bluuebunny/crossref_metadata_2025 huggingface dataset:
A Quantitative Approach to Technical Analysis of Tennis in a Physical Education Setting
Authors: Wang Yangyang
Published: December 2024

Tennis sports technology analysis is an evaluation of tennis sports technology from multiple perspectives, such as level and content, and is an important means of movement instruction for students in physical education. The application of intelligent technology for tennis sports technology analysis can reduce the workload of teachers and assist in tennis teaching. In this paper, multiple sensor nodes and the host are used to construct a wearable sensing network and realize the network communication connection. A support vector machine algorithm based on particle swarm optimization is proposed, and parameter optimization is performed on kernel function parameters and penalty factors to ensure the efficiency and accuracy of action recognition. Then a smaller number of action words are utilized to represent the original human motion sequence, and the use of angular features to represent the gestures of human motion is proposed to form a sequence of angular features. Finally, using the key gesture extraction and hierarchical clustering method, action words are extracted, and the generation of action text is realized by replacing each frame of data in the original action sequence with the action word that is closest to it. The accuracy of action recognition of this paper’s algorithm is 7.5% higher than that of the decision tree. The Spearman correlation coefficient between the quantization method of this paper and the traditional quantization method is 0.844, which shows a very strong correlation. Therefore, the overall fit between the performance rankings measured by this paper’s method and those measured by the teachers is high, proving the effectiveness of this paper’s quantization scheme in analyzing tennis sports techniques in physical education.
An Empirical Study of Augmented Reality Technology for Enhancing Interactivity in Language Learning in Higher Education English Language Learning
Authors: Zheng Lu
Published: December 2024

The current problem of insufficient speaking environment for learning foreign languages in China has led to many difficulties in the process of language application. This paper proposes a language interaction system based on speech recognition technology, integrates it with AR English classroom teaching, and designs a new teaching mode. In order to verify the effect of AR technology on the enhancement of language interaction, the study is based on the collection of speech data from the experimental classroom of the preschool education program of a teacher training university, and after collecting and organizing the data, the effect of different data sets on the recognition accuracy of the language interaction system in this paper is tested by changing the size of the data set. After the data set was enlarged, the language interaction system’s accuracy increased by 4.3%. Then, the comparative analysis of teaching language between AR English language interactive classroom and traditional English classroom is carried out from three aspects of language structure, teacher tendency and question and speech, respectively, and it is found that there is a big gap between the two, such as question and speech characteristics, in the AR English language interactive classroom. The rate of active speech among students is as high as 17.8%, while the rate of active speech in traditional English classrooms is 9.5%. The experiment verified that teaching in an AR English language classroom has a significant improvement in students’ language learning interactions.
Exploration of multiple regression analysis and prediction methods for power grid carbon emission factors
Authors: Ye Fan , Xiao Qiang , Xie Lu , Wu Jungang , Zhang Jian , Chen Yuguo
Published: December 2024

Carbon emissions from the power sector account for about one-third of China’s total carbon emissions, and carbon emission reduction in the power sector is crucial to the realization of the “double carbon” goal. This paper proposes a prediction model for grid carbon emission factor based on the combination of multiple linear regression models and the GM(1,1) model. The grid carbon measurement model is built using the theory of carbon emission flow, and the grid carbon emission accounting model is built using the consumption side. The average grid carbon emission factor is calculated by dividing the grid carbon emission factor into three different dimensions. The multiple linear regression model is used to study the correlation between the independent variables and the dependent variables, and the specific values of each regression factor are predicted by combining with the GM(1,1) model, and it is judged whether the prediction model is reasonable or not. Among the contributions of the increase in carbon emissions from the power grid, the contribution of electricity consumption increased from 2010 to 2014 and reached a peak of 2.9824 million tons in 2014, and the carbon emission factor value of the power grid gradually decreased from 0.719kg CO2/(kW·h) in 2010 to 0.593kg CO2/(kW·h) in 2022. The MR-GM(1,1) model is applied to the prediction of carbon emissions from power grids, and the absolute error of the results is within 15,000 tons, and the maximum relative error is only 2.42%. The calculation and prediction of carbon emission factors of the power grid can help power grid enterprises to clarify the trend of carbon emission, which is conducive to the realization of the low-carbon goal of “carbon neutral” and “carbon peak”.
Research on the Integration of Traditional Dress Craft Teaching and Online Learning Platform Based on AR Technology
Authors: Gao Xuan
Published: December 2024

