bluuebunny/crossref_metadata_2025 huggingface dataset:
A study on the impact of theater performing arts combined with drama arts on the stage in the context of big data
Authors: Yin Yiming
Published: January 2024

In this paper, based on the law of motion, combining the spherical coordinate system representation with the drama art of action feature recognition in the process of theatrical performance, the joint points of wrist, elbow and shoulder and the corresponding feature vectors as well as the school angular velocity are calculated. The affine invariant domain of feature matching is constructed, and the algorithms of dynamic frame difference merging and dynamic detection of human-computer interaction are applied to obtain similar feature components of the recognition of body movements and gesture commands in the process of theatrical performance. The harmony factor, emotion factor and contrast factor in the stage scene are used as evaluation parameters to derive the color evaluation function and keyframes of theatrical stage lighting combined with drama art. For the research purpose, the research on the stage influence of the theatrical performance of combining drama is designed, and the example analysis of the stage influence of the theatrical performance of combining drama is analyzed by using origin software. The results show that the level of the audience’s arousal dimension is significantly higher than its level in CSP, t(1, 29)=3.959, p<0.001, upper threshold (Engagement=0.38, Arousal=0.26), lower threshold (Engagement=0.35, Arousal=0.21), i.e., the specific performance episode for the audience to bring about significant emotional relaxation. Audience ratings of CAC were generally higher than their ratings of CSP, with differences ranging from 0.2 to 1.5. The mean times that subjects were in the “S(n)=1” state in the three modes were 219.86 (SD=60.62), 287.37 (SD=80.68), and 310.7 (SD=45.83), respectively. 45.83). This study greatly improves the impact of stage art and gives a whole new life to the combination of theater performance and drama stage art.
The path of management of dispute cases of legal issues of webcasting bandwagon industry in the information age
Authors: Chang Chao , Zhang Wei
Published: January 2024

In this paper, for the common live streaming with cargo dispute cases in the context of the information technology era, the live streaming with cargo industry dispute case retrieval algorithm based on case-based reasoning calculates the attribute similarity measure and weights of the dispute cases in order to realize the live streaming with cargo industry dispute case retrieval. Three thousand judicial documents with live streaming with cargo disputes as the cause of the case were crawled from the China Judicial Documents Network as the initial data for the study and the method of BIOES was used to annotate the initial data and formulate eight basic legal elements of live streaming with cargo dispute cases. The form of extracting legal elements of live streaming with goods industry is transformed into a multi-label text classification task, and the neural network modeling method combined with the attention mechanism is used to design the extraction model of legal elements of the live streaming with goods dispute cases, and then the live streaming with goods dispute cases on the Internet are analyzed by examples. The results show that the Acc value of this paper’s model is 0.973, the Loss value is 0.051, and the F1 value is 0.981, and on the whole, this paper’s model performs better compared with the other five models, i.e., it shows that this paper’s model can be more intelligent and accurate to collect the case element information under the field of live streaming with goods disputes. This study aims to contribute to the development of a new sales model of live streaming with goods benignly.
An analysis of the effects of a physical education web-based instructional program on college students exercising at home during COVID-19
Authors: Li Chunyan , Han Yue , Du Wanxin
Published: January 2024

Teaching online physical education courses under the epidemic normalization plays a positive role in students’ physical fitness. In this paper, taking 308 college students of X Sports College as a research case, personalized recommendation of physical education online teaching courses is carried out through a user collaborative filtering recommendation algorithm based on fuzzy clustering and user interests. The model of sports skill action development is constructed based on the mountain peak model and hourglass model, and the exercise intensity of the initial exercise is modified according to the results of home exercise intensity adjustment to obtain a personalized home exercise program suitable for individuals. Finally, the effectiveness of the home exercise optimization program was verified through the analysis of teaching constraints and exercise effects. The results show that under the epidemic normality, the difference between the demonstration movements and the test results in the 1st, 2nd and 3rd optimized teaching phases is between ±5.86, which is closer to the value of each index of the demonstration movements, indicating that the optimization and adjustment scheme of the home exercise of the physical education network teaching course has good effects. This paper has reference value for universities to conduct online teaching and training of university physical education courses in the context of major public health emergencies.
The Impact of the Big Thinking Program on Students’ Mental Health in the Context of Three-Way Parenting
Authors: Liu Yan
Published: January 2024

