bluuebunny/crossref_metadata_2025_split huggingface dataset:
Construction of urban livability evaluation index system by principal component analysis combined with entropy value method
Authors: Yang Jiaoshi 
Published: April 2024

Abstract
As cities become central hubs for human civilization and economic activities, enhancing urban livability is a critical challenge amid rapid global urbanization. This paper introduces a novel evaluation framework for urban livability, merging principal component analysis with the entropy value method. Focusing on economy, culture, ecological environment, infrastructure, and social welfare as critical dimensions, we develop and empirically test livability indices using Province M as a case study. Results reveal a significant cumulative variance contribution of 97.511% across the dimensions, with Province M’s livability score improving from 3.8 in 2015 to 4.7 in 2022, marking an overall increase of 0.8091. This research offers valuable insights into assessing and enhancing urban livability.
Research on the Application of Blockchain Technology in the Carbon Trading Market of Substations
Authors: Liu Shasha , Liu Jun , Li Yuelong , Zhou Cong , Wang Congli 
Published: April 2024

Abstract
This study examines the entire lifecycle carbon emissions from the construction of substations, emphasizing the demand response from the carbon emission trading market. We use blockchain technology to establish an intelligent contract framework to manage and control substation configurations within digital substations’ physical environments. Based on Blockchain, a regional substation intelligent control model is developed to facilitate optimal decision-making in the carbon trading market. Simulation analyses reveal that adjustments in capacity to 150MW can enhance the peak range from 041.2% to 042.0%, indicating a 0.8% improvement in efficiency. Additionally, this research assesses the carbon emission savings, correlating the volume of carbon transactions to the verification time, particularly noting a significant increase in time cost within the first 200 transactions. This paper contributes to understanding how digital technologies can optimize carbon emissions management and energy savings in substation construction.
Research on the Construction of Campus Security Prevention and Control System Based on Internet of Things Technology
Authors: Peng Yuanru , Hu Li 
Published: April 2024

Abstract
Campus safety is related to the healthy growth of students, and the research focus of this paper is to explore the impact of Internet of Things (IoT) technology on campus safety prevention and control. Based on the correlation between ISM and DEMATEL methods, this paper constitutes an integrated DEMATEL-ISM model by using neighbor matrix and reachable matrix to transform each other. It constructs a risk factor model for campus security prevention and control evaluation based on Internet of Things technology according to the modeling steps after soliciting experts’ suggestions through questionnaires. Combined with the SEM model to estimate students’ campus risk identification ability, the path index was used to construct the college security awareness score index to explore the relationship between latent variables (influencing factors) and observed variables (risk identification ability). The results show that every 1% increase in the safety climate of the social environment will lead to the rise of 0.58%, 0.20%, and 0.52% in the on-campus environment factor, the campus safety management team building factor, and the students’ literacy factor, respectively. A 0.17% increase in the on-campus environment will occur with every 1% increase in students’ literacy in higher education. This study contributes to a deeper understanding of the role of IoT technology in enhancing campus security prevention and control. It can provide deep research references for subsequent risk grading evaluation, risk warning prevention and control, and supervision in campus risk management.
Improved YOLOv5s Algorithm for Target Detection in Highlighted Field Camera Surveillance Images
Authors: Sun Dan , Liao Zhiwu , Zhou Zhimin , Zhang Lei , Wu Wenfeng 
Published: April 2024

Abstract
The complex and changing environment in the field brings a more significant detection challenge to camera surveillance. This paper proposes target detection in camera surveillance images using the improved YOLOv5s algorithm for target tracking in surveillance images. Firstly, to address the weak feature extraction ability of YOLOv5s for small-scale and overlapping targets, the feature extraction performance of YOLOv5s is improved by combining the attention mechanism and substitution loss function in the deep learning network to improve the feature extraction performance of YOLOv5s for target detection in field camera surveillance images. Then, to test the improved algorithm’s performance, the improved algorithm in this paper is compared with SSD, Faster R-CNN, and YOLOv5s detection methods, and performance comparison experiments are done on the basis of the dataset. The results show that the average detection accuracy (MAP) of the algorithm in this paper is improved by 19%, 14.5% and 6.3% than SSD, Faster R-CNN, and YOLOv5s, respectively, and the average speed of detection is 324 FPS, the accuracy is improved, the detection is faster, and for the YOLOv5 m with DA and PT has a higher AP than the other models in this paper. This study enhances the scalability of YOLOv5s algorithm in complex environments, which is crucial for advancing image target detection.
Detection of antibiotic resistance mechanism and research on new anti-infection measures based on big data analysis
Authors: Ji Yan , Jiang Xiuling , Wang Dongyan 
Published: April 2024

