bluuebunny/crossref_metadata_2025_split huggingface dataset:
Rural health intervention research based on public participation: the application and effect evaluation of smart media
Authors: Gao Zhenghan , Zheng Anzhu 
Published: July 2024

Abstract
Public participation serves as a critical component of rural health interventions and epitomizes the full realization of people’s democracy. Consequently, it is essential to tailor rural health construction based on public feedback. This study introduces an opinion mining model based on Long Short-Term Memory (LSTM) networks, designed to extract public opinions from intelligent media platforms. The methodology includes data preprocessing through text filtering, word segmentation, and lexical tagging to prepare the data for analysis. To enhance the model’s performance and avoid overfitting, dropout techniques were employed during training. Opinion classification was subsequently performed using a softmax function. Initial findings from the opinion mining process indicated that 38.29% of the analyzed comments expressed a negative view of rural health conditions. Following targeted interventions to address areas receiving low sentiment scores, a notable improvement in perceptions was observed. Specifically, the sentiment score concerning the attitudes of healthcare workers in the village increased by 14.75%. Additionally, enhancements in waste management practices led to a 19.34% increase in the related sentiment score, contributing to an overall rise of 19.85% in positive public sentiment. These results underscore the efficacy of employing this LSTM-based opinion-mining approach in fostering improvements in rural health environments through informed public participation.
Artificial intelligence-driven performance space design and virtual reality interaction model
Authors: Wu Xinjing 
Published: July 2024

Abstract
The evolution of stage design is fundamentally linked to advancements in modern science and technology, which, in turn, catalyze further opportunities for innovation in this field. This study meticulously explores the potential of artificial intelligence in enhancing performance space design and introduces an advanced visual design system tailored for performance spaces underpinned by virtual reality technologies. To facilitate accurate three-dimensional modeling of performance spaces, this research adopts the generative adversarial network (GAN) training mechanism, incorporating point cloud data as a direct input to enhance network architecture. This approach innovatively integrates a multi-resolution point cloud completion network structure that leverages fused graph attention features. Furthermore, to streamline model complexity, an inverse residual network is employed. Alongside this, a novel semantic segmentation method tailored for 3D scenes utilizes a self-attention mechanism, demonstrating significant advancements in the field. Through comparative experiments and the construction of 3D scenes, the study evaluates the efficacy of the proposed design model. The findings reveal substantial reductions in the Chamfer Distance (CD) mean—ranging between 43.75% to 67.47% for the residual point cloud and 40.68% to 67.89% for the complete point cloud—significantly outperforming three alternative algorithms. The semantic segmentation method further showcases enhanced precision in building 3D scenes, achieving an average intersection ratio of 47.33% and a pixel accuracy of 76.05%. Collectively, the experiments corroborate that the model developed in this study not only surpasses traditional models in terms of innovation but also meets the stringent real-time and accuracy standards required for engineering applications.
Visualization of Basketball Tactical Evolution in Generative AI Big Models for Teaching and Learning
Authors: Liu Zhuoxiao 
Published: July 2024

Abstract
Basketball tactics teaching occupies a major position in both professional sports teams and schools, even in social basketball training institutions. The paper suggests an improvement plan based on the shortcomings of the generative AI grand model, and integrates the enhanced model into the basketball tactics teaching process to create a visualization method for basketball tactics evolution. The proposed teaching model was applied to students’ basketball tactics training courses, and the use of the teaching experiment was investigated by using comprehensive research methods such as questionnaire survey method, paired-sample t-test, and one-way ANOVA, with students majoring in physical education in GT College as the experimental subjects. The results showed that the individual offensive and defensive tactics, local offensive and defensive tactics, and team-wide offensive and defensive tactics of the students in the experimental group and the control group were significantly improved after the experiment relative to the pre-experimental period and that the improvement of the experimental group (9.655-13.989) was more significant than that of the control group (4.844-6.515), and that the experimental group assisted with the basketball tactics teaching model based on the generative AI was more effective than the control group assisted with traditional tactics training method. Control the group using the conventional tactical training method. The study provides a reference for the implementation of teaching reform and improvement of teaching quality in the process of teaching basketball tactics in the future.
Research on the training of tennis players’ serve speed improvement based on the OPT model
Authors: Bian Jin 
Published: July 2024

