bluuebunny/crossref_metadata_2025_split huggingface dataset:
Path analysis of tourism contributing to rural revitalization by combining elastic regression network algorithm
Authors: Zheng Chengkang 
Published: January 2024

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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.
Construction of personalized learning service system based on deep learning and knowledge graph
Authors: Huang Min , Xu Gaojian , Li Huilin 
Published: January 2024

Abstract
With the development of information technology, it is difficult for people to find effective information from the massive Internet information, and personalized services are in short supply. This paper explores the essential association between knowledge graphs and deep learning and examines the construction process of knowledge graphs. Based on the content and collaborative filtering recommendation method, the theoretical method of personalized learning service recommendation is being studied. Knowledge graphs are introduced in collaborative filtering to accurately portray user and item vector representations. The knowledge graph is used to represent the TransR model, forming an entity space and a multivariate relationship space. The students’ demand for personalized learning service systems is analyzed from the user’s point of view, the personalized learning service system is constructed, and the accuracy of the personalized learning service system constructed in this paper is analyzed. The accuracy rate of DLKG is 0.1425 when K=10, which is the highest among the five models. In the effect of personalized teaching, the mean value of the metacognitive ability of the students in the experimental class is higher than that of the control class by 0.4155, 0.0261, 0.3995, 0.7967, respectively, and the experiment proves that the personalized learning service system based on the DLKG model proposed in this paper is more effective.
Application of Blockchain Based on Fabric Consensus Network Model in Secure Encryption of Educational Information
Authors: Yuan Bo , Wu Faguo 
Published: January 2024

Abstract
This paper combines blockchain technology with an information encryption algorithm to design a blockchain-based educational information protection model. It focuses on the role of Fabric architecture and blockchain data structure for information security protection. A chaotic cipher is used to encrypt the information, combined with the iteration of nonlinear functions to generate pseudo-random numbers to realize the unpredictability of the information. Using symbolic dynamics to obtain the control parameter or initial value of the chaotic mapping, combining the sequence of symbols to solve for another value, and finally presenting it in the form of ciphertext in the client for the data accessor to query and access the data. The effectiveness and practicality of educational information security encryption are examined by applying the model of constructed information protection. The results show that the response time of the blockchain module changes depending on the information, and the response time is basically maintained between 2.2 seconds and 2.4 seconds, which is in a reasonable range. In educational information security defense, the information protection model is able to effectively defend the network against attacks, with the highest number of attacks against the attack named external, with the highest number close to 50 million.
Quantitative Evaluation of Domestic Cultural and Tourism Integration Policies Based on PMC Index Modeling
Authors: Xia Yu 
Published: January 2024

Abstract
This paper constructs a text mining and quantitative evaluation model for cultural and tourism integration policies based on LDA and PMC index models. We find research samples of cultural and tourism integration policies through relevant websites and databases and use the LDA model to mine high-frequency words in the policies and make a high-frequency glossary. The quantitative evaluation index system of cultural and tourism policies is constructed according to the glossary and the definitions of policy evaluation by authoritative scholars, and then the scores of each policy are calculated based on the PMC formula, and the PCM surface diagram is drawn for quantitative evaluation. The results show that 57.14% of the 63 policies belong to the excellent level, and most of the policies have high scores in terms of policy timeliness, subject, tool, field, evaluation, and function, ranging from 0.5 to 0.8. Thirteen policies were poorly rated in terms of policy nature, with only 0.333-05, and there is much room for improvement. Based on the results of the study, an optimization concept focusing on optimizing the nature of policies is proposed to improve the problems existing in the current policy formulation of cultural tourism integration.
A Study on the Evolution of Sculpture Cultural Communication Methods and Public Art Forms Applying the Hierarchical Analysis Approach
Authors: Hu Weiguo , Liu Yaoqi 
Published: January 2024

Abstract
Based on hierarchical analysis, this paper constructs a model for evaluating the effect of sculpture culture dissemination, sculpture culture dissemination mode and evolution of public art form, and for the defects of hierarchical analysis, it constructs a complementary matrix by using fuzzy comprehensive evaluation method, and uses the scale method of 0.1-0.9 instead of 1-9 to optimize the performance of the model. This model is used to analyze the dissemination mode and dissemination driving mechanism of sculpture culture based on the model to analyze the dissemination mode and dissemination driving mechanism of sculpture culture, explore the influence of sculpture culture and cultural dissemination mode on the evolution of public art forms, and measure the mutual influence of high and low popularity sculpture culture in the dissemination process. The results show that public art forms, books, and public buildings have the highest frequency of dissemination of sculpture culture, with dissemination indexes above 0.65. Sculpture culture change has a promotion effect on art form evolution. The sculpture culture change index is 1, 1.2, 1.4, 1.6, respectively, and the probability of the evolution of public art form when the time node is 1 is 0.58, 0.65, 0.7, 0.78, respectively. The study provides a positive reference value for the study of spreading sculpture culture and developing public art.
Research on Physical Education Teaching Mode in Colleges and Universities Based on VR Technology
Authors: Kong Dezhi , Zhang Aoyao 
Published: January 2024

Abstract
This paper utilizes VR technology to construct a virtual sports training situation and proposes a sports training feedback teaching mode based on VR technology. Aiming at the VR high-resolution scene generation technology, it analyzes the image super-resolution recovery algorithm based on multi-frames, introduces the regularization solution method, and, on this basis, proposes a generalized entropy variational image super-resolution recovery algorithm to realize better VR panoramic visual teaching. Taking Taekwondo movement training in K-school as the research content, we compared the learning attitude change, the influence of special physical quality, and the technical mastery ability of Taekwondo movement between the experimental group and the control group. The evaluation results found that the technical score of movement completion ability after the experiment was 94.98±2.36 in the experimental group and 85.79±5.32 in the control group. The quality of physical education teaching can be improved by using VR technology in teaching mode.
Research on the Differentiation of Tourist Flow Network of Different Tourist Attractions in the Region
Authors: Zhang Yun 
Published: January 2024

Abstract
Tourist flow research is an important part of tourism research, providing the basis for the development of tourism. This paper takes different scenic spots in nine regions of M as the research object, takes social network analysis as the primary research method, and evaluates the node and overall network structure characteristics of tourist flow in M through the social node and overall network structure indicators. Using the “Octopus Collector” software to collect data, integrating 685 online travelogues about this region on the platform of related tourism websites, and using related software to process and analyze the data, it is found that there is a great deal of variability between different tourist attractions in M. From the viewpoint of node network structure, M1 scenic spot is in the center position between M tourist attractions, and among the 38 different scenic spots investigated in M area, there are only 6 attractions with extremely strong competitiveness, which can play the role of guiding the flow direction of tourist streams, and the others basically rely on the driving of the tourist volume of these tourist nodes in order to develop. From the overall network structure, the outward value, inward value, outward value and inward value close to the center potential of the degree center potential in the tourist flow network of M is greater than 30%, the overall scenic nodes of M are not closely connected, and the difference between the core scenic spots and the marginal scenic spots in terms of tourist flow is large.