Abstract
In this paper, a prototype network model is used for event extraction of antibiotic resistance and new anti-infection information, and also limited or small amount of labeled data is used to obtain a prediction model with excellent generalization performance. The Bi-LSTM framework for antibiotic resistance element detection is a mainstream sequence annotation framework that combines bidirectional long- and short-term memory networks, and its main idea is to obtain contextual information through bidirectional long- and short-term memory networks, and to fuse antibiotic as well as bacterial entity information, and trigger word information for the assignment of element roles. In the keyword co-occurrence analysis, combination therapy and phage had the highest frequency with a centrality of 0.57 and 0.59, respectively, indicating that phage-antibiotic therapy effectively treated patients with drug-resistant bacterial infections. There was a high correlation (r=0.57) between the number of days of ICU stay and the number of days of phage-antibiotic combination therapy, which was further analyzed to show that the number of days of fever, the number of days of indwelling urinary catheter, and the number of days of mechanical ventilation, phage-antibiotic combination days are more important influencing factors.
Reflections on the English Teaching Mode in Colleges and Universities under the Environment of Multimedia Network Technology
Authors: Shi Dandan 
Published: April 2024

Abstract
With the advancement of educational technologies, multimedia and network technologies have significantly enhanced classroom teaching efficiency and quality through their dynamic and intuitive nature. This study introduces a flipped classroom teaching model for college-level English, utilizing the SPOC platform, grounded in constructivist theory and task-based language teaching methodologies. Conducted in a university in City H, this research involved two classes. It employed a paired-sample t-test and principal component factor analysis to evaluate students’ English performance and learning interest pre- and post-implementation. Additionally, a Student Satisfaction Scale was developed to assess the model’s reliability and effectiveness. Results indicated a 1.39-fold increase in learning interest, with independent learning needs’ mean value rising from 10.69 to 16.78 and a notable improvement of 12.49 points in English grades. The factor analysis confirmed the model’s robustness, with all variable influence coefficients surpassing 0.75 and fitness values exceeding standard benchmarks. The SPOC-based English flipped classroom model has proven effective in promoting independent learning, fostering mutual learning spirit, and enhancing academic performance.
Research on the enhancement of informatization literacy of design practice teaching faculty in applied colleges and universities based on OBE model in the context of artificial intelligence
Authors: Gong Daxiao , Xiao Peng 
Published: April 2024

Abstract
The level of informatization literacy of college teachers is related to the comprehensive development of design professionals. In this paper, from the perspective of design practice teaching, we utilize the OBE model to construct a “one-core, six-double” design professional talent cultivation model. We also point out the prospects for applying the OBE model in design practice teaching. The Delphi method is used to construct the teachers’ information literacy evaluation index system. To avoid the influence of the correlation between the indexes on the evaluation results, the AHP-gray correlation combination algorithm is used to calculate the weights of the evaluation indexes. Finally, the complete evaluation index system was used to perform empirical analysis. The results show that the F-statistic of teachers’ informatization awareness and attitude (P1) is 2.349, and the P-value is 0.168, which is greater than 0.1, indicating that there is no significant difference between the scores of teachers’ informatization awareness and attitude in universities in Guangzhou and Shanghai. This study provides a foundation and reference for improving the computer literacy of design practice teaching faculty in applied colleges and universities. It aids in the advancement of design practice teaching.
Analysis of the changes in the art curriculum of preschool children’s education in the new media era
Authors: Gao Xiangyu 
Published: April 2024

Abstract
Art education for preschool children is the basis for the cultivation of young children’s perceptual ability, and the cultivation of young children’s perceptual ability plays an essential and fundamental role in young children’s understanding of the world, feeling of beauty, and discovery of beauty. This paper uses AR technology and microclassrooms in the context of new media to construct an educational model of preschool children’s art curriculum, and a portrait of preschool children’s scholars is built. It focuses on combining the hierarchical clustering algorithm with the radial function method of multivariate interpolation to analyze the classroom behaviors of preschool children, mining the correlation between the course learning behaviors and the learning effect through the Apriori algorithm, and constructing a personalized art learning path for preschool children based on the ant colony algorithm for practice. The results showed that preschool children were divided into four categories, with the highest proportion being excellent preschool children (52.5%). The mean score of preschool children’s art perception score was 8.225, and their scores were normally distributed, with the highest number of preschool children between 8.00 and 8.25. This study is significant for changing the art curriculum in preschool children’s education. Teachers should be guided in teaching activities and focus on children’s perceptual experiences and expressions.
Exploration of Finance Digital Transformation Path Based on RPA Technology
Authors: Zhang Yunhao 
Published: April 2024

