bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Construction of Digital Management Platform for Civic and Political Education for Future College Education and Its Intelligent Teaching Practice
Authors: Wu Juan , Ma Fei 
Published: October 2024

Abstract
Civic education in colleges and universities is facing the transformation of digital management mode, and this paper proposes to build a whole-process autonomous multi-dimensional fusion platform for the implementation and management of civic education in colleges and universities. The platform takes the big data analysis layer, object application layer and service management layer as the overall structure, builds the dynamic database of the Civic and Political Education program, and superimposes the tripartite comprehensive evaluation database. This paper improves the Apriori algorithm for association rules and applies the improved algorithm to the management platform for information mining. Intelligent teaching practices are designed based on the digital management platform, and their teaching effectiveness is analyzed. The performance of the Apriori algorithm before and after optimization is compared, and with the optimized algorithm, the execution efficiency is improved by about 10% to 15%. Students using the Civics education platform showed significant differences at the 1% level in all three dimensions of cognitive load, learning motivation, and mind-flow experience compared to students in the traditional teaching mode.
Research on Artificial Intelligence-Assisted Teaching Methods in Chinese Classical Dance Movement Training
Authors: Yan Li 
Published: October 2024

Abstract
Taking movement training in the teaching of classical Chinese dance as an entry point, combined with the application of digital technology, improves and enriches the existing teaching methods of movement training of classical Chinese dance. Based on the Kinect skeleton data acquisition technology, the study pre-processes the collected data and proposes a dance movement data segmentation method based on movement rhythm to segment dance movement segments. The ST-GCN network structure is improved to recognize Chinese classical dance by AAST-GCN, a spatio-temporal graph convolutional network based on adaptive and attention mechanisms. Finally, the DTW algorithm is used to analyze the degree of similarity between the recognized action sequences and the standard action sequences, so as to provide targeted assisted teaching of classical Chinese dance. The results show that the intersection and concurrency ratio of the human dance posture detection method based on deep convolutional learning is always located in [0.5, 1.0], and the system can give training suggestions according to the comparison results, and the trainer can reasonably adjust the movements according to the software prompts, so as to achieve the purpose of assisted training, and then effectively improve the trainer’s dance level. After 12 weeks of AI-assisted training, the dancers obtained more obvious improvement than the control group in both rotational speed and the number of rotations, and the enhancement of these two abilities is precisely the necessary condition for realizing high-quality classical dance turn-like movements.
Research and Innovation of Animated Movie Production Technology Based on Computer Graphic Design
Authors: Yan Qifeng 
Published: October 2024

Abstract
The animation technology of computer graphic design can creatively integrate artificial intelligence technology and animation art, and use artificial intelligence technology to realize the creation of animation with the support of computer graphics. Based on this, this paper constructs a particle special effects system to realize the innovation of animation film production technology. This paper first analyzes the functions that need to be realized by the system and carries out the overall design of the system framework using modeling language. This includes the detailed design and graphical representation of the particle module, scene module, texture module, and so on in the particle special effects system. Then, simplify the mathematical model of snow, rain, fountain, etc., establish the particle system model of snow, rain and fountain, and realize the special effects simulation of snow, rain, fountain and other landscapes. Through the experiments, the performance of this system passes the standard of 70 frames per second, and the average score of the evaluation index of “whether there are common phenomena in animation” reaches 9.1 points, but the average score of the particle effects to express the emotions of the characters is only 6.3 points, which indicates that this system realizes the special effects simulation of snow, rain and fountain. This shows that the system in this paper has achieved the special effects simulation of snow, rain, and fountain phenomena, but there is still room for improvement in the expression of characters’ emotions with particle effects. On the whole, the system in this paper has achieved excellent special effects simulation and has realized the innovation of animation film production technology.
Research on modern art creation trend and its visual expression based on deep learning technology
Authors: Zhang Jichao , Cao Sisheng 
Published: October 2024

