bluuebunny/crossref_metadata_2025 huggingface dataset:
Chinese Natural Language Processing: From Text Categorization to Machine Translation
Authors: Peng Haitao
Published: July 2024

The level and volume of automatic computerized processing of linguistic information has become one of the most important criteria for measuring whether a country has entered the information society. The study begins with statistical linguistics and aims to process complicated Chinese information. In this paper, after establishing the word database of the Chinese language, the language model is smoothed and compressed, the Chinese character information and Chinese language information are extracted, and the processing of Chinese grammar and Chinese semantic information is emphasized. Among them, Chinese grammar processing includes Chinese word analysis and basic phrase analysis based on the maximum entropy model, and Chinese semantic processing includes Bayesian-based word sense disambiguation, semantic role labeling based on the conditional random field model, and thesaurus-based semantic similarity calculation method. In addition, SECTILE-based Chinese text categorization and statistical linguistics-based machine translation methods are explored and tested for their effectiveness in Chinese natural language processing. The results show that the total average check accuracy and check the completeness of Chinese text are 78.65% and 72.24%, respectively, and the BLEU values of the translation methods are improved by [1.62,3.73] and [0.93,5.01] compared with the Baseline method, which is able to process the Chinese information accurately. The research plays an important role in the process of information processing based on Chinese language processing.
Research on multi-sensor data fusion technology for underwater robots for deep-sea exploration
Authors: Zhao Haixiao
Published: July 2024

The ocean area occupies a large part of the earth’s area, how to use underwater robots to carry out deep-sea exploration tasks has become an urgent problem in the field of marine resources. In this paper, we design a small AUV underwater robot from five aspects: power supply, control motherboard, power, communication, and sensor. Due to the complexity of the underwater environment during deep-sea exploration, the sensors of the underwater robot need to be calibrated to facilitate data collection and acquisition. To acquire and process underwater image data, the robot uses optical and acoustic imaging principles. The bitmap algorithm is employed to construct a multi-sensor fusion model for depth detection, which is then analyzed for application. The underwater robot is basically able to reach the specified position quickly and smoothly according to the set motion, and its underwater robot infiltrating the bitmap algorithm (x-axis time of 89s, y-axis time of 98s, and z-axis time of 99s) is obviously faster than that of the traditional SLAM algorithm in terms of convergence speed. The underwater robot navigates approximately 400 m in advance of the deep-sea probe’s localization, which allows for fast and stable error convergence. This study meets the covertness requirements of underwater robots when performing detection tasks, and can achieve independent and autonomous navigation of underwater robots, which has a good application prospect.
Exploring the Intertwined Influence of Theater and Political Propaganda in the Southland Society Period
Authors: Tan Aiping
Published: July 2024

Drama, which has evolved over a millennium, is notably characterized by its subjective nature of propaganda in both form and content. This study focuses on plays created during the period of China’s South China Society, specifically within the context of the resistance war era. It examines these plays through the lens of political propaganda, analyzing their inherent characteristics influenced by the political milieu of the time. To delve deeper into the dynamics of political propaganda within the drama, the SIQS model was developed. This model facilitates an exploration of the impact of stochastic elements on the behavior of political propaganda, thereby illustrating the complex interplay between drama and political propaganda. The findings reveal that the apex of drama production under the influence of political propaganda occurred in 1943, a year that saw the publication of 126 high-quality dramas marked by their propagandistic content. During this period, the intertwined intensity between dramas and political propaganda reached a significant level of 0.706. By reflecting on these historical insights, the study offers valuable lessons for the current application of political propaganda by China’s ruling party, highlighting the potent role of drama as a medium for political communication.
A study of distribution grid topology and its optimization in planning and operation
Authors: Zhang Hui , Wang Zhixin , Li Xiao , Liang Yuting , Tian Wei
Published: July 2024

This paper combines the characteristics of a distribution network grid, analyzes the topology and application scenarios of a typical grid, and puts forward the design requirements for the optimization of radial DC distribution network grid structure. Based on the constraints of grid optimization, a Pareto multi-objective planning method is selected, and a multi-objective genetic algorithm is designed to improve the grid reliability index of the distribution network grid planning steps. Analyze the parameters of the example, encode the initial 110kV distribution network frame, carry out the optimal solution of the multi-objective genetic algorithm, compare the iteration number and convergence of different genetic algorithms, and obtain the best economic effect of the optimization of the distribution network frame structure. Analyze the power supply reliability index of distribution networks with different grid switching schemes and explore the degree of reliability influence on grid switching and power supply capacity. The optimal solution is obtained in 10 iterations of the algorithm, that is, the objective function is 65.2421 million yuan, and the optimal solution is reached in the interval of the number of iterations [0,100], and the fitness value is in the range of 2 × 104 million yuan.
Study on the Current Situation and Countermeasures of Young College Students’ Participation in the Construction of Rural Culture in Ethnic Areas--Taking Yulin Normal College as an Example
Authors: Chen Ling
Published: July 2024