Abstract
The OPT model is an efficient training model that is convenient and highly operational and can provide a scientific training program template for tennis players’ physical training. In this paper, six kinds of physical training contents, including warm-up training, core/balance/rapid extension compound training, speed training, agility and quick reaction training, resistance training, and relaxation training, were developed according to the structure of the OPT model. In order to better regulate the training process, the tennis players monitored their body indicators in real time by wearing smart wearable devices during the training process. In order to digitally scan the collected data, this paper processes the physical training data under the OPT model based on time-series data mining, and finds out certain patterns that show periodic appearance in the time-series database through the DTWP algorithm. The OPT model training resulted in a significant improvement in the physical performance of tennis players through the experimental study. Before and after the measurement comparison of athletes’ tennis serve speed, the tennis players’ serve speed after OPT model training under digital monitoring, compared with the tennis players’ serve speed under traditional physical fitness training, had a significant improvement in the relevant indicators, in which the p-value of the average speed of the first zone serve and the average speed of the second zone serve were 0.043* and 0.043*, respectively, and a statistical difference appeared. It proves that OPT model training can have a positive effect on tennis players’ serve speed.
Research on Corporate Governance and Internal Audit Wisdom Building under Financial Sharing Model Based on Logistic Modeling
Authors: Wu Hongli 
Published: July 2024

Abstract
In recent years, the assessment of corporate financial risk has become increasingly significant for banks. Therefore, studying models for corporate financial risk assessment holds substantial practical importance. This paper combines the Logistic model and the Lasso model based on their basic principles to construct an improved Lasso-Logistic regression model. Immediately after that, this paper selects 15 representative indexes from the four aspects of the enterprise’s profitability, solvency, operating ability, and growth ability as the indexes to respond to the company’s financial situation and extracts 4 public factors after factor analysis and analyzes them using the Lasso-Logistic regression model designed in this paper with these 4 public factors as the variables. The results show that the coefficients of public factors F1, F2, F3, and F4 are -2.9513, -1.8347, -1.9659 and -2.2714, respectively, and the coefficients of the four public factors are negative, and the classification accuracy of the Lasso-Logistic combination model in this paper is 89.46%, the misclassification rate of the first category is 6.21%, and the F1 score, RS2 score and AUC values are overall better than the two single models of Lasso and Logistic, the Lasso-Logistic model designed in this paper can well help enterprises assess their own financial risk and make targeted decisions.
Model Construction and Implementation Strategies of Civic Education in Colleges and Universities under the Influence of Social Media
Authors: Tang Wenyan 
Published: July 2024

Abstract
The rapid development of social media and information dissemination has profoundly affected the ideology and value orientation of college students and put forward new challenges and requirements for ideological education work in colleges and universities. This paper takes the characteristics of social media as an orientation, studies the problems of ideological education in colleges and universities, and carries out a SWOT analysis of ideological education under the influence of social media. Based on social media, we constructed a complex network, gave a measure of its network topological characteristics, and then combined it with the classical information dissemination model to establish a SEIR information dissemination model of Civic and Political Education in colleges under the influence of social media. Taking the “Tang Palace Night Banquet” in Province H and the Civic and Political Education Skills Competition in University H as research objects, we analyzed the characteristics of the social network of Civic and Political Education information and verified the explanatory ability of the SEIR model in the dissemination of Civic and Political Education information in colleges and universities. People’s Daily has the highest incidence value and middle centrality of 63 and 72 in social media networks, and its middle centrality is 28.57% higher than that of Henan Satellite TV. The SEIR model tends to stabilize on the 180th day of the evolution, when the refusers of the dissemination of information on civic and political education are 700, and the disseminators are 300. Social media can expand the content of Civic Education in colleges and universities, combined with diverse star network nodes, can enhance the ability of Civic Education in colleges and universities, and improve the level of students’ Civic Education.
Color Use and Psychological Feeling in Modern Interior Design - Based on Emotional Calculation Perspective
Authors: Dong Jian , Qin Lan , Han Shilong , Wang Zhanpeng , Chen Junyue , Liu Xiaochen , Xu Jiaxin , Zhang Xiyuan 
Published: July 2024

