bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploring Random Forest Modeling of Accounting Disclosure Quality and ESG Performance in the Face of Big Data Era
Authors: Zhang Rongkun , Yang Zi , Liu Xinxin 
Published: November 2024

Abstract
This paper combines the theoretical knowledge of the current research on accounting information disclosure and ESG performance, selects seven first-level indicators, which are truthfulness, completeness, materiality, relevance, timeliness, comparability, and comprehensibility, and then subdivides these seven first-level indicators to obtain 22 second-level indicators, thus forming the evaluation index system of accounting information disclosure quality. Based on the high flexibility and robustness of the Random Forest (RF) model, it is proposed to use the Random Forest (RF) model to calculate the weights of the evaluation indicators. The evaluation index system’s comprehensive evaluation results are calculated using the TOPSIS method immediately. The comprehensive evaluation results of accounting information disclosure quality are taken as the explanatory variables of the fixed-effects model, and the data of the explanatory variables and control variables originated from a certain data system, and the fixed-effects model is chosen to clarify the relationship between the quality of accounting information disclosure and ESG performance. The regression coefficient for accounting disclosure quality is 0.0349, and there is a significant positive correlation between accounting disclosure quality and ESG performance at the 1% level. When the quantitative value of corporate accounting disclosure increases by 1 unit, the quantitative value of ESG performance improves by 0.0349 units.
Research on Efficient Data Warehouse Construction Methods for Big Data Applications
Authors: Zhao Chenggang , Du Junwei , Wang Furong , Li Haojie 
Published: November 2024

Abstract
In computing application scenarios with large volumes of data, time-efficient data warehouses are the primary choice for most businesses. The metadata module will be designed with MySQL as an intermediate node for information exchange among modules in an efficient data warehouse in this paper. The first and second-layer data scheduling algorithms are utilized to monitor the progress of queries and updates in the data warehouse system in real-time, and to realize the intelligent setting of dynamic priorities for data processing tasks. Subsequently, the data scheduling and execution module is built based on the scheduling algorithm, and the efficient data warehouse system is constructed using the Hadoop open-source computing framework. The results show that each module of the efficient data warehouse system passes the functionality test, and the data processing time in real and synthetic datasets can fully satisfy the actual time requirements of big data processing and data analysis. In addition, the performance of this paper’s data warehouse system is better than the comparison data warehouse system, and the query time of this paper’s system can be reduced by 87.74% compared with the comparison system in the 1-dimensional data dimension of the SD2 dataset. The efficient data warehouse system designed in this paper is able to achieve high throughput and low latency optimization, which improves the efficiency of data processing and provides a reference for related research in the field of big data processing.
Impact of media attention, corporate announcements on stock market returns based on big data
Authors: Xue Ziyu , Zhu Sha 
Published: November 2024

Abstract
The rapid development of big data technology has led to a profound impact on the stock market from media reports, corporate announcements, and other public opinion data. To address this issue, after collecting relevant data, a panel regression model is used to analyze the specific mechanism of media attention on stock returns. Multiple regression models are also used to analyze the effect of corporate clarification announcements on their response to stock market returns. The value of Hauseman’s statistic for the panel data on stock returns and media attention is 0.964, and the probability is 0.67. The correlation between media attention and stock returns is positive. While media attention is significant at a 1% confidence level, every 1% increase in the stock attention index increases the stock return by 0.002%, keeping other variables constant. The overall significance of the regression results for the quality of clarification announcements and their effect is evident, with a R-square value ranging from 11% to 21%. This suggests a good fit between the regression equation and the credibility of the multiple regression results. The regression results show that the time lag, level of detail, and defense attitude of corporate clarification announcements influence their clarity effect, thereby significantly impacting stock market returns. The findings of this paper are significant in promoting the stable development of stock and capital markets.
Natural language processing in language learning: personalized and adaptive English language teaching using artificial intelligence
Authors: Li Deyi , Wang Hongbin 
Published: November 2024

