bluuebunny/crossref_metadata_2025 huggingface dataset:
Analytics and Usage Gaps of Digital Platforms for Mathematics Education in Uruguay
Authors: Rodríguez Zidán Eduardo , Bentancor Biagas Gustavo , Solari Martin
Published: April 2024

Antecedent. Uruguay is known for its early and sustained incorporation of programs that foster the use of digital resources in public education. The country selected the mathematics education platform Bettermarks to support the educational process of students. Objective. This research analyses the data on access and usage of the digital platform for mathematics education among secondary school students both before and during the COVID-19 pandemic. Methodology. A descriptive and inferential statistical approach was used to analyze historical data on individual student interaction with the online learning activities. Results. The findings revealed that, from 2017 to 2020, there was a notable increase in the coverage rate, rising from 22% to 49%. Similarly, the activities completed by active users experienced an upward trend in 2020. The platform provided greater coverage; however, when analyzing the activity rate across the years, no significant differences were observed. Originality. The analysis tested several hypotheses to elucidate the heterogeneities in the access and interaction modalities among students using the digital resources. Statistically significant differences were observed in terms of coverage and activities performed by students based on different factors.
New records of rare water mites from New Zealand, with the description of a new genus (Acari: Hydrachnidia)
Authors: Smit Harry , Pešić Vladimir
Published: April 2024

New records of rare water mites mostly from interstitial habitat of New Zealand are presented. One new genus, Zelandostygolimnochares n. gen. (Piersigiidae) with the type species Z. curtipalpis n. sp. is described. Zelandobates occidentalis Smit and Pešić, 2020 is synonymized with Z. tongariro Smit and Pešić, 2020. The male is for the first time described for Zelandotonia orion Cook, 1992, and the female is for the first time described for Aciculacarus amalis Cook, 1983. New records of a number of rare species are presented.
Musculoskeletal examination of the forelimb of the horse
Authors: Kamm J. Lacy , Odegaard Jens , Hoagland Cherise
Published: April 2024

OBJECTIVE

The intention of this tutorial video is to illustrate the methods of examining the forelimb and neck of a horse in order to identify abnormalities that may be associated with lameness or disease.

ANIMAL

A 16-year-old quarter horse gelding was used for examination.

METHODS

The horse was examined for abnormalities by means of physical examination.

RESULTS

The examination of the forelimb and neck of the horse was successfully completed.

CLINICAL RELEVANCE

This examination technique is required to identify abnormalities in the equine forelimb and can be utilized during a lameness examination.
Research on Space Optimization Design of High-rise Residential Building Based on Genetic Algorithm
Authors: Huang Youwei , Zhang Xin
Published: April 2024

With the rapid development of urbanization and the continuous growth of population, the design and planning of high-rise residential buildings have become increasingly important. The purpose of this study is to explore the space optimization design method of high-rise residential buildings based on genetic algorithm(GA), focusing on the comparative analysis between traditional GA and Adaptive genetic algorithm(AGA). In this paper, AGA is used to establish the spatial optimization model of high-rise residential buildings. By dynamically adjusting the parameters of the algorithm, AGA makes the algorithm better adapt to the characteristics of the problem and improves the search efficiency. The results show that AGA is superior to traditional GA in global convergence probability, especially when the population size is large. AGA improves the adaptability and robustness of the algorithm by dynamically adjusting the crossover and mutation probability. AGA has better flexibility and adaptability in the design of high-rise residential buildings and is expected to provide more optimized solutions for solving complex design problems. The findings of this study provide a useful reference for innovation and sustainable development in the field of high-rise building design and also provide practical methods and tools for the application of GA.
Research on 3D Animation Scene Plane Design Based on Deep Learning
Authors: Liu Yanqi
Published: April 2024

At present, most graphic design methods of 3D animation scenes only get a small part of 3D animation scenes, and all of them are in a 3D coordinate system, with observers as the core, so it is difficult to express the depth information of 3D animation scenes. This project intends to study a plane design method for 3D animation scenes based on deep learning. CNN (Convolutional Neural Network) is used to build a multi-view 3D animation scene generation network, and 3D geometry and structure of objects are reconstructed through multiple or a group of images. On this basis, the feature extraction method of 3D animation scenes is studied, and the collaborative learning model of multiple networks is established to improve the modeling accuracy of 3D animation scenes. The experimental results show that the network model is superior to the method based on multi-view and 0-1 voxel in detecting retrieval performance, and the accuracy rate can reach 91.725%. The multi-view 3D animation scene generation method in this paper has achieved better results than the current advanced methods, which proves that the multi-view feature fusion network proposed in this paper is a more reasonable method to fuse multi-view image features.
GPF Filtration Characteristics Considering Fractal Characteristics of Particles and Filters
Authors: Zhang Jian , Wang Lei , He Chao , Liu Xueyuan
Published: April 2024