Abstract
In this paper, the HSV color space model is used to collect the color characteristics of modern interior design and classify them into three types: hue (H), saturation (S), and luminance (V). At the same time, it combines with the theory of color psychology to construct a PAD emotion model for interior design. Then, it selects experimental samples and data analysis tools to carry out an example analysis of interior design from the emotional perspective. The data show that the selection of people warm and bright color interior design in the interior design of the background color across the amplitude of the largest and more concentrated in the 47.5°, the main body color across the amplitude of the smallest and most stable, the accent color value of the whole relatively high, the highest 123.6°, the background color saturation is the highest of 34.6°, and the brightness of more than 63.9°, the overall presentation of the warmth of comfort indoor environment. Error-values were 0.004, 0.0698, and 0.038 in order, with the errors all below 10%. This study integrates psychology and color into interior emotional design to better create visually appropriate, comfortable, and culturally rich interior environments for people, and also to promote the development of the interior design field.
Research on the Teaching Mode of English in Colleges and Universities by Integrating Excellent Traditional Chinese Culture from the Perspective of Multimodal Discourse
Authors: Geng Yanmei 
Published: July 2024

Abstract
Integrating excellent traditional Chinese culture into English teaching in colleges and universities can enable students to acquire the ability to express traditional culture in English, which is of practical significance for cultivating students’ cultural self-confidence. The article takes the excellent traditional Chinese culture as an orientation, studies the specific path of its integration into English teaching, and establishes a flipped classroom English teaching model by combining it with the SPOC teaching platform. Taking the sophomores of non-English majors at University T as an example, we chose the canonical books of excellent traditional Chinese culture as the teaching content and studied the specific effect of the integration of excellent traditional Chinese culture into English teaching in colleges and universities through the method of teaching experiment. After conducting the teaching experiment, students’ independent learning needs increased from 11.56 to 14.78, and the mean value of pre-course knowledge preview increased by 27.62%. The traditional culture awareness test score of students in class A was 48.64±5.24, which was 7.22 points higher than that of class B. The mean value of students’ attitudes and perceptions towards English teaching with excellent traditional Chinese culture was 3.974. The effective integration of excellent traditional Chinese culture and English teaching in colleges and universities can effectively promote the generation of students’ traditional cultural awareness and help to enhance students’ intercultural communication skills.
A Study of Measurement Modeling of Decision Trees in Machine Learning Processes
Authors: Li Guo , Qin Yi , Wang Minghua 
Published: July 2024

Abstract
Accompanied by the rapid development of economy and science and technology, the ordinary measurement model with a single method of parameter determination and accuracy is not guaranteed, which has made it difficult to adapt to the measurement needs of complex data in industrial engineering and other systems. This study proposes a measurement model for complex data through the optimization of decision trees in the process of machine learning. Firstly, the gradient-boosting-based decision tree measurement model (GBDT) is constructed by analyzing the decision tree model, and then the model is solved. At the same time, latent variables were included in the model, SEM described the reflection relationship of explicit variables to latent variables, and the GBDT optimization model, including latent variables, was constructed by using the results of the model measurement, including latent variables. Then, for the measurement of multivariate data, the fusion convolutional network was used for image data feature extraction, and the combined measurement model with multi-source data fusion (MDF-DTFEE) was constructed on the basis of the decision tree measurement model. In the empirical analysis of the measurement model, the predicted and actual values of the model training were fitted between 4~60 mg/L and 5~45 ml/L, respectively, and its R² on the training set and test set were 0.948 and 0.886, respectively, with the RMSE lower than 1.2, and none of the MAPE exceeded 0.2. The practical application always had an error range of 1 mg/L, which is in line with the requirements. It fulfills the practical application requirements, demonstrates the practical value of the measurement model in this paper, and provides a useful solution for measuring complex data.
Diversified Optimization of Vocal Singing Teaching Mode in Colleges and Universities under Multi-sensory Audiovisual Integration
Authors: Ma Yu 
Published: July 2024

Abstract
As an important part of higher education, vocal teaching bears the important mission of cultivating future vocal talents for society. Through the integration of a variety of vocal singing teaching modes, the research develops a diversified vocal singing teaching mode that incorporates multi-sensory audio-visual. On this basis, vocal music enthusiasts were selected as the experimental subjects, and after being divided into three groups with comparable levels of vocal singing, the three vocal singing teaching modes were compared in the teaching experiment. After the experiment, the students’ vocal singing effects under the three modes were empirically analyzed, and the students’ experiences under the diversified vocal singing teaching modes were further explored through questionnaires to investigate the promotion effect of the diversified vocal singing teaching modes on vocal singing learning. The analysis shows that the diversified vocal singing teaching mode is better than the other two teaching modes, and its effect on the students’ breath change, breath use, word biting, understanding of the work, and expression movements during singing is 100%. At the same time, more than 90% of the students were satisfied with the teaching method, and more than 60% of the students agreed that the technique had improved their learning abilities and interest. The development needs of vocal singing majors in colleges and universities can be met through the use of a diverse vocal singing teaching mode, which is an important channel for vocal singing teaching in colleges and universities to connect with the future.
Granting and Limiting Divorce in Ancient China in the Context of Big Data Technology
Authors: Pei Baoli , Wang Wei 
Published: July 2024