This paper combines the stepwise regression algorithm as well as the decision tree algorithm to design a decision tree stepwise regression algorithm model of the impact of the big Civics program on students’ mental health. This paper focuses on the use of a stepwise regression algorithm to eliminate the independent variables that do not have a significant impact on the dependent variable, and through the decision tree, ID3 method to test all the features, in-depth exploration of the degree of influence of the large courses of ideology and politics on students’ mental health. In order to be able to more deeply solve the degree of influence of the large course of thought and politics on students’ mental health, a oneway linear regression analysis is carried out on the basis of the relevant analysis data of students’ mental health. The results show that the histogram of the independent variable of the large course of ideology and the dependent variable of the total mean score is distributed in a normal curve, with a mean of 2.82E-16, a standard deviation of 0.999, and a correlation coefficient squared of 0.057, which indicates that the large course of ideology has a predictive effect on the mental health of students and that the students’ anorexia mental health is influenced by the large course of ideology by 0.057. This study shows that the large course of ideology is able to promote the physical and mental health development of students and contribute to the mental health of the students. This study shows that the large ideology and politics program can promote the healthy development of student’s physical and mental health, provide a direction for mental health education to become an effective carrier of “moral education”, and also provide a breakthrough point for the reform and innovation of students’ mental health education.
Study on the Historical Evolutionary Process and Practical Significance of Xiangxi Nuo Witch Culture Based on the Hierarchical Analysis Method
Authors: Hu Qian , Liu Jinming
Published: January 2024

This paper, through the method of subjective screening indicators, initially determined the Xiangxi Wu Nuo cultural evaluation indicators, and the use of hierarchical analysis of the history of Xiangxi Wu Nuo cultural indicators decomposed into different levels, and then the way the block diagram to indicate the hierarchical recursive structure and the affiliation of the factors. According to the effective amount of information provided by the metric data, using entropy weighting method to calculate the subjective weights to construct the subjective evaluation model of the historical evolution of Xiangxi Wunuo culture and research and analysis of Xiangxi Wunuo culture. The results show that based on the hierarchical-entropy weight method of Xiangxi Wunuo cultural history evaluation of the likelihood ratio test of P<0.05, McFadden R2 value between 0.2 ~ 0.4, indicating that based on the hierarchical-entropy weight method can be more accurate to Xiangxi Wunuo cultural history evolution process evaluation. The overall satisfaction of the current status of the communicative revitalization of Xiangxi Wu Nuo culture is 2.504, the importance is 4.381, and the IPA index is 29.296, indicating that the intangible cultural heritage has a stronger communicability. This study provides theoretical guidance for the study of the historical evolutionary process and practical significance of Xiangxi Wunuo culture and is of practical significance for the promotion of the sustainable development of Xiangxi Wunuo intangible cultural heritage.
Application of Electronic Communication Signal Modulation Recognition System Based on Fourier Transform
Authors: Liu Jingxue , Zhang Huale , Cheng Rui , Liu Jun
Published: January 2024

In this paper, the weighted class fractional Fourier transform is redefined by means of the weighted superposition of state functions, and the Fourier transform is applied to dissect the intrinsic relationship between the M-WFRFT and the 4-WFRFT and to obtain the weighting coefficients of the electronic communication signals. On the basis of the WFRFT discrete algorithm, the electronic communication signal is expanded to include M a term after the M -WFRFT and the hybrid carrier modulation method based on the WFRFT is given. According to the design idea of the electronic communication system, the hardware part and software part of the electronic communication system are designed, and the electronic communication signal modulation recognition system is experimentally analyzed by using the simulation experiment method. The results show that when the signal-to-noise ratio is -8dB and the optimization algorithms are the Sgd algorithm, Sgdm algorithm, and Adam algorithm, the modulation identification accuracy of OFDM signal is 39.3%, 57.5% and 43.5%, respectively, which indicates that the Sgdm optimization algorithm is the most suitable one compared with other algorithms, and it is more effective in the modulation identification of OFDM signals at low signal-to-noise ratio. The number of scans of the three-layer multi-parameter WFRFT signal by the non-cooperative party is 6.4 × 1013 times, and the increase in the number of scans leads to an increase in the cost paid by the non-cooperative party, which confirms that the secure communication system based on three-layer weighted fractional-order Fourier transform has good resistance to parameter scanning characteristics and high confidentiality. This study further improves the a priori parameter setting of the electronic communication system and enhances its complexity, resulting in better anti-interception identification features.
Research on Exhibition Marketing Strategies in the Context of Network Era
Authors: Qian Ruo
Published: January 2024