To reduce the emission of fine particulate matter (PM) from gasoline engines, a gasoline particulate filter (GPF) filtration model that considers the fractal characteristics of both particulate matter and filters is designed and its filtration characteristics are analyzed based on several GPF filtration models. Based on the GPF filtration mechanism, a new mathematical model of fiber efficiency filtration is established after correcting the classical filtration formula based on correcting the particle size of particles and considering the relationship between the porosity of the fiber filter and the fractal dimension of the filter. Simulation of the filtration efficiency of the established mathematical filtration model is carried out to obtain visual filtration efficiency curves. The filtration efficiency and pressure drop of the model are analyzed, and the effects of parameters such as particle fractal dimension, filter fractal dimension, filter thickness, flow rate, and fiber diameter on filtration efficiency are also comprehensively analyzed. The results show that when the fractal dimension of particles is in the range of 1.8-2.8, the most penetrating particle size decreases with the increase of the fractal dimension of particles. When the particle size is small, the effect of fractal dimension on filtration efficiency is not obvious. When the particle size is larger than the most penetrating particle range, the larger the fractal dimension, the filtration efficiency increases obviously. Considering the relationship between the fractal dimension of the filter body and the porosity and the influence of each on the filtration efficiency, the optimal fractal dimension of the filter body should be between 1.82 and 1.925, and the thickness of the filter has some influence on the filtration efficiency. The slower the gas flow rate is, the better the trapping effect will be. However, considering the problem of automobile emission, a lower exhaust speed can be chosen. Increasing the fiber diameter can improve the trapping efficiency of the model, but will reduce the porosity of the trapping collective. Therefore, the fiber diameter should not be too large under the combined action.
Research on the Application of Big Data in College Physical Education Teaching and Training
Authors: Wang Dongle , Chen Yong
Published: April 2024

During college physical training, a substantial amount of data is continually generated through various activities. Historically, technological constraints have hindered the effective collection and utilization of this data, limiting its potential to enhance physical education (PE) and training through intelligent support. This study explores the application of data mining (DM) in managing and analyzing PE classrooms. It aims to streamline PE teaching management and evaluation, conduct in-depth analyses of students’ physical fitness data, and ultimately elevate the quality of school PE instruction. In designing a big data system for this purpose, data collection is prioritized based on its difficulty. To facilitate data analysis and presentation, a high-performance framework for storing and analyzing data is selected. The results indicate a 13.28% improvement in accuracy compared to traditional assessment models. By leveraging DM in PE classroom assessments, we can mitigate subjectivity and uncertainty associated with manual weight and correlation coefficient selection. This approach enhances the intelligence, adaptability, and usability of the assessment model, paving the way for more effective PE teaching and learning.
A Study of Big Data Prediction in Accounting Management Risks
Authors: Chen Jinhua , Cai Yuan
Published: April 2024

With the continuous development of big data technology, the application of big data prediction in enterprise risk management is getting more and more attention. After proposing a framework for applying big data prediction in accounting management risk, this study builds an accounting management risk prediction model based on the optimized particle swarm and random forest algorithms.Company X’s accounting management risk-related data is taken as a research sample, and the effect of the constructed accounting management risk prediction model is investigated by comparing the models and assessing the risk prediction accuracy. The study shows that the PSO-random forest model built in this paper has faster convergence and higher accuracy than the ordinary random forest, and the overall accuracy of accounting management risk prediction is 12% higher. The model’s accuracy in predicting the overall and various types of risks in Company X’s accounting management is more than 85%. The PSO-Random Forest model is a reliable tool for predicting accounting management risks, which is of great practical importance.
Laser Descaling Area Recognition Method Based on LabVIEW and Machine Vision
Authors: Gao Feng , Zhao Yuantao , Shangguan Fujun , Chen Xinfeng , Li Wenge , Xu Yanlong , Rong Xiancheng , Shi Shanshan , Yang Zhiyuan , Qu Wendong , Yu Zhonghan
Published: April 2024

Automated laser descaling represents a crucial advancement in marine maintenance, particularly in localized corrosion treatment. This research utilizes AH32 marine steel for corrosion testing, applying color feature extraction and the OTSU thresholding method, refined with morphological processing, to accurately delineate descaling areas. We have engineered a laser descaling protocol with an impressive 97% recognition accuracy through the innovative application of LabVIEW technology combined with machine vision. Implementing this technology promises enhanced corrosion resistance for marine vessels, setting a new standard for maintenance efficiency and quality.
Research on the Logic and Path of Red Culture in the Information Age for Promoting the Casting of Chinese National Community Consciousness ---- Taking Guangxi as an Example
Authors: Zhou Jinhua
Published: April 2024