Abstract
In recent years, artificial intelligence technology has begun to be widely used in the field of language teaching in colleges and universities. As an important branch of artificial intelligence, the study introduces natural language processing technology into English teaching in colleges and universities, utilizes it to extract rich semantic features in English teaching resources, combines LSTM and attention mechanism, and designs an English teaching resource recommendation model based on student’s interests. Based on the recommendation model, an adaptive platform for English teaching is constructed. A small-scale trial is conducted to discuss students’ feedback after the trial and explore the application effect of the platform. The results of each index of the English teaching resources recommendation model are optimal, and the recall (88.65%), accuracy (90.29%) and NGDD (0.3725) are higher than those of other models, which proves the model’s effectiveness in resource recommendation. The positive feedback from students on the adaptive effect, applicability, and recognition of the adaptive platform for English teaching is basically above 50%. The analysis reveals that the AI-based resource recommendation model and adaptive English teaching can aid English teaching in colleges and universities and enhance the quality of English teaching.
Artificial Intelligence-Assisted Simulation Research on Intelligent Behavior of Film and Television 3D Animation Characters
Authors: Lin Yesheng 
Published: November 2024

Abstract
With the continuous development of artificial intelligence technology, the continuous improvement of three-dimensional animation design technology has become an inevitable trend. This paper conducts a simulation study on the intelligent behavior of three-dimensional animation characters in film and television, using finite state machines as the basis. First, we look at the basic parts of the character behavior diagram design and behavior modeling. Then, we use the decision state of the finite state machine to define the intelligent behavior of a three-dimensional animation character. Finally, we combine the character behavior operation principle with the character action generator to finish building the character intelligent behavior model. Under the technical support of the film and television animation character behavior model of the finite state machine, Anima Studio is used to realize the construction of the film and television animation character simulation platform, and the platform of this paper is used to explore the simulation of intelligent behavior of animation characters. Upon exploration, we discover that the animated character, utilizing the finite state machine model, operates efficiently and consistently, thereby demonstrating the simulation effect of the film and television animation character simulation platform in a vivid and realistic manner.
Research on the Application of Montage Technique in the Integration of Construction Technique and Design of Cultural Elements of Patchwork Clothing
Authors: Wang Haitao 
Published: November 2024

Abstract
In modern clothing design, quilting as a means of emphasizing pattern decoration and enriching fabric texture form, its application has presented a diversified and diversified trend. This paper utilizes the montage technique in the process of designing patchwork clothing. The cultural elements of quilted clothing are being innovated through the use of the unique creative art technique of montage. Patchwork clothing design and montage techniques are cross-analyzed to explore the commonality of the two in creative techniques and artistic expression. In order to objectively measure the design effect, AHP is used to determine the weights of the indicators, and then TOPSIS is used for the comprehensive evaluation, which is constructed into a comprehensive evaluation model of quilted apparel design integrating the montage technique. The design evaluation results were achieved by combining the consistency test of the model and the hierarchical total ranking. According to the hierarchical analysis method, the weights of the secondary indicators are calculated, and practicality (25.46%), comfort (20.96%), and functionality (15.37%) rank in the top three, which have a greater impact on the effect of quilting garment design incorporating the montage technique. When the two techniques are applied to apparel design, the understanding and application of practicality, comfort, and functionality should be deepened.
Intelligent optimization of process parameters and regulation mechanism for the preparation of water-based ink for polyethylene-polyvinyl acetate films
Authors: Yao Xiaoping 
Published: November 2024

Abstract
Ink is the printing industry’s most basic raw material, mainly composed of resin and organic solvents. However, these organic solvents not only harm the industry’s staff but also have a great potential for environmental pollution. In recent years, with the continuous modification of resin, the structure of new products in the ink category has also changed greatly. This paper first analyzes the basic principle of polyvinyl acetate to form water-based ink, based on the synthesis method of ink, water-based ink prepared through experiments, and put forward the corresponding ink performance testing and analysis methods. Subsequently, according to the proposed test method, the prepared water-based ink was analyzed in terms of performance and water absorption. Orthogonal tests were designed to optimize the ratio of poly (vinyl acetate) copolymerization raw materials. Then, the experimental data were processed to derive the optimization formula of the process parameters for the preparation of PVAs slow-release film, and finally, the mechanism of regulating the morphology and structure of PVAs core-shell ink was obtained. The ink water resistance test showed an increase in ink surface tension from 54.154 mN/m to 60.545 mN/m due to an increase in R. The average particle size of ink particles of different core layers was around 178 nm, which was less affected by the change of core layer, and the ink particle size of different shell layers ranged from 120-290 nm and increased gradually with the increase of shell layer.
Research on Data-Driven Visual Element Positioning and Brand Impact Analysis Methodology
Authors: Huang Xuan 
Published: November 2024

