bluuebunny/crossref_metadata_2025_split huggingface dataset:
Chinese Natural Language Processing: From Text Categorization to Machine Translation
Authors: Peng Haitao 
Published: July 2024

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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.