bluuebunny/crossref_metadata_2025_split huggingface dataset:
Practical Dilemmas and Coping Strategies of Meta-Cosmos in Helping the High Quality Development of Ideological and Political Education in Colleges and Universities
Authors: Xu Xunen 
Published: February 2024

Abstract
With the technological innovation, meta-universe changes the education of ideology and politics in colleges and universities. This paper discusses the dilemmas and strategies of applying meta-universe technology in the ideological and political courses in colleges and universities to improve the quality of education. First, it discusses the impact of meta-universe technology on the education of ideology and politics pointing out its potential in enhancing the interactivity and practicability of teaching. However, it also faces problems such as technology integration, teacher training, and uneven student participation. A survey of 100 university teachers and students found that the application of meta-universe technology resulted in a 30% increase in student engagement and a 20% increase in learning outcomes. Multi-dimensional strategies including optimizing teaching design, enhancing teacher training, and improving students’ interactive experience were proposed to meet the challenges. Meta-universe technology can effectively enhance the teaching quality of ideological and political courses. Still, it must be combined with actual teaching needs and conditions to develop a reasonable application program.
The significance and value of living and regionalizing the aesthetic education curriculum on the topic of Jing Chu culture
Authors: Zhang Kain 
Published: February 2024

Abstract
This study explores the significance and value of the living and regionalization of Jing-Chu culture in the aesthetic education curriculum, strengthens the combination of regional cultural characteristics and modern aesthetic education, and explores the new value and direction of cultural education in contemporary times. Through quantitative and qualitative analysis, we study Jing Chu culture’s aesthetic education function and digital transformation. We use questionnaire survey, experimental analysis and literature research methods to focus on the aesthetic education elements of Jing-Chu culture and its application in modern education. Elements such as myths, sorcery, and Chu Rhetoric in Jing and Chu culture have a new vitality in the digital environment. Through the questionnaire analysis of 50 art majors, it was found that 90% of the students believed that the elements of Jing-Chu culture enriched their artistic creation and aesthetic experience, and the application of Jing-Chu cultural primitives in the digital teaching environment significantly enhanced the students’ sense of identification with the culture and their motivation to create. The living and regionalization of Jing Chu culture not only enriches the connotation of the aesthetic education curriculum, but also provides new ideas for the inheritance of traditional culture. Art educators are encouraged to dig deeper into the value of Jing Chu culture to bring innovation and vitality to the contemporary aesthetic education curriculum.
Design of computer algorithms based on parametric models
Authors: Bai Jiexian , Qiao Hongkai , Li Haifang 
Published: February 2024

Abstract
In this paper, the objective function is effectively optimized by improving the fitness function in the computer algorithm. The improvement mainly focuses on adjusting the weighting coefficients of completion time, load balance and execution cost. The article then proceeds to optimize the algorithm’s parameters based on the algorithm’s optimal parameterization criterion, and designs a hybrid hill-climbing-simulated annealing optimization algorithm based on the parameterized model. To verify the safety of the algorithm, avalanche effect experiments were conducted in the study. The experimental results show that when the number of iterations is 14, the number of changed bits reaches 32, indicating that the algorithm is susceptible to the avalanche effect. In addition, for the application effect of the algorithm, the study was tested in the Oliver30 dataset. When the number of iterations reaches 25000 times, the algorithm has reached the optimal value distance 432.82, which shows the superiority in urban path recognition performance. Meanwhile, the algorithm has achieved an accuracy 0.8286 for feature recognition in remote sensing datasets, with a maximum classification accuracy of more than 90%. The study provides critical practical data and theoretical support for further application of the computer algorithm.
Research on Regional Tea Tourism Product Development Strategy Combined with RMP Analysis
Authors: Huang Lingyun 
Published: February 2024

Abstract
Tea culture tourism perfectly combines agricultural economic development and cultural tourism, a new trend in today’s tourism industry development. Based on the life cycle theory of tourist places and RMP theory, this paper comprehensively analyzes the three core dimensions of regional tea culture tourism product development: resources, market and products, using Province F as a case study. In the resource dimension, the combination assignment method containing preference information was used to determine the weights, and the fuzzy comprehensive evaluation model was applied to comprehensively evaluate the tea culture tourism resources. The market dimension analysis covers tea tourism’s development status and the characteristics of tourists’ travel behavior. For the product dimension, a quadrant diagram analysis was conducted using the IPA model by combining tourists’ perceived importance and satisfaction with the product. The study results show that Province F excels in tea tourism product development, with a comprehensive resource evaluation score of 90.756 points. Between 2010 and 2019, the tea tourism market received tourists at an average annual growth rate of 12.28%, reflecting the strong growth momentum of the market. Regarding product development, the average values of tourists’ perceived importance and satisfaction were 3.99 and 3.78, respectively, indicating that tourists’ overall satisfaction with tea tourism products is high. The study will help further enhance the attractiveness and competitiveness of tea tourism products and promote sustainable tourism development.
Analysis of the application of BIM combined with GIS in engineering digital management
Authors: Lin Junhong 
Published: February 2024