The use of augmented reality (AR) technology in the field of education is becoming more and more common, and this study combines it with an online learning platform, applies the AR visual interaction function to the teaching of traditional dress handicrafts, and builds an online learning system of AR traditional dress handicrafts. Through the evaluation of the teaching quality of this online learning system, the performance of the AR traditional dress handicraft online learning system in teaching is revealed. The immersion experience, learning engagement, and system satisfaction scales were used to explore the student’s sense of using the online learning system constructed in this paper after testing the teaching effect. In the evaluation of teaching quality, the mean values of the three-level indicators were between 3.68 and 4.34, of which the mean values of lecture-practice fit (3.980), learning habits (3.680) and inquiry learning (3.740) did not exceed 4. The mean values of the first-level indicators and the second-level indicators ranged from 4.017 to 4.272, and from 3.725 to 4.314, respectively. The mean value of the cognitive posttest of the subject students was 87.591, and the mean value of the pretest was 32.485. The significance of Sig. The value was 0.000, and the difference was significant. The mean values of the dimensions of students’ immersion experience, learning engagement, and system satisfaction were between 3.92 and 4.09. The students reported feeling good about using the online learning system in this paper.
Research on collaborative task scheduling and cooperative control strategy for construction robots based on improved particle swarm optimization algorithm
Authors: Chen Jin , Li Xiaoliu , Zhou Yulong , Liu Tao , Li Ruiping
Published: December 2024

A research program based on collaboration and cooperative control of construction robots is important for the development of the construction industry. This paper aims to develop and design a program based on collaborative construction robots and cooperative control technology to improve construction productivity. We construct a task planning and execution system for construction robots under distributed architecture, design the structure of the information management module, incorporate a hybrid network topology combining star and ring, improve the BEB algorithm to solve the channel collision problem, and form a multi-robot cooperative communication network system. Establish a multi-robot coordination model based on task division, adopt the idea of two-level division, propose a hierarchical distributed coordination method, and establish a hierarchical distributed coordination system framework. Use linearly varying inertia weights and acceleration factors to balance the global exploration and local search abilities of particles to form an intelligent path planning algorithm for construction robots. The simulation experiment environment is chosen, and each algorithm’s performance is analyzed. The simulation experiments involving collaboration and cooperative control of construction robots demonstrate the efficiency and practical application value of the optimization scheme designed and proposed in this paper.
Research on Behavioral Prediction and Cooperative Control Strategy of Construction Robots Based on Deep Learning
Authors: Zou Haona , Chen Jin , Li Ruiping , Wang Haobo , Wu Shun
Published: December 2024

This paper combines game decision-making and learning decision-making models to learn all possible types of strategies in robot behavior, describes human joints as a tree diagram structure through pose estimation, uses dynamic programming algorithms to derive joint information, extracts and models robot behavioral pose features, and identifies the action behaviors of construction robots. Through path tracking and other controls, robot behavior can be controlled to achieve the effects of construction robot behavior prediction and cooperative control. Set up simulation experiments to collect and preprocess the behavioral data of the construction robot, identify its behavior, predict its intent, and assess the safety risk of the construction robot’s action route. The robots constructed in this paper are put into the project, and the safety management input calculates the safety management efficiency. After adding the loss function to the model, the precision, recall, and F1 value mean of the construction robot are improved by 5.895, 5.461, and 5.765, respectively, and the derived safety management efficiency of the construction robot construction is 70, and the input of the construction robot brings a higher level of safety management to the construction project.
Flexible Manufacturing Line Design and Digital Twin Simulation for Sheet Metal Processing of Complex Parts
Authors: Li Chunhui , Ding Haitao , Huang Junsheng , Zhang Huiju
Published: December 2024

Traditional sheet metal processing enterprises are facing problems such as upgrading manufacturing systems, lower material utilization rate, and lower efficiency of CNC machining. In this paper, we design a flexible manufacturing production line for sheet metal processing of complex parts, use the DQN algorithm to optimize the scheduling of each part of the work in the production process of the production line, and optimize the adaptability of the DQN algorithm by using the action selection strategy and the reward function and so on. Then, the digital twin simulation system is constructed to simulate the process of a flexible manufacturing production line for sheet metal processing. The results show that the DQN algorithm can effectively assign the corresponding processing machines and processes to the workpieces in the production line, and the digital twin simulation system can also accurately simulate the actual situation of the production line. Meanwhile, it is found that the optimized production line can reach 87.52% of the production beat balance rate, which is 23.64% higher than the original production line balance rate, and it can improve the average utilization rate of the main operating units in the production line. The optimized production line proposed in this paper can effectively solve the practical problems in sheet metal production lines, improve the mobility of the production line and corporate efficiency, and provide new ideas for the lean production management of large-scale machinery manufacturing enterprises.
Technical Application of Artificial Intelligence-Based Voice Interaction Control and Intelligent Scheduling for Throwing and Retiring Reclosing Gates
Authors: Bai Yiming , Lin Xiongfeng , Peng Shifeng , Ruan Zhijie
Published: December 2024