Chinese national community consciousness is an important task and distinctive main line to strengthen and improve national work in the information age, and the role of red culture as an essential carrier of Chinese national historical memory to promote Chinese national community consciousness cannot be ignored. The transformation of red culture resources through digital empowerment is described in this paper, and the digital development path of red culture in the information age is constructed. Then, it analyzes the internal logic of red culture forging the sense of community of the Chinese nation, and utilizes the coupling model and regression analysis to study the path of red culture forging the sense of community of the Chinese nation. Finally, taking Guangxi Province of China as an example for empirical evidence, the comprehensive score of Guangxi’s red culture development rises from 0.268 in 2016 to 0.735 in 2022, an increase of 0.123, and the degree of coupling and coordination between red culture and casting a firm sense of community of the Chinese nation is in the range of 0.3 to 0.5. It indicates that the red culture and casting a firm sense of community of the Chinese nation of Guangxi Province have an excellent coordinated development trend in the period of 2016-2022, and the red culture for the promotion of Chinese national community consciousness is a good solution. The trend of coordination development provides a practical path for red culture to promote the development of casting Chinese national community consciousness.
Analysis of the Integration Path of Chinese Traditional Culture in College English Education and Teaching under the Background of Big Data
Authors: Su Tao
Published: April 2024

The cloud platform teaching system utilizes the optimized load balancing algorithm and DP algorithm to allocate and cluster massive teaching resources respectively, organize massive Chinese cultural knowledge scientifically and rationally into relevant network modules, and present it to English learners in a combination of graphic and text, audio and video. By investigating the selection of resource content and the quality of each functional module on the cloud platform, it can be found that the five primary cultural contents are generally well balanced, with the two that account for the most significant proportion of the content being cultural practices and cultural products, and the proportion of the other three varying little. Most students preferred the functional modules of Learning Center (84.3%), Resource Center, Extracurricular Paradise, and PK Pavilion, but only 12% preferred the Psychological Center module. The correlation coefficient between different factors and the intensity of Chinese culture penetration is the highest, 0.924. The average score of the degree of realization of the five teaching objectives in teaching practice is 3.838, close to “basically realized”. The scores of the four major dimensions of the university students increased significantly (p<0.05). The most significant improvement was seen in the quality of thinking dimension, with a mean increase of 2.678 points.
Construction of fuzzy mathematical model for judging financial indexes of private enterprises under the perspective of deep learning
Authors: Li Min , Tu Yanshi
Published: April 2024

This paper introduces a novel financial evaluation framework combining deep learning, hierarchical analysis, and fuzzy comprehensive evaluation to form the AHP-fuzzy comprehensive model. This model is designed to refine financial analysis by constructing precise evaluation indexes and determining weight values, specifically tailored for the financial management of private enterprises. Through a case study on Enterprise A, focusing on solvency, operational efficiency, and cash flow, we observed significant trends: a decline in the quick ratio from 0.92 in 2017 to 0.49 in 2021, a decrease in the accounts payable turnover ratio from 2.58 in 2017 to 2.01 in 2020, and a concerning downward trend in the cash to current liabilities ratio, culminating in −11.30% in 2020. These findings validate the effectiveness of the AHP-fuzzy comprehensive evaluation model in providing nuanced financial assessments for private enterprises.
Exploration of Talent Cultivation Mode for Industry-Teaching Integration in Higher Vocational Education Based on Multi-scale Feature Integration
Authors: Liu Weilu
Published: April 2024

Industry-teaching integration of vocational education is a systematic and innovative schooling system that effectively integrates the resources of the government, vocational colleges and industrial enterprises to realize the coordinated development of applied talent training. This study focuses on using multi-scale feature fusion to study the classroom attention of students in the talent training classroom. It sets up the classroom facial expression detection and head posture estimation modules to realize the intelligent teaching mode reform of teaching, learning and doing integration. Then based on the background of integration of industry and education, combined with the concept of triangular helix, explore the talent training innovation model of higher vocational education, and utilize the QCA method to carry out empirical analysis to explore the synergistic path of integration of industry and education and talent training. The average accuracy of the constructed model for identifying student expressions has been shown to be 93.56%. The original coverage (0.38651) of big business * project motivation * project constraints is the highest, which explains more than 38% of the resultant variables, which is about to be nearly 40% of the industry-teaching fusion projects obtaining high project effectiveness through this path. The synergistic model of industry-teaching integration and talent cultivation in higher vocational education is provided with new ideas by this study.
Synergistic development path of ecological civilization construction and rural revitalization
Authors: Ma Zhaoli , Guo Xia , Liu Xin
Published: April 2024