In recent years, with the full implementation and steady advancement of the rural revitalization strategy, the topic of young college students and the construction of rural civilization has become a popular research direction. In this paper, we summarize the information collected in the previous period, design a questionnaire for young college students to participate in the construction of rural culture in ethnic areas, and test the reliability of the questionnaire by combining the KMO value and Cronbach’s alpha coefficient. The questionnaire was designed to be distributed to Yulin Normal College to collect relevant data, and the survey data was statistically analyzed using Excel and SPSS software. The survey results showed that only about half of the college students surveyed participated in the construction of rural culture in ethnic areas. The number of young college students who expressed general concern for the construction of rural culture was 264, which indicates that their participation level was not high. The survey and analysis of the influencing factors found that the employment mentality of the personal factors and the extra points or priority admission policy of the institutional factors have a greater influence on the participation of young college students in the construction of rural culture in ethnic areas. The paper establishes a basis for improving the participation of college students in rural culture construction, and the countermeasure program proposed for the survey results serves as a reference for relevant government departments.
Construction and application of a performance assessment model for teaching operations research based on Bayesian network technology
Authors: Cheng Yuandong
Published: July 2024

Operations research plays a pivotal role in fostering effective management, sound decision-making, and modern management practices. Its significance in the academic realm, particularly within higher education, is increasingly acknowledged. This study leverages a Bayesian network to introduce a Markov chain, thereby constructing a dynamic Bayesian network-based model for evaluating the teaching performance of operations research. Initially, a questionnaire survey method was utilized to make preliminary adjustments to the performance evaluation index system. Subsequently, various methods, including the principle of halves and the coefficient of variation, were applied for coarse and fine screening of indices, culminating in the development of a comprehensive index system for evaluating operations research teaching performance. The efficacy of the constructed model and index system was tested by assessing the performance of five operations research instructors. Key metrics such as teaching performance, student trust, and student interest were assigned the highest weights, with respective values of 0.153, 0.127, and 0.114. Notably, Teacher D achieved the highest total performance score of 9.051, surpassing the other four instructors. The assessment results obtained from the designed model are closely aligned with those derived from fuzzy clustering techniques, underscoring the model’s robustness and applicability. Thus, the performance assessment model and index system designed for operations research teaching work demonstrate substantial practical effectiveness.
Analysis of international trade transportation strategy of logistics under game theory model
Authors: Tang Yuzang , Zhang Fangfang
Published: July 2024

It is of great significance to build a modern comprehensive transportation system and coordinate the development of various modes of transportation for economic development. This paper introduces the game theory model into the logistics international trade transportation strategy problem, establishes the Stackelberg game model, takes the transportation cost, transportation time, external cost, transportation security as the evaluation index, uses the DHGF comprehensive algorithm to decouple, and constructs the logistics international trade transportation model based on the game theory. The selection of container transportation from place A to five other locations is an example of a quantitative analysis of different transportation options and strategies in logistics international trade transportation under various demands. The optimal path is based on the demand of managers to control the external cost of 27,500 to 31,900 yuan, the demand of consumers of high-value goods to control the cargo damage rate of 1.43% to 1.59%, the optimal path of the demand of operators for the more economical railroad transportation. The final utility evaluation of the optimal path of this paper’s model is 0.18%~3.99% higher than the comparison model. The results show that the model in this paper can effectively provide a higher utility optimization scheme and route reference for international trade transportation path optimization under different demands of participants.
Evaluation method of e-government audit information based on big data analysis
Authors: Zhang Lei
Published: July 2024

In order to improve the problems of low efficiency of intelligent auditing and long approval cycles in the evaluation of e-government audit information, this paper proposes a model for the evaluation of e-government audit information. The model covers the acquisition of audit information, evaluation rules, and e-government auditing. The intuitionistic fuzzy roughness model is applied to determine the distinguishing relationship between objects based on the intuitionistic fuzzy values of different objects and to determine the evaluation rules for audit information. An e-government auditing approach based on big data analysis is also proposed, and a genetic algorithm is used to optimize the relevant parameters of a convolutional neural network to enhance the stability of the e-government auditing model. Audit information evaluation activities are carried out at Changchun Housing Provident Fund Center in Jilin Province, China, whose shared approval information data failure records in 2023 accounted for as high as 70.54% of all documents, with low stability. The number of cases and closure of the provident fund center accepting the extranet from 2017 to 2023 only accounted for 4.57% and 3.99% of the whole. In the audit information evaluation indicators, nine secondary indicators, such as credit management and indirect income, have an evaluation value of more than 0.5 in the “medium” evaluation level, and many indicators have an evaluation value of more than 0 in the “poor” evaluation level, so there are many shortcomings in the business.
Innovation of Talent Cultivation Path for Preschool Education Majors in the Internet Era
Authors: Gu Zhenglin
Published: July 2024

