bluuebunny/crossref_metadata_2025 huggingface dataset:
A Practical Approach to the Reform of “Three Teachings” in the Age of Digitalization to Promote the High-Quality Development of Higher Vocational Education
Authors: Cao Wei
Published: February 2024

It has become difficult for conventional higher vocational education to fulfill the needs of the digital era, and reforming the “three teachings” is now a crucial decision to promote the high-quality expansion of higher vocational education. Promoting the high-quality development of higher vocational education by adopting a practical approach to reforming the “Three Teachings” in the age of digitalization. In a composite system model, the sequence parameters for the higher vocational school subsystem are determined by the sequence parameters of the ‘Three Teachings’ reform. The TOPSIS method and Moran’s I were used to assess the rate of growth of China’s higher vocational school system to look into the main factors that have contributeds to the good development of higher vocational education in that nation. The results show that there is weak geographical clustering, with each region’s 2022 Moran’s I for the “Three Teachings” reform and the high-quality development of higher vocational education being just 0.1280. Moreover, Moran’s I show a general downward trend from 2013 to 2022, suggesting that challenges need to be addressed to keep improving higher vocational education in a top-notch way. The ‘Three Teachings’ reform strategy presented in this study may help further sustain the long-term, high-quality expansion of higher vocational education.
Research on Computer Network Security Vulnerabilities and Encryption Technology in Cloud Computing Environment
Authors: Peng Peng
Published: February 2024

Inadequate network security defense measures threaten the information and property security of the state and the public, and how to safeguard network security is of vital practical significance. This paper proposes a dynamic security threat assessment model and a robust optimal control strategy to improve the efficiency of detecting network vulnerabilities and the accuracy of detecting network threats in a cloud computing environment. It also protects the privacy of the user's identity through a multi-factor continuous authentication method, encrypts and protects the user's data using a homomorphic encryption algorithm, and strengthens the ability of computers to resist intrusion. Three case studies are conducted to verify the effectiveness of the proposed technical approach: dynamic assessment of security threats, control policy, authentication, and network encryption. The results show that in the network vulnerability control policy and authentication case study, when adding the control policy Tk
= 40, the percentage of network normal nodes, malicious nodes and restorer nodes are 0.98, 0.02, and 0.009, respectively, and the encrypted plaintext ASCII value is distributed in [0,60] in an unordered manner, and the network is in a very desirable security state. Real-time accurate assessments of network security state can be provided by cloud computing-based network security vulnerability and encryption technology.
Research on the application of digital media technology in dynamic visual communication design
Authors: Zhang Wendi , Shao Lin , Wang Xinmin
Published: February 2024

With the continuous development and improvement of digital media technology, its position in dynamic visual design is also increasing. In this paper, we first combine LCEOPaCH algorithm to extract color features from visual images, use local energy pointing mode to get image color transformation information, optimize the dynamic visual measurement method based on dynamic binocular reconstruction, and construct a dynamic visual communication model combined with visual SLAM. Through the empirical data of the visual communication system, the localization accuracy of different methods in dynamic environments is compared based on the root mean square error value of absolute trajectory error in dynamic datasets A, B, and C. The quantization results of this paper’s algorithm under dynamic visual measurement analysis and color feature extraction data comparison in 6 sets of simulated images, the PSNR value is higher than 30, and the average value of PSNR is as high as 38.11 under 24 feature colors. The SSIM value for 8 feature colors is higher than 0.75 in the same quantization. The study demonstrates the advantages of digital media technology in visual communication design and provides practical design ideas.
Analysis of public resource allocation model based on BP neural network
Authors: Yang Maolin
Published: February 2024

Accelerating the rational allocation and optimal integration of urban public resources plays an extremely important role in national and regional development. Based on the public resource allocation model of BP optimization and the analysis method of public resource allocation efficiency, this paper, on the basis of constructing the indicators of the public resource allocation model, calculates and analyzes the data of each indicator from 2012 to 2020 of four cities A, B, C and D in Z, to test the validity of the constructed model and to derive the efficiency of public resource allocation of these four cities. Lastly, the Tobit regression model is employed to explore the factors that influence public resource allocation. In terms of public resource allocation efficiency, 2017, 2018 and 2019 are the concentrated years in which the public resource allocation of the four cities reaches the effective value of 1. The average value of the public resource allocation efficiency of the four cities from 2012 to 2020 is around 0.9, which does not reach the effective value of 1, and the overall allocation efficiency is low. Among the 24 selected influencing factors, 20 influencing factors have a positive effect on public resource allocation efficiency, accounting for 83.3%, of which 11 factors have a significant effect, satisfying P < 0.1.
Research on photovoltaic energy storage unit charge state detection method based on improved limit learning machine
Authors: Ma Xue , Li Fang , Li Xiantao , Ying Zhiping , Gong Siyu , Xiao Yu
Published: February 2024