Abstract
RPA technology as one of the key technologies to drive financial digital transformation, this paper combines it with AI technology to build an enterprise financial intelligent audit model to realize financial digital operation. Based on the essential operation of RPA technology in the field of financial management and the sorting of financial automation process, the financial intelligent audit process under RPA technology is designed, and the decision tree algorithm is combined with the financial intelligent audit early warning index system to carry out enterprise financial crisis judgment and risk early warning. Taking Enterprise A as an example, early warning simulation of financial accounts and rolling budget simulation of funds are carried out respectively. The audit early warning indicator has a threshold of 0.06, and the average weight of each indicator’s characteristics and the early warning interval are calculated. Taking the indicator A1 as an example, the weight of the characteristic evaluation is 0.153, and the audit early warning signal will be output when the proportion of the balance of the accounts receivable ledger reaches 4.03%. The audit warning signal provides substantial operable space for enterprise financial management and operation.
A study on the application of mixed reality technology in experimental teaching in economic colleges and universities
Authors: Lv Fengqi , Lin Zhixuan 
Published: April 2024

Abstract
With the continuous development of the computer field, mixed reality technology is increasingly used in various fields of life. This paper aims to create a mixed reality interactive experimental teaching system for economic colleges and develop the overall framework of the system using the target detection algorithm. It first designs the interaction system module based on monocular visual spatial localization. Then it builds a teaching evaluation system based on face detection, recognition, and gesture estimation for the experimental teaching of economic colleges and universities for the mixed reality interaction system. This paper empirically analyzes the proposed mixed reality interaction system for experimental teaching in economic colleges. It can achieve a processing speed of 19 frames per second and a high recognition accuracy of 88.23% in the teaching test. The average scores of each index after the testers’ use are above 4, and the average value of the system’s overall score is 4.66. This study has excellent performance and provides a practical roadmap and reference value for developing mixed reality technology in the direction of experimental teaching.
Research on the Path of Improving the Management Ability of College Counselors Based on Structural Equation Modeling
Authors: Wang Xi , Li Yihua , Li Mingqian 
Published: April 2024

Abstract
Aiming at the management problems of students in colleges and universities, this paper analyzes the influencing factors of counselors’ management ability based on the construction of structural equation model. The survey sample and questionnaire are selected according to the research objectives. To ensure the authenticity and validity of the research results, we test the reliability and validity of the questionnaire data, considering their usability. Research hypotheses are put forward according to the actual situation of college counselors’ management ability. At the same time, latent and measurable variables are set, followed by completing the construction of the structural equation model based on counselors’ management ability. Based on the acquired questionnaire data, the partial least squares method was used to conduct a case study on counselors’ management ability. The results show 26 standardized factor loadings >0.705 on the 50 observations of the hidden variables. The compound correlation coefficient R2<0.5, indicating that the five dimensions of leadership, sense of efficacy, adaptability, innovativeness, and execution are positively correlated with the improvement of tutors’ competence. All of them have a positive impact on the improvement of management competence.
Integration of higher education student management and pedagogical concepts based on data-based decision making
Authors: Wu Jun 
Published: April 2024

Abstract
In the context of big data’s growing influence on education, our study presents a novel approach to managing higher vocational student data through a model based on the “three-round education” philosophy. We construct a predictive model to dissect and categorize student performance at X higher vocational college by integrating K-prototypes and LSSVM algorithms. Our findings reveal three primary groups: high achievers (43.65%), average performers (23.38%), and those with challenges (32.97%), each showing apparent differences in academic success indicators. Impressively, the model forecasts student enrollment numbers with less than 1.077% error, providing a reliable tool for educational administrators to make informed decisions and tailor student management strategies effectively.
Statistical Inference Methods for Clinical Medical Data with Missing and Truncated Data
Authors: Cai Kejin 
Published: April 2024

