bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysis of the Influence Path of Confucianism in the Civic Education of Contemporary College Students in the Context of Big Data
Authors: Chen Cheng 
Published: September 2023

Abstract
Under the background of big data, college students’ Civic Education has realized the adjustment of teaching technology and educational paradigm, and the value of big data technology for college students’ Civic Education has become increasingly intuitive. In this paper, firstly, the data points designated for clustering are selected in the dataset as the initial clustering centroids. In response to the Euclidean distance treating variables equally, the coefficient of variation method is proposed for subjective weighting. The support vector machine for solving the two-class classification problem is obtained as a real-valued function to test the parallel efficiency of different clustering mining algorithms in the same experimental setting. Finally, for the training sample input data, it is concluded that the algorithm has a better clustering effect and improves the speed and accuracy of clustering. The feasibility of the proposed influence path is demonstrated by comparing it with the data application of the subjective empirical weighting method. The results show that 8% of students before the experiment thought that integrating Confucianism into Civic Education was valuable and meaningful, and after the experiment, the number of students who thought it was valuable and meaningful increased from 8% to 58%. It indicates that the integration of excellent traditional Confucianism into the ideological and political education of college students is very important to strengthen the ideological and political education of college students.
Innovation of tax incentives in the context of integration of traditional industries and digital economy
Authors: Chen Wei , Chen Ding 
Published: September 2023

Abstract
With the development of the digital economy, the innovation of the tax preference method is necessary. This paper integrates traditional industries with the digital economy through digital technology, standardizes the tax preference data of digital industries by using a fuzzy comprehensive evaluation algorithm, and builds an innovative mechanism of tax preference by establishing two weighting indicators of tax relief ratio and Q value (tax relief locational entropy) through data feedback. To ensure the accuracy of the feedback indicators, the full-factor algorithm is invoked to detect the intensity of the mechanism’s preferences in the digital industry. To verify the effectiveness of the mechanism, the results of the practical analysis show that after the innovation mechanism constructed in this paper is put into practice, the proportion of tax breaks in two digital industries, manufacturing and industry, increases by 29% and 34%, respectively, and the Q values of the five industries increase by about 4.2% on average, and the yields all increase by about 5.12 percentage points. This illustrates that the tax preference innovation mechanism constructed in this paper can accelerate the economic development of industries and is conducive to giving full play to the positive incentive effect of tax preference on their material benefits.
Research on the Evaluation of the Effect of Tourism Revitalization of Intangible Cultural Heritage in China in the Context of New Media
Authors: Chen Zegeng , Fu Shimin 
Published: September 2023

Abstract
In this paper, a tourism revitalization model of intangible cultural heritage is constructed, and firstly, feature factors are extracted and multivariate features are combined using methods such as kernel density estimation to provide support for reliable prediction. Then decompose the MLP network structure, i.e. multilayer perceptron, and use Sigmoid function as the activation function. The importance of the feature factors is calculated using the random forest algorithm, and the collected tourism data are mined for the relationship between intangible cultural heritage and tourism revitalization to obtain the residual mean square of out-of-bag data. Finally, the coupling coordination degree is used to derive the development of ICH and tourism revitalization. The experimental results showed that 78% of the tourists were moderately to highly involved in the interactive participation of ICH, and only 22% were not interested in it. Therefore, the combination of ICH tourism and new media may become a new way of communication, allowing more general public to have the opportunity to approach and know ICH tourism.
Deep learning model-based reading of Chinese language and literature classics and situational experience
Authors: Chen Lu 
Published: September 2023

Abstract
In this paper, a new media scenario experience model is constructed to integrate Chinese language and literature works through deep learning algorithms. Firstly, the model is trained as a whole, RBM is a special form of Boltzmann machine, and the energy function is defined by combining the input layer vector and the hidden layer vector to calculate the marginal probability distribution. Then the defined energy function can be used to derive the joint probability formula of state values, link this probability formula with the hidden layer between the neuron nodes, use the logistic function to define the energy of the whole Boltzmann machine, and finally, after repeated training to derive the entropy function of the RBM, to complete the construction of a new media-based scenario experience platform. The experimental results show that after a semester of teaching based on this platform, the scoring examination of new media scenario experience classical reading was conducted. The percentage of those who passed was 82%, and only 18% failed. Therefore, we should make full use of multimedia technology, innovate efficient Chinese language and literature teaching methods, turn the classroom into a stage, enhance the novelty of Chinese language and literature courses, and enhance the intuitiveness of classical reading in Chinese language and literature.
The significance of senior education in the Internet era for the construction of lifelong education system
Authors: Qi Jingying , Wang Tuo , Huai Fule 
Published: September 2023