The core strategy for national development in the new era is the establishment of an ecological civilization. In contrast, the overall understanding of the three concerns facing rural communities in the new era is the rural revitalization strategy. The paper examines the present state of the linkage development between constructing an ecological civilization and implementing a rural revitalization strategy in rural areas. It does this by developing an evaluation index system and drawing on the theoretical underpinnings of the linkage development between the two strategies (rural revitalization strategy and ecological civilization construction). The entropy value approach is used to compute the comprehensive index and determine the weights of each index. The coupling and coordination degree models are used to measure the coordination degree and coupling correlation of the two, and the correlation factors between them are analyzed by constructing the gray correlation model. The findings indicate that overall, County A’s rural revitalization development level between 2012 and 2021 tends to be better, although overall levels are not very high. The comprehensive index of development for rural revitalization goes from 0.194 in 2012 to 0.754 in 2021. Yearly fluctuations in ecological civilization-building are evident, with the complete index of ecological civilization construction rising from 0.380 in 2012 to 0.945 in 2021. The overall trend is slowly increasing when the coupling coordination degree of 0.610 from 2015 is taken as a limit, but high-quality coordination is still a significant distance away.
Practical Exploration of College Students’ Ideological and Political Education under the Perspective of Collaborative Parenting in Colleges and Universities
Authors: Wang Cheng
Published: April 2024

Aiming at the problems existing in the ideological and political education of college students, this paper puts forward the research on the ideological and political education of college students based on CIPP evaluation. From the CIPP evaluation, the fundamental value of ideological and political education evaluation of “enhancing output” and the evaluation objectives of effect, efficiency and effectiveness are clarified, and the four-dimensional evaluation content framework of ideological and political education of college students is formed. An evaluation index system consisting of 4 first-level indicators, 11 second-level indicators, and 36 third-level indicators was finally created by selecting experts. Through the second round of expert consultation, we obtained the results of assigning the degree of importance of indicators at all levels. Then we finalized the weights of indicators at all levels using the hierarchical analysis method. Based on the evaluation index system, colleges and universities’ ideological and political education is analyzed through examples. The results show that the overall evaluation scores of the three colleges and universities are all in the “ good “ range, with the scores of 78.3005, 80.4134 and 81.6171, respectively. This study aims to provide guidance and reference for the practice of ideological and political education for college students, and to promote the standardization and sustainable development of ideological and political education. This study aims to provide guidance and references for the practice of ideological and political education of college students, and promote the standardization and sustainable development of ideological and political education.
Research on Intelligent Monitoring Technology of Municipal Road and Bridge Engineering Construction and Quality
Authors: Wang Dong
Published: April 2024

This study addresses quality control challenges in municipal road and bridge construction by introducing an intelligent monitoring approach. Utilizing three-dimensional laser scanning, we monitor roadbed settlement and deformation accurately. Compaction quality is assessed through vibration acceleration metrics from milling operations, applying a compaction monitoring value. Furthermore, a combination of regression models and stochastic processes in a Kriging function model evaluates the reliability of detecting bridge steel corrosion. In J city’s political road bridge analysis, we observed a differential settlement with the least affected areas showing subsidence within 250mm. In contrast, the most impacted point, B1, recorded a settlement of 2597mm in December. Compaction quality monitoring revealed that control error margins for E and CV indicators lie between −2.65% to 2.35% and −2.7% to 2.6%, respectively, demonstrating a narrower error range for E compared to CV.
Analysis of the Effectiveness of Generative Adversarial Technology in Intelligent Buildings in terms of Design
Authors: Wang Lu
Published: April 2024

This paper combines the training method of generative adversarial network and the robust row layout design method of building based on CGAN, and selects pix2pix model to carry out the spatial layout design of intelligent building, to explore the actual effect of intelligent building design. Using the building layout design of a generative adversarial network, different parameters and residual block numbers are set to compare the impact of building texture generation. The intelligent building using GAN technology is selected to carry out the spatial design characterization of both Light and shadow and luminance, and the SD spatial environment evaluation factor is used to refine the discussion of the spatial design experience of intelligent buildings designed using generative adversarial technology. The Light and shadow distribution of intelligent building design is mainly presented as four types, in which the light and shadow location types of reading room, hall, rest space and exhibition hall are primarily offered as horizontal division types. In a public intelligent building, the rest area is separated into 25% of the distance and 25% of the vertical division, with an improved design balance.
An Inquiry into the Factors Influencing the Role of Marxist Chineseization on the Discourse System of Chinese-Style Modernization
Authors: Zhang Haili
Published: April 2024