In order to accurately detect the photovoltaic energy storage unit charge state, this paper selects the parameter charge state as the detection quantity in the equivalent model, establishes the PSO-ELM method to detect the charge state of photovoltaic energy storage unit, optimizes the limit learning machine network using the particle swarm optimization algorithm, and improves the problems such as redundancy of neurons in the implicit layer of the limit learning machine and the poor ability to identify the unknown input parameter, so as to increase the detection accuracy of the PSO-ELM method to improve the detection accuracy of photovoltaic energy storage unit charge state. The relative error between the method established in this paper and the results of the PV storage unit charge state detected by the definition method in the charging state is kept within ±1.9%, and the detection accuracy of the improved method in the dynamic working condition can reach about 97%. The PSO-ELM method established in this paper can accurately detect the charge state of PV energy storage units under various conditions, as demonstrated experimentally.
Optimization and innovation of enterprise finance and accounting supervision system under big data technology
Authors: Liu Guohua , Wang Xiaoyan , Wang Luhui
Published: February 2024

With the continuous development of the social economy, financial and accounting risk control and early warning have become an important part of the sustainable development of enterprises. This paper combines the C4.5 decision tree and Benford law-based random forest audit warning model by constructing enterprise financial risk assessment indicators and audit warning indicators, calculates the indicator data of 100 companies to get the financial risk assessment rule set, and validates it with the financial data of Company A in 2018-2020 as a sample. Our method of obtaining the audit warning interval for 8 indicators and validating it is by using Company B’s indicator data from 2019-2020 as a sample. The assessment results are ‘yes’ when company A is used as an example for empirical analysis, confirming the accuracy of the financial risk assessment model. Early warning intervals are obtained from the Random Forest audit early warning model, in which accounts receivable ledger balance X1 > 5.72, accounts receivable aging X7 > 33.14, accounts payable aging X8 > 4.76, and provision for bad debts X9 > 14.10. The result of the test in the fourth quarter of 2019 for Company B is an early warning status with a probability of 73%. The warning interval is triggered by four indicators, which include the accounts receivable ledger balance X1, accounts receivable aging X7, accounts payable aging X8, and bad debt provision X9.
Effective Application of Smart Logistics Technology in Rural E-commerce Logistics Distribution
Authors: Wei Wenji
Published: February 2024

With the continuous development of smart logistics technology, the status of rural e-commerce logistics and distribution has also increased. This paper combines the intelligent logistics technology framework based on rural e-commerce logistics distribution situation, the selection of rural e-commerce distribution node sites, and distribution path optimization. Furthermore, construct a game model for the rural e-commerce logistics and distribution industry chain with the goal of generating synergy. We examine the traditional rural e-commerce logistics and distribution scheme, distribution node setting, and benefits game based on this basis. The results show that the total cost of the smart logistics distribution program is reduced by 200.7 compared with the traditional distribution program, and the total cost of the smart logistics distribution program saves 5% compared with the traditional distribution program. The average transportation time of smart logistics distribution is 11.22min, which is significantly reduced compared with traditional logistics distribution. The rural smart logistics distribution system for e-commerce that uses benefit sharing and cost sharing profit 1242 is the best program when comparing benefits. To sum up, smart logistics technology plays a significant role in rural e-commerce logistics distribution, which can effectively save logistics distribution costs and enhance distribution efficiency.
Construction of Chinese Youth Football Players Cultivation System Based on Discrete Regression Algorithm
Authors: Hu Hongquan
Published: February 2024

In the course of the development of Chinese soccer, the development of youth soccer plays a very important role, so it is very important to build a scientific training system for youth soccer. In this paper, Bootstrap resampling technique is used to train the multidimensional logistic regression algorithm, and the genetic algorithm is used to optimize the parameters, which in turn improves the logistic regression algorithm. The HBase discrete regression algorithm model is constructed by combining the improved logistic regression algorithm with the HBase database system. Experiments were conducted on the running ability, performance prediction, and mental health disorder detection of Chinese youth soccer players, and finally the clubs in five places that improved the training system of youth soccer players through the HBase discrete regression algorithm were evaluated. The experimental results show that the maximum instantaneous explosive power of the athletes is close to 80 m/s2. In the performance prediction experiment, the error between the performance of the youth soccer players predicted based on the HBase discrete regression algorithm and the real value is less than 0.5. In the five clubs that have improved the cultivation system of the youth soccer athletes based on the HBase discrete regression algorithm, the overall average score of the evaluation of the cultivation system is more than 83 points.. This study has the potential to help improve the development of youth soccer in China.
Analysis of the Professionalism of College Teachers in the Information Age Based on Teaching According to Materials
Authors: Qiang Xiaojing
Published: February 2024