Abstract
Visual element positioning is the main soul of a brand, which can directly give the public the brand identity from the appearance impression and can play an icing on the cake for the enhancement of brand influence. In this paper, we collect consumers’ online review data and preprocess the data, extract the keywords of visual element positioning and brand influence using the TF-IDF algorithm, and then analyze consumers’ sentiment scores for each dimension using the sentiment value calculation method. Finally, a multiple-step regression model is constructed based on correlation analysis and data-driven analysis to analyze the relationship between visual element positioning and brand influence. The results show that there is a significant positive correlation between the visual element positioning of the sign and each dimension of brand influence (r>0, P<0.05). And the logo design (P=0.010<0.05) and auxiliary graphic design (P=0.000<0.05) in visual element positioning can have a significant positive impact on brand purchase tendency and brand identity. This paper shows that visual element positioning can promote the development of brand products, provide a reference for good and accurate image positioning of the brand, help improve the brand value and uniqueness, and then improve the brand influence.
Construction and Application of Online Learning Community for Teacher-Student Relationship Based on Online Classroom
Authors: Wang Haihong , Feng Lichun , Zhang Wen 
Published: November 2024

Abstract
The application of information technology in the education business makes the traditional education mode gradually withdraw from the stage of history, and the online learning classroom begins to emerge in the teaching field. This paper builds an online learning community classroom for teacher-student relationships by combining MVC architecture technology with various online learning modes in the online classroom. FIAS interaction analysis and multiple regression models are used to quantitatively analyze interactive behaviors and changes in teacher-student relationships. The online learning community classroom model of this paper improves the average grade of the experimental class by 3.15 compared with the control class, with a p-value of 0.015, which is less than 0.05, and there is a statistically significant difference in the data. The teaching model of this paper can adjust the structure of teacher-student speech in teaching, and the teacher changes from “teaching alone” to “discussing with teachers and students”, and the students’ speech improves by more than 10%. In addition, this paper finds that for every one unit change in subject and teacher, the teacher-student relationship changes by 0.135, 0.261, and for every one unit increase in the teacher’s “creation of learning groups for grouping tasks”, the teacher-student relationship improves by 0.364. Similarly, for every one-unit increase in the teacher-student verbal interaction, the relationship between the teacher and the student increases by 0.142, 0.364, and 0.364, respectively. In summary, through the design and practical application of the online learning community classroom model in this paper, the functions and effectiveness of the system have been verified, which basically meets the needs of teacher-student interactive teaching.
In-depth Analysis of the Positive Impact of the Organic Integration of Nonheritage Aesthetic Education and Art Healing on College Students’ Mental Health in the Age of Artificial Intelligence
Authors: Zheng Sheng , Chen Yuqun , Zou Jinding 
Published: November 2024

Abstract
In the increasingly competitive situation, college students are facing various pressures such as study, life, emotions, etc. It is highly probable that these pressures will have negative effects on both physical and mental health. In this paper, non-heritage aesthetic education and virtual interactive technology are respectively used as the driving force and model mechanism to construct an effective path for the organic integration of non-heritage aesthetic education and art healing, and the virtual interactive space integrating non-heritage aesthetic education is designed by using 3D max modeling technology and unity3d development platform. The changes in the mental health of college students were quantified by biofeedback measurement, happiness index scale, and psychological distress scale. The results showed that the alpha wave of the brain of the college students with low levels of psychological distress before and after the virtual interaction experiment gradually increased within 30 minutes, and the systolic and diastolic blood pressure decreased, indicating that they showed a state of relaxation and concentration during the interactive process of experiencing the non-heritage. In addition, there were highly significant differences (P<0.01) in the scores of study anxiety, loneliness tendency and physical symptoms of college students before and after the experiment of the subject college students, and the other dimensions of psychological distress were also well regulated. This paper shows that the integration of non-heritage aesthetic education and art healing has a positive effect on promoting the psychological health of college students to a certain extent and is of profound significance for contemporary colleges and universities to cultivate socialist successors with positive energy and responsibility.
Research on Intelligent Scheduling and Resource Optimization for Elderly Patient Care
Authors: Gui Haifeng , Ren Wenjing 
Published: November 2024