Speech recognition, as an important carrier of human information exchange, is characterized by ease of use and high efficiency, and is an excellent choice to act as a medium of information interaction between humans and machines. In this paper, with the background of the application of throwback reclosing in the field of electric power, a speech recognition model is constructed using the DTW algorithm. Subsequently, on this basis, an intelligent dispatching command generation system integrating speech recognition, generation, and interaction systems was built, and the functional characteristics of the intelligent reclosing model were characterized through simulation experiments. After 40-50 rounds of training, the Loss curve of the model in this paper settles to about 0.16. After training for 100 rounds, the word error rate stabilizes at around 7%. In the call corpus, the speech recognition system constructed in this paper has a error rate of 1.124%. The recall in the Scheduling instruction corpus and Scheduling telephone corpus is 0.982 and 0.947 respectively. And, the model in this paper has better performance in terms of the number of errors in speech recognition samples and the word error rate of specialized vocabulary. In addition, the model in this paper can normalize the correlation of electricity consumption between different time points under abnormal conditions. In conclusion, the model in this paper is both efficient and stable in the power field, especially in the application of reclosing technology.
Research on Agricultural Product Marketing Education Models and Management Strategies Driven by Internet Technology
Authors: Piao Chensheng , Yu Linling , Li Xuefeng
Published: December 2024

Internet technology is bound to be a big opportunity for agricultural marketing, how to effectively use the Internet technology innovation of agricultural marketing for the current focus of the research direction. The paper examines agricultural product marketing that is driven by Internet technology from the perspectives of agricultural product marketing mode innovation and marketing education mode innovation. The design of a mixed teaching mode for agricultural product marketing aims to cultivate talents in agricultural product Internet marketing technologies. The analysis of the development of agricultural product marketing education mode uses a comparative method and is divided into two stages: online marketing teaching and overall marketing mode teaching. The improved RFM model is used to solve the value of agricultural product customers, and the consumption characteristics of customers of different age stages are found. Among the four types of customer groups, 25-40-year-olds accounted for the highest proportion in the developing and maintaining customer groups, and 40-55-year-olds and 10-25-year-olds accounted for the highest proportion in the low-value customer and high-value customer groups. Agricultural product marketers should focus on customers under 55 years of age as the target of agricultural products, focusing on services and implementing precision marketing of agricultural products.
Optimization Study of Youth Ice and Snow Sports Training Data - Analysis of TensorFlow Platform Based on One Belt and One Road Region
Authors: Wang Ying
Published: December 2024

Technology-enabled snow and ice sports data optimization facilitates the development of snow and ice sports training strategies and provides support for ensuring the safety and enhancing the training effect of youth snow and ice sports. This paper designs a system to collect and track snow and ice sports data. It is designed to extract electromyographic signal data from snow and ice sports training through a high-frequency wavelet function. A clustering algorithm is used to process and optimize snow and ice sports training data, and then a sports feature data mining model is established for snow and ice sports auxiliary decision support. The deep learning TensorFlow framework was used as the basis to realize the construction of a generalized dynamic fuzzy neural network, and a variable sliding window was used for model learning in order to realize the accurate prediction of the training load of youth snow and ice sports. The GD-FNN model predicted the muscular strength level of snow and ice sports training with a relative error of only 1.74%, and it also accurately predicted the blood oxygen saturation. The RMSE value of blood oxygen saturation was only 0.68. Under the personalized cyclic impedance training mode, the hemoglobin content of the experimental group was 152.64±8.76 g/L, which was significantly different from that of the control group at the 1% level. Relying on the training data of youth ice and snow sports in the Belt and Road, clarifying the physiological conditions of athletes in different countries can help to enhance the synergistic improvement of the ice and snow sports level in the Belt and Road countries.
Automatic essay scoring for natural language processing: feature extraction and scoring models
Authors: Lu Jia , Ni Pingli
Published: December 2024