Abstract
This study centers on the application of digital intelligence technology in project management, takes the geohazard project in Z area as the research object, and evaluates and predicts the grade of the danger of slope disaster and mudslide disaster in this area. The study begins with an in-depth analysis of the integrated fusion of BIM and GIS technologies. The integrated assessment and prediction model of geologic hazards was constructed using fuzzy comprehensive evaluation and support vector machine algorithm. The study unfolded the analysis of the hazard class and risk prediction of geohazards. The results showed that most of the hazard classes in slope hazards were assessed as low danger, accounting for 33.33%. Meanwhile, about 70% of the mudslide hazards were assessed to have a low to medium hazard rating. Regarding risk prediction, the prediction accuracy of slope and mudslide hazards reached 89% and 90%, respectively. In addition, the detection rate of all geohazards in the ROC (receiver operating characteristic) curve was above 85%, while the false alarm rate remained between 14% and 22%. This result verifies the accuracy of the model in geohazard risk prediction. The comprehensive assessment and prediction model proposed in this paper will help the risk assessment and prediction of geohazards, provide adequate technical support for managing disaster information, and enhance the science and rationality of disaster prevention and mitigation.
Research on the Regulation of Intelligent Elderly Service Laws in the Age of Artificial Intelligence
Authors: Ning Wanyu , Wei Xize 
Published: February 2024

Abstract
The artificial intelligence senior care model brings about work efficiency improvement and human resource cost saving to old care service enterprises and government departments. Taking Maslow’s hierarchy of needs theory as an entry point, the article systematically combs through the needs, legal source relations, and potential risks of intelligent senior care services. To accurately assess the relevant influencing factors of the legal regulation of innovative senior care services, linear regression and seemingly uncorrelated regression models are introduced. The model parameters are estimated by Bayesian estimation method, and the empirical analysis is conducted based on the baseline regression and seemingly uncorrelated regression models. When the local government pension policy decreases by every 1 percentage point, the degree of legal regulation of innovative pension services will decrease by 0.598 percentage points. In addition, in the likelihood uncorrelated regression model, the influence coefficient of education level is −0.372, which is 38.81% lower than the benchmark regression model. To better guide the standardized development of innovative senior care services, the central and local governments must actively introduce relevant policies to help the public better understand and accept the advantages of intelligent senior care services.
Modeling and tracking control of underwater unmanned underwater vehicles for deep-sea marine environment detection
Authors: Wang Qiusheng , Wang Jingnan , Qi Xiangdong 
Published: February 2024

Abstract
This paper focuses on enhancing target tracking techniques for unmanned underwater vehicles (UUVs) used for deep-sea exploration, especially for the latest advances in digital technology. The article begins with an innovative UUV target tracking algorithm improvement based on the correlation filtering algorithm. Introducing the spatio-temporal regularization method and penalty function optimizes the filter parameters and enhances the algorithm’s performance. Then, a new objective function is constructed by combining the optimal feature weights and baseline function calculated by the dynamic feature weighting method, which effectively excludes the influence of interference peaks in the algorithm. In addition, by applying the Gaussian correlation method, the article further improves the algorithm’s robustness. When the obstacle avoidance ability of the algorithm is analyzed, it is found that the control error of the obstacle avoidance speed in both X and Y directions is less than 0.1 m/s, and the difference between the actual angle and the desired angle of the attitude angle is less than 0.5 degrees. This indicates that the algorithm can effectively avoid all obstacles and accurately track the target. The target tracking experiments show that the tracking performance scores of the algorithm are generally higher than 9, and the tracking accuracy is more than 95%, which is significantly better than other existing algorithms. The optimized tracking algorithm proposed in this paper not only provides essential technical support for the development of unmanned underwater vehicle technology, but also provides valuable reference for the future application and practice of the algorithm.
Analysis of new energy vehicle battery temperature prediction by combining BP neural network
Authors: Xie Yuyang 
Published: February 2024

