zhang Qian 
Published: January 2024

Abstract
In this paper, we first constructed an online interactive English teaching model through the interaction hierarchy tower model and adopted a data-driven social cognitive network analysis approach to explore the evolutionary dynamics of cross-border e-commerce English learning communities in higher education and their potential correlation with the development of participants’ interaction patterns. Then, the online synchronous and asynchronous interaction patterns of learners are compared and integrated by extracting the characteristics of online interactive teaching learners. Finally, an instructional design for an online English for Cross-border E-commerce course was used to explore the differences and associations between online interactive teaching modes. The results show that in the teaching experiment, students have 39 nodes in the synchronous interaction network (SMN) and 34 nodes in the asynchronous interaction network (UMN), and the degree centrality and eigenvector centrality Rank=4.07 and 3.15 of the SMN are also significantly higher than those of the three interaction networks. The SMN interaction model is found to be the most efficient in the online interaction teaching process. This study helps to improve the dynamic regulation and precise guidance of the online learning process for cross-border e-commerce English, which ultimately enhances the quality of online teaching.
Analysis of the effect of music therapy on psychological anxiety relief based on artificial intelligence recognition
Authors: Xin Lei 
Published: January 2024

Abstract
In order to improve the accuracy and reliability of EEG emotion recognition and avoid the problems of poor decomposition effect and long time consumption caused by manual parameter selection, this paper constructs an EEG emotion recognition model based on optimized variational modal decomposition. Aiming at the modal aliasing problem existing in traditional decomposition methods, the KH algorithm is used to search for the optimal penalty factor and the number of decomposition layers of the VMD, and KH-VMD decomposition is performed on the EEG signals in the DEAP dataset. The time-domain, frequency-domain, and nonlinear features of IMFs under different time windows are extracted, respectively, and the Catboost classifier completes the construction of the EEG emotion recognition model and emotion classification. Considering the two conditions of the complexity of the network structure of the KH-VMD model and the average classification accuracy of different brain regions in different music environments, the WEE features of the target EEG can constitute the optimal classification network by taking the WEE features of the target EEG as the input of the KH-VMD classification model. At this time, the average classification accuracy that can be obtained with differentiated brain regions and differentiated music environments is 0.8314 and 0.8204. After 8 weeks of music therapy, the experimental group’s low anxiety scores of pleasure and arousal on the Negative Picture SAM scale were 3.11 and 3.2, which were significantly lower than those of the control group’s low-anxiety subjects. The experimental group with high anxiety had anxiety scores and sleep quality scores that were 5.23 and 3.01 points lower than before the intervention. Therefore, music therapy can effectively alleviate psychological anxiety and enhance sleep quality.
The construction of rural e-commerce and logistics synergistic development model based on the coupling model
Authors: Mi Jing , Meng Que 
Published: January 2024

Abstract
By connecting the consumption and demand of the city and the countryside through the use of e-commerce platforms and logistics as an intermediary bridge, this study creates a model for the synergistic growth of rural e-commerce and logistics. A multi-dimensional index system is created by combining the actual state of rural e-commerce and logistics, using Shaanxi Province as an example. The degree of coordination between logistics and e-commerce can be ascertained by applying the coupling coordination model. Determine the weights of the indicators to solve for the level of coordinated development, the degree of linked coordination, the degree of rural e-commerce and logistics coupling, and the coordination level of each year using the entropy value technique. Together with the gray correlation degree, we will examine the crucial elements of optimizing the logistics chain for rural e-commerce. According to the study, rural e-commerce and logistics have a coupling coordination degree of 0.0913 in 2010 and 0.6347 in 2019. The degree of coupling coordination between the two is increasing, indicating a major coordination degree in 2019.
A personalized recommendation algorithm for online teaching resources of vocal music based on graph neural network
Authors: Wang Lina 
Published: January 2024

Abstract
In the development process of education informatization, realizing personalized learning is the urgent demand of learners. In this paper, we construct an online teaching resources recommendation algorithm (VGNN) based on a graph neural network (GNN). The project-based collaborative filtering algorithm is used to find highly similar teaching resource materials using Pearson’s correlation coefficient in order to personalize the recommendation of online teaching resources. The personalized recommendation algorithm for online teaching resources was tested and analyzed using the online teaching course Fundamentals of Vocal Music Theory as a case study. The results show that the course “Fundamentals of Vocal Music Theory” is divided into 4 clusters with clear boundary contours under the graph neural network algorithm, and the number of knowledge points in the 4 clusters is 2308, 655, 513, and 97, respectively. After learning the personalized recommended content from the 4 clusters of knowledge points, the average rate of loss of points for each of them decreases by about 0.3. The algorithm effectively solves the accurate classification of vocal knowledge and implements personalized recommendations for educational resources.