In the network era, consumers’ behavior of shopping through the Internet can be seen everywhere in daily life. In this paper, starting from consumers’ online shopping behavior preference, the equilibrium mode of conventional advertising is studied, based on which the mass and targeted advertising strategies under decentralized and centralized decision-making modes are proposed, respectively. After comparing and studying the marketing channel structure in various modes, the corresponding advertising optimization model was established to derive four theorems. According to the deduced theorems, the enterprise revenue model is constructed and solved to maximize the benefits. Compare the mixed and separated equilibrium models of the two-stage model in the sales process, and at the same time, construct the XGBoost algorithm model to classify the characteristics of consumers’ shopping behaviors and collect the enterprise’s product marketing strategies. The results of the empirical experiments show that the reasons why consumers do not buy the exhibits of Company W are mainly due to “the price is too high”, “the sense of participation is insufficient” and “the attraction is too low”, with the values of 2.5, 2.5, 2.5, 2.5 and 2.5 respectively. The number of consumers who are satisfied and very satisfied with W brand exhibitions is the largest, and the number of people in all four aspects is around 50, so the marketing strategy of W company exhibitions adjusted according to consumer behavioral preferences is effective.
A Study on Macro Measurement Methods and Volatility Characteristics of Interest Rate Risk of Commercial Banks under the New LPR Mechanism
Authors: Wang Lingling , Shang Keru , Wang Xiaoyu
Published: January 2024

The interest rate risk of commercial banks is closely related to the effectiveness of the LPR mechanism. In this paper, the interest rate market is divided into three stages according to the process of interest rate marketization, and a six-sector New Keynesian MS-DSGE model is constructed by adding monetary regulation variables. The parameters in the model that are influenced by interest rate marketization and the new LPR mechanism are transformed by Markov zone transformation. The interest rate risk of commercial banks is measured by the impulse response functions of uncertain interest rate shocks to the interest rate sensitivity gap and the duration gap, and the volatility characteristics of interest rate risk in different stages of interest rate marketization are compared and analyzed. The results show that in the third stage (2019-present), the LPR mechanism is transformed from old to new. Under the δR
= 0.5 shock, the commercial lending interest rate tends to stabilize around 0.00038, and the borrowing interest rate tends to 0 in all 3 differentiated target parameters in the 10th period. For this reason, the differentiated interest rate pricing behaviors of commercial banks should be considered comprehensively, and the LPR target should be set reasonably so as to get the optimal policy effect.
Informatization of Physical Education Curriculum Education and Training Management in Colleges and Universities under the Maximum Information Entropy Model
Authors: Wang Wanli
Published: January 2024

Currently, there are problems such as weak training purpose, poor training effect and backward auxiliary decision-making means in college physical education. In this paper, we first construct a college sports training management decision-making system based on Multi-Agent and adopt the blackboard model to realize the communication between Agents. The training management decision-making agent system uses the maximum information entropy model to identify the benefits and drawbacks of executing college sports training management decisions. Secondly, feature selection is carried out through the correlation filter (CFS), and the best priority search method is used to obtain the required subset of features. Finally, the reliability of the college sports training management decision-making agent system was verified by testing experiments. The results show that the inter-rater of the system is 0.920.95, and the intra-rater is 0.94, reflecting the good reliability and practicality of the training management decision-making Agent system. This study enhances the effectiveness of sports training management to some extent, and it also serves as a valuable reference for the development of similar systems.
The Practical Path of Ruling Colleges and Universities According to Law in the New Era Combined with Big Data Analysis
Authors: Ma Yingjun
Published: January 2024

With the development of the information age, big data analysis has become the basis for social management and the development of new ideas for intelligent governance. In this paper, the governance process of colleges and universities is presented and stored in the form of data by simulating the content of governance through the full domain data set, and the relationship between different subjects and object features is mapped through the generalized Cartesian product. From there, various data patterns are clustered to effectively manage various types of operations’ linkage. The multi-objective optimization algorithm is used to solve the Pareto optimal solution for different governance subjects, i.e., the mutual coordination between teachers and students. The objective optimization function is established to identify the Pareto frontiers of various governance programs and emergency plans. The results show that in the driving pathway of college big data governance, the correct rate of classification of policing grid governance events in 28 colleges and universities is 0.8279 on average, which effectively improves governance efficiency. Big data governance in colleges and universities enables college governance to continuously move from decentralized to centralized, from part to whole, and to achieve accurate and efficient governance modes.
Analysis of the timeliness of teaching methods of university education oriented to comprehensive development in student management
Authors: Xu Wenting
Published: January 2024