Abstract
The increasing demographic aging of society has led to the increasing demand for home health care services for the aging population. The planning and scheduling of home care pathways is a challenging problem in in-home medical care services. To this end, this paper proposes an improved hybrid immune genetic algorithm (HIGA) to design a least-cost medical care human resource scheduling strategy for the home care needs of elderly patients so as to provide high-quality home care services for elderly patients. It is tested with a genetic algorithm, modal factorization algorithm and simulated annealing algorithm to compare the arithmetic cases, and then HIGA is applied to find the optimal solution of the path and scheduling planning scheme of home care personnel for elderly patients. In all cases, HIGA has the best optimization effect on the model, and its optimal route cost is lower than the other three algorithms. Its variance is smaller than the other algorithms except for the R121_120 algorithm. This implies that the solutions generated by HIGA are superior and more uniform. The solution time of HIGA is less than 6 seconds in the path and scheduling planning problem of home caregivers for elderly patients in region M. The average total cost of caregivers to serve a single client point is 95, and the proportion of the time window penalty cost to the total cost is only 3.9%, which indicates that it is fast and the quality of its solution is higher, which is in line with the expectations of the decision-makers. This paper is of great significance in designing an effective care resource scheduling method to reduce the operating costs of home care agencies as well as to improve the quality of medical care services for elderly patients.
Research on the Application of Intelligent Algorithms in Preventive Damage Prediction and Diagnosis of Power Cable Channels
Authors: Guo Kang , Li Qian , Wang Siying , Zhang Jun , Zhang Zexin 
Published: November 2024

Abstract
In this paper, according to the definition of power cable channel damage and the actual situation, the vibration signals of mechanical excavation, crushing hammer construction, manual excavation and heavy vehicles passing by are selected as the initial data for the prediction of preventive damage of power cable channels. After completing the data collection, Variable Difference Modal Decomposition (VMD) is applied to reduce noise and obtain the IMF components. The eigenvalues such as energy entropy, cliff factor, waveform factor, center of gravity frequency and frequency standard deviation of each IMF component are extracted to form an eigenvector set, thus forming the data set for the study and analysis. The data set is divided into a training set and a test set according to the ratio of 8:2, and the long and short-term memory neural network is used to study the power cable channel damage prediction and diagnosis. The MAE in the single-step prediction of LSTM is 1.08, the MRE is 2.69%, and the RMSE is 1.39, and the prediction model in this paper is much better than the control prediction model, which indicates that the LSTM network can well predict the vibration of the damage of the power cable channel. It shows that the LSTM network can accurately predict and diagnose the signal trends and fluctuations caused by damaged power cable channel vibration.
Cross-border e-commerce oriented international logistics supply chain management model construction
Authors: Jia Shengqiang , Zhang Ke 
Published: November 2024

Abstract
This paper first introduces the lean supply chain international logistics management model and then determines the optimal conditions of the logistics supply chain for B2C enterprises through logistics service integrators and logistics service subcontractors. The paper then employs a combination of the factor analysis method and the factor rotation method to identify 17 key indicators that significantly influence the service quality of the international logistics management model for cross-border e-commerce. It then analyzes these relevant indicators and proposes targeted improvement countermeasures. The results revealed that the respondents have a high level of recognition for the 17 indicators that impact international logistics management, and their mean and standard deviation are stable. The results demonstrate that the first four factors can effectively explain the majority of the original data. Their eigenvalues are 8.157, 2.338, 2.132, and 1.045, and the variance contribution rates of their factors are 47.98%, 13.75%, 12.54%, and 6.14%, respectively, with the cumulative variance contribution rate explaining 80.41% of the original data. By combining the characteristics of the indicators, we identified four key factors: procurement, logistics and customs clearance, after-sale, and overall supply chain links. This study helps to better assist in the development of an international logistics supply chain management model oriented towards cross-border e-commerce.
Research on the application of data analysis technology and the mechanism of teaching effectiveness enhancement in sports training in colleges and universities
Authors: Cao Haibo 
Published: November 2024

Abstract
Data analysis technology can deeply analyze and fully mine the physical measurement data of college students to extract valuable information, thus providing data reference for teachers to improve teaching effectiveness. The article first researches the algorithmic process of the Apriori association rule algorithm, combines the transaction compression and hash technology and the Apriori algorithm to further optimize and improve Apriori, and finally applies the mechanism based on the improved data analysis technology in college sports teaching. This paper uses the improved Apriori algorithm to analyze physical test data of students in a college. In the 2021-2022 association rule, data mining results found that the “total score grade” passing students accounted for 74% of the students tested in that year, which can be obtained, the majority of the student’s physical test scores for the passing grade. After a period of a teaching experiment, the p-value of the four dimensions of students’ learning interest is 0.015, 0.048, 0.014, and 0.000, respectively, which is significantly different, thus indicating that the experimental group of students’ learning interest is significantly better than the control group.