Abstract
We propose the AI painting model based on the generative adversarial network and analyze the color, pattern, and visual hierarchy of the AI painting’s visual expressiveness. Starting from the painting sketch, the corresponding generator and discriminator are integrated to construct the AI painting model based on a generative adversarial network, and the training strategy, optimization objective, and loss function calculation formula of the model are given. The visual analysis of the AI painting based on deep learning technology is combined with research analysis. In terms of simplifying sketches and generating pictures, the model presented in this paper performs more prominently than the control models (CNN and SVM), which is reflected in the loss value and F1 value, respectively. In addition, there are significant differences between AI paintings and traditional paintings in the use of color (P = 0.035, T = 1.478), pattern cultural allegory (P = 0.011, T = 0.347), and visual hierarchy (P = 0.008, T = 2.993), and AI paintings are more visually expressive than traditional paintings, and at the same time, the regression equation of the AI paintings’ visual expressiveness is 0.125+0.179*Color Use+0.188*Pattern Cultural Allegory+0.234 Visual Hierarchy. This study provides a clearer perception of the modern art creation trend and its visual expressiveness, which is of enormous significance in boosting the development of the art field.
PLC mechatronics technology in the field of intelligent control application analysis
Authors: Zhang Li , Wu Baoyin 
Published: October 2024

Abstract
The traditional manual operation mode has problems such as high manpower cost, low efficiency, low safety, low operating precision, etc. Achieving unmanned intelligent systems in the field of mechanical and electrical engineering has become the key to transforming and upgrading relevant enterprises and improving their overall competitiveness. In this paper, an improved fuzzy PID control system is constructed based on a PLC control system combined with a fuzzy PID intelligence algorithm. It is applied to the pumping motor, coagulation dosing system, and other specific devices for simulation experiments, compared to the conventional PID algorithm, and evaluated the control system in this paper. The fuzzy PID control algorithm of this paper reduces the steady-state adjustment time of the response curve by 30% compared to the conventional PID algorithm, and the overshooting amount is reduced by 25%. With almost no overshoot, the pumping motor that was equipped with this paper’s PID algorithm reached its stable target speed in 0.3 seconds. In addition, this study found that in the coagulation dosing system model incorporating the fuzzy PID algorithm of this paper, when the model is accurate, only 20% of the overshooting amount occurs after the system has been running for some time. The conventional PID algorithm’s 50% overshoot is significantly less than this, and the time it takes to reach a steady state is also 50 minutes earlier than the conventional PID control. When the model is imprecise, fluctuations occur in both conventional PID control and fuzzy PID control, but the amplitude of the fluctuations in fuzzy PID control is relatively small. In conclusion, this paper shows that the fuzzy PID control algorithm in this paper has higher control accuracy, response speed, and stability than the conventional PID control algorithm.
Research on the Optimization Path of Student Management Strategies Driven by Artificial Intelligence on the Cultivation of Innovative Ability of Students in Colleges and Universities
Authors: Zhang Weiwei 
Published: October 2024

Abstract
Based on artificial intelligence management, this paper takes students’ innovation ability as the research object and adopts the improved Apriori algorithm for mining, feature selection and data correlation of the survey data through the questionnaire survey method. With the purpose of improving students’ innovation ability, we summarize the factors affecting the cultivation of students’ innovation ability in colleges and universities and provide new ideas for the optimization of management for the improvement of students’ innovation ability driven by artificial intelligence. The experimental results found that there is no significant difference in the scientific research and innovation ability of master’s students in different grades, while the F-value of the type of undergraduate institution and the type of master’s institution on the scientific research and innovation ability of master’s students (21.121, 45.609) reaches a significant level (P < 0.01). The level of research and innovation ability of master’s students showed a high correlation with the P-value of all 4 factors of students under AI-assisted management < 0.01. The empirical analysis verified that all the variables related to university student management strategies have a significant effect on students’ innovation management ability. Obviously, artificial intelligence provides a new program for cultivating students’ innovative abilities.
Research on the practical application of BlockTune, a blockchain-based music copyright management system, in the field of music education
Authors: Zhao Danning 
Published: October 2024

Abstract
Blockchain has the characteristics of decentralization and traceability, and not easy to tamper with, and has been widely used in music copyright management systems. To apply BlockTune to music education, this paper proposes a BlockTune system that utilizes blockchain and a recommendation system that utilizes deep learning. The system’s overall structure is divided into five layers, which include the application layer, control layer, consensus layer, network layer, and data layer. The functional modules are then divided into four modules, based on the FISCO BCOS alliance blockchain, using the Solidity language for smart contract writing, and using the improved PBFT consensus algorithm as the consensus algorithm of the system, which improves the consensus efficiency of the system. Finally, IPFS is used to store the backed up music works, which relieves the storage pressure on the blockchain. Through the platform loading, the time information is integrated into the neural collaborative filtering algorithm, and the music resource recommendation algorithm based on deep learning is proposed to better recommend the music that needs to be queried at this stage for the users at the right time. The BlockTune system meets the application standards in terms of the average CPU occupancy rate and maximum memory consumption. Half or more of the students think that the system can help them learn music or inspire them to create music, which shows that the system can be well applied to the field of music education and achieves the purpose of the system design in this paper.
A Data-Driven Modeling Study of Factors Influencing Preschool Students’ Intention to Teach
Authors: Zhao Yue 
Published: October 2024