With the development of higher education, the number and scale of college students are expanding, and the new situation poses challenges to the management of college students. This paper proposes a comprehensive development evaluation model for college students based on combination assignments and conducts a consistency test for expert ranking using Spearman’s rank correlation coefficient. The indicators are scored using the fuzzy affiliation degree method to eliminate the influence of dimensionlessness and the positive and negative differences between indicators. The correlation coefficient of G1 is corrected by standard deviation to determine the optimal combination of weights for the objective function, and it is dynamically adjusted according to the changes of the data in practice to reflect the degree of deviation and the comparative difference of each single weight. Finally, School C was chosen as the research object to study the timeliness of the comprehensive development teaching model in student management. The results show that among the 650 students in School C, the highest score of student comprehensive development evaluation is 4.083±0.65, which indicates that the comprehensive development evaluation in School C possesses goals and needs with high recognition as the premise of implementation and has strong theoretical and practical significance for the comprehensive development of college students.
A Practical Study of Computer-Assisted College English Intelligent Teaching Course Based on OBE Theory
Authors: Chen Bimei
Published: January 2024

The development of wisdom teaching has brought great impact and examination to the traditional English education mode. Based on the educational platform of Rain Classroom, this paper constructs a university English wisdom teaching classroom, designs the teaching activities of wisdom teaching classroom, and constructs a diversified evaluation index system for wisdom teaching mode based on the OBE concept. The objective weights obtained by the entropy weight method, CRITIC method and coefficient of variation method are combined by linear weighting method to solve the comprehensive weights of each evaluation index. In order to verify the effectiveness of the relevant methods in this paper, the verification and analysis of the data were carried out with the actual situation of the students in the School of Foreign Languages of Zhuhai Institute of Science and Technology. The results show that the highest weights of teachers’ classroom teaching organization and students’ classroom communication and cooperation under the wisdom teaching mode are 0.3761 and 0.3649, respectively, and the correlation of each evaluation index exceeds 0.5, showing a strong correlation. The fuzzy comprehensive evaluation score of university English teaching quality in the School of Foreign Languages of Zhuhai College of Science and Technology is 75.975, indicating that the overall teaching quality of university English smart classrooms is good to excellent. The English smart teaching course helps cultivate students’ independent learning abilities and innovative thinking and promotes the deep integration of language proficiency and intercultural communication skills.
Innovative Research on Industrial Upgrading and Transformation Path of Regional Economy in the Perspective of Digital Economy
Authors: Ge Xuan
Published: January 2024

This paper utilizes the digital economy, regional spatial distribution digital mining technology, establishes the indicator system, assigns values to the indicators, and applies the indicator system to evaluate the development of industrial structure upgrading and transformation of the regional economy. According to the research results of the basic structure and algorithm of the self-organized neural network model, combined with the classification layer smoothing algorithm, the regional spatial clustering model is constructed. Using the constructed model, the regional economic spatial dynamic data is mined, and the path of industrial transformation and upgrading in the regional spatial area is dynamically studied. Furthermore, using the CA algorithm, the evolution law of land use structure in the region is predicted, and the development of the regional economy is inferred. At the same time, through the spatial autocorrelation regional prediction model, the relevant regional spatial expansion prediction method is proposed, the three research hypotheses of this paper are made, and the constructed model is utilized to innovate the exploration of industrial transformation and upgrading paths from the spatial dimension. Using empirical research methods, descriptive statistics, and mediating effect heterogeneity analysis are carried out to analyze the factors that influence regional economic variables in place A. The empirical analysis shows that the fluctuation range interval of industrial structure is between [0.811,10.2805], which brings a large positive impact on the regional economy.2017 national digital economic growth rate changed from -0.17446 to 0.17143 to realize a positive growth rate, and at the same time, there is a heterogeneity in the development of the east-west and central regions of A. The hypotheses presented in this paper are all valid.
Research on Talent Cultivation Mode of Vocational Education in the Context of Information Technology
Authors: Chen Xinrui
Published: January 2024

This paper mainly analyzes the educational level of vocational education in the context of information technology from the perspective of matching degrees of vocational education specialty settings and talent demand. Combined with the framework of vocational education service supply under information technology, the SARIMA-BP model is utilized to predict the demand for talent training, and then the match between the professional setting and the education level is explored in a quantitative description. The PSO algorithm is used to optimize the linear combination prediction model of the SARIMA-BP neural network, and the prediction accuracy is compared. The degree of vocational education development and talent cultivation mode are analyzed from four aspects. According to the division of secondary vocational school graduates according to the three industries, the proportion of graduates from Guangdong’s primary industry decreased by 0.1053, and the proportion of graduates from the secondary industry decreased by 0.0123. At the same time, the proportion of graduates from the tertiary industry increased by 0.0243. It can be seen that, to cope with the change of industrial structure in the context of information technology, secondary vocational education should adjust the relevant specialties offered to upgrade the industry’s development and the market’s need for the Talent cultivation mode.
A study on the construction of the ideological elements of public physical education courses in colleges and universities using multivariate data fusion
Authors: Chen Kai
Published: January 2024