Aiming at the problem that it is difficult to objectively analyze the degree of teaching based on teaching materials in the traditional way, this paper establishes an index system based on the opinions of experts and the characteristics of teaching based on teaching materials. A BP neural network analyzes the index system to measure the level of teaching by university teachers based on teaching materials. This paper aims to improve the running speed of the BP neural network by employing the gradient-at-every-turn method and optimizing parameters. Moreover, the maximum-minimum value method is used to normalize the data, and the entropy value method is used to calculate the weights of the indicators to provide more accurate data for the BP neural network. Once the model construction was finished, it was put through its paces in teacher training and science colleges for trial operation. The absolute value difference between the output of the neural network and the expert evaluation is between 0.09 and 0.052, which are all less than 0.1. Most of the teachers’ scores are at the excellent level, around 0.8-0.9, but the score for diversified teaching methods is 0.6784, which is on the low side, proving that there is still room for improvement in this aspect.
Research on Innovative Parenting Mode of Ideological and Political Education in Colleges and Universities under the Background of Big Data
Authors: Che Yanqiu
Published: February 2024

In the context of the new era, the education concept has been transformed, and practical parenting has attracted much attention, and the talent cultivation mechanism of colleges and universities therefore urgently needs to be innovated to meet the requirements of the development of the times. In this paper, we optimize the original objective function of the sample of students’ civic education, use Taylor’s formula to expand the objective function approximation, calculate the complexity of the tree model, and complete the construction of XGBoost student learning behavior. Improve the K-means algorithm based on Canopy, combined with the improved SVM algorithm, to provide early warning for students’ academic performance in Civics. The assessment framework for teaching effect is designed to assess students’ Civics learning process. The results show that after the intervention of the model proposed in this paper, the students’ Civics performance improved from 60.59 to 65.63. The cognitive ability of Civics has a significant effect on social learning and individual learning behaviors at the same time, with the effects of 0.8623 and 0.9782. The innovative nurturing model of Civics in colleges and universities is improved by the proposed model in this paper.
The Embodiment and Application of Minimalism in Graphic Design Teaching Reform Based on Big Data Analysis
Authors: Wen Jie
Published: February 2024

In the context of the deep development of modern science and technology and multimedia technology, the design style of minimalism is also developing in a diversified direction, but there are few studies on its application in teaching reform. Therefore, this paper uses TF-IDF text mining, combined with the K-Means algorithm, to construct a knowledge construction mapping literature intelligent analysis model to reveal the embodiment of the application of minimalism in the teaching reform of graphic design. The use of CHI_TF-ID is intended to address the issues of TF-IDF mining that are both time-consuming and unsatisfactory. By using DBI and DI index, the clustering effect of the K-Means algorithm can be enhanced. A new approach to graphic design design teaching is proposed by using keywords. In the teaching practice, the average results of the experiment class were 85.82, and the average result was 6.96. In contrast, the average score of the control class was 80.43, a difference from the previous score of 79.04. Teaching minimalist graphic design can effectively enhance the effectiveness of teaching.
Teaching Reflections on the Integration of the course ideology and politics into Tourism Management Majors in the Context of the Internet
Authors: Jin Xiaohong
Published: February 2024

The primary task of education is to realize the goal of “establishing morality and educating people”, and to give full play to the role of the course ideology and politics Education, however, the degree of integration of the course ideology and politics Education in the current tourism management profession is not deep enough. In this paper, we start from the perspective of evaluation of the course ideology and politics Politics in the curriculum, use random search algorithm to optimize the hyperparameters of NN-Stacking algorithm, obtain the optimal hyperparameter configuration value based on the Leaky ReLU activation function to initialize the weights of the method, and construct the teaching evaluation methods of RG-UNNS and RG-CNNS, and at the same time, we use the coefficient of determination, the average absolute error, and the average error as the evaluation indexes to evaluate the effectiveness of the constructed methods. Evaluation indexes are used to assess the effectiveness of the constructed methods. In this paper, using the constructed teaching evaluation methods to evaluate the teaching effect of the course ideology and politics in the course of Tourism Management, 84.6% of the students were affected by the course ideology and politics education in the classroom of Tourism Management, and 42.35% of the students strongly agreed that this classroom improved their ability to link the theory to the practice, teamwork ability, independent learning ability, and professional literacy level.
Reform Method of Music Teaching Theory System in Colleges and Universities Based on Deep Learning Analysis Technology
Authors: Man Xiangyi
Published: February 2024