Abstract
This paper uses Bayesian networks for the state combination of random variables to describe the relationship between prior probability and posterior probability by likelihood. Meanwhile, the elimination of complex variables is achieved by combining the operation results of multivariate non-independent joint conditional probability decomposition. Based on this, Bayes’ theorem is used to calculate the learning efficiency, the comprehensive pass rate of any interactive courseware, and the growing value of the visualized learning process to improve the sharing of resources for senior education. To verify the feasibility of the model, a teaching effectiveness test was conducted, and the results showed that 66.6% of older adults believed that participation in senior education could strengthen their bodies and minds. The percentage of medical and health care knowledge courses was 63.20%. The direct effect of the learning environment on the participation behavior of senior education was 0.143, while the indirect effect of educational resources on the participation behavior of senior education was 0.083. In addition, 61.78% of seniors thought that attitude towards senior education was very important. Therefore, it can be concluded that the model of the elderly education system fills the gap in the structure of the lifelong education system, enriches the uppermost structure of the lifelong education system, and promotes the improvement and development of the lifelong education system.
Research on the application of improved V-detector algorithm in network intrusion detection
Authors: Zhong Yuming , Chen Leyou 
Published: September 2023

Abstract
Network intrusion detection has been widely discussed and studied as an important part of protecting network security. Therefore, this paper presents an in-depth study of the application of an improved V-detector algorithm in network intrusion detection. In this paper, we construct a V-detector intrusion detection model, adopt the “self-oriented” identification principle, and randomly generate detectors with large differences from the health library. A smaller number of detectors are used to compare the data information generated by the computer, and if they are similar, they are judged as intrusions. Intrusion detection experiments are performed on multiple types of networks by using classifiers to determine whether the access to be detected is an attack access. The experimental results show that the model has the lowest false alarm rate for mixed feature networks, with a false alarm rate of only 13% and a detection rate of 89%, with a sample size of 25,987. After the improvement of the V-detector intrusion detection model, the error correction output problem leads to a network intrusion with a miss rate of only 11% and a protection rate of 85%. The experimental data proved that the model has the advantages of large data size and comprehensive intrusion attack types.
Integration of government accounting system reform and university infrastructure consolidation based on type two fuzzy sets
Authors: Mi Rui 
Published: September 2023

Abstract
Type II fuzzy set can innovate the accounting method of infrastructure consolidation and integration work. Based on this, this paper constructs a new and feasible accounting system for the integration of government accounting systems and university infrastructure. The specific application is that any point on the financial subordination domain and its corresponding subordination interval constitutes a type two fuzzy set, and the fuzzy set is used as the object for modeling. Using the interval type-two fuzzy set for word calculation, the result of the calculation is output by the decoder and sorted, and the value of the accounting account amount can be derived. The mutual subset measure between the input interval type II fuzzy set and the rule antecedent interval type II fuzzy set is used to check the accounting bills of the rule activation interval and to verify the performance of its use in the capital consolidation work of S universities. The experimental results show that after transferring the balance of $4,982,600 for prepaid construction and $4,956,200 for prepaid provisioning to the prepaid account on the basis of ensuring the consistency of the output KM algorithm, the balance of the account becomes $9,938,800. This result shows that the type II fuzzy set saves 42% of the arithmetic cost for this transfer of university infrastructure accounts, and contributes to the realization of the government accounting system reform and the improvement of financial management of the integration of university infrastructure accounts.
Research on the Application of Civic Education into the Brain and Heart Based on Physiological Data Recognition Algorithm
Authors: Zhang Guanglei , Li Min 
Published: September 2023

Abstract
This paper designs a Civic Education model based on a physiological data identification algorithm, highlighting the training enhancement of physiological data mining Civic Education for students. In the design process, the clustering similarity is calculated based on the attribute distance, and the optimal number of clusters is selected using the contour coefficient. On the basis of determining the optimal number of clusters, the maximum number of iterations is performed, and the output at termination is used to divide the thinking and teaching ability and ability assessment index association distinction. The minimum confidence threshold association rule is developed through the candidate item support, and weighted random selection is performed for each dimension. To verify the feasibility of this educational model, its teaching effect is analyzed. The experimental results show that the accuracy of the output results is high, and the average time of Civic Education of the philosophy of dealing with the world is about 0.65 seconds. The highest psychological recall rate of Civic Education reached 0.59. It shows that physiological data mining can guide students to build a Civic Education thinking system so that the course and Civic Education can form a synergistic effect, thus forming a horizontal and vertical synergistic education situation.
The challenges of ideological and political education in higher education institutions in the era of big data and its path analysis
Authors: Liu Ting 
Published: September 2023