Based on a multimodal topic network, this paper constructs a knowledge combination model for the cross-discipline of public sports and civic politics. Through multimodal data fusion, the knowledge combination between the two kinds of public sports courses and Civic and political education in colleges and universities is obtained. Finally, using the China Knowledge Network database as the source of data retrieval, the hot spots and their evolution paths of Civic Politics in public sports courses were explored so as to excavate the elements of Civic Politics in Civic Politics of Public Sports Courses. The results show that among the elements of ideology and politics in the curriculum, “patriotism education” has the greatest emergence intensity, with a value of 49.382, followed by “establishing moral character” with an emergence intensity of 16.338, which indicates that the main purpose of the construction of the elements of ideology and politics in the physical education curriculum is to cooperate with the orientation and requirements of ideological and political education, which is the most important part of the public sports curriculum. It shows that the main purpose of the construction of the ideological and political elements of the physical education curriculum is to match the orientation and requirements of ideological and political education and to clearly link the goal of one’s struggle with the destiny of the state and nation.
Innovative Practice of Physical Education Teaching Mode in Colleges and Universities in the Information Age
Authors: Zheng Zheng , Xia Qiudong , Yang Renwei
Published: January 2024

The information age needs to change the traditional physical education teaching mode, set up modern teaching concepts, and pay attention to the cultivation of strong physical talents. This paper combines the ADDIE model and MOOC education platform to construct a hybrid teaching model for college sports, and gives the teaching design of the three phases of college sports hybrid teaching before, during and after class. Based on the GCN model and the similarity between MOOC sports teaching resources, a sports teaching resource recommendation model based on link prediction was proposed. Relevant research subjects and questionnaires were selected, and a blended teaching experiment was designed. Empirical analysis was conducted using the method of comparison of teaching experiments. The results show that the NDCG metrics of sports teaching resources based on the GCN model improved by 0.99%, 1.30%, and 1.16% on average compared with the CF-User algorithm on the Gowalla, Yelp2018, and Amazon-Book datasets. After going through the sports blended teaching experiment, the students in the experimental group improved their average scores on exercise attitude by 1.5 to 5 points, and their interest in learning increased by about 1 point. The blended teaching mode of combining MOOC platform and college sports teaching in the information age has changed students’ learning attitude to a certain extent, which can effectively enhance the quality of college sports teaching and improve the cultivation of college talents’ physical quality.
Machine Learning Based Optical Separation of Overlapping Handprints
Authors: Li Tong
Published: January 2024

Since overlapping handprints often have the potential to become a breakthrough point in criminal cases, extracting and separating overlapping handprints at the scene has become an urgent problem to be solved in criminal technical examination. In this context, this paper proposes a machine learning-based optical separation method for overlapping handprints, which uses SVM to simplify the classification of the features of the training samples and completes the measurement of the features based on the statistical properties of the image grayscale histogram. Using image blind source separation, independent component analysis and pixel iteration algorithm to separate the overlapped image to get two different spatial resolution images, SSIM is chosen to evaluate the quality of the separated image. Then, the target classification recognition and extraction techniques of the method in the paper are analyzed by overlapping handprint optical separation experiments. The results show that compared with the traditional algorithms, the TPR, FPR, overlap degree and accuracy of this paper’s method in dealing with overlapping handprint images with deep fuzzy features are at a minimum of 0.9258, 0.3723, 0.4645, 0.9572, which are all greater than several other algorithms, which proves that the overlapping handprint optical separation method proposed in this paper based on machine learning has obvious advantages.
New Vocational Education Law on Artificial Intelligence Helps Build a Skilled Society
Authors: Zou Xiangling , Chen Xiaoxu
Published: January 2024

