bluuebunny/crossref_metadata_2025 huggingface dataset:
Integration of traditional structures and modern green building materials of residential buildings in Guangdong region
Authors: Li Fengyan , Lu Qi
Published: August 2024

In recent years, the concept of environmental protection has taken root in people’s hearts. The construction industry is actively involved in environmental transformation, developing and adopting green building materials and combining them with traditional residential buildings to create more livable residential spaces. Modern green building materials are used in the study to design traditional residential buildings in Guangdong, and the BIM platform is used to design the building structure. The dynamic response analysis model of the building structure is constructed through the structural layer model, and the dynamic analysis of the planar structure is used to investigate the structure of the designed Guangdong traditional residential building and analyze the performance of green building materials. The cooling coatings CWC-S1 and CWCS2 used in traditional residential buildings designed in Guangdong in this paper meet or even far exceed the relevant cooling standards with excellent performance. Glass substrate insulation coatings are capable of effectively insulating 36.3% of visible light and 78.9% of near-infrared light, resulting in a cooling effect. In the seismic response experiment, the Guangdong traditional residential building structure can achieve the seismic effect of “not broken by a small earthquake” and “not collapsed by a big earthquake”, and the safety is high.
Innovation of English Translation Teaching Mode in Virtual Reality Environment
Authors: Li Feng , Chen Xiang
Published: August 2024

English translation teaching is often neglected to create a real situation and leads to the teaching failing to highlight the student’s main position. With the help of VR technology to carry out English translation, teaching can effectively solve the above problems. In this paper, on the basis of analyzing the effective application of VR technology, we have established an English translation immersion teaching mode and set up an immersive English translation teaching environment. Based on the students’ learning data of the virtual platform, the DKVMN model is used to assess the student’s knowledge mastery, and the DTW-FCM algorithm analyzes the students’ online learning behaviors to construct a learner portrait. Based on learner profiles, knowledge graphs are combined to obtain the learning degree of learners so as to achieve personalized learning path recommendations for English translation courses. The list of English translation teaching content exercises generated using the DKVMN model is 0.884 in accuracy, and the mean value of the personalized learning paths generated by this paper’s method is 27.04 in terms of the translation of the personalized learning paths to the real paths, which is 28.35% lower than that of the PageRank algorithm. Group A scored 42.41 points after the teaching experiment, which is 25.51% higher than that of class B. Class A’s students have a higher average value for the immersive teaching environment, with an overall satisfaction mean of 4.6 points. Using VR technology to create an immersive learning environment can help students improve their English translation and expression skills, as well as their English intercultural communication skills.
A Model Study on the Exploration and Practice of Digitally Empowered Big Ideology and Politics Courses in the Context of Smart Education
Authors: Li Huansheng
Published: August 2024

Based on the portrait model, this study collects learner data and outputs the overall portrait and class portrait in this study after K-means clustering analysis. Six-month practice data of precision Civics teaching in a university were collected, from which comparative experiments were carried out to analyze the data of pre-test and post-test of teaching to explore whether precision teaching can significantly improve the learner portrait and the overall learning results. The distribution of questionnaire results and learner satisfaction questionnaires was done to understand the evaluations of lecturers and students on the implementation effect of precision teaching. The results showed that the style tendency of students in a university’s Big Ideology course was visual (72.9% of the total). The optimal cluster analysis for K=4 resulted in the division of student portraits into 4 clusters. Compared to pre-teaching, the students’ performance in Civics and Politics was significantly improved after the teaching, and the potential and hard-working learners made the most progress. And the post-teaching scores were centrally distributed in the range of 40-100 points. More than 70% of students believe that accurate teaching can meet their learning requirements. This paper’s experimental results confirm the effectiveness of precision teaching based on learner profiling.
Research on the Implementation Effect of Personalized Education Management and Cultivation of Top Talents under the Framework of Multiple Intelligences Theory
Authors: Pan Xiaohong , Ge Haijiang , Huang Rui
Published: August 2024