Abstract
Willingness to teach is an important condition for improving pre-service teacher literacy to promote the professional development of preschool teachers. In this study, we randomly selected 600 students from six types of preschool education majors, and processed the data using a data-driven model that included an independent sample t-test, correlation analysis, and multiple linear regression model. The data results showed that the overall mean and standard deviation of preschool education students’ willingness to teach was 3.91±0.982, and preschool education students’ willingness to teach was high overall, but there were still students who expressed a lack of significant willingness to teach. Further regression analysis revealed that individual characteristics, family environment, school environment, and teacher career perception had explanatory power of 5.8%, 20.7%, 6%, and 3%, respectively, and the factors influencing preschool education majors’ willingness to teach were diverse. Measures at both the government and university levels are necessary to comprehensively improve the willingness to teach.
Tapping the Economic Potential and Optimizing Strategies of Intangible Cultural Heritage under Digital Transformation
Authors: Zheng Zeling 
Published: October 2024

Abstract
Intangible cultural heritage has important historical, cultural, and spiritual values. This paper selects the intangible cultural heritage of Yunnan Painting, the national architectural decoration of Dali, as the case study object. We use web crawler technology to extract the consumer’s comment text data, establishing the Yunnan Painting consumer comment text dataset. Secondly, we extract high-frequency words from the dataset using text mining technology, TF-IDF keyword extraction, and LDA themes, and cluster them using the K-means method. Finally, we evaluate the economic potential of Yunnan Painting in terms of consumers’ cognitive abilities and the emotional appeal of its products, based on the extracted results. The study reveals that the dressmaking, painting, and tourism industries are the main economic activities of Yunnan color painting, with the tourism industry requiring further strengthening. According to the text mining of high-frequency words, the frequency of “product” in Yunnan painting was the highest at 296 times, followed by “culture,” “technology,” “cultural creativity,” and “theme.” The analysis of consumers’ emotional text features reveals that most consumers have positive emotions towards Yunnan-colored paintings, while very few have negative emotions. The economic optimization strategy that is proposed is based on the results and provides a reference value for the economic development of other intangible cultural heritage.
Strategies for cross-cultural digital media content creation and communication facilitated by emerging technologies
Authors: Zhou Dong 
Published: October 2024

Abstract
Cross-cultural communication is an effective way to enhance national soft power and international competitiveness, but the cultural differences between different countries hinder cross-cultural communication to a certain extent, and the efficiency of communication needs to be further improved. This study is based on the generative adversarial network algorithm in computer vision technology, which is applied to the method of creating cross-cultural digital media content. Taking the digital media content creation of traditional Dong tattoos as an example, the tattoo content created using this paper’s method is compared to the tattoo content created using Diffusion’s stable diffusion model. According to the different cultural and professional backgrounds of the interviewees, the tattoos were analyzed in terms of three evaluation dimensions, namely, the appearance characteristics, the inner performance and the practical value of the tattoos. The interviewees unanimously agreed that the digital media content of Dong traditional tattoos produced by this paper is superior to the comparative model and has more cultural identity. Finally, this paper proposes a specific strategy for using digital media to promote cross-cultural communication.
Study on the Coupled and Coordinated Development of Rural Tourism and Rural Revitalization Strategy
Authors: Zhang Yinling , He Suheng 
Published: October 2024

Abstract
Rural tourism development is an important part of the rural revitalization strategy. This paper explores the coupling mechanism between rural revitalization and rural tourism and proposes a combined evaluation index system for rural tourism and rural revitalization. The entropy value method and comprehensive index evaluation method are used to construct a model for measuring the comprehensive development level of rural tourism, and the level of rural revitalization is measured by using the comprehensive scoring method and combining the subjective empowerment method and objective empowerment method. The data are standardized, and the weights of the indicators are assigned to construct the rural revitalization-rural tourism coupling model; the coupling coordination function model is established to explore the level of coordinated development between rural revitalization and rural tourism. The degree of coordination between rural tourism and rural revitalization is analyzed in Anhui Province, China. The coupling curve of rural revitalization and rural tourism in Anhui province rises steadily, soaring from 0.4566 in 2016 to 0.85 in 2023, while the coupling coordination degree grows from 0.2824 to 0.8366 from 2016 to 2023. The coupling coordination degree of rural revitalization and rural tourism in each city of the province is in the range of 0.3 to 0.9, with the mean value reaching 0.591.
The Construction of a Network Alliance of Foreign Language Teacher Development Communities in the Age of Artificial Intelligence
Authors: Lu Jianshun 
Published: October 2024