Under the guidance of the new vocational education method of artificial intelligence, this paper divides the skill-based society into skill-based organizations, and constructs a knowledge dynamic equilibrium model based on superimposed knowledge fields. The knowledge-explicit module of skill-based talent flow and the external dynamic equilibrium module are integrated to achieve the evolutionary modeling of knowledge resources in skill-based organizations. Based on the discussion of the new vocational education law, the characteristic models of intellectual resource development, knowledge dynamic growth, group evolution and talent motivation in skill-based organizations are proposed respectively. The simulation analysis of the knowledge dynamic equilibrium network is combined with the analysis of influencing factors to inspire the education of higher vocational colleges and universities under the new vocational education method. As measured by the data, the average path length mean values of the intra-organizational knowledge network when N=160, 260, 330 are 2.2761, 2.4437 and 2.5394, respectively, which indicates that skilled talents have a strong willingness to interact with each other and share knowledge. The construction of skill-based organizations should fully create a strong environment for talent exchange and focus on cultivating students’ willingness and ability to communicate in vocational education.
Modernization of Intellectual Property Discipline Governance Based on Multivariate Statistical Analysis Towards the Construction of a Powerful Intellectual Property Country
Authors: Qi Yin
Published: January 2024

In this paper, after using the TF-IDF algorithm to calculate the weights of intellectual property keywords of digital content, the weights of fused word multi-features are improved to obtain the proportion of intellectual property keywords. Based on intellectual property keywords, combining adversarial fingerprint generation and intellectual property authentication, an intellectual property protection model based on RCNN is constructed. From the perspective of strong nation-building, the research on intellectual property affecting the artificial intelligence industry is designed, and multivariate statistical analysis of scientific governance of intellectual property in the context of strong nation-building is carried out. The results show that the SSIM values obtained by the method of this paper are much better than those obtained by the comparison method in terms of model analysis. Except for the anti-quantization attack, the rest of the indicators are all greater than 0.9. It confirms that the method presented in this paper has excellent robustness in protecting intellectual property. In the empirical analysis of the impact of intellectual property rights on the artificial intelligence industry, except for RDF, which is significant at the 5% level, the regression coefficients of the other explanatory variables are all significant at the 1% level, 2 R amounting to 0.860771 and with a DW value of 1.667387 in the range of 1.5-2.5, that is, it indicates that the level of China’s intellectual property rights protection and the competitiveness of the AI industry are positively correlated. It is positively correlated. This study promotes the improvement of China’s innovation ability and the formation of innovation mechanisms from the aspect of intellectual property protection so as to realize the comprehensive catching up of technology and economy of late-developed countries.
A study to analyze the importance of establishing a mathematical model for teaching college physics
Authors: Liang Jinrong
Published: January 2024

Numerical simulation technology to assist the teaching of university physics is a higher education to continuously adapts to the social development of its own needs. This paper classifies the common forms of university physics courses involving numerical computation, explores the current computer simulation in physics teaching, and establishes the development process of the university physics computer numerical computation simulation program. Numerical simulation technology is applied to the design of university physics teaching, and two examples of numerical simulation technology assisting university physics teaching are designed from two cases of grating diffraction intensity distribution and gas diffusion based on Matlab. In Example N = 10, the light intensity distribution of diffraction grating with different slit numbers is analyzed by numerical simulation, and it is obtained that at 1, there are 9 minima between two adjacent main maxima, 8 sub-maxima, and the maximum value is 100, which verifies the theoretical results of the physical derivation of the grating diffraction intensity distribution. In the exposition, mathematical modeling is combined with examples to show that mathematical modeling can greatly exert the role of mathematical ideas in physics teaching, simplify physics teaching, and further cultivate students’ ability to solve practical problems.
Path analysis of tourism contributing to rural revitalization by combining elastic regression network algorithm
Authors: Zheng Chengkang
Published: January 2024

The development of suitable tourism according to the countryside’s local conditions can greatly help to improve the overall economic level of rural areas. This paper uses the elastic network method to optimize the penalty coefficient of the regression model so as to construct the elastic network regression model. In order to explore the effective path of tourism to help rural revitalization, this paper, through the selection of research variables, takes rural revitalization farmers’ income as an explanatory variable and tourism income as a core explanatory variable. The impact of tourism on rural revitalization was analyzed in several ways, including descriptive statistics of variables, coupling relationship tests, and benchmark regression. The results show that the mean value of farmers’ income in rural revitalization has increased by 5.045 compared with the minimum value, and the tourism industry has helped the local farmers achieve income generation to a certain extent. The disposable income of farmers is in the interval of [-1.8,-1.2], the level of agro-tourism integration is in the interval of [9,10], and the level of agro-tourism integration is positively correlated with the disposable income of farmers. The regression coefficient of industrial affairs expenditure is 0.503, which has a positive effect on tourism income at a 1% significance level. Tourism enhances the implementation effect of rural revitalization in the form of increasing farmers’ disposable income, and provides new help to optimize the rural industrial structure and enhance the ecological development level of tourism products.
Customized Research on Fault Diagnosis of Civil Aircraft Onboard Maintenance System Based on Big Data Technology
Authors: Chen Yuqin , Cheng Xiuquan
Published: January 2024