To improve the quality of education in higher vocational colleges and universities, it is necessary to reform and innovate their education management mode, and education can truly promote social development only by promoting the harmonious development of personality. This paper constructs a personalized education management and top talent cultivation model based on the framework of multiple intelligences theory and establishes an evaluation index system to assess its implementation effect. The hierarchical analysis method is used to determine the weights of the indicators, and then the implementation effect of the management and cultivation model is assessed through the multilevel gray comprehensive evaluation method. The evaluation of the implementation effect of the higher vocational colleges and universities found that the average score of the implementation effect evaluation of the four higher vocational colleges and universities is between 3.94 and 4.59 points, which is at a high level, indicating that the implementation effect of personalized education management and top talent cultivation model is better. It is also found that students in higher vocational colleges and universities are more satisfied with the teaching method, management method, curriculum, and cultivation objectives. The model improvement suggestions put forward in this paper from the perspective of students provide valuable references for educational administrators and teachers of higher vocational colleges and universities so that students in higher vocational colleges and universities can achieve the desired effect of cultivating top-notch talents.
Innovative Strategies for Language Education in the Context of Media Convergence - From Traditional to Digital Media
Authors: Yang Yang
Published: August 2024

Based on the special nature of language subjects, if the teaching methods adopted by teachers in the language classroom are not appropriate, it is easy to make the classroom atmosphere boring and depressing, which is not conducive to mobilizing students’ learning initiative. The use of digital media technology is more likely to increase students’ enthusiasm for learning and enhance the teaching impact. To address language education’s shortcomings, this paper utilizes digital media technology to enhance language education through media integration. In order to evaluate the teaching effect of integrating digital media in language teaching, this paper combines the Apriori algorithm and C4.5 algorithm to analyze the knowledge and information about the teaching law and teaching situation from a large number of teaching evaluation results, which is used to judge the effect of the application of digital media in language teaching, after comparing the combination algorithm with the traditional rule-mining algorithm. The Apriori algorithm is applied to secondary school language teaching, incorporating digital media for correlation analysis, and the pre-processed dataset is mined and the quality of language teaching in digital media has a great relationship with the quality of teaching and the content of teaching. In this paper, based on the Apriori-C4.5 mining algorithm, we can analyze the factors associated with teaching effectiveness and propose strategies for digital media application in language education innovation.
Intelligent physical education: an exploration of virtual reality applications in college martial arts courses
Authors: Zhang Shuangjian
Published: August 2024

Aiming at the existing sports and martial arts teaching system without VR simulation modeling, which leads to poor mastery of the training content of the trainees and high time delay of the system, we design the sports and martial arts teaching system based on VR virtual technology. Through VR technology to build a virtual training environment, realize the modeling of the three-dimensional scene of the VR system. First of all, design the system motion capture function module, according to the module to obtain the data of the students’ sports and martial arts action teaching, use the data to correct their errors in a timely manner, and complete the action estimation through the human body posture recognition technology to extract the key points in the course of the students’ three-dimensional coordinate information, to obtain the joint angle of the joints of the martial arts action joints trajectory and other multi-dimensional spatial and temporal data. Then, the recognized martial arts movements are compared and analyzed with the reference movements from the standard movement library. Finally, a multi-view collaborative layout is constructed to build a wushu action data visualization interface based on a multi-view layout, which intuitively displays the quantitative information of wushu actions and provides support for users to explore the information of wushu actions. At the first training, system 1 in this paper masters 10% more training contents than training system 2 based on pressure sensor technology and 17% more training contents than training system 3 based on mechanical vision technology. The time delay of System 1 is lower than that of System 2 and System 3 at every point during the gradual increase in the number of students. The test of student training content mastery and the system time delay test demonstrated that the system has strong practical performance.
Adjustment and optimization of the competence structure of accountants in digital transformation
Authors: Min Rui
Published: August 2024

The digitization and refinement of accounting are propelling accounting work towards intelligence, leading to a further restructuring of accountants’ professional competence. Based on the existing competency structure framework for accountants, this paper proposes an optimized “main-core” competency structure for accountants, taking into account the new requirements for accountants’ competency in digital transformation. Based on the optimized accounting personnel competency structure, an evaluation index system is designed and combined with the entropy weight-TOPSIS method to analyze changes in accounting personnel competency. To examine the factors that affect accounting personnel’s competence, a static panel regression model was designed based on the multiple linear regression model and combined with the competence structure. The accounting personnel ability structure is the most weighted at 0.2614 in the financial and accounting management ability index, and the information technology application ability rose from 0.346 to 0.486 between 2017 and 2023, adding up to 40.46%. Each 1% increase in accounting personnel’s professional knowledge increases their competence by 0.614%, and behavioral motivation and professional ethics have a positive effect on their competence at the 1% level. As a result, accountants’ ability structure must focus on the application of digital technology, consolidating their professional knowledge, and promoting high-quality accounting work development.
A Practical Study of Traditional Sports in Physical Education Teaching in the Context of the Internet
Authors: Rong Cheng
Published: August 2024