This paper starts from the definition of the concepts of both Marxism and Chinese-style modernized discourse system, and carries out the division of independent variables, control variables and dependent variables to pave the way for the construction of the multiple linear regression model later. Based on determining the variables, the Pearson correlation coefficient formula is used to obtain the correlation between the variables, followed by the construction of the multiple linear regression model and other methods such as significance test to analyze the influencing factors of Chinese-style modernized discourse system. The results show that all the regression coefficients are positive, indicating that the six independent variables positively influence the construction of modernization discourse. The standard regression coefficient of “Deng Xiaoping Theory” is 0.227, which is significantly higher than the regression coefficients of the other indexes, indicating that Marxist political economy dimension of “Deng Xiaoping Theory” has a positive influence on the construction of modernization discourse, and that “Deng Xiaoping Theory” is more important than the other indexes. Deng Xiaoping Theory” has the most significant influence on the modernization discourse system. The Chinese modernization discourse system is a system that promotes both the development of revolution and construction practice, as well as cultural modernization and the generation of people’s subjective consciousness, as revealed by this study.
An analysis of the effectiveness of linguistic ecosystem building on local landscape language governance
Authors: Xu Haoran , Zhang Xinyu , Wang Yifang , Yang Zihan
Published: April 2024

With the social and economic development and the improvement of people’s living standards, people have put forward higher requirements for the governance of the ecological environment, and the goals for the management of local landscapes are becoming more and more diversified. This paper constructs a dynamic and coordinated GRL governance model according to the characteristics of local landscape language. It uses the gray correlation model to explore the correlation between the constituent factors of the damaging ecological environment effect. Taking the loess hills landscape of S province as the research object, the governance effect of ecological environment construction on vegetation, soil, and landscape patterns is explored. The study shows that after the environmental environment management, the number of landscape patches in the region increased by 18, and the fragmentation index of each landscape increased by 0.0475 Block / km2 on average, which increased the spatial structure complexity of the landscape. The study’s findings can provide theoretical guidance for managing local landscape language comprehensively and have a specific scientific basis.
Research on enterprise talent ladder construction strategy based on multidimensional data analysis methodology
Authors: Zhang Qiulin , Zhang Qiuli
Published: April 2024

In the face of increasingly fierce competition for talents, strengthening the cultivation of high-potential talent echelon and improving the core competitiveness of enterprises have become the most serious, urgent and realistic issues. The competency iceberg model and the talent echelon construction process are combined in this paper, and a talent competency model and a hierarchical thesaurus are established. For the influencing factors and comprehensive evaluation of talent competency elements in enterprise talent ladder construction, this paper introduces the entropy weight and TOPSIS methods for assessment. It explores the relevant factors of talent competency through multiple linear regression model. The research example is Enterprise Z, and appropriate research data is gathered through questionnaires to examine the development of enterprise talent echelon construction based on multidimensional data analysis technology. The study found that among the elements of talent competency, the weight of knowledge and skills reaches 0.3718, and the highest relative closeness of the ten middle managers is 0.798. The enterprise’s talent competency will significantly increase by 0.772 percentage points when the job evaluation process rises by 1 percentage point. The enterprise talent ladder construction needs to improve the corresponding job assessment process, establish a sustainable talent reserve system, and smooth career development channels to effectively enhance the enterprise talent ladder construction capacity.
Imagery Recognition and Semantic Analysis Techniques in Chinese Literary Texts
Authors: Zhang Wenfu
Published: April 2024

Chinese literary texts contain a sizeable vivid imagery vocabulary, which makes it difficult for average readers to judge the boundaries between words, and the current pre-trained language model is also difficult for them to learn its implicit knowledge effectively, which brings troubles to machine semantic analysis. The study uses CRF training to obtain a semantic analysis model of Chinese literary texts that recognizes the semantic relationship between two words. SVM is used to train classifiers for confusing categories, and the two semantic relations in the output of the CRF model are further recognized to determine the final semantic relations between word pairs. Finally, the LCQMC dataset is used as the experimental data, and the semantic analysis technique based on CRF and SVM is employed to obtain the participle, lexical, and dependent syntactic annotations. According to the results, the model’s correct rates on the LAS for paraphrase recognition and dependency analysis of Chinese literary texts are 74.83% and 92.05%, respectively. The study enhances the efficiency of semantic analysis of relevant Chinese texts and is crucial for the study on the semantic analysis of terms.
The role of social media data analytics in rural tourism market trend forecasting
Authors: Zhang Zhe , Dai Minghua
Published: April 2024