Abstract
With the continuous development of information technology, digitalization and networking have become the main features of today’s society; in such a context, ideological and political education in higher education institutions faces many challenges. In this paper, the acceptance process of ideological and political education for higher vocational students is divided into five major elements: transmission subject, acceptance subject, acceptance object, acceptance intermediary, and acceptance environment, and the interaction mechanism between the five major elements is analyzed. Secondly, it proposes to adopt the knowledge tracking of fusion learning factors (EKPT) model to decompose contradictory factors for the prior probability of curriculum fusion ideological and political knowledge matrix V and the prior probability of fusion ideological and political elements modeling students’ knowledge level tensor U. The final results of the empirical analysis of acceptance of ideological and political education based on the EKPT model show that the correlation coefficients between teaching efficacy and acceptance of ideological and political teaching behaviors range from 0.361-0.559, and the correlation coefficients between psychological strength, psychological optimism, total psychological resilience scores, and ideological and political teaching efficacy show high correlations ranging from 0.538-0.683. The research in this paper helps higher education institution’s ideological and political education to better adapt to the needs of the data era and improve students’ ideological and political quality and comprehensive literacy.
Analysis of the regulatory environment on Green innovations Efficiency and its Impact Effect
Authors: Dai Xuan , Liu Nian 
Published: September 2023

Abstract
This paper investigates the mediating effect model and threshold effect model used to examine the relationship between the regulatory environment and advancements in green technology. Spatial factors are incorporated into the model constructed in this paper, and spatial autocorrelation tests are conducted on relevant data. The created model is labored to assess the effectiveness of green innovations in Zhejiang Province from 2010 to 2021, and on this basis, the changes in efficiency values are elaborated on different scales and spatial and temporal dynamics. Then, carbon finance and resource allocation are used as mediating variables. Thus, the two variables of carbon financing and resource allocation are utilized in the mediating model to assess the effect of the regulatory environment on green technological innovation. Finally, this paper investigates the threshold effect of the regulatory environment in the procedure of technology service industry agglomeration affecting green innovations efficiency, and according to this, to experimentally determine whether the regulatory environment has a threshold value, a panel threshold model is built. After the model test, when the intensity of the regulatory environment is greater than 0.0334, the coefficient of technology service industry agglomeration is meaningfully negative −0.0687, representing that the different intensity of the regulatory environment makes a significant difference in the effect of technology service industry agglomeration. Therefore, the regulatory environment is conducive to green technological innovation, and green technological innovation tends to form agglomeration in the region.
Study on the Rationalization of Human Resources Allocation in Hospitals in the Post-Epidemic Era
Authors: Jiao Haiyan , Li Jiangbo , Liu Lin , Zhao Haibo 
Published: September 2023

Abstract
Rational hospital human resource allocation planning is important to improve the efficiency of China’s health human resource allocation and reduce the losses caused by staff waste and shortage. In this paper, we take the medical and nursing configuration of a general tertiary hospital in X city as a guiding framework and use inductive and deductive methods to summarize the factors affecting medical and nursing staffing and the experience of management in the previous period. By proposing an adaptive algorithm based on learning rate for improving BP neural network with differentiated learning rate, the dynamic adjustment of weights between different nodes is achieved. Finally, through database design and module design, two functional modules of human resource management and human resource prediction are constructed. The results of the case validation show that the HR demand forecasting model has the best prediction effect for health technicians, and the relative errors are all less than 5%, with an average relative error of 1.23% and a minimum value of only 0.25%. The relative error between the predicted and actual values of the ARIMA (2, 2, 2) dataset for practicing (assistant) physicians is less than 0.005. It shows that the HR model constructed in this paper has a certain quantitative guidance value for the rational planning of human resource allocation for hospital positions.
Research, analysis and optimization of the drive characteristics of the drive wheel of the machine tiller based on SPH method
Authors: Li Zhongzhi 
Published: September 2023