Teaching environment, teaching equipment, and some other problems limit the vigorous development of traditional sports in college physical education teaching, which, to a certain extent, has an extremely unfavorable impact on the preservation and development of traditional sports. This paper analyzes the combined weights of traditional sports in different dimensions, calculates the coefficient of variation and expert authority coefficient of the indexes, establishes the important coefficients for constructing the integration of traditional sports into modern physical education teaching, and realizes the effective combination of traditional sports and physical education teaching. The results show that this paper constructs a 3-dimensional curriculum content index system, which includes 3 first-level indexes, 10 second-level indexes, and 26 third-level indexes. The weights of the three first-level indicators of motor ability, physical integrity, and health behavior were calculated to be 0.3232, 0.3279, and 0.3488, respectively. The scoring results of the first- and second-level evaluation indicators were between 81.303 and 82.009, 81.388 and 82.196, respectively, and all of them were rated as good grades. It is clear that sports character, as one of the first-level indicators among the three dimensions of sports teaching, is a key starting point for integrating traditional sports into modern sports teaching. The results of the study help to better promote the sustainable and healthy development of traditional sports in colleges and universities and provide scientific references for the smooth implementation of traditional sports in physical education teaching.
Construction and Talent Cultivation of Tourism Specialty Groups under the Perspective of Shared Prosperity
Authors: Shi Meishan
Published: August 2024

This paper defines the evaluation indexes from the aspects of evaluation purpose and standards and, through the hierarchical analysis method of empowerment, completes the construction of the evaluation system of the construction of tourism characteristic professional group, including three first-level indexes, 11 second-level indexes, and 30 third-level indexes. The policy implementation group and the control group were subjected to double-difference regression from the spatial and temporal perspectives, and the economic growth effect of the construction policy of the tourism specialty group was analyzed and verified by combining it with the heterogeneity test. The results show that City Z has realized the original intention of the construction and improved the quality of talent cultivation in the specialty cluster. The weight of the construction capacity of tourism-related specialty groups is the largest at 0.529, which is the core of the construction, followed by the construction effectiveness of tourism-related specialty groups (0.299). In lngdp, the economic effect of tourism characteristic specialty group construction policy in the fourth period after implementation (6.725) is significantly higher than that in the fourth period before implementation (1.0716), and in lnpgdp, it is 1.634 higher after the policy is implemented compared with that before implementation. The economic impact in economically relatively backward areas is significant at the 1% confidence level.
Theoretical Followings and Practical Strategies of Physical Education Evaluation in China’s Schools in the Context of Deep Learning
Authors: Wang Di , Zhang Aying
Published: August 2024

In this paper, we first studied the basic content of deep learning in college sports and explored the principles of physical education evaluation in colleges and universities in the context of deep learning. Then, the framework of the physical education evaluation index system is constructed, the indexes are screened and optimized by combining the Delphi method, and the weights of the indexes are calculated by using the fuzzy comprehensive evaluation method. Then, based on the expectation and satisfaction data of students in the sample colleges and universities, the gap is analyzed according to the perception-expectation matrix, and the SERVQUAL model is used to analyze each issue of the quality of physical education in colleges and universities one by one. The maximum value of the expectation of the quality of physical education in colleges and universities is 6.558 points, the minimum value is 6.348 points, the maximum value of the mean value of perception is 6.349 points, the minimum value is 5.797 points, and the scores are above 5 points, which makes the quality of education in colleges and universities better. This study further enriches the theory of quality evaluation of education in sports colleges and establishes the evaluation model and method with specific specifications.
Exploration of the standardization strategy of enterprise economic management mode in the context of the digital economy era
Authors: Wang Yuan
Published: August 2024