The rapid development of social media provides new means for market trend and quotation prediction. This paper realizes market trend prediction by performing TF-IDF keyword extraction and vectorization on social media data, improving the deep typical correlation analysis to realize semantic mining, and constructing a consumer intention mining method based on social media data. The rural tourism market trend prediction for Haikou City, Hainan Province, China focuses on examining the number of tourists and the economic income of rural tourism. The future number of inbound tourists and the total number of tourists in Haikou City will still show an upward trend overall, with the total number of tourists predicted to reach 73,641,100 in 2028. With the continuous development of rural tourism, the tourism economy of Haikou City reaches 67.068 billion in 2022, an increase of 259.67% from 2008, and is predicted to double in 2027, and is expected to reach 148.282 billion in 2028. The number of overseas tourists and foreign exchange earnings from rural tourism will continue to increase.
Research on the core ability cultivation mechanism of college students returning to their hometowns for innovation and entrepreneurship under the strategy of rural revitalization
Authors: Liu Limin , Liu Jieshu
Published: April 2024

This study explores the innovation and entrepreneurship capabilities of college students who return to their hometowns, particularly within China’s rural revitalization strategy. By constructing a comprehensive framework, this paper examines four key dimensions that influence these abilities, employing logistic regression analysis to assess the impact of various factors. Notably, including policy support as a variable in Model 2 significantly enhances the Model’s explanatory power by 22.4%, a statistically significant finding (p < 0.001). This underscores the critical role of policy support in bolstering students’ innovation and entrepreneurial skills. Further, through applying structural equation modeling, this research delves deeper into the nexus between policy, institutional environments, and the cultivation of core entrepreneurial competencies, offering insights into the external factors that facilitate competence development. The Model’s hypotheses are rigorously tested for fit, confirming the effectiveness of the proposed framework in understanding and supporting the entrepreneurial endeavors of returning college students.
Precision Teaching of Civics Integration in Universities and Primary Schools with Individual Differences in the Age of Artificial Intelligence
Authors: Jia Yu
Published: April 2024

Leveraging the unique capabilities of intelligent technologies, this study presents an advanced approach to Civics and Politics education, emphasizing personalized and multimodal teaching strategies suitable for various educational stages. We establish an Integrated Civics and Political Teaching Platform using multimodal feature fusion algorithms coupled with personalized recommendation techniques. This platform incorporates genetic algorithm-based analysis of students’ learning behaviors, facilitating a Precision Teaching Service Model that tailors education to individual needs. A comparative study of semester scores highlights the model’s effectiveness: notably, a substantial 19.89 point increase in declarative knowledge scores and a significant reduction in the variability of strategic knowledge scores by 5.28 points. These results affirm the benefits of personalized teaching in enhancing student outcomes in Civics education.
Research on Rural Social Governance Approach under the Threshold of Spatial Theory
Authors: Lin Miao
Published: April 2024

This study employs spatial theory to investigate rural social governance, revealing how it influences the spatial layout of rural settlements. By utilizing GIS spatial analysis and spatial autocorrelation methods, we systematically categorize and organize rural territorial spaces, developing an optimal regional planning system for rural areas. Through spatial econometric analysis, we examine selected villages’ comprehensive governance levels and ecological governance efficiency. Our evaluation focuses on five key areas: economic development, public services, social order, environmental livability, and overall governance effectiveness. Findings indicate a significant annual growth in the villages’ overall development level by 14.6%, with rural governance effectiveness improving from 0.819 to 0.859 between 2012 and now. Moreover, disparities in governance effectiveness within these areas are narrowing. This research broadens the scope of rural governance studies through a spatial lens, offering valuable insights and benchmarks for future inquiries.
Gray correlation analysis of strategic human resource management and corporate performance
Authors: Liu Yuxuan , Zhang Huiling
Published: April 2024

In today’s competitive business landscape, effective human resource management (HRM) is pivotal for the growth and performance of enterprises. This study uses gray correlation and multiple regression analyses to investigate the connection between HRM practices and corporate performance. We developed an evaluative framework to assess the impact of strategic talent management on company outcomes. Survey data were analyzed to unveil the dynamics between HRM variables and corporate performance. Our findings highlight a significant relationship between employee recruitment, incentive programs, promotion pathways, and an innovative culture with corporate success, with p-values less than 0.01. Notably, stock options (0.354), bonus schemes (0.325), and promotion opportunities (0.331) show the strongest correlations. The gray correlation analysis further indicates that the HRM-performance linkage in three surveyed companies exceeds 0.7%, underscoring HRM’s vital role in enhancing enterprise performance. This research presents gray correlation analysis as an effective tool for businesses to evaluate the impact of their HRM strategies on performance.
Research on the Construction and Effectiveness of Teaching Resource Sharing Platform for Art and Design Majors
Authors: Peng Yiqing
Published: April 2024

