bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on the current situation and countermeasures of student employment management in higher education institutions based on multiple regression analysis
Authors: Shi Jirui 
Published: September 2023

Abstract
Employment management in higher education institutions has an important influence on the employment situation of graduates, and this study aims to give corresponding countermeasures by analyzing the current situation of employment management. This paper investigates and studies the employment situation and the perceptions of employment management of graduates from higher education institutions and obtains relevant data on employment and employment management. The correlation between career guidance courses, career guidance methods and career guidance websites and graduates’ employment rate is analyzed using multiple regression methods to develop countermeasures for employment management optimization. The regression coefficients of professional construction, ideological construction and psychological counseling of career guidance courses on their comprehensive evaluation were 0.1654, 0.0872 and −0.0475, respectively. The regression coefficients of the three influencing factors on the comprehensive evaluation of the career guidance website were 0.7485, −0.0213 and 0.1457. the regression coefficients of the three influencing factors on the comprehensive evaluation of career guidance methods were 0.7485, −0.0213 and 0.1457. The multiple regression models achieved good significance. Based on the multiple regression analysis, the key factors of employment management in higher education institutions were clarified by data modeling methods, which helped to better propose countermeasures for employment management.
Research on the influence factors of innovation and entrepreneurship education based on neural network model
Authors: Wang Peng , Dong Keping 
Published: September 2023

Abstract
This paper selects the evaluation indexes that fit with the teaching mode and evaluation objectives of university innovation and entrepreneurship education in the new media environment. The limitations of the existing evaluation indexes are analyzed and combined with the characteristics of students’ physical and mental development and cognitive level; the indexes are screened and integrated, and a new evaluation system is constructed. Based on the improved particle swarm algorithm, the BP neural network is optimized to establish the evaluation model of students’ innovation ability and improve the defects of the particle swarm algorithm, covering the selection of the network topology, the number of neurons in each layer, the setting of the parameters of the improved particle swarm algorithm, and the dynamic adjustment of the weights and thresholds, so as to build the evaluation model. Analyzing the influencing factors of college innovation and entrepreneurship education in terms of college factors and individual factors, 45.7% of students want college innovation and entrepreneurship education courses to focus on entrepreneurial opportunities or environment analysis in the teaching process, 41.4% of students feel average in terms of teaching resources, and more than 50% of college students are conservative in the direction of employment or entrepreneurship in terms of personal factors. Comprehensive analysis shows that the influencing factors, such as inflexible teaching methods, unsound curriculum systems, imperfect practice platforms, and college students’ own ideological awareness, are very significant and worth noting.
Deep learning algorithms in enterprise accounting management analysis
Authors: Zhou Xuemei 
Published: September 2023

Abstract
This paper first constructs two accounting management prediction models. The first one is the CNN-GRU model, in which samples are input to the CNN model for extracting high-level abstract features by convolution and pooling and then input to the GRU model to train time-series potential features. The other is the CNN+GRU fusion model, where both CNN and GRU models are Merge fused, and the abstract features extracted from the two models trained separately are stitched together and then trained together. Then, through experimental comparison with other machine and deep learning methods, the two models developed in this study er on every evaluation index. The CNN+GRU Finally, the index system of accounting management is established, including seven categories of indicators reflecting the characteristics of the enterprise, which are divided into 23 secondary indicators, and the prediction of the enterprise accounting management of ST Boyuan in 2013 and 2014 is made by using the obtained deep learning. The results show that: the judgment rate of the enterprises in the year before the crisis is higher than that of the enterprises in the two years before the crisis, but both reach more than 90%, and the overall prediction accuracy rate reaches 95%, indicating that using deep learning for accounting management prediction can achieve very good results. The research results of this study help the enterprises’ internal management and thus have a guiding influence on their economic development.
Optimisation of an integrated water resources management system for the Yellow River based on numerical simulation
Authors: Fei Yihan , Chen Lu 
Published: September 2023

Abstract
With the development of digital information technology, the requirements for information technology in the management of the Yellow River are gradually increasing, and the application of information technology in the various operations of the Yellow River system is becoming more and more extensive. This paper firstly attempts to conduct an integrated study of the Yellow River water resources management system, integrating various business systems for water resources management and realizing the sharing of resources and information. Secondly, through numerical simulation, a numerical prediction model of water resources based on coupled atmosphere-hydrology-sediment environment and a numerical simulation system of hydrology-sediment is constructed to optimize the system of integrated water resources information and management of the Yellow River basin. Finally, the system is applied to the Yellow River basin, and its rationality is tested. The results show that in the dynamic water resources deployment experiment, the water resources utilization efficiency is 87.0%, which is 8.8% more efficient compared to the water resources system deployment before optimization, and the joint probability constraint and water resources utilization efficiency in the case are 0.01 and 79.6% respectively. In this paper, the system optimization of the integrated water resources management system of the Yellow River based on numerical simulation has improved the accuracy and real-time performance of water resources management, as well as the efficiency of water resources utilization, completing the integration and optimization of the integrated water resources management system of the Yellow River.
Analysis of the packaging characteristics of creative products in the context of new media based on Bayesian networks
Authors: Xie Lingyun , Li Beibei 
Published: September 2023