This paper dissects the BP neural network and RNN on the basis of existing research, obtains the improved long and short-term memory network, introduces the attention mechanism into it, and designs the fault diagnosis model of airborne maintenance system based on AM-LITM with big data technology. Focusing on the use of the BP learning algorithm to obtain the reference error of each unit needed to adjust the weight of each connection, real-time updating of information through the long- and short-term memory network to solve the problem of gradient dispersion of RNN, and at the same time, the method designed in this paper is compared with the traditional method from the aspects of fault diagnosis and prediction. The results show that the average prediction error of the traditional fault diagnosis algorithm is around 0.06, and it only has good diagnosis performance for the A-type fault, except for the classification accuracy rate of 0.9845. The rest of the performance index is 1. The diagnosis accuracy of the AM-LSTM fault diagnosis algorithm for three types of faults can reach 1, and all the indexes for the A, B, and C faults are 1, which shows that it greatly improves the performance of the traditional fault diagnosis algorithm. Diagnostic accuracy of civil aircraft on-board maintenance system faults is verified to verify the effectiveness and superiority of the designed model.
Research on the Aesthetic Value of Piano Playing Art Based on Multiple Intelligences Theory
Authors: Yu Minghui
Published: January 2024

In this study, a new exploration of a classic problem in the field of music aesthetics was carried out through the research methods of cognitive neuroscience and the brain mechanism of the formation of artistic aesthetic value in piano performance based on the theory of multiple intelligences was analyzed. In terms of EEG signal preprocessing, an EEG signal preprocessing method based on baseline average was proposed. In terms of EEG feature extraction, a decision-level feature fusion method is proposed, which uses SVM as the base classifier to extract time-domain, frequency-domain and nonlinear features, respectively, train the base classifier, and integrate the output of multiple basic classifiers through decision fusion. A feature fusion method based on music and ERP was also proposed to predict the response of subjects after listening to a piano performance. Based on DS evidence theory, emotion recognition and classification were carried out using EEG and music features from the perspective of decision-making level fusion. The results showed that piano performance mainly activated the left inferior frontal gyrus, right precentral gyrus, left auxiliary motor area, right superior parietal gyrus, cerebellar Crus1 area, right lingual gyrus and left inferior occipital gyrus, with peak t values of 4.67, 4.8, 5.76, 5.16, 7.02, 7.12 and 8.3, respectively. The activation of auxiliary motor areas, cerebellum, inferior frontal gyrus and other areas indicates that the artistic beauty felt by listening to piano performance can enhance people’s creativity, and the activation of the right superior occipital gyrus can enhance people’s imagination.
Optimization of the visual communication path of data news in the context of the Internet
Authors: Cao Tongying
Published: January 2024

Visual news belongs to a kind of data news, which uses emerging technology to bring users a new reading experience and improve the news dissemination effect. In this paper, we utilize the self-attention mechanism and BiLSTM model to extract the content of data news documents and select and classify the audio features of data news by the AdaBoost algorithm. ResNet50 is used as the backbone network, combined with multiple residual unit modules for news multi-scale image feature extraction, and the text, audio and image features of the data news are fused by constructing a multimodal feature adaptive fusion model to further optimize the visual display of the data news. This paper verifies the model’s effectiveness for the data news visualization technique through multiple perspectives, including training loss curve, performance comparison, and ablation experiment. The results show that the loss value of the model based on the Self-Attention-BiLSTM model for news text feature extraction is 0.211 after 150 iterations. The AdaBoost-based news audio feature classification method has an average classification accuracy of 97.56% for the positive diagonal when the noise is raised from 0dB to 30 dB. By adding the residual unit module to the ResNet50 backbone network, the accuracy of the multi-scale image feature extraction model has been improved by 2.77% compared to the single backbone network. The information age requires the full integration of technology and news and combining the corresponding Internet platform for the visual display of data news in order to promote the expansion of the visual communication path of data news.
Development of computer application system and database testing based on data encryption technology
Authors: Tang Wei
Published: January 2024