With the advent of the big data era, information flow and data sharing on a global scale have become the norm. This change has not only changed people’s way of life but has also had a profound impact on enterprises’ economic management mode. The purpose of this paper is to examine the enterprise economic management innovation mode in the digital context and then create a fuzzy, hierarchical, comprehensive evaluation model to examine its application advantages. This foundation is used to construct a standardized evaluation system for enterprise economic management. Specifically, combining the internal and external environments of the enterprise, the enterprise economic management standardization index system is constructed, the indexes are assigned through the hierarchical analysis method, Company A is taken as an example, and the questionnaires are issued to the internal personnel of the enterprise, and the indexes are rated comprehensively. From the comprehensive score of Company A, the standardized level of debt repayment, operation, profit, and development of the enterprise is 3.3125, 0.3242, 3.3588, and 3.2126, respectively, and the standardized level of economic management of Company A reaches 3.3415, which is in a stable state of development, but it can still be further improved. This paper’s use of the digital enterprise economic management model not only enhances Company A’s management operation but also serves as a model for standardizing economic management across other enterprises.
The Contribution of Music Information Retrieval System Optimization to Music Analysis in the Context of Big Data
Authors: Yin Junbo , Du Yuefeng
Published: August 2024

With the rapid popularization of Internet big data worldwide, people are able to transmit, download, and listen to huge amounts of music, which directly contributes to the demand for music information retrieval. In this paper, a music information retrieval system is constructed based on extracting music features. Both time and frequency domains characterize the music, and the transformation relationship between time domain, frequency domain, cepstrum domain, and power spectrum is proposed to extract music features. Further, the convolutional deep confidence network algorithm is applied to music information retrieval, an unsupervised greedy layer-by-layer algorithm carries out pre-training, and the network parameters are adjusted to improve the retrieval and recognition ability of the model. Functional validation of the system in this paper. In the music feature extraction experiments in this paper, the system’s accuracy for extracting feature points from different songs is more than 80%. In the music information retrieval experiments in nine different styles of music in the style of music in this paper, the average judgment of the system correct rate of 92.59%, in different proportions of the number of tracks in the retrieval success rate, is higher than 88%. In music analysis fields such as music recommendation and music soundtrack design, the music information retrieval system constructed in this paper plays a significant role.
Cooperative planning of new distribution system grid and energy storage system based on distribution robust optimization
Authors: Gao Chong , Zhang Junxiao , Li Hao , Xu Zhiheng , Hao Peng
Published: August 2024

With the increasing penetration of distributed power sources, the stochastic and fluctuating nature of distributed power sources poses a great challenge to the reactive power optimization of the distribution network system. In this study, a dynamic reactive power optimization model with two-stage robust optimization is established, proposing whether the energy storage is charged or discharged. The number of groups of group-switching capacitors is taken as the variables in the first stage. The power of the energy storage charging and discharging and the amount of static reactive power compensator compensation are placed in the second stage. The control strategy in the first stage ensures that the control strategy in the second stage can maintain the safe and stable operation of the distribution network under the worst scenarios. The grid-storage joint optimization technology based on distributed architecture establishes an optimization planning model for the distribution network energy storage system with the goal of optimal technical and economic performance of the transmission and distribution network and considering the constraints of safe and stable operation of the transmission and distribution network, respectively. The PG&E-69 node system arithmetic example is used to verify the effectiveness and feasibility of the proposed model and algorithm. The results of the arithmetic example show that the strategy obtained based on the robust optimization model can achieve voltage magnitude stability within the safety range of 1.0-1.05 p.u. in the simulation scenario that has the best economy. At the same time, the mismatches of each distribution system under cooperative planning are all 0, which indicates that the proposed optimization strategy can fully cooperate with the resources of transmission and distribution networks, promote the safe consumption of clean energy, effectively improve the economy of transmission and distribution networks, and achieve the goal of “mutual benefit and win-win”.
The Application of Artificial Intelligence Technology in Improving the Quality of Teaching and Learning in Computer Education
Authors: Zheng Yanyan , Pan Yifeng , Zhang Zhengmin , Chen Ying
Published: August 2024