Abstract
In clinical medicine, due to some accidents will inevitably produce the situation of missing data, this study for its with missing and truncated data, the use of mathematical statistics methods for inference supplement. After classifying the types of incomplete data, the article utilizes the great likelihood and empirical likelihood to form a linear statistical model to infer such data. It verifies it through simulation experiments and example analysis. In the simulation experiment, for the case of the same missing probability, as the number of samples increases from 150 to 300, the bias, variance, and mean square error of this paper’s algorithm in parameter β
1 are reduced to 0.0122, 0.1435, and 0.1441, respectively. In the actual statistical inference analysis of cardiac disease and heart transplantation, the standard error of this paper’s method reduces by 0.0576 compared with that of CAA, and the inference The results are by the reality. In clinical medicine, this study proposes a practical statistical extrapolation method and a realization path for objective interpretation when incomplete data is present.
Optimization path of physical training in college soccer teaching based on multivariate statistical analysis
Authors: Feng Xinyuan 
Published: April 2024

Abstract
Physical training in college soccer teaching has the problems of poor science and insufficient data management, this paper applies multivariate statistical methods to uncover data associations in training to construct a digital planning method. The digital characteristics of random vectors can be identified through the theoretical analysis of the multivariate statistical analysis algorithm. Correlation analysis is applied to test the validity of the research data, followed by the construction of regression equations of pre-competition functioning on competition fitness, to achieve the statistical examination of the research data. The multivariate statistical analysis algorithm was used to conduct a case study on physical training for college soccer. The results showed that after 16 weeks of soft ladder training the average muscle strength of the left rectus femoris muscle of 35 players in the experimental group increased from 31.17Kg to 33.32Kg (P < 0.01), and the average muscle strength of the right rectus femoris muscle increased from 30.29Kg to 32.37Kg (P < 0.01) There was a highly significant difference. This study provides theoretical references for physical training in college soccer teaching and promotes the development of college sports teaching.
Supply Chain Finance and Financing Efficiency of Technology-based SMEs
Authors: Liu Huan , Fu Zheng 
Published: April 2024

Abstract
Shortage of funds and inefficient financing have been the main problems faced by science and technology-based SMEs. Supply chain finance is aiding science and technology-based SMEs in obtaining financing opportunities and reducing the cost and difficulty of financing. This paper constructs a model for assessing financing efficiency with the help of Data Envelopment Analysis (DEA). And combined with the financing constraints commonly encountered by SMEs in the financing process, which affect the financing efficiency, it proposes a mediation effect model to analyze the influence of financing constraints. At the same time, the financing constraints faced by SMEs in science and technology are examined through an empirical model, and the mitigating effect of supply chain finance on financing constraints is analyzed through a model test. In the analysis of financing efficiency, the interest expense and pre-tax debt financing cost of DL science and technology-based companies are decreasing after supply chain finance financing. The interest expense is reduced by 2,009,200,200 in 2022 compared with 2019, and the pre-tax debt financing cost decreases to 6.12%. The proportion of supply chain financing in financing loans is more than 50%, the speed of capital turnover and financing efficiency have significantly improved, and the debt servicing capacity, operating capacity, and profitability have been improved.
Analysis of the Role and Influencing Factors of Strengthening Mental Health Education in Student Management
Authors: Xu Ying 
Published: April 2024

Abstract
This paper introduces mental health education into student management, utilizes ID3 algorithm of data mining technology to realize the classification of student information data, and designs the security algorithm of data storage based on C/S structure to complete the security calculation of mental health assessment. Combining the actual measurement results of students’ mental health development, a proposal is made to strengthen mental health education in student management. Taking the development of mental health education as the central perspective, exploring the specific influencing factors of the development of the level and quality of student management information technology construction, the Analysis shows that there is a significant difference between the 22-year-old students and the 18-19-year-old students in terms of information technology application ability. There is also a substantial difference in the quality of students’ participation in student management work with different levels of mental health, and the quality level of management work participated by students with good mental health status is 137.48±7.56, which is more capable of dealing with student management work than student workers with poor mental health status.
Modular design of smart home under the concept of whole-house customization integration
Authors: Zhang Xiaohui 
Published: April 2024

Abstract
Digital empowerment of home product design and manufacturing integration, to achieve the whole process of personalized customization of home products innovative design. Using big data for user analysis, we obtained functional demand data for smart home modules, and 28.5% of user demand is reflected in cell phone interconnection. Using the KANO model, user customization demands can be calculated to form basic and excitement type demand expectations represented by A and M. Then based on the fuzzy QFD method for demand raw data conversion, to get the initial weights and weighted weights of each demand item, taking A14 home space utilization efficiency as an example, the initial weights and weighted weights of A14 are 0.66 and 0.10, respectively, and the importance of demand sorted seventh. Combined with the specific application of modular design in smart homes, the modular design of smart homes is verified. Further adjustments should be made to enhance the innovation degree of smart homes.