In this paper, we use the MapReduce programming framework for the development of a computer application system and design the vision module, control module and transaction module of the system based on MVC architecture. Focusing on the encryption design of the database, the data stored in the database is chunked through the Map function, and all the chunking results are aggregated based on the Reduce function, and synchronized encryption of the database is combined with the Paillier homomorphic encryption algorithm. On this basis, the system environment is configured, and the application system developed in this paper is tested, focusing on exploring the stability of the database. The test results show that the decryption output time is 21s when the Paillier encryption algorithm is 200, and the first set of database peak is 76% of the server load, which is within the tolerable range. Security test on the database: the results show that the probability of an attack on all ports with a database security factor less than 6 is around 0.3. There is no significant difference, and the database test is good.
The Innovative Integration of College Students’ Mental Health Education and the Path of Civic and Political Education in the Perspective of Educational Psychology
Authors: Huang Haibin , Zhang Linhua , Zheng Huina , Li Longqian , Yi Lei , Xie Fengjun
Published: January 2024

This work presents the automated assessment method of civic education using fusion psychology. The basis for it is the development of abilities in psychological and civic education. Five first-level evaluation indicators and seventeen second-level indicators have been filtered out. The computerized assessment model of Civic and Political Education of Integrated Psychology is constructed with timeliness by preprocessing the quantified index data with dynamic clustering and fusion using the fuzzy C-mean clustering algorithm, which is based on the evaluation indexes and training sample set. The research program on the relationship between mental health education and civics instruction is designed with the incorporation of mental health into the civics course as the starting point. Statistical analysis tools are used to analyze civics education examples that incorporate mental health education from the perspective of educational psychology. The model in this paper may successfully enhance the precision of the evaluation of the standard design of Civic and Political Education, which includes mental health education, as evidenced by its smaller RMSE and MAE of the evaluation results when compared with BP and RBF, which are 0.3151 and 0.1834, respectively. Cultural confidence appears to have a partly mediation effect between curricular citizenship and mental health since curricular civics positively impacts cultural confidence (p<0.001), and neither curricular civics nor cultural confidence is beneficial to mental health (p<0.001). The purpose of this study is to offer guidance for advancing the development and integration of political, ideological, and mental health education. College students’ overall growth in morality, intelligence, physical fitness, and aesthetics is greatly influenced by this.
Current Situation and Practical Path of Cultivating Students’ Core Literacy in the Context of the New Era
Authors: Wang Zhanfeng , Liu Yunfei
Published: January 2024

In this paper, Bayesian estimation and Coleman filtering are used to compose a multidimensional data fusion algorithm to study the cultivation of students’ personalized core literacy. A Trans E model is constructed based on the calculation of students’ specific course ratings using collaborative filtering algorithms. Combining the knowledge graph and collaborative filtering methods, the similarities between the course and user ratings are calculated respectively. The user’s rating situation can be predicted by combining similarity. Through the empirical analysis method, the overall and specific competency dimensions of students’ core literacy and the effect of core literacy cultivation, as well as students’ satisfaction, were analyzed, and the corresponding practice paths were proposed based on the analysis results. The mean value of students’ core literacy test is 46.25, and the number of students scoring between 50-60 points is the largest, but the number of excellent students is 0, which is poor in the cultivation of core literacy. The analysis of the effect of core literacy cultivation shows that in the correlation analysis of teaching effect and teaching support, the p-value is less than 0.01, but most of the correlation coefficients are less than 0.35, and there exists a weak relationship between the two, and the school authorities should strengthen the teaching support of core literacy.
Research on Hierarchical Network Security Situational Awareness Data Fusion Method in Big Data Environment
Authors: Wu Liwan , Yang Chong
Published: January 2024

With the globalization of information and the development of big data technology, people rely more and more on the network. The network brings convenience to everyone at the same time, and many security problems also come. This paper first introduces the NSSA model from different perspectives and analyzes the characteristics of its application, combined with the information fusion to put forward the H-NSSA system model, and constructs the framework of the network security posture assessment. Then, we assess the credibility of the intrusion behaviors in the network, classify and fuse the relevant evidence, and optimize the evidence conflict synthesis rules on this basis to improve the confidence of the event. The Bayesian network model is constructed by describing the causal relationship between elements using the assignment relationship model. Finally, experimental simulation and practical application analysis methods are used to study the network security situation and situation assessment, as well as the practical application of the actual situation in enterprises. The results show that the network suffered a large degree of attack in the 9th-12th time window and a medium degree of attack in the 42nd-43rd time window, and the H-NSSA algorithm model can reach asymptotic convergence in only 68 iterations, and the performance of the algorithm is high.