The personalized recommendation of courses and exercises can realize more accurate, tailor-made teaching, significantly improve teaching efficiency, and stimulate students’ learning interest and motivation. In this paper, we first obtain the knowledge point data of computer specialties and then extract the course knowledge point entities using the TF-IDF algorithm. We then use artificial rules to extract the relationships between the entities, design an estimation method for students’ mastery of the knowledge points, combine the knowledge graph to generate different learning sequences for students, and recommend course resources for them. Then, we use a simple Bayesian classification algorithm to classify and characterize the text of exercises and recommend personalized exercises to learners by combining their mastery of knowledge points, degree of difficulty, and other characteristics. The system in this paper is applied to a computer program at a university in Guangzhou to compare the teaching effect. It was found that the average grade of the experimental class was 11.25 points higher than the average grade of the control class, an improvement of 11.92 points compared to the pre-test, and the distribution of the scores clearly progressed from the 75-80 point range to the 85-90 point range. In the three dimensions of perceived usefulness, perceived ease of use, and intention to use, the vast majority of the respondents chose to agree or strongly agree, and the average score of the survey was 4.31, 4.24, and 4.18, respectively, indicating that the system is easy to operate and has a reasonable functional design and that the results of the recommended course resources and exercises basically conform to the learners’ psychological expectations and practical needs. This study proposes a feasible path for the integration of artificial intelligence technology into computer teaching, which will improve the quality and efficiency of computer education and teaching.
Analysis and research on the efficiency improvement mechanism of automated invoicing process of outage ticket based on queuing theory
Authors: Bai Yiming , Shi Xiaojing , Zhang Bingsheng , Ruan Zhijie , Peng Zhenhua , Liang Shaoming , Chen Kunming , Liu Xinsheng
Published: August 2024

The electricity ticket system is an important basis for staff to carry out maintenance plan designation and execution. With the gradual progress of the work of the grid grassroots staff to reduce the burden, the need to simplify the process of electricity ticket invoicing and improve the efficiency of electricity ticket invoicing is increasing. This study first optimizes the scheduling and data capture problem of electricity based on queuing theory. Then, it constructs a recognition model for electric ticket data based on deep learning and combines the CTPN text detection algorithm with the DesNets text recognition algorithm to establish the CDNets algorithm model for recognition optimization. An automated generation model of the blackout ticket was created using the LSTM network. Taking into account the power company’s needs, combined with Intranet intranet software development concepts and Net software technology development and design of the ticket automation system. The AP of this paper’s blackout ticket recognition model under the mixed date of the ticket has a disadvantage of 0.7% compared with YOLOv4, but the reasoning speed is relatively improved by 2 times, and the overall algorithm is more cost-effective. The highest accuracy, F-value, and AP of this paper’s model for stamp data are 95.3%, 97.6%, and 99.2%, respectively. And in the login test and invoicing test, the system in this paper is faster than the traditional system by 298.4ms and 136.7ms, respectively. The electric ticket automation system in this paper is able to improve the automatic generation of electric tickets and the efficiency of electric ticket invoicing, and to enhance the level of lean management at the grassroots level of the grid, with wide adaptability.
Optimization of data model-driven design thinking in the software development process
Authors: Li Yun , Li Lianwei
Published: August 2024

Model-driven software development has become a hot research topic and discovery trend in the field of software engineering. Its core idea is to treat analysis and design models as equivalent to code. Better integration of models and code can greatly increase the chances of effective improvement and achieve automated software development through abstract models. In this paper, we first constructed a data model-driven architecture system based on the meta-modeling hierarchy, using a data dictionary for data storage. The mapping relation loader transforms the data extracted from the dictionary. Using the differential evolution algorithm, the model is defined as a metamodel that actually exists. At the same time, the MapReduce framework is combined to parallelize the computation of the DE algorithm based on the island model in order to solve the problem of poor optimization of the differential algorithm. Apply the model to actual software development and realize data visualization and display using Flex technology. Simulation experiments are set up to test the performance of the model and the platform. After CSI uncertainty estimation, the MSE index of the model is analyzed. This paper’s data model-driven method, with an MSE value of only 0.01084, stands out among the five methods in Case 4. Under the condition of 300 users concurrently, the user’s access response time is tested, and it can be seen that the user’s response time is within 1~2.9s, which passes the performance test.
Exploration of Interactive Teaching Models Integrating Augmented Reality Technology in University Science and Technology Parks
Authors: Yin Hongting , Miao Jianjun
Published: August 2024