Under the wave of the Internet era, the traditional preschool education professional talent cultivation mode is experiencing profound changes. The cultivation of innovative preschool education professionals’ talents has become an important issue. The study proposes the collaborative cultivation path of preschool education professionals. It analyzes the effectiveness of collaborative cultivation of preschool education professionals and the influencing factors of cultivation effectiveness through factor analysis and multiple linear regression analysis. The results show that the five common factors extracted from the measurement indexes of the collaborative cultivation path of preschool education professionals can explain 89.006% of the overall variance, and the results of the factor analysis of the cultivation objectives are relatively satisfactory. Among the first-level indicators, the strongest correlation with cultivation effectiveness is the management system, with a correlation coefficient of 0.235, and the weakest correlation is the curriculum construction, with a correlation coefficient of 0.186. Finally, the formula of the multiple regression model for the synergistic cultivation of preschool education majors is as follows: cultivation effectiveness = = 1.525 + 0.145*cultivation objectives + 0.225*management system + 0.105*curriculum construction + 0.143*Teaching system + 0.198*Quality evaluation. The talent model created in this study has a significant positive impact on the development of preschool education talents.
Research on the Enhancement of Innovation and Entrepreneurship Ability by the Use of New Media Technology
Authors: Wang Haohe , Huang Qing , Zheng Zihao , Jiang Yuqi , Xing Yimeng
Published: July 2024

The emergence of new media technology offers a significant opportunity to enhance innovation and entrepreneurship. This paper explores the underlying mechanism of this enhancement through statistical analysis. A theoretical correlation framework identifies relevant variables for the study and proposes appropriate measurement methods. A regression model, centered on partial least squares and incorporating principal component analysis, is constructed to address multicollinearity issues via residual analysis. Following the preliminary work, research samples from various regions were selected, data was collected, and input into the model, and the results were verified and discussed. The findings indicate a positive and significant correlation between “teaching practice” and innovation and entrepreneurship abilities. The regression results show that the “teaching practice” variable significantly positively affects innovation knowledge competence (β = 0.783, P < 0.05). Other dimensions also positively impact innovation knowledgeability, and the PLS model has been fully validated.
Construction of personalized genomics model and clinical application in precision medicine
Authors: Li Haoyu
Published: July 2024

Sequencing technology continues to evolve, and pharmacogenomics is increasingly pivotal in the pursuit of personalized medicine. This study delineates the personalized genomics model into two core modules for framework construction: data preprocessing and prediction. Within the data preprocessing module, a denoising submodule and a genomic feature distribution alignment module are dedicated to processing the genomic features associated with diseases and assimilating them into the spatial feature distribution of the model. The prediction module employs a fully connected neural network alongside a graph convolutional neural network to forecast drug dosages based on the disease's genomic features. We propose clinical applications of personalized genomics models across three distinct pathways. To assess the practical impact of these models, experiments were conducted focusing on their clinical application. After 14 days of medication administration, the International Normalized Ratio (INR) value for the drug model group reached 2.67, surpassing that of the conventional treatment group, with nearly 60% of participants achieving the target range. Furthermore, in evaluating the safety and efficacy of the clinical application of the genomics model, the incidence of serious bleeding events in the drug model group was recorded at 16.67%, which is below the standard allowable probability of 23.81%. Therefore, the personalized genomics model introduced in this study meets the established safety and efficacy standards.
Research on Strategies of Digital Media in Shaping and Communicating City Image--Text Mining and Sentiment Analysis Based on Image Communication
Authors: Wang Nanting
Published: July 2024

Shaping and spreading a good city image can effectively improve the comprehensive strength of the city, promote investment attraction, promote the development of the tourism industry, and help social civilization and harmony. The research utilizes the TextRank algorithm for text mining of city images. Construct an emotional analysis model for city images, using the calculation of emotional tendencies, to make a comprehensive evaluation of the city’s image communication. For example analysis of Hangzhou city, the overlap rate of high-frequency words between city officials and tourists on Hangzhou’s city image reaches 43.3%. The two perceptions of the imagery of Hangzhou are both cross and different, and the overall satisfaction score of tourists in Hangzhou is 3.84 points. Most of the tourists in Hangzhou commented positively, and the percentage of positive, neutral, and negative sentiment comments accounted for 81.17%, 4.50%, and 14.33% of the overall, respectively.
Deep learning in the assessment of movement disorders in Parkinson’s disease
Authors: Li Yumeng , Chen Zixuan , Deng Yulin
Published: July 2024