The traditional music teaching theory system is usually based on test scores as the only evaluation index, which is difficult to reflect the learning dynamics of students in real-time, thus making it difficult for teachers to strengthen the teaching of students’ weak knowledge points in real-time. To address this problem, this paper uses the DKVMN knowledge tracking model, combined with the recommendation algorithm to design a music theory analysis and recommendation model for college students based on deep learning analysis technology. In it, the Softmax function is utilized as the activation function of the output layer of the LSTM network, and the weight vector is increased to enhance the recurrence probability of students’ unfamiliar knowledge points. After the model design was completed, it was used in the music program of a teacher training school, and the overall effect of the use, the students’ personalized diagnostic reports, and the operation of the model were analyzed and explored separately. From 54.51% during the first test to a maximum of 81.42%, the accuracy rate progressed gradually. For the 7th time after the music theory knowledge level test, the experimental group of students scored 81.23, which was significantly higher than the score of the control group of students 74.25. The p-value tested was 0.004, which indicates a significant difference between the levels of the two groups.
Towards Chinese-style Modernization: Digital Economy Helps Liaoxi - An Innovative Path for High-quality Development of Beijing-Tianjin-Hebei Logistics Enterprises
Authors: Duan Lijun
Published: February 2024

An in-depth study of the boosting role of the digital economy is crucial to promoting the high-quality development of the economy in the Liaoxi-Beijing-Tianjin-Hebei region. This paper uses the gray correlation method and global entropy value method to evaluate the weights of the constructed index system, analyze and get the 4 main influencing indicators on the high-quality development of the logistics industry in the Liaoxi-Beijing-Tianjin-Hebei region, and construct the innovation path. By analyzing the development level of the four indicators and the financial performance of logistics enterprises in 14 cities, it is found that the economic open development level of logistics enterprises in Beijing can reach 1.0 in 2021 and that the open development level of Fuxin City grows rapidly from 0.3 to 0.7 within 8 years, while the total return on assets of logistics enterprises increases by 0.8% within 7 years, so that the innovation path constructed in this paper can strongly promote the transformation of logistics enterprises in Liaoxi-Beijing-Tianjin-Hebei region to high-quality development.
Research on the Innovation and Development Strategy of Stage Art Design in the Context of the New Era
Authors: Lv Hang
Published: February 2024

People’s aesthetic concepts have changed a lot in the modern context, and the relevant requirements for stage art design are also constantly improving. The purpose of this paper is to propose a strategy for the innovative development of virtual stages using augmented reality technology. Specifically, the process involves extracting stage movement frame data through the virtual environment and processing stage mechanical movement data. Combined with the stage in the actual operation of the situation, the use of linear functions to optimize the stage data and the data correction at the same time reduce the virtual stage in the movement parameters of the error. The immersive stage is constructed using augmented reality technology, and the elements of color, lighting, and music are added to the stage. Sound presentation, interactive performance, and satisfaction analysis are the three perspectives that examine the impact of stage art design. In the sound presentation, the difference between the top panels of the three heights under full stage conditions is between 5 and 7 dB, with an average value of 5.7583 dB, and the sound presentation is closer to the ideal state after full stage. Nearly 50% of the audience thought that the stage engagement was better, giving a high satisfaction score of 5. The use of augmented reality technology has enhanced the choreography’s interactivity.
Research on the application of visual illusion in the field of art and design
Authors: Qi Lu , Wang Genbing
Published: February 2024