Augmented reality technology is regarded as one of the modern information technologies that are most likely to change education and is widely used in education and teaching by virtue of its virtual, visual, and interactive features. In this paper, the skin color model and background model are used to recognize gestures in complex backgrounds during interactive teaching, and the optical flow features of the corner and edge points of the gesture image are extracted by the Harris method to recognize the occlusion gestures in interactive teaching. On this basis, the interactive teaching platform integrating augmented reality technology is established by combining the gesture recognition method with Unity 3D and EasyAR systems. After one semester of teaching in a university science and technology park, the average grades of the students in the experimental class applying the interactive teaching mode and the control class in the traditional multimedia teaching mode are significantly different (P=0.001<0.05). Students learning attitudes after the teaching experiment are significantly different from their learning attitudes before the teaching experiment. The teaching mode designed in this paper is of great significance for teaching and has a wide range of application prospects and use value in the field of education, and the optimization strategies proposed from the AR context design and other aspects lay the foundation for stimulating students’ interest in learning and improving the efficiency and effectiveness of teaching.
A multifactorial detection model of young children’s physical abnormality based on image recognition technology under the concept of physical and health integration
Authors: Chen Jundan , Zhang Lifang
Published: August 2024

This paper analyzes the influence of “the concept of integration of body and health” on the physical development of young children and proposes that scientific sports are an important way to intervene in the poor physical appearance of young children. In order to facilitate and accurately identify young children with poor posture, the boundary tracking algorithm is used to detect the human body contour, and based on the physical characteristics, a human posture recognition algorithm based on multi-feature fusion and image similarity is proposed. To model common toddler body postures and obtain toddler posture features, a star model is employed. Combined with the advantage of the SVM classifier, the principal component analysis algorithm is used to design a classification system for abnormal behaviors of toddlers, which combines the static and dynamic posture data images of toddlers to detect abnormalities of toddlers’ body postures. When the difference between the angle of the left elbow to the left shoulder and the angle of the right elbow to the right shoulder to the left shoulder is about 16.58°, the toddler has a high-low shoulder posture. The detection accuracy of the method in this paper meets the needs of young children’s posture detection, and the misjudgment rate reaches 10.25%, which can assist in detecting the abnormalities of young children’s posture and facilitate the teachers and staff to carry out the sports related to young children’s posture.
Application of Machine Vision Technology in Defect Detection of High Performance Phase Noise Measurement Chips
Authors: Deng Jianxun , Hu Chunxia
Published: August 2024

Defect detection plays a crucial role in chip quality control, and the chip field has widely researched and applied machine vision-based surface defect detection methods due to their high efficiency, accuracy, and real-time performance. In this paper, we utilize imaging equipment to collect images of high-performance phase noise measurement chips, and we use a mean filtering algorithm and a Sobel operator to preprocess the collected chip images. Then, the PCA method is applied to downscale the extracted chip shape and texture features, and the improved support vector machine algorithm using a genetic algorithm is used to classify and recognize chip defect features. The test results show that the error rate of the defect detection method for high-performance phase noise measurement of chip surface defects is only 1.82% at the highest, and the average error of the measurement of the chip pin width and pitch is much lower than the actual production of the specified error rate. Meanwhile, the design requirement of 3 pcs/s detection efficiency in the actual production of high-performance phase noise measurement chips is satisfied by the theoretical maximum defect detection efficiency of the method. The chip defect detection method presented in this paper has both practical application value and theoretical research significance.
Probabilistic-based Markov chains for behavioral prediction
Authors: Fang Xiaochao
Published: August 2024

Due to the wide application of Markov chains, it makes some models that cannot be computed due to a large amount of computation have an approximation. In this paper, based on Markov, combining probability theory with a state transfer probability matrix and using the ordered clustering method to divide the behavior into clusters, we construct a behavioral prediction model based on the probabilistic Markov chain to solve the problems that the model tends to have such problems as low overall prediction accuracy and limited applicability. By testing the model’s performance on the relevant dataset, we can predict the occupants’ in-room status. The Gowalla dataset has an MMP model that is 16% accurate and 21% recall. Classifying households and identifying indoor behavior patterns of different households is sufficient so that the indoor behavior patterns of the same type of households are closer to each other. The method is capable of considering various household characteristics parameters and their influence on in-room behavior comprehensively and classifying actual behavior reasonably.
Predictive modeling of soil water and salt dynamics for ecological restoration of mines in arid zones
Authors: Li Chengzhi
Published: August 2024