In the information society, the sharing characteristics of Internet information provide students with rich teaching resources. This study integrates Hadoop technology with the teaching resource sharing system for art and design majors in colleges and universities. It builds an open-source parallelised computing and distributed architecture based on the traditional B/S model, using the distributed file system HDFS to store massive teaching resources. On this basis, MapReduce, a parallelised programming model, is used to provide parallel computing retrieval functions, and the innovative contract technology of blockchain is introduced to store data-heavy shared teaching resources in the underlying IPFS to ensure the security and trustworthiness of shared data. The results show that under the blockchain environment, the retrieval time of teaching resources is as low as 12ms only, and the Gas value consumed by the operation of storing data totals 0.1385 ETH, which meets the performance requirements of the platform and provides a new practical solution for sharing teaching resources.
A Study on the Precision Effect of Blended Learning in English Teaching and Learning
Authors: Wang Aifei
Published: April 2024

Realizing personalized and precise teaching using traditional English methods is challenging. This paper proposes a blended precision teaching model that relies on student portraits, using technical methods to provide tailored learning resources for every student. A deep neural network is used to extract student features, and the k-means algorithm is used to construct a clustered portrait of students. Based on the student portraits, the similarity between student objects is calculated, and the collaborative filtering method is combined to achieve personalized recommendations for English learning resources. And the learning warning model is established by considering the ranking order relationship when predicting students’ English scores. Setting up the experimental class and the control class to analyze the effect of blended teaching precision, in terms of English scores, the average score of the experimental class is 6.06 points higher than that of the control class, with a significant P-value of less than 0.05, which shows a considerable difference. Its classroom teaching observation dimension score totaled 91.6, students’ classroom performance and teaching effect performed well, English literacy was improved, and the mean values of each satisfaction of emotional experience showed significant differences (P<0.05). The mean values of several dimensions of learning motivation were higher than those of the control class, with highly significant differences in the dimensions of extrinsic goal orientation, learning beliefs, and intrinsic goal orientation (P<0.01).
A Study of Marketing Capabilities and Their Performance Impact Based on SWOT Matrix Modeling
Authors: Wang Jianrong
Published: April 2024

Marketing capability is a vital resource capability, this paper first utilizes the gradient descent algorithm to calculate the matrix decomposition problem and mine the relevant data of marketing capability. Then combined with the ANP algorithm, it solves the problem of the SWOT algorithm being unquantifiable. It constructs a SWOT-ANP strategy analysis model, and empirically examines the influence of enterprise strategy and performance. The model is applied to the enterprise’s marketing capability, with performance relationship as the target layer, SWOT as the criterion layer, and the weight values of 15 influencing factors are calculated through the network hierarchy. The weight of the opportunity layer in the local weight is higher than that of the disadvantage layer, which leads to the influence of sub-influence factors, and the highest weight of the disadvantage influence factor is 0.04388 lower than the lowest influence factor of opportunity. Combining with the factor intensity score value, the integrated performance influence of O, T, S, and W is calculated to be 8.438, 6.00747, 7.42637, and 7.69062, respectively, and the sample is obtained through the strategy positioning The development strategy of the enterprise is S-T strategy.
Comprehensive Evaluation of KOL’s Guiding Mechanism and Influence in E-commerce Live Streaming Carrying Mode
Authors: Luo Jie , Lv Xiaohui , Liu Hongya
Published: April 2024

In the rapidly evolving live broadcast economy, Key Opinion Leaders (KOLs) are reshaping e-commerce by promoting products in real-time. Our study investigates this phenomenon using a sophisticated model of user interaction and behavior guidance among KOLs. By proposing a multichannel decision-making model that includes KOLs, brands, and traditional retailers, we aim to understand the dynamics of profit-driven decisions and their impacts. Analyzing data from 25 KOL anchors, we find a notable trend. Despite positive skewness in daily sales and conversion rates, there’s a range of fluctuation (0 to 13) that hints at diminishing returns from KOL live broadcasts, ultimately affecting the effectiveness of influencing consumer behavior.
Innovative Research on the Volunteer Service Work of College Students’ Civilization Practice in the Context of the New Era
Authors: Liu Jingwen
Published: April 2024