The visual illusion is complementary to the art design techniques, which can be partially alienated according to this psychological characteristic of human beings and increase the interest in art design works. In this paper, after designing visual art images, the original local binary pattern is optimized to obtain an improved directional LBP algorithm to improve the accuracy and comprehensiveness of feature extraction. The K-means algorithm is used to cluster the colors extracted using the color space method into a color feature vector in the visual illusion art image. The empirical analysis is carried out from three aspects: feature vector similarity of visual illusion art images, image color clustering, and the application of visual illusion in the field of art design. The results show that: in the application example of clothing art design, the mean value of line spacing Z1=0.4cm is significantly larger than the line spacing Z2=0.8cm and smaller than the line spacing Z3=1.2cm in the line width Y1=0.4cm, which is larger than 1.25 and smaller than 0.09, respectively. Z3 is significantly larger than Z2, i.e., Z3>Z1>Z2. The mean value of Z2 (M=1.25) on the line width of 0.8cm is significantly greater than Z3 (M=0.8), indicating that lines with narrow width and wide spacing have the best slimming effect. The application of visual illusion in the field of art design can strengthen the effect of visual communication, enhance the interest of works, and improve the creativity and connotation of works.
A Study on Lexical Disambiguation in English Translation Based on Twin Neural Networks
Authors: Cui Cui
Published: February 2024

To solve the problem of the lack of effective algorithmic models to improve the accuracy of lexical disambiguation in English translation, this paper constructs a twin network lexical disambiguation model based on the characteristics of twin networks, and studies the construction process from the original corpus to the input sample pairs. The Stacked-LSTM algorithm is utilized to align the input Chinese and English corpus and expand the dataset. To achieve disambiguation, the input sample similarity is calculated after training the twin neural network, which extracts corpus features using BiLSTM Attention. After comparing the disambiguation experiments of various algorithms, the model of this algorithm can effectively calculate the similarity of the input samples and achieve the disambiguation accuracy of 68.23% for English vocabulary translation, and 87.0% for vocabulary segmentation of complex English sentences or articles. This shows that the model of this algorithm has good performance for disambiguating English translations.
The design of teaching system for university English digital course based on deep learning model
Authors: Fu Li
Published: February 2024

In this paper, the dependency relationship between different knowledge points is constructed by statistically counting the correct rate of answering knowledge points at adjacent times, finding the prior knowledge of each knowledge point, and the prior of the prior. The dependencies of each knowledge point are stored as key-value pairs and added into the loss function of the model as constraints, thus completing the construction of the deep learning knowledge tracking model. Aiming at the shortcomings of the deep learning knowledge tracking model, we propose to improve the DT-BKT learning knowledge tracking model and use it to design the teaching system of the university English digital course and analyze the teaching system of the university English digital course by using simulation experiments. The results show that the shortest time for acquiring the digital materials of college English is 12.35s, which is 52.87s shorter than that of the conventional English teaching resources information management system, indicating that the system in this paper is more suitable for the development and innovation of college English teaching in colleges and universities. This study can mobilize students’ willingness to participate in English learning in all aspects and has a promoting effect on the development of university English digital course teaching in colleges and universities.
Exploration of a deep learning-based mechanism for predicting the work competence of community caregivers
Authors: Huang Juan , Li Li , Zhang Lifang , Qiao Xindi , You Feng
Published: February 2024

To predict the workability of community nursing staff and provide corresponding training strategies based on the results. In this study, a nursing staff workability prediction model based on R-GCN-GRU was constructed. In the process of community nursing staff workability feature extraction, the attention mechanism is introduced, combined with the degree of association between the captured nodes of the R-GCN network and the long-term memory capacity of the GRU network, and the model optimization is carried out using the cross-entropy loss function. Finally, the workability of community caregivers in a city in Guangdong Province was predicted to verify the accuracy of the model from multiple perspectives. The results showed that clinical handling ability, keen observation ability, and communication ability were more valued by most caregivers, and their selection rates all reached 98.4%. On the other hand, clinical research, organizational management, and innovation abilities were relatively low. In the ability prediction of individual characteristics, the highest income personnel’s working ability was second only to the lowest salary personnel reaching 44.61±6.03. The working ability of older age and higher-position nursing staff, and nursing staff with more than 25 years of service reached 45.62±6.14, 48.30±5.22, and 45.86±5.52, respectively.
Readability Assessment of Chinese Linguistic Texts Based on Dependent Syntactic Networks
Authors: Zhao Jun
Published: February 2024

Based on Chinese linguistic text features, this paper classifies dependent syntactic networks into two types: supervised and unsupervised, and researches to illustrate the inter-conversion relationship and difference between the two. Based on traditional linguistic features, the orthogonal features in linguistic features are fused with the neural network features extracted from the pre-trained model utilizing feature projection to complete the construction of the Chinese linguistics text readability assessment model, and the Chinese linguistics text readability assessment model is empirically analyzed. The results show that the accuracy of the six classification algorithms takes the range of 0.379-0.648 when only the baseline model is used, which is much lower than the performance of the corresponding classification models on the feature set constructed in this study, confirming that the algorithms in this paper can better fulfill the task of automatically assessing the readability of Chinese linguistics texts. The research results in this paper can be applied to educational scenarios to help teachers select reading materials of appropriate difficulty for learners.
Research on the Design and Application of Online Learning Activities for Chinese-foreign Cooperative Universities under the Perspective of Deep Learning
Authors: Xiang Yu , He Yingjie
Published: February 2024