Abstract
The construction of a professional learning development community for foreign language teachers is related to the personal development and group development of college teachers and is a guarantee for the improvement of the quality of foreign language teaching in colleges and universities. Starting from the model of professional learning networks and network learning communities, this paper establishes a teacher development community using the mean drift clustering algorithm optimized by the Gaussian kernel function. The scale-free network BA algorithm is utilized to construct a network alliance of foreign language teachers’ development community and establish indicators related to network metrics. The data of foreign language teachers’ communication platforms is used as an example to analyze the network structure of the community network alliance, and a comparison experiment is designed to analyze the application effect of the community network alliance. When the clustering cluster of foreign language teachers’ community is defined as 5, the clustering sum of squares is 79.45%, and the clustering effect is the greatest. The average interaction degree number of network members was only 1.853, and only six foreign language teachers had mediated centrality above 0.5. The teaching abilities of ordinary and excellent teachers improved between 0.36 and 0.66 points after implementing the network alliance of foreign language teachers’ development community. Making full use of intelligent technology to carry out the establishment of foreign language teacher development community network alliance helps to improve the teaching ability of foreign language teachers and realize the improvement of foreign language teaching quality.
Detection of Efflux pump MexX and MexY genes in Multidrug Resistant Pseudomonas aeruginosa
Authors: Ali Kadhum Attia , Ghassan Enass 
Published: October 2024

High antibiotic resistance among Pseudomonas aeruginosa could be viewed as the primary cause of nosocomial infections. In this study, 60 isolates of Pseudomonas aeruginosa were isolated from urine, sputum, burn, ear and wounds swab. The major goal was to determine the relationship between MexX and MexY and the resistance of MDR P. aeruginosa to many drugs. Prevalence of multidrug resistant (MDR) Pseudomonas aeruginosa was 22 isolates (36.66%) and 38 isolates (63.34%) were found to be non-MDR isolates. Moreover, molecular detection of MexX and MexY genes was done for MDR isolates.MexY gene was found in all MDR isolates and MexX gene was detected in 20 (90.9%) MDR isolates. Susceptibility test showed highly significant differences p≤0.01. Highest resistance was found against piperacillin/sulbactam (45%), followed by ceftazidime/avibactam with 33.33%, and by ceftolozane/tazobactam and levofloxacin which shared same percentage at 31.67%. Almost 23.33% were less resistant to both doripenem and colistin, and 25% to tobramycin. All these findings confirmed a positive correlation between the presence of MexX and MexY genes and an increase in the resistance for all antibiotics used in this study the results of which were highly significant at p≤0.01 for all antibiotics. The study found that some antibiotics that had not been studied previously, also had a relationship with the presence of these genes and the resistance of bacteria to antibiotics such as penicillin, unlike it was previously believed that they do not have relation with the efflux pump mechanism in P. aeruginosa and that this bacterium use other mechanisms to resist them.
Synthesis and Study Biological Activity of Some New Substituted Thiazolidin-4-one Derivatives
Authors: Abdulhussein Nooralhuda M. , Abood Zeid Hassan 
Published: October 2024

The microwave (MW) method was used to create a series of new thiazolidin-4-one derivatives containing benzothiazole and azo groups. Azoaldehyde derivative A was synthesized via the coupling reaction of 2-aminobenzothiazole diazonium ions and 2-hydroxybenzaldehyde. The resultant azoaldehyde A was then subjected to condensation reactions with the primary aromatic amines using the MW method to give azoimines derivatives S1-S5. Finally, compounds S1-S5 were reacted with α-mercaptoacetic acid by the MW method to generate the thiazolidin-4-one derivatives T1-T5. The novel-produced compounds T1-T5 were identified by FT-IR, 1H NMR, and 13C NMR spectroscopy. The DPPH was used to determine the antioxidant activity of the novel-produced compounds T1-T5. The obtained results for T1 and T5 were excellent as antioxidants in comparison with ascorbic acid, while in the antibacterial study, it was discovered that T2, T3, and T5 were found to be more successful than Gentamycin as a control drug against Staphylococcus aureus in an antibacterial investigation, while T3 was found to be more effective than the reference drug against Escherichia coli.