Abstract
Divorce has been a significant societal issue since antiquity, warranting careful scholarly attention. The evolution of divorce systems from ancient times to the present day mirrors broader societal, ideological, and marital transformations. This paper presents an analytical exploration of the social implications of ancient divorce legislation through the lens of four historical divorce models. By assembling a corpus of ancient divorce texts and employing the vector space model for data representation, this study leverages the TF-IDF algorithm for keyword extraction. Subsequently, it utilizes a keyword co-occurrence network to scrutinize pivotal elements within the ancient divorce systems. Furthermore, the study employs the Latent Dirichlet Allocation (LDA) model to investigate the thematic evolution of these systems. Analysis of the corpus reveals that the term “separation” appears 513 times, underscoring its prevalence. The keyword co-occurrence network exhibits a point degree centrality of 0.523, indicating significant interconnectivity. The principal legal term, “shall,” occurs 68 times, reflecting its normative importance. Notably, the study identifies subtle variations in legal stipulations across different dynasties, primarily concerning changes in the grounds and moral considerations for divorce. These historical divorce systems were profoundly influenced by the dynamics of marital relationships, as well as patriarchal, familial, and societal constraints. This historical perspective offers valuable insights for contemporary marital law implementations, suggesting a nuanced understanding of divorce’s legal and social dimensions.
Research on Strategies for Cultivating Piano Players’ Psychological Quality in the Information Age
Authors: Shi Liuwanyue 
Published: July 2024

Abstract
Psychological quality directly affects the playing level of a piano player’s ability. In this paper, we use the advantage of multi-source data information fusion to extract multiple physiological signal features of the piano player, combine with RBF kernel function to optimize the SVM emotion recognition, and form the DBN-SVM-based performance emotion state recognition algorithm. The initial feature set of physiological signals is established, the feature selection results for various classification tasks are examined, and the statistical data on effective features are obtained. The recognition of three emotional states of calmness, fear, and pleasure is done, and relevant strategies are proposed to cultivate good psychological qualities in players. The accuracy rate of emotional classification of the subjects is analyzed, and the accuracy rate of different subjects is more than 77.50%, indicating that the classification effect is evident. The psychological characteristics of the performers were clarified to facilitate the implementation of corresponding cultivation strategies.
Citespace-based Knowledge Mapping to Analyze the Hot Spots and Frontier Research on the Integration of Excellent Traditional Chinese Culture into English Teaching in Colleges and Universities
Authors: Geng Yanmei 
Published: July 2024

Abstract
The orderly development of educational reform in colleges and universities has provided sustained impetus for the integration of excellent traditional culture and education. English education, as a crucial component of modern education, has also become a focal point for cultural integration. This study focuses on integrating excellent traditional Chinese culture into English teaching in colleges and universities as the research object, constructs a knowledge map using Citespace, and establishes a knowledge ontology model based on data analysis. Afterward, we established the overall structure and process of central computing tools and analyzed the keywords of excellent traditional Chinese culture for their application in English teaching. Upon analyzing the research on the integration of excellent traditional Chinese culture into English teaching in colleges and universities, we found that, as of the statistical cut-off date of 2020, 733 articles had been published in related research, with master and doctoral theses and core journals publishing the highest number of articles annually, at 89 and 15 respectively. We can divide the annual publication volume of related literature into three historical stages: the rapid development stage, the decline stage, and the steady development stage. The analysis of research hotspots and frontiers reveals that countermeasures (0.75), cultural integration (0.44), and innovative education (0.36) rank as the top three keywords in terms of centrality. The experiment concluded that the hot spots and frontiers of research on the integration of excellent traditional Chinese culture into English teaching in colleges and universities primarily focus on innovation and reform, as well as cultural integration. These areas will continue to influence relevant research in the field of English teaching for some time to come.