After clarifying the development characteristics of Sino-foreign cooperative education in a depth perspective, this paper designs a framework of online learning activities for Sino-foreign cooperative education in combination with the components of online learning activities. Correlation analysis and cluster analysis are used to explore the learners’ knowledge preparation of online learning activities and learners’ behaviors are mined to explore the correlation between behavioral characteristics and learning effects. Regression analysis is conducted with the interactive learning dimension as the independent variable and the learning outcome as the dependent variable to construct a multiple regression model of students’ interactive learning on the learning outcome of online learning activities, and to analyze the influence of online learning autonomy and interactivity on the learning outcome. It also explores the relationship between online learning activity design, teaching quality, faculty, and student satisfaction during internship practice and overall satisfaction. The data show that personal background variables and online learning autonomy explain 0.408 of the variance in learning outcomes, which is an increase of 0.390 in the strength of explanation over that of only personal background factors. The substantial increase in the R-square of the model suggests that the level of autonomy of students in the online environment is an important factor influencing the variance in learning outcomes. The more autonomy the students have in their online learning, the more competent they become in the online learning activities of Sino-foreign cooperative universities.
The Auxiliary Utility of Big Data Intelligent Translation in English Writing
Authors: Zhang Lihua
Published: February 2024

With the popularization of big data technology, intelligent translation technology gradually rises and is applied in daily life, and this paper explores its utility in English writing. English writing can benefit from the auxiliary utility of Big Data intelligent translation The grammatical error correction model for intelligent English translation is constructed based on statistical classification and deep classification to optimize the English translation system. Through the performance testing of the intelligent translation system, the performance of the algorithm model of this paper is improved by 3.03, 2.64, and 8.55 compared with CYK, CYK-PU, and the shift-and-return algorithm, based on which the intelligent translation system is applied to English writing for the evaluation and analysis of the effect, and the reliability coefficients of the three scales are greater than 0.9 through the reliability and validity test and correlation analysis. Finally, a practical analysis of the auxiliary utility of intelligent translation in English writing is conducted. Finally, the auxiliary utility of intelligent translation in English writing is practically analyzed, and in the final achievement test, its various ability test scores and comprehensive achievement scores are all greater than 0.9. An intelligent translation system can help cultivate and improve English writing ability, which enhances the realistic reference significance of intelligent translation to aid English writing.
Innovative Practice of Physical Education Teaching in Colleges and Universities Based on Artificial Intelligence Technology
Authors: Guo Jun
Published: February 2024

With the development and improvement of artificial intelligence technology, the teaching innovation mode of combining college sports courses with artificial intelligence has gradually received widespread attention. This paper is based on artificial intelligence technology for the design of intelligent sports detection wearable devices, through which students’ sports data are collected, low-pass filters are used to reduce the noise of the collected data, normalization is carried out, and the AlphaPose algorithm is combined with the assessment and extraction of the human movement posture of college sports. The artificial intelligence sports teaching framework is built to innovate college sports teaching based on artificial intelligence. Finally, the impact of sports recognition is examined, and a comparison experiment is carried out to examine the practical implications of this teaching method. The four experimental targets had sports recognition errors that were less than 10% on average according to the results. The two classes under the experimental control have a P-value of less than 0.05 in the comparison of physical skills and physical fitness test data, and there is an improvement of 5-20 in all scores, which indicates that the experimental class has a higher teaching effect and is significantly helpful in performance improvement. Based on the above, this paper researches the practice of artificial intelligence technology in college sports teaching to provide an innovative path for the transformation of traditional sports teaching to artificial intelligence sports teaching.
Exploration of Innovative Teaching Models of Civics in College Programs with Big Data Analytics
Authors: Hu Yanhua , Jiang Huan
Published: February 2024