Abstract
Clarifying the features of the packaging of cultural and creative products is beneficial to out-of-the-loop cultural and creative products. In this paper, starting from probability theory, graph theory and information theory principles, we combine Bayesian network structure and feature selection theory to construct a feature extraction model for cultural and creative product packaging. The maximum mutual information principle is used to optimize the feature selection scoring function, and experimental analyses of execution time and performance comparisons are conducted for the BNCC-FS method. In terms of execution time, the average training time of the BNCC-FS method on the eight datasets is 4.73s, which is 14.53% and 43.44% lower compared to CC-FS and ECC-FS, respectively. In terms of performance comparison, the average HammingLoss value of the BNCC-FS method on sixteen datasets was 0.155, which was 2.52% and 10.41% lower compared to CC-FS and ECC-FS, respectively. This shows that the Bayesian network-based feature extraction method can effectively achieve feature extraction of the data and also provides a new research database for the analysis of the packaging features of cultural and creative products.
The application of friend recommendation algorithm in the design of traditional handicraft art communication platform
Authors: Wang Wenyan , Tao Peitian 
Published: September 2023

Abstract
Cultural awareness is a context in which the integration and development of traditional arts and crafts can be promoted by establishing an exchange platform. In this paper, the exchange platform is designed through the exploration of traditional handicraft art resources and the study of different classifications. The main points of the platform design and key operational processes are explored based on the analysis of the users’ needs for the traditional handicraft art platform. In response to the lack of accuracy of the traditional buddy recommendation algorithm, a buddy recommendation algorithm incorporating user interests was proposed based on big data to carve out different user preferences for traditional arts and crafts. The user interaction response rate of the platform was good, with TPS of 98.7, 137.4 and 75.6 on the sending side, service side and receiving side, respectively, in stable operation. The friend recommendation algorithm incorporating user interests can effectively dig out user groups with similar interests, which is optimized by 11.83% compared to the traditional friend recommendation algorithm. The exchange platform supported by big data, based on friend recommendations to strengthen user interaction, can effectively promote the exchange and integration of traditional handicraft arts.
Symbolic semantic design of industrial products based on Big data technology
Authors: Li Na 
Published: September 2023

Abstract
Exploring the symbolic semantic design path of industrial products is to make industrial products more compatible with the diverse emotional needs of consumers. In this paper, starting from the sentiment analysis model, the PLSA-FSVM sentiment analysis method is constructed using a probabilistic latent potential semantic analysis method and support vector machine based on the Fisher kernel. The method’s validity is verified for comparative experiments and sentiment word frequency analysis evaluation. From the comparison experiments, the ten-fold cross-average precision and recall of PLSA-FSVM were 89.18% and 88.35%, respectively, 4.15% and 2.59% higher than PLSA-SVM. From the sentiment word frequency analysis, the percentages of sentiment words such as atmosphere, practical, and worthy are 23.08%, 22.59%, and 24.72%, respectively. This shows that the PLSA-FSVM sentiment analysis method can effectively realize the sentiment analysis of industrial product evaluation, promote the symbolic semantic design to be more in line with consumers’ emotional needs, and then realize the symbolic design of industrial products to reach the meaning with shape and enjoy with meaning.
Model innovation construction of social work participation in grassroots community governance based on fuzzy comprehensive evaluation model
Authors: Hu Jiayan 
Published: September 2023

Abstract
Grass-roots community governance is a large volume in China, the “last mile” for implementing national policies, and has a special status in promoting the construction of China under the rule of law. Guided by the theory of the rule of law government, governance and good governance theory, competence-based theory and system theory, this paper constructs a model of grassroots community multi-governance. And by using the theoretical knowledge of the fuzzy comprehensive evaluation model and the Delphi method, we analyzed the factors influencing the rule of law competence of grassroots cadres and focused on constructing an index system of the grassroots cadres’ rule of law competence and establishing a multi-level evaluation model. The results show that: through the empirical analysis of the grassroots community multi-level shared governance model, the KMO values are 0.728 and 0.851, respectively, which are greater than 0.7 and pass the KMO test. The approximate chi-square values are 415.127 and 1254.23, respectively, and the significance level sig is 0.000, which passes Bart’s spherical test and has good sexual validity. The grassroots community pluralistic shared governance model proposed in this paper improves the comprehensive service capacity of urban and rural communities in China, complements the governance shortcomings at different levels, and takes multiple measures to improve the governance level of urban and rural communities China.
The Impact of Chinese Stories on the Foreign Communication of Shaanxi Local Culture Based on Deep Learning Models
Authors: Tang Yanhua 
Published: September 2023

Abstract
Exploring the influence of good Chinese storytelling on the foreign communication of local culture in Shaanxi is to develop local culture better and expand the influence of the local cultural industry in Shaanxi. In this paper, starting from deep learning neural networks, the attention mechanism is introduced by using convolutional neural networks, and the attention mechanism-based detection model for cultural information dissemination is constructed by vectorizing the data of the pre-trained model. The performance of the CNN-ATT model constructed in this paper is experimentally analyzed on two data sets. The accuracy of this paper’s model on the Ma_Dataset and CED_Dataset datasets is 96.23% and 95.21%, respectively. The best results are obtained when the convolution size is 3,4,5, and the accuracy is improved by about 4.03% compared with the convolution size of 4,5. This shows that the model of this paper can effectively analyze the influence of cultural information dissemination and also provides a research basis for the detection of the influence of telling Chinese stories