Abstract
The boat tiller (machine tiller) uses the floating working principle to make the hull and drive wheel bear the general tractor drive wheel load and drive two functions, respectively, so that it has good applicability in the operation of deep muddy foot water field, which greatly improves the tillage efficiency of China’s water field farming. The drive wheel is an important component of the machine tillage boat; its structural parameters have a significant impact on the driving performance and efficiency of the machine tillage boat. In this paper, combined with the kinetic analysis of the drive wheel, a single-wheel leaf-soil smooth particle hydrodynamic model of the drive wheel is constructed based on the SPH method, and the influence of the parameters of the wheel spurs of the drive wheel unit group on the driving performance is analyzed, and the drive wheel mechanism parameters with the best driving efficiency are finally obtained through simulation analysis. The research results show that the maximum propulsive force of the optimized single-wheel blade structure increases by 35.8% compared with that before optimization, the slip rate decreases by 3.9% compared with that before optimization, and the driving efficiency increases by 14.4% compared with that before optimization. The structural design and parameter selection of the drive wheel of the research results of this paper provides a certain theoretical basis, which is of great significance to the later improvement of the drive efficiency and performance of the drive wheel of the machine tiller in paddy soil.
Design of automatic tobacco trash detection system based on quadratic fuzzy theory
Authors: Jin Zhenxun , Wang Wei , Wang Youli , Wang Gang , Zhang Qiang 
Published: September 2023

Abstract
Fuzzy sets and deep learning models have accurate recognition accuracy in automatic detection. To be able to accurately identify tobacco debris and improve the quality of cigarettes, this paper proposes the design of a tobacco debris detection system with a deep learning model and fuzzy quadratic theory. The collected data is stored to AL422B by quadratic fuzzy set timing conversion, the cached image data is read by the microcontroller, the image pixel points are output, and the external controller and internal registers are set to read the tobacco image. The integrated Thumb extended instruction set to obtain the CPU clock frequency makes the controller interrupt and ensures PWM output. Integrate the internal fixed oscillator and external integrated control circuit to debug the program interface circuit to prevent power on and off misoperation. The negative log-likelihood function is obtained by following the activation rules given by the visible layer and hidden layer activation functions. The RBM is trained by quadratic fuzzy set estimation to optimize the parameters; test sample sets appear overfitting, combined with DBN pre-training and fine-tuning, iterative output, and labeling target data to meet the preset requirements to achieve intelligent detection of tobacco debris. The result analysis shows that the deep learning model and the quadratic fuzzy set generalization ability and accuracy are high, the highest F-value in tobacco clutter detection reaches 100%, and the system is designed to detect tobacco clutter automatically with high accuracy and good detection of clutter.
A study on the principles of Chinese painting line drawing figure sketching techniques based on cognitive mapping constructs
Authors: Luo Hongqiang 
Published: September 2023

Abstract
It is the basic requirement of Chinese painting line drawing figure sketching to express its unique divine mood and spiritual quality by shaping the figure through lines. This paper constructs a figure sketching technique model based on cognitive mapping, and the constituent elements of line drawing figures are used as individuals of the genetic algorithm population. Multiple constituent elements are trained with data using a genetic algorithm, and the selection and crossover operations are continuously performed according to the fitness threshold; a particle swarm optimization strategy is added, and the principle of the line drawing technique is derived after several iterations of calculation. The performance test of line drawing and figure sketching was conducted for the research class and the control class. The experimental results showed that the control class scored 60.35 and 65.32 in the two tests, the research class scored 72.59 and 79.15, and the research class outperformed the control class in the overall average score and the average score of the six grades. It shows that the cognitive mapping construction based on which the form of line drawing is continuously enhanced and developed has strengthened the importance of line drawing and made Chinese painting line drawing figure sketching more attractive and relatively independent.
Research on the focus of national traditional sports culture inheritance based on weighted function algorithm
Authors: Deng Chengyuan , Liu Yang , Cheng Lifen 
Published: September 2023

Abstract
In order to make the traditional national sports can be inherited in a lasting way, this paper focuses on the study of national traditional sports culture inheritance from the perspective of moral education. Firstly, we add the teaching content of traditional ethnic sports in physical education courses; secondly, we use the weight update method and base classifier in the weighting function to improve it. And finally, we use the system to conduct experiments. The results show that the teaching experiment of pearl ball as the teaching content of public physical education courses can better improve students’ performance in 4 qualities, and the improved teaching mode can promote students’ learning attitude towards physical education. From the perspective of cultural inheritance, it is of practical significance to explore the new mode of national traditional sports education in colleges and universities under the new conditions of the times in order to inherit traditional national sports and enrich the cultural connotation of college students.