Automatic essay scoring technology is an important application in the field of natural language processing, which combines machine learning, deep learning, and other technologies to automatically assess the quality of essays through computer algorithms. This paper combines the features of convolutional neural networks and long- and short-term memory neural networks to create the MLSN neural network model. The automatic scoring of essays using local semantic features, global semantic features, topic layer features, and shallow linguistic features aims to improve the fairness and accuracy of scoring. The clustering of 810 essay samples into 6 classes in this paper facilitates the subsequent analysis of the experiments. The model in this paper converges successively in terms of loss, accuracy rate, recall rate, and F1 after being trained on 20–40 batches. At approximately 0.08, 0.93, 0.91, and 0.88, respectively, their values stabilized. The evaluation indexes of this paper’s model have all significantly improved compared to the comparison model. This paper’s model has improved the QWK scores of essay samples for different topics to varying degrees compared to the comparison model. When combining multi-level semantic feature modules, the ablation experiment reveals a 6.91% improvement in the scoring effect of this paper’s model compared to the topic-only semantic feature module. The above experimental results fully demonstrate the superior performance of this paper’s model, suggesting that it has better applications in automatic essay scoring.
Research on Dynamic Adjustment of Enterprise Resource Integration and Strategic Management Based on Cloud Computing Optimization
Authors: Wang Geng
Published: December 2024

The extent to which modern enterprises utilize their resources significantly influences their strategy formulation and even raises questions about their ability to remain competitive in the market. This paper finds the best way to use traditional enterprise resources by using cloud computing. It does this by creating a multi-objective scheduling model to combine enterprise resources and using a stochastic-aware real-time task scheduling strategy to make the most of the combined enterprise resources and raise their utilization rate. Based on the dynamically changing enterprise resource information, a strategic integration model is constructed based on the dynamic resource view to adjust the enterprise development strategy in real-time. Company A, an automobile production enterprise, has been selected to conduct an example study to examine its resource integration and strategic management effect after experiencing cloud computing optimization. The deployment time of enterprise resources has increased after cloud computing optimization, significantly enhancing the efficiency of resource integration and deployment. In the small-scale workflow, the enterprise resource utilization rate achieves a 50% improvement, while in the large-scale workflow, the resource utilization rate exceeds 40%. Compared to the financial status of Company A before and after the optimization, its solvency, operating capacity, and profitability have significantly improved after the adjustment. The satisfaction scores of Company A’s management team on the five dimensions of quality of resource integration, efficiency of resource deployment, speed of response to market feedback, familiarity with the market, and reasonableness of the strategy are all above 4, indicating promising results in resource integration and strategic management.
Modeling the Impact of Cultivating Entrepreneurship and Creative Skills on Future Career in Music Education
Authors: He Rui
Published: December 2024

The current trend of mass entrepreneurship and innovation encourages college students to approach the new opportunities and challenges of employment with a positive mindset, while also expanding the opportunities for music majors to engage in “double creation.” The article establishes a model of music education based on the double helix model and outlines the competence structure and framework necessary for cultivating music talent. To quantify the cultivation of entrepreneurship and innovation ability in music education, this article introduces the Rasch model to assess and analyze the level of students’ entrepreneurship and innovation ability. To analyze the importance of entrepreneurship and innovation capability in future career planning, the SEM for parameter estimation using PLS is introduced to construct a model of influencing factors. Through examples, we analyze the quality of students’ dual-venture level, which integrates entrepreneurship and innovation abilities in music education, and explore the degree of influence this level has on career planning. The mean value of the measure (in logits value) of students’ bi-initiative level is 3.463, placing them at level IV overall. The study found that the cultivation of entrepreneurship and innovation ability in music education significantly influences future career planning, with path coefficients of 0.572 and 0.337, respectively. The integration of entrepreneurship and innovation-based teaching content in music education can help enhance students’ ability to plan for their future careers and contribute to the high-quality development of music professionals.
Design and Practical Effectiveness Evaluation of Intelligent Teaching Platform for Music Education in Colleges and Universities
Authors: He Rui
Published: December 2024

The development of the Internet, artificial intelligence, and other technologies has put forward new requirements for intelligent music education in colleges and universities. This paper utilizes Internet technology to construct an intelligent teaching platform for music education in colleges and universities, incorporating the intelligence of music appreciation, online examination, and music knowledge learning. The forward neural network multi-feature fusion algorithm in the music appreciation module constructs the music emotion classification model, arranging the content based on the appreciation content and emotion type. The online examination module uses the simulated annealing method to improve the genetic algorithm, which then intelligently groups papers. The method of hierarchical analysis is used to quantitatively and qualitatively analyze the students’ satisfaction and design evaluation indexes for music-intelligent teaching platforms from the perspectives of teaching content and teaching quality. The music education classroom of a southern university is selected to apply the intelligent teaching platform for testing, and as the number of students gradually rises to 300 and above, the stability of the platform still performs well. Simultaneously, the evaluation results of the teaching platform indicate that the teaching quality and grouping rationality index scores are 8.94 and 9.02, respectively. These scores indicate that the platform significantly meets the students’ needs in terms of teaching effectiveness and grouping rationality.
Pattern Recognition Based Music Style Recognition and Teaching Application in Higher Education Music Education
Authors: Yue Qiannan , Wang Lin , Luo Jia
Published: December 2024