Movement disorders are the main symptoms of neurological diseases such as Parkinson’s disease and deep learning-related methods can provide some intelligent solutions for the assessment and diagnosis of Parkinson’s movement disorders. In this paper, we propose a Kinect-based movement disorder assessment and analysis method, which uses the Kinect algorithm to capture and inverse kinematics analysis of human skeletal points, and further suggests the study of movement disorder assessment method based on dynamic time regularization algorithm so as to further achieve the effect of movement disorder assessment. Through the clinical experimental research on Parkinson’s disease patients and healthy subjects of the same age group, the use of the algorithm proposed in this paper is 15.18% higher than the GaitSet method in the CL state. The error of the algorithm proposed in this paper in the experiments comparing the gait parameter with the gold-standard motion capture system is close to 0.03s, which is a better improvement and upgrade compared with the advanced skeleton-based methods. In summary, the algorithm proposed in this paper is valuable and feasible for use in the assessment of Parkinson’s dyskinesia.
Risk screening of large reservoir bank slopes based on deformation monitoring using InSAR technology-A case study of the Baihetan reservoir bank
Authors: Shizheng Wang , Tingxuan Chen , Chen Chen , Anchi Shi , Xiaohui Chen , Liuyuan Zhao
Published: July 2024

The large reservoirs in the southwestern Alpine Canyon region are characterized by long reservoir banks and complex geological structures. The problem of finding the deformation zone quickly and efficiently is urgent and needs to be resolved. In this study, taking the area 110 km upstream of the Baihetan dam site as the study area, the applicability of various interferometric synthetic aperture radar (InSAR) techniques was summarized, and the small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) method was used to carry out large-scale disaster risk screening using multi-source satellite SAR data. A total of 40 hidden danger points were identified, with 22 of them being newly discovered. The differences in the deformation results from the multi-source satellite SAR data were discussed. By analyzing ComparSAR-based deformation monitoring results of a large reservoir, a new risk screening method for slopes in alpine-canyon regions can be provided.
The Analysis of AI Productivity and Its Implications for the Training of Students in Higher Vocational Colleges
Authors: Chen Laifang
Published: July 2024

Data mining as a data analysis technology is becoming more and more widely used in the field of education. The article firstly studies the theory of data mining technology under the analysis of AI productivity, proposes an improved algorithm of Apriori to improve the mining speed of association rules, and finally proposes a model of student cultivation in higher vocational colleges and universities based on relevant theoretical research. Under the guidance of the model and assumptions, a higher vocational college in Zhejiang Province is used as the research object to verify the effectiveness of the algorithm and model proposed in this paper and to analyze the relationship between student cultivation, student performance, and student employment. By using association rules and other methods to mine student employment data and calculate the factors affecting student employment, such as the province of the employment unit, the type of city of the employment unit, the student’s major, and the student’s place of origin. From this, it can be concluded that data mining technology can provide many effective data analyses for the cultivation of students in higher vocational colleges and universities through fair and objective statistics and analysis in order to better promote the talent cultivation program of higher vocational colleges and universities.
Rural health intervention research based on public participation: the application and effect evaluation of smart media
Authors: Gao Zhenghan , Zheng Anzhu
Published: July 2024

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

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

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

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

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

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

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

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

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

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

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

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

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.
Study on Cultural Change and Adaptation of Media Talents in Film, Television and Art Media Driven by Emerging Technologies
Authors: Tian Chang
Published: July 2024

Emerging media technologies, epitomized by short video intelligent recommendation algorithms, are catalyzing substantial transformations within the realm of film and television culture. This study delves into the secondary creation of film and television works facilitated by algorithmic recommendation technologies. Specifically, it introduces a novel short video intelligent recommendation algorithm founded on deep learning principles. This algorithm harnesses joint features derived from the scene and behavioral attributes of target short videos, employing a graph convolutional neural network to model the long-term and short-term preferences, thereby enabling intelligent recommendations for the secondary creation of film and television works. Further, this research designs and implements questionnaires to formulate research hypotheses and conducts surveys targeting both general film and television audiences and industry professionals. The objective is to scrutinize the profound alterations instigated by emerging algorithmic recommendation technologies in film and television culture and to assess the adaptability and acceptance of these changes among media practitioners. The findings reveal that both explicit personalization (t=9.26, P<0.001) and implicit personalization (t=8.107, P<0.001) significantly enhance the immersive experience of viewers. The application of such technologies has rendered film and television audiences more discerning in their evaluation of various aspects of media productions. Notably, film and television media practitioners aged 30 years or older exhibit a more favorable disposition towards algorithmic recommendation technologies. This investigation not only underscores the significant impact of algorithmic recommendation technologies on film and television culture but also proposes new avenues for the seamless integration and innovative development of film and television media with information technology.