Ecological restoration of mines in arid zones is an important initiative to promote the harmonious coexistence of man and nature and realize green and low-carbon development, in which the prevention and control of soil secondary salinization is crucial for ecological restoration. This paper takes the soil and water environment (soil secondary salinization) of the Shendong mining area as the research object, and after systematically analyzing the ecological restoration of the study area, collects relevant soil water and salt data and processes them, and analyzes the characteristics of soil water and salt changes in the study area respectively. On this basis, combined with the basic mathematical model of soil water-salt transport, a 3-layer feed-forward BP network modeling method was invoked to predict the soil water-salt dynamics under the study’s comprehensive conditions, and then the sensitivity of soil salinity and soil alkalinity to each factor in the input layer was analyzed by using the default factor test method, and predictions were made for long-term ecological restoration. The sensitivity indices of soil water content to soil salinity as well as soil alkalinity were large, with R of 4.46 and 3.89, respectively, and the effects of each factor on soil water-salt dynamics should be considered comprehensively in the actual ecological restoration of mines in arid zones. In addition, through the prediction of soil water salinity dynamics, the crops in the study area were irrigated with 3.2g/L brackish water four times during the reproductive period, with an irrigation quota of 360mm, and with the measure of spring irrigation water volume of 148mm, which could achieve the purpose of reasonable utilization of salty water and water-saving irrigation, and effectively realize the ecological restoration of mines in arid zones.
Construction of Interactive Path Model of Digital Economy and Green Financing Based on Complex Network Theory
Authors: Li Dan
Published: August 2024

With the rapid development of science and technology and the in-depth popularization of the concept of environmental protection, green financing has become an important issue in the development of the digital economy nowadays. The research is based on the theory of digital economy and green financing, and the interaction model between digital economy and green financing is constructed using the complex network model. The digital economy and green financing network are constructed to carry out network characterization and prediction. To analyze the correlation coefficient matrix of the digital economy and green financing, the MIC statistic is chosen as the model basis. The average aggregation coefficient and network density of the sample countries and regions selected in this paper show a decreasing trend year by year between 2015 and 2020, while the average path length shows a gradual increase. The predicted results of the complex network model for the digital economy and green financing in 2021 are as follows: 165 projected network nodes, 865 edges, average degree value of 6.976, average clustering coefficient of 0.312, average path length of 2.782, network diameter of 6, and network density of 0.039. “The Belt and Road Initiative” policy was put forward after that, the MIC values between most of the sample countries have increased, and the digital economy exchanges and green financing cooperation between countries and regions have shown a thriving development.
Study on the Extensibility of Chinese Traditional Culture in College Education by Combining Gray Correlation Analysis Methods--Taking Miao Batik as an Example
Authors: Li Qishu
Published: August 2024

Miao batik’s unique cultural connotation suggests that it has important inheritance significance as a part of Chinese traditional culture. Combined with the discussion on the protection and inheritance of Miao batik, this paper proposes to utilize the entropy value method and the hierarchical analysis method to analyze and screen the influencing factors of the inheritance and development of Miao batik in college education and to calculate the weight coefficients of the four levels of human resources, material resources, financial resources, and intelligence. By using the greyscale correlation analysis method, the correlation between each influential factor and the development of the educational inheritance of Miao batik in colleges and universities can be calculated, and the degree of importance can be ranked. Based on the development of traditional culture courses in colleges and universities, the teaching path of Miao batik technique courses in colleges and universities is proposed, assisted by information technology. According to the ranking of the degree of relevance, the indicator “curriculum construction (0.9364)” has the greatest relevance to the development of the educational inheritance of Hmong batik culture in colleges and universities, and the relevance of “club construction (0.6008)” to the development of the educational inheritance of Hmong batik culture in colleges and universities is the smallest. Minimum. Colleges and universities can adjust the curriculum structure of Miao batik to improve the extension and development of traditional Chinese culture represented by Miao batik in colleges and universities.
Multi-objective Optimization Algorithm Research on Tobacco Leaf Blend Formulation Design
Authors: Li Xingliang , Guo Lei , Du Xiaozhou
Published: August 2024