This paper presents a summary of a range of characteristic parameters that define the tone features. This is achieved by studying the time-frequency and frequency characteristics of music signals with different instrumental timbres, and it represents the characteristics of the music in various frequency bands and time domains. The optimized DTW pattern recognition algorithm achieves the classification of music styles. The conducted experiments clearly recognized several basic violin bowing styles. Jazz’s classification and recognition effect is 80% accurate. The accuracy rate of the music brief spectrum recognition exceeded 95%. The teaching method based on music pattern recognition has a significant teaching effect in the knowledge and skill dimensions, with a Sig. value of 0.001.
Research on the Design and Practice of Smart Elderly Public Service Network Architecture in Ethnic Areas
Authors: Zhang Jing
Published: December 2024

In the context of the “Internet +” era, smart pension services have become an important way to solve the problem of elderly pensions in ethnic areas. This paper analyzes the feasibility of smart elderly care for elderly individuals in ethnic areas from different perspectives. It puts forward the main needs of the elderly service in ethnic areas, takes the welfare pluralism theory and resource dependence theory as the theoretical basis of the smart elderly public service system, and understands the smart elderly public service system from the three levels of technology, service and organization. Combine intelligent alarm technology for elderly falls with the Internet of Things technology to build a smart public service system for elderly people. Improve the intelligent sensing technology from the perspective of environmental perception and use Michelson fiber optic sensing technology as the medium for elderly fall signal detection. Test the main control and communication modules of the IoT platform. Analyze the role of improved sensing technology in recognition of fall actions, and increase the forward fall alarm rate to more than 90%. Research and statistics on the degree of satisfaction of the smart elderly public service system for elderly care and medical rehabilitation needs. The demand for convenient elderly maintenance in ethnic areas in the smart elderly service system accounts for 39.54%, which is lower than the 46.88% registered appointments. The smart elderly public service system can satisfy the life needs of the elderly to a certain extent, but there is a need to further increase the elderly’s knowledge of the smart elderly public service system in order to effectively satisfy the elderly services in ethnic areas.
Research on Automatic Sculpture Morphology Generation and Artistic Aesthetics Evaluation System Based on Machine Vision
Authors: Wang Chunxin
Published: December 2024

Sculpture has become a work of unique artistic charm by virtue of its rich visual aesthetics and unique carving method. The combination of computer vision and sculpture art has become a hot research topic in the field of art. Based on this, the article concludes the research on automatic morphology generation methods based on machine vision. Firstly, we use the morphology recognition machine to recognize and process the sculpture image, attach the source model to the background target model grid and fuse it, and generate the final sculpture model through the grid parametric mapping between the source model and the target model. Then, the automatic sculpture form based on machine vision is selected as the research object, and the fuzzy comprehensive evaluation method is applied to fuzzy evaluate the selected evaluation indexes. The fuzzy comprehensive evaluation method is used to evaluate the artistic aesthetics of the automatic sculpture form based on machine vision. The comprehensive target layer vector is calculated to be B = WR = (0.1713 0.1084 0.0772 0.0173 0.0143), and the final evaluation value is 27.527, and the evaluation grade is very good.
Construction of a model for analyzing the trend of suicidal tendency among college students based on mental health monitoring
Authors: Gong Xun , Rao Zhouzhou
Published: December 2024

In recent years, college student suicide has become the second cause of death on campus after accidents. This project introduces machine learning methods to the mental health monitoring of college students and constructs a model for analyzing the trend of college students’ suicidal tendencies using the SVM algorithm. First, we researched the mental health problems of college students in several colleges and universities and constructed the SVM model by using screened mental health monitoring variables as input features. Its performance is analyzed through model evaluation and comparison, and it is used in the intervention of college students’ mental health problems. Experimental analysis reveals that the SVM model constructed in this paper presents a better performance in analyzing the trend of suicidal tendencies, with a prediction accuracy of 0.935 for different suicidal tendencies, and the results of different assessment indexes are better than the comparison model. After using the model to assist universities in providing mental health interventions for students, the suicidal ideation among sample students decreased by 42.41%. The use of the SVM model to predict college students’ suicidal ideation is effective, and it can be used as a convenient and efficient tool for screening and assessing the risk of suicide attempts to improve the efficiency of suicide prevention.
Research on the Innovation of Publicity Work in Colleges and Universities under the New Media Environment
Authors: Tang Yanhua
Published: December 2024