Curriculum Civics is a key educational concept for colleges and universities to implement the fundamental task of cultivating people with moral character, and the innovative teaching mode of curriculum Civics is conducive to promoting the quality of work in colleges and universities. Based on ADDIE, this paper constructs the innovative teaching mode of “network+classroom+practice”. By improving the learning behavior cluster analysis method of the K-Means algorithm, the learning state of students’ course Civics is carefully classified and the regression model is used to analyze the interrelationship between the dimensions of students’ Civics thinking and the constructed teaching model. Based on the effectiveness of the model proposed in this paper, we take X college as the research object and conduct empirical analysis from three aspects of students’ learning performance, learning behavior, and level of Civic and Political thinking. The results show that the F-statistics of critical thinking, creative thinking, value thinking, spiritual thinking, and conscious thinking in students’ civic thinking are 148.923, 241.125, 112.561, 83.254, and 84.968, respectively, and the significance is less than 0.05. There is a significant linear relationship between the elements of the innovative teaching model of the civic thinking of the college curriculum and the dimensions of civic thinking, which can improve the level of students’ Civic and Political Thinking.
Intelligent Design of Home Products Based on Digital Intelligence Technology
Authors: Huang Linshi
Published: February 2024

Aiming at the problems of high cost and too much reliance on the creator’s inspiration in traditional home product design, this paper combines digital technology to design home products. Specifically, the attention mechanism is utilized to improve the YOLOv5 network, and the home products are identified through the improved technique to obtain the home product dataset. The generative adversarial network is trained using the dataset, the new design scheme is output through the trained generative adversarial network, and the generative model is evaluated using the IoU metrics to realize the intelligent design of home products. After the model design is completed, the home products are intelligently designed according to the customer’s requirements. The IoU values of the 3D voxel model are 0.6858, 0.6872, 0.7834, and 0.6268, which are more accurate than those of other methods with contours. The European furniture IoU value is 0.534, which is higher than the generation effect of other methods and the CE value of noise floats up and down at 0.110. The 3D voxel reconstruction works best when the projection view angle K is 6, and the table works best at K=8 with 0.65. Overall, the model generated in this paper modeled 3D home products with high definition, good quality, and design.
Data-driven innovation in university library management and service models
Authors: Li Yan , Wu Shaoqun , Zhu Zhengang
Published: February 2024

With the rapid development of the data and information age, the digital-driven library has become an inevitable trend of library development. In this paper, through the Apriori association rule algorithm, the digital-driven library model for the influence factors of information mining, combined with data mining influence factor information to build a data-driven library management system, through the data library lending system optimization and book scheduling optimization to optimize and improve the overall optimization. Finally, it is verified through empirical analysis of association rule analysis and the scheduling effects of data-driven libraries. Through empirical analysis, it can be seen that the staff management efficiency of the management system lending system, and library circulation scheduling enhancement degree are 5.103 and 6.103, both greater than 1. The length of the reader queue and the percentage of reader loss of the data-driven library are between 5~15 and 0%~17%, respectively, and the efficiency of the data-driven library is superior to that of traditional libraries. Combined with the above, this paper based on the data-driven university library management service model can effectively solve the book scheduling problem, improve the management and service efficiency, so that readers have a better experience, and provide a guarantee for the innovative development path of the data-driven library management service model.
Artificial Intelligence-Based Comfort Assessment and Simulation of Architectural Sound Environments
Authors: Wang Weiling , Zhang Yu
Published: February 2024

This paper determines the influencing factors of architectural acoustic environment comfort assessment from the perspective of green building acoustic environment comfort, and constructs a two-by-two comparison judgment matrix for each questionnaire survey result. Through the consistency test of the judgment matrix, the weights of the factors influencing the comfort of the building sound environment are obtained, and the construction of the assessment model of the comfort of the building sound environment is completed. Based on the architectural acoustic environment comfort assessment model, optimization variables are selected and multi-objective optimization is used to determine the objective function and constraints of architectural acoustic environment comfort. The comfort of the acoustic environment of the campus building is evaluated and analyzed through simulation analysis. The results show that the two measurement points, point 8 and point 15, located on the north side of the library and information building and the center courtyard, respectively, have relatively low continuous sound pressure levels L
eq of 51.7 dB and 44.4 dB, respectively, which are relatively favorable for the creation of a comfortable acoustic environment. Improving the building arrangement through the multi-objective optimization method under the acoustic environment assessment model can provide good environmental protection for people’s daily lives and work.
The Construction of Interactive Teaching Platform for College English Based on Digital Intelligence Technology
Authors: Chen Qian
Published: February 2024