The optimal design of formulated products is a complex and comprehensive technology. In order to obtain formulations with excellent performance and meet the requirements, it is necessary to reasonably select raw materials and determine the dosage ratio relationship of various raw materials through testing, optimization, and identification. Combining the BP neural network and NSGA-II algorithm was used to study the design optimization of tobacco leaf group formulation in this paper. Firstly, the chemical composition and sensory quality data of single-ingredient tobacco samples were collected and normalized, and then correlation analysis was performed to obtain the single ingredient tobacco proportion-chemical composition relationship model and chemical composition-sensory score relationship model. Then the two relationship models were imported into the BP-NSGA-II model to calculate the chemical composition of the leaf group formulation, and the sensory quality score was predicted based on the chemical composition to obtain the optimization results of the proportion of the tobacco leaf group formulation. There was a strong correlation between the chemical composition and sensory quality of tobacco at the significant level of α = 0.01. Except for the aroma index, the mean error of prediction of the methods in this paper for the rest of the sensory quality indicators was smaller than those of SVR and multiple linear regression methods. The absolute error of prediction for all indicators was less than the traditional BP and SVR models. The sensory quality scores of the optimized formulations in this paper are basically consistent with the results of expert evaluation, and the absolute values of relative errors are less than 4%, which is of strong practical significance for the optimization of formulation design of tobacco leaf groups.
Interactivity Analysis and Modeling of the Reversal Effect of Internet Technology and English Teaching in Colleges and Universities
Authors: Li Yanping , Tang Diandi
Published: August 2024

With the in-depth application of Internet technology in the field of English education, the connection between Internet technology and the reverse dialing effect of English teaching in colleges and universities has become increasingly close. The theory of the reverse dialing effect is introduced in this paper, and an Internet technology framework is proposed that incorporates an online English learning platform and a personalized recommendation model of English resources. The viscous binary particle swarm algorithm with nonlinear factors is used as the algorithm for recommending learning paths to build the online learning platform. At the same time, the online learning platform is also used as the background, and the S-CNN model is constructed by relying on the convolutional neural network model framework to propose a personalized course resource recommendation algorithm based on deep learning. University Q in Changchun City, Jilin Province, China, was used as the research site for practice. The English scores of the students in the experimental class were significantly improved, and the mean values of cooperative communication ability, problem-solving ability, and information literacy in English learning ability were higher than those of the control class by 4.427, 4.394 and 3.918, respectively, which showed significant differences (P<0.05). The average value for all learning status dimensions after the experiment was greater than 3.5, which was higher than before the experiment. The mean value of English teachers’ total teaching beliefs reached 163.76, and the mean values of all classroom behaviors except feedback and guidance behaviors were all higher than 3.5. The positive effects of students’ learning and teachers’ teaching were significantly increased.
Research on the Method of Improving the Efficiency of Dynamic Allocation of Educational Resources in the Environment of Internet of Things Based on MLP Network Modeling
Authors: Li Zongrui , Hou Yan , Wei Jianghua
Published: August 2024

The effective allocation of educational resources has significant practical value and importance in ensuring the fairness of education. The study examines the efficiency of educational resource allocation for 30 schools in City Z from 2020 to 2023 using the DEA model. Reasonable data are screened out based on the DEA model, and then the MLP model is used to construct a model of educational resource allocation efficiency, and the sample data are comprehensively evaluated, so as to screen out the optimal program. Then, according to the results of the MLP model, we determine the importance of each input parameter to obtain the reference basis for adjusting each investment factor to improve the efficiency of educational resources. The method for improving the dynamic allocation efficiency of educational resources is summarized at the end. The allocation efficiency of educational resources in the sample schools is above the medium level, and the comprehensive technical efficiency is 0.61~0.67, which fails to maximize the use of educational resources. The MLP model has a good predictive effect on output variables, and the teaching area (0.319), paper books (0.281), and fixed investment (0.269) are the most important input factors. It is recommended that the DEA-MLP model be used to optimize and optimize the resource management system, improve the scientific evaluation and supervision system, and enhance the management capacity of teachers, so as to further promote the efficiency of the dynamic allocation of educational resources.
Analysis of the Impact of AI Editing on Film and Television Post-Production in Digital Transformation
Authors: Liu Jiaoyan
Published: August 2024

This paper studies the framework of an AI intelligent editing system, explores the functional modules of intelligent editing, deeply analyses the use of AI editing in film and television post-production, and carries out an in-depth study of AI editing methods. Then, we established an impact effect analysis model using the analysis of variance, t-test, and regression analysis methods. Based on this model, we compared the audience viewing data for AI editing and ordinary editing, analyzed the audience’s emotional tendency and participation, and studied the impact of AI editing on the effects of film and television post-production. The study demonstrates that AI editing has a significant promotion effect on creative freedom, content and theme fit, cost-effectiveness, and diversity of content in film and television works, with significance coefficients of 0.046, 0.023, 0.012, and 0.006, respectively. This study holds significant value in promoting the integration and development of AI technology in film and television, as well as strengthening its application in the field of digital media.