New media has become a new propaganda carrier of the development of the times, today’s society with the massive use of mobile devices, all kinds of new media content in the form of fragmentation of high-speed dissemination. How to use new media in colleges and universities has become a key issue that must be considered in publicity work. In this paper, based on the topology and characteristics of the complex network, the complex network data model is constructed, and on this basis, the SIS propagation dynamics model and sentiment analysis are added, and the final propagation density formula is derived through the derivation of the critical value. Through the convolution operation of a graph neural network, the various orders of propagation phenomena in social media networks are modeled, and a prediction model is proposed to predict user preferences in the social perspective of new media. The user and content vectors are used as inner products to predict user ratings for the public numbers advertised. The model is optimally adjusted using the loss function. The WeChat public number of the subject university, University B, showed high reading peaks in March, May, October, and November, with reading counts of 75107.95, 75575.95, 72767.99, and 107,821.3 per read, respectively. University B’s official public microblog keeps a steady reading count, and individual extremely excellent works produce reading peaks. The publicity sentiment of student users to the official WeChat public number of University B is mainly positive and reaches a maximum value of 4.248 after 13 days of the publicity video release, followed by sad and fearful sentiment release to keep in line with the positive sentiment, the University B handles the publicity of the graduation season better, and the students’ sentiment is more positive.
A Topological Mapping Study on the Enhancement of Students’ Career Prospects by the Industry-Education Integration Model in Local Universities
Authors: Wang Yuxi , Dou Liang , Jin Jienan
Published: December 2024

This paper proposes a container network mapping algorithm (MMigration) for career prospect enhancement for the integration of production and education in local colleges and universities and constructs a topology mapping model for the enhancement of college students’ career prospects. After testing the performance of the model, it analyzes the impact of the container network topology mapping model on the career prospects of college students under the mode of production-teaching integration. Finally, based on the experimental results, it points out the direction for the “internship-employment-culture” industry-education fusion linkage training model of local colleges and universities on the improvement of students’ employment quality. Compared with 2019, the number of internship training bases (14.17%), the number of teachers hired from enterprises (41.18%) and the number of in-service teachers exchanging and studying in cooperating enterprises (151.61%) in local colleges and universities are all on the rise. When local colleges and universities integrate industry and education with enterprises, the performance of each of the six tasks of school-enterprise cooperation shows a significant upward trend. In addition, the mean employment rate of the students’ professional counterparts in industry-education cooperation enterprises increased by 64.87%, 72.15%, 86.51%, and 94.51% from 2019 to 2022, respectively. This indicates that the locally efficiently explored schooling model of industry-teaching integration in local engineering colleges is extremely helpful for students’ career prospects enhancement.
Hierarchical analysis-based retrofitting of old residences for age-appropriate interior design
Authors: Zhang Weiwei
Published: December 2024

At present, the aging of the population, the aging of buildings and environmental facilities and other problems are becoming more and more serious, and the aging renovation of old communities is an effective measure to solve the problem of population aging. Based on the demand analysis, this paper combines expert opinions to construct an index system for aging-appropriate interior design and renovation of old residences, including 1 target layer, 4 guideline layers, and 17 index layers. The AHP-fuzzy comprehensive evaluation model is created by combining the hierarchical analysis method with the fuzzy comprehensive evaluation method. The AHP-fuzzy comprehensive evaluation model is utilized to evaluate each index of the old residential interior design renovation that is age-appropriate. Finally, it is concluded that the weights of the indicators of the criterion layer (B) to the target layer (A) are spatial function (0.4495), mobility accessibility (0.2596), electrical equipment system (0.1707), and thermal environment (0.1202). The weights that were assigned to the indicators of the indicator layer (C) to the target layer (A) were most significant for bedrooms (0.1651) and least significant for temperature regulation and ventilation (0.0072). The overall quality of interior design for aging in older homes was “good” (0.796), with kitchen design (0.4) being the worst. Based on hierarchical analysis, the study proposes remodeling strategies for several important aspects that need improvement.
Applying Game Theory to Analyze the Development Path of School-Enterprise Cooperation in Vocational Education
Authors: Shen Jie , Zhang Silei
Published: December 2024