In the teaching platform, providing students with personalized learning solutions by tracking their learning status is the current trend in the development and research of digital intelligence teaching. In this paper, a Bayesian knowledge tracking model based on multiple interactions is used to construct a knowledge point tracking module, and students’ learning behaviors and memory forgetting factors are simultaneously integrated into the IBKT model to construct the PRL-PLP algorithm, and then a Bayesian knowledge tracking model integrating the behaviors and previous factors is obtained, and real-time prediction of students’ mastery is realized using the extended model. Putting the platform into use, it was observed that the total number of student logins to the platform in two days was 680, with an average of 340 logins per day. After using this educational platform for half a month, the students of class A showed an overall improvement in their English test scores compared to their scores before using the platform, with the number of students scoring less than 60 narrowing down from 5 to 0, and an increase of 5 students between the subsections of 91-100, and an increase in the subsections of 81-90, also from 26 to 43 students. By using the IBKT model in the online teaching platform, teachers and students can receive timely feedback on prediction results, teaching efficiency can be improved, and personalized learning guidance can be provided to students.
The Dilemma and Breakthrough of Professional Ethics Education for Higher Vocational Accounting Professionals in the Internet Era
Authors: Chen Xuemei , Wu Jian , Wang Hui , Zhang Yuan
Published: February 2024

With the development of the Internet, people are more and more pursuing the high-quality development of society, and the cultivation of high-quality talents is also more and more important. Aiming at the dilemma of professional ethics of senior accounting professionals, this paper introduces generator and discriminator structure based on a deep clustering algorithm and constructs a double autocoding deep embedded clustering model, i.e. DADEC model. After completing the model construction, iterative optimization of the clustering center is carried out by combining the small batch stochastic gradient descent and backpropagation algorithms to reduce the clustering loss. The optimized model is utilized in the professional ethics education of senior accounting professionals to categorize their dilemmas and explore breakthrough strategies. The results show that the perceptions of accounting majors in 15 higher vocational colleges and universities in terms of ethical knowledge, sense of professional dedication, professional ethical will, and professional ethical conduct are below 0.6 points. The mean value of the classroom effect of professional ethics education is 0.588, and there is a dilemma between a single teaching form and outdated teaching content. The scores of students in honesty, trustworthiness, love, and dedication are below 60 points. Although there are certain challenges in the current training of senior accounting professionals, the combination of this study points out the direction for overcoming these challenges.
Research and practical application of a bilinear integration learning model for a college psychology course
Authors: Yang Shengxue , Zheng Susheng
Published: February 2024

Information technology in education has triggered a change in “psychology” learning, and dual-line integrated learning will become an important form of learning in the future. The impact of information technology on education has led to changes in psychological learning, and dual-line integrated learning will become a crucial form of learning in the future. Then, based on the FuzzyCDF model of fuzzy set theory, the students’ psychology cognition, learning ability, and knowledge mastery were tested to assess the student’s cognitive level and learning effectiveness of psychology courses. Then, we analyzed the effect of dual-line integration teaching, evaluated the teaching recognition and cognition of students in different grades, and explored in depth the effects of online and offline integration teaching on students’ learning attitude, learning anxiety, self-efficacy, and academic performance. Comparative analysis was used to analyze the impact of psychology course education on students’ mental health. The results showed that the student’s recognition of the dual-line integration learning mode was all above 3.7, the correlation of the online and offline learning mode on the dimensions of students’ learning attitude, self-efficacy, and academic achievement were all between (0.12,0.65), and the negative correlation on students’ learning anxiety. Psychoeducators in colleges and universities can benefit from this study in developing effective teaching strategies and improving the quality of psychology courses for college students.
Research on the Evaluation of Deeply Intelligent Classroom Teaching and Learning in Colleges and Universities Based on Data Analysis
Authors: Liang Fenglan , Shen Weiwei , Chen Le
Published: February 2024

In the context of the era of modern information technology to promote the digital transformation of education, it is also imperative to explore the intelligence of classroom teaching evaluation. This paper proposes a Bayesian probabilistic model based on PyMC3, weights it, and introduces the principle of incremental learning, which greatly reduces the error of the plain Bayesian algorithm in collecting and processing data teaching evaluation data. The Bayesian algorithm is used to classify and filter original classroom teaching evaluation data. The data analysis part of this paper examines the intelligent classroom, the teacher’s lecture scoring, and the student’s grades. With the help of the weighted plain Bayesian algorithm, the level of student participation in the traditional lecture mode and intelligent classroom were determined respectively, from which the classroom acceptance level and the probability of high or low evaluation of teaching were calculated. From the data collection, it can be seen that the full attendance rate of students in three months reached 54%, and the average satisfaction score of the algorithm on the teacher’s instruction reached 0.53. Therefore, the plain Bayesian algorithm used in this paper can effectively analyze the teaching evaluation data and accurately visualize the data association between student classroom engagement and teaching evaluation.