This study explores how motivation and incentives impact college students’ volunteer service within civil practices. Utilizing a factor analysis data model, we constructed factor loadings for volunteer service work, rotated the factor matrix, and estimated the correlation coefficients of factors using regression methods. Our “motivation-incentive” analytical model frames this research, alongside proposed hypotheses. Descriptive analysis of the sample confirmed these hypotheses. Results reveal a significant path coefficient of 0.224 (p < 0.001) for engagement on continued volunteering willingness, underscoring engagement’s positive influence. Furthermore, positive emotions in volunteering motivation significantly correlate with engagement and sustained service willingness (coefficients: 0.315, 0.745, 0.269; p < 0.01), serving as a mediator. This study elucidates the mechanisms of influence in volunteer work, offering theoretical guidance for enhancing college students’ participation in civilized practice volunteer services.
Metaphorical Interpretation of Early Works of Art Using Symbolization Methods
Authors: Wei Ping
Published: April 2024

The unique style of early works of fine art depends on the infinite derivation of the image factor symbols metaphorically behind them, so the symbolic interpretation of early works of fine art is a search for the missing beauty of contemporary art. In this paper, we start from multi-scale association rules, use Gaussian pyramid and cubic convolution methods to extract image metaphor features in fine art works, and weight the features. Based on Putschke’s emotion classification, a multimodal metaphor dataset is constructed. The symbolization method is used to represent the symbolic emotions in the art works, and then the bidirectional Bi-LSTM model is used for recognition. On this basis, using the model constructed in this paper, the symbolic and imagery features of art works are analyzed, and the symbolic techniques of art works are interpreted from three perspectives: brushstroke, color, and spatial metaphor. Structural metaphors in fine art works contain 40% neutral emotions, followed by 36.4% positive emotions. Stroke A has a higher mean score at 3 and 4 line sample points, respectively, of -1.1646 and -1.1106, and the emotions triggered by these two line samples are more significant. Interpreting early art works can help enhance the aesthetics of contemporary art for modern audiences.
Teaching Quality Assessment of English Courses in Colleges and Universities Based on ISSA-DRNN
Authors: Yu Guoying , Li Jun
Published: April 2024

The optimized sparrow search algorithm (ISSA) is built on top of the deep neural network (DNN) in this paper, along with a new deep recurrent neural network (DRNN) algorithm that is proposed by improving the DNN. Ultimately, an ISSA-DRNN-based model for assessing the quality of English course teaching has been established. To examine the application impact of the ISSA-DRNN-based English course quality teaching evaluation model, SA University has been chosen as the study location. Two groups have been created: an experimental group and a control group. The experimental group’s academic level scores grew by 5.1 points in terms of English achievement, whereas the control group’s average score increased by 0.36 points, indicating a very significant difference (P<0.01). The four characteristics of satisfaction with teaching effectiveness—interest in learning, ability improvement, desire to learn behavior, and course satisfaction— showed significant differences (P<0.05) among students in the experimental group. In the self-assessment of English literacy, the dimensions with the most important proportion of “relatively large” ratings are learning motivation and class participation, accounting for 43.73% and 42.92%, respectively. The dimensions with the highest proportion of “substantial” grades are English learning ability and learning motivation, accounting for 21.03% and 20.63% in that order.
Design of Intelligent Interactive Teaching System for College English Based on Streamlined Bilinear Attention Networks
Authors: Yu Guoying
Published: April 2024

Intelligent methods such as deep learning provide an innovative optimization path for English teaching in colleges and universities. In this paper, the attention mechanism is based on traditional CNN. Embedded attention and multilayer convolutional feature fusion are used to complete the design of streamlined bilinear attention networks. The streamlined bilinear attention network is used to obtain the characteristics of students’ classroom behavior in the process of English teaching, combine the characteristics of students’ classroom behavior and computer programming language to design and implement the intelligent interactive teaching system of English in colleges and universities, and test and apply the analysis of the intelligent interactive teaching system of English. The results show that in the query performance test report, even though the number of requests issued in the test is 2,000, the error rate is always kept at 0, the throughput is 39.8, and the response time is kept at 95~1144s, which indicates that this system can meet the performance requirements with a moderate number of users. In the application analysis, the total score of the teaching method of English Intelligent Interactive Teaching System (mean=94.62) is higher than that of the traditional English teaching method (mean=89.65), which indicates that the teaching method of English Intelligent Interactive Teaching System is more capable of improving the interaction and communication ability of the students in English teaching. The system constructed in this study can meet the diverse needs of students and contribute to the quality improvement of English teaching in colleges and universities.