In the context of today’s rapid economic and social development, school-enterprise cooperation in vocational education has become increasingly important. The cooperation process can be challenging due to the differences in the interests of the cooperating parties. The study constructs a vocational education school-enterprise cooperation model based on the use of game theory in school-enterprise cooperation and combines it with the game model of the school-enterprise cooperation mechanism and the power mechanism of the school-enterprise cooperation game. Examine the impact of school-enterprise cooperation on the evolution strategy of school-enterprise parties in school-enterprise cooperation and propose recommendations for the development path of school-enterprise cooperation. In school-enterprise cooperation, the different initial willingness of school enterprises, cooperation benefits, extra costs of the university side, positive benefits of the university side, and betrayal benefits all have impacts on the strategy evolution process. Among them, the initial willingness of the school enterprise, cooperation gains, and positive gains of the university side are positively correlated with the strategy evolution process. When both the university and the enterprise value their initial willingness at (0.9), they tend to exhibit a positive cooperative tendency. When the cooperation gain (R) reaches a value of 50, the system evolves to (1,1). The system steadily transitions from the stability point (0,0) to (1,1) as the university side’s positive gain increases from 1 to 3. In contrast, as the extra costs and betrayal gains on the university side increase, university-enterprise cooperation shows a negative trend.
The linear programming model of the optimization configuration of education resource optimization for higher vocational students
Authors: Han Yushan
Published: December 2024

Promoting the optimal allocation of the ideological and political education resources for higher vocational students is the key to realizing the work of higher vocational ideological and political education. On the basis of analyzing the connotation characteristics and content framework of the ideological and political education resources, the article explores the optimization mechanism and configuration objectives of the ideological and political education resources. Based on the data envelopment model, a DEA-CCR pairwise planning model is constructed by combining the linear programming theory, and the Malmquist index is introduced to explore the dynamic optimization and allocation efficiency of the ideological and political education resources. The input redundancy and output of Civic and political education resources are not enough to obtain the specific measures for their optimal allocation, and the DEA-CCR model for optimal allocation of Civic and political education resources is also solved by using LINDO software. Panel data from 31 provinces in China were used as an example to quantitatively analyze the allocation efficiency of civic education resources for higher vocational students.The values of the allocation efficiency of civic education resources for higher vocational students during the period of 2017-2022 were all in the range of 0.78-0.85, with a 33.73% increase in purely technical efficiency, a 140% increase in the number of regions where the DEA was realized to be effective, and an increase in the Malmquist index of 0.375.In the linear programming model of civic education resources, based on input redundancy and output insufficiency it is possible to obtain targeted strategies for the optimal allocation of civic education resources for higher education students.
Tax Incentives, Innovative Development of Digital Economy Industries and Green Innovation Efficiency in Cities
Authors: Wang Hongyan , Peng Aimei , Xu Wenwen
Published: December 2024

Focusing on the value of green innovation efficiency in cities, this paper explores the intrinsic mechanisms of tax incentives and the innovative development of digital economy industries in promoting efficiency. This paper first proposes the principle of the regression algorithm required for the study as its theoretical foundation. In the principle, it focuses on the solution method of the LS method, proposes the univariate regression model and the multivariate regression model respectively, and determines the parameter estimates through the residual vector derived by the least squares method. Combined with the regression model, the mediation effect model is proposed to examine the impact of tax incentives on urban green innovation efficiency by taking government subsidies and tax incentives as the entry point of tax incentives. The results show that the regression coefficients of government subsidies and tax incentives are 1.769 and 1.838, respectively, which are positive, and the tax incentives can significantly improve urban green innovation efficiency and can realize the improvement of urban green innovation efficiency by promoting the innovative development of the digital economy industry. The effect size of tax incentives on urban green innovation efficiency in different regions of East, Central, and West China shows regional heterogeneity.
A study on the innovation of one-stop school registration management mode and the application of graph theory algorithm in the context of digitization
Authors: Che Yaqian , Liang Gaoyan
Published: December 2024