Abstract
With the rapid development of the new energy industry, the safety research of battery technology has become a key topic. This paper focuses on the temperature prediction of new energy vehicle batteries, aiming to improve the safety and efficiency of batteries. Based on the new energy vehicle battery management system, the article constructs a new battery temperature prediction model, SOA-BP neural network, using BP neural network optimized by SOA algorithm. This model can accurately predict the battery temperature, and the effectiveness of its temperature control is verified through experiments. The results show that the SOA-BP neural network model outperforms the traditional BP, CNN, and RNN models in temperature prediction. Regarding evaluation indexes, the model’s root mean square error (RMSE), mean absolute error (MAE), and R2_Score are 0.953, 0.909, and 0.837, respectively. It is worth noting that the model can effectively regulate and control the battery temperatures at different temperatures, ensuring that the maximum temperature difference of each battery is maintained within 5°C. The model can also be used to predict the temperature of the batteries in different temperatures. This battery temperature prediction model not only provides an effective means for predicting and controlling the battery temperature of new energy vehicles, but also provides an essential reference for improving the vehicle’s performance and developing energy management strategies. This study offers a new solution for the safety and efficiency of new energy vehicle batteries.
Formation Mechanism and Analysis of Intelligent Connected Vehicles Fleet under Meta-Cellular Automata Simulation Conditions
Authors: Zhao Yu , Wen Lizhi , Wang Lei , Wei Mingjiang , Wang Yu 
Published: February 2024

Abstract
This paper analyzes the intelligent networked fleet formation mechanism under adaptive cruise control (CACC). By constructing a communication architecture system including network layer, coordination layer, control layer and physical layer, and based on environment sensing technology and 5G network, a layered control structure for autonomous driving vehicles is established. In the study, the inter-vehicle distance control strategy is proposed, and combined with the theory of metacellular automata, the study constructs an intelligent networked fleet model, which adopts the full speed difference model and adaptive cruise control vehicle following model. The simulation analysis is carried out through the actual data of a section of G6 Beijing-Tibet Expressway, and the simulation environment is a two-lane highway of 3000m, considering different CAV vehicle penetration rates (0% to 100%). The results show that with the increase of CAV penetration, the traffic flow and the congestion significantly improved. The intelligent Connected Vehicles fleet performs well in the obstacle avoidance task, effectively reducing unnecessary lane changes and shortening the congestion time compared to the conventional system, with the distance error controlled within 1m. This study shows that the intelligent connected vehicles-connected fleet has significant advantages in improving traffic flow’s operational efficiency and safety.
Brain Liberation - An Anthropological Reflection on the Threat of Artificial Intelligence
Authors: Zhou Yun , Luo Qing 
Published: February 2024

Abstract
This study examines the threat of AI to the emancipation of the human brain, with a particular focus on its impact on human logical thinking and creativity. It reveals the centrality of AI in knowledge engineering by analyzing expert systems constructed by the Symbolist school, which emphasize the role of knowledge bases and reasoning machines by simulating human logical thinking. The study also examines how AI affects modern human subjectivity, utilizing the “Valley of Terror” curve theory to explain the changes in human attitudes toward AI Further, the study introduces human brain-based AI models, such as the application of back-propagation algorithms in neural networks, as well as a cognitive-based model of knowledge operations in the human brain. The results show that the development of AI poses a threat to human brain power, especially in information processing and decision making. AI can replace human brain functions, leading to human logic and creativity degradation. For example, the application of ChatGPT in education can significantly improve students’ test rankings and reduce the reliance on individual thinking skills. In summary, AI may lead to the degradation of human logical thinking and creative ability while improving efficiency and convenience, affecting the overall development of human beings. Therefore, the focus should be on balancing the relationship between the utilization of AI and the development of human brain capacity, significantly to enhance the cultivation of human creativity and imagination in education and innovation.
A study of the impact of financial news media coverage patterns on stock price fluctuations
Authors: Xue Ziyu , Yin Lijie , Wang Junkai 
Published: February 2024

Abstract
This paper examines the impact of media communication on the stock market in the context of the digital age, particularly its role in stock price volatility. With the significant increase in the speed, breadth and depth of media communication, the efficiency of stock market information transmission has been dramatically improved, significantly impacting stock price volatility. The article first explores the specific impact of media coverage characteristics and methods on stock price volatility by quantitatively analyzing media coverage’s breadth, manner and content. Then, the article utilizes multiple linear regression models to deeply explore the impact of various news texts on stock price volatility in different reporting modes (e.g., live reporting, television, and text reporting) in the Shanghai and Shenzhen stock markets. The findings show a significant association between the breadth of media coverage and stock prices at the 1% significance level. In addition, the regression coefficients of content and manner of coverage on stock price changes are 0.096 and 0.229, respectively, which are both significant at the 5% significance level. The research results of this paper not only reveal the close relationship between media communication and stock market volatility and provide theoretical support for predicting dramatic stock market volatility, which helps to promote the construction of a healthy and orderly capital market order.
Spatial Design Research on Digital Media Technology Intervention in Immersive Art Theory Exhibition Venues
Authors: Zhao Xi 
Published: February 2024