School registration management is an important part of the school management process, which is the basis of other work. This paper proposes an innovative school registration management system that integrates the school registration early warning system into the one-stop school registration management model. The data mining method is utilized to mine and process students’ school registration information to extract useful information. On this basis, the academic registry management system and the academic registry early warning system are constructed, and the graph theory-based subspace clustering algorithm is introduced to realize the innovative academic registry management model integrating academic registry early warning. Behavioral data provided by the information center of University A is used as the basis for the analysis of students’ campus card usage data. The subspace clustering algorithm proposed in this paper can obtain accurate results for clustering students’ usage behaviors, and the accuracy of the algorithm is consistently maintained between 80% and 90%. Then the academic data of the 2018 to 2021 graduates in University A is used as an experimental analysis object to predict the clusters to which the performance points belong, and the clusters generated by clustering are mined to find out the common characteristics of outstanding students and the relationship between the student data and the academic data. Finally, feature data clustering is performed on students’ academic characteristics to obtain information on students with abnormal academic status, and the implementation of dynamic monitoring of academic status reveals that 95% of students do have abnormal academic characteristics.
Research on Content Innovation Path of Journalism and Communication Education Driven by AI Technology
Authors: Chen Feijing
Published: December 2024

Under the background of the big model of artificial intelligence, the cultivation of journalism professionals in colleges and universities is facing major challenges, and this paper explores the content innovation path of news communication education empowered by AI technology with the help of the structural equation model. By summarizing the development history of “AI+Education”, it extends the impact of AI technology on journalism and communication education. Combined with the principles of questionnaire design and the actual situation of journalism and communication education in colleges and universities, the questions in the questionnaire are designed, and a structural equation model is constructed for the content innovation of journalism and communication education empowered by AI technology, and the model in this paper is used to analyze the examples. The 20 items in the questionnaire satisfy the condition that the absolute value of skewness and kurtosis is less than 3, its sample data based on the questionnaire conforms to normal distribution, and all the paths have passed the significance test with a significance level of 0.05. This study demonstrates the interaction mechanism and linkage between the paths of content innovation in journalism and communication education, empowered by AI technology, using a questionnaire and structural equation modeling.
Pattern Recognition and Algorithm Improvement for Error Analysis in Voltage Transformer Low Voltage Testers
Authors: Chen Xu , Zhang Haomiao , Zhang Chao , Cheng Zhiqiang , Xu Yinzhe , Yan Yu , Zhang Xinrui
Published: December 2024

To ensure the fairness and accuracy of electric energy measurement, it is necessary to carry out on-site calibration of voltage transformers in operation according to the cycle, and due to a large amount of measurement workload and many dangerous factors, a low-voltage tester is used at this stage to carry out the measurement work. This paper explores the basic method of low-voltage testing, sorting out the steps for the use of low-voltage testers in voltage transformers and proposing a resonance-based CVT analysis method to assist in the voltage transformer measurement operation of low-voltage measuring instruments. When performing the calculation of the error on the low-voltage side, the low-voltage extrapolation method is used to extrapolate the measurement error on the high-voltage side of the voltage transformer, and on this basis, a neural network architecture is proposed to suggest an improvement strategy for the existing algorithm. Using the method proposed in this paper, the voltage transformer low voltage test error analysis, the method proposed in this paper is consistent with the error trend measured by the overall error test method, and the maximum value of the error deviation is 0.0436%, which is not more than 0.05%, and is smaller than the error limit of the test article. At the same time, in different modes of voltage transformer error characterization, with the ambient temperature from -35 ° C to +22 ° C in the process of change, the ratio difference of voltage transformer from 0.183% change to 0.152%, phase difference from 4.18′ change to 4.68′, the whole process, the ratio, phase difference is not exceeded, the error measurement effect is good.
A Study on the Reform Direction of Virtual Reality Teaching Tools on Traditional Chinese Literature Teaching Methods
Authors: Cheng Xirong , Pan Tingting , Wang Mulan
Published: December 2024

This paper uses virtual reality technology, augmented reality technology and other means to combine the virtualization design with traditional Chinese literature, interpreting a “virtual realm” in the future world from a new perspective and reforming the teaching of traditional Chinese literature through three aspects of literary imagery, scene and cultural display. This is a reform of traditional Chinese literature teaching, focusing on the three aspects of literary imagery, scene, and cultural display. The results of applying VR technology to the teaching practice of traditional Chinese literature show that on a natural level, the imagery of smoky rain and willow is mainly used. At the level of humanistic architectural landscape, temples, Rainflower Terrace, and Phoenix Terrace are the main imagery. At the level of social and cultural activities, the frequency of the Six Dynasties is the highest (40). Classical garden art and culture can be demonstrated in the scenes constructed throughout traditional Chinese literature, including poetry and literature. Compared to traditional teaching methods, the satisfaction rate for cultural display in VR teaching of traditional Chinese literature is as high as 92.5%. In the comparative analysis of teaching feedback, the experimental class mainly focuses on the score range of 60-80, while the distribution of the control class mainly focuses on the range of 30-60 points. The use of VR technology, on the other hand, allows students to devote themselves to the course and improves the learning process.