Abstract
The article takes the application of digital media technology in the spatial layout design of art exhibition halls as the entry point, and utilizes Web technology and the integrated simulation platform of urban VRGIS to establish the virtual space of immersive art exhibition halls. The article obtains binocular imaging data through binocular visual imaging model and solves the three-dimensional coordinate system by using the method of polar geometric constraints, and then reconstructs the three-dimensional space through the point cloud data to realize the design of the virtual space of the immersive art exhibition hall. The article evaluates the effectiveness of the immersive art gallery virtual space from three aspects: interactivity, DPI recovery value and eye movement data visualization. It is found that users are most effective with direct interaction within an interaction depth of 1.1 m to 1.7 m. In comparison, ray interaction is more appropriate when the interaction depth exceeds 2.3 m. Applying the method of this paper, the global DPI recovery value of the immersive art gallery can reach 89.67%, and the pupil diameter of the subjects can reach about 5.79 mm in the virtual space test over 160 seconds. In this paper, digital media technology can more effectively realize the immersive presentation of art theories, to better satisfy people’s growing spiritual needs and provide more diverse cultural experiences.
Mining and Application of Digital Health Elements in Higher Education Student Management and Education
Authors: Yu Haibo 
Published: February 2024

Abstract
This study explores the mining and application of digital health elements in higher education student management and education, refining student user profiles through data mining techniques and applying them to student management and education to improve the accuracy and effectiveness of education management. The basic process of data mining, including data cleaning, integration, selection, transformation, mining, pattern evaluation and knowledge representation, was first carried out in the study. Then, a clustering recommendation algorithm based on user characteristics was designed to construct a clustering model of user interest preferences by calculating the distance between user attributes and filling the rating matrix using rating time and item type. Then, the study constructed a student user profiling system and analyzed techniques such as fuzzy C-mean clustering, association rule algorithm and user-based collaborative filtering. The study results show that applying digital health elements in student management and education helps identify potential association patterns of students’ mental health problems. For example, in the W vocational school case study, the association rule algorithm found that the sense of learning stress and compulsion were the most frequent combinations of psychological problems among students, with support levels of 0.7451 and 0.6518, respectively. In addition, the study evaluated the effects of educational management interventions on the mental health of higher vocational students, and found that, after adopting student user profiles for educational management interventions, the experimental class students’ mental health scores for each variable were 0.602 to 1.113 points higher than those of the control class, which significantly improved the students’ psychological quality.
Assessment of the Effectiveness of Intelligent Computing Modeling Application Environment for Sustainable Integration with Civic Education in Colleges and Universities
Authors: Chen Xiaoyan , Zhou Yamin 
Published: February 2024

Abstract
Incorporating the concept of environmentally sustainable development into the Civics program in colleges and universities is an important initiative to promote the service of environmental sustainability by the Freshmen. Innovative teaching mode of ecological sustainability and civic education, and the deep integration of green development concept and civic education are crucial to cultivating high-quality talents with environmental sustainability. In this paper, the collected data were standardized and defuzzified, and the CRITIC combination assignment method was used to assign weights to the indicators to obtain the optimal combination weights. Based on this, the indicator data’s gray correlation coefficient and correlation degree were calculated to construct the effect assessment model. The evaluation content for integrating the cultivation of the concept of environmental sustainability and ideological education is proposed in the paper, and the effect evaluation of this was implemented for 11 years. The evaluation results show that in the three classes of college A in the pilot area, the integration of the concept of environmental sustainability and Civic and Political education of college students was significantly improved, and the mean values of the measured improvement were 4.96, 5.05, and 4.95, respectively, which showed a better effect. Among the dimension scores, the mean value of the scores of the three classes in the five dimensions is 3.624.This result indicates that the cultivation of the concept of environmental sustainability has a significant enhancement effect on the performance of Civic and Political Education, and the integration of the two is having a significant impact. The study in this paper incorporates the concept of environmental sustainability into the ideology and political science curriculum of colleges and universities is an effective strategy that not only enhances students’ environmental awareness, but also strengthens the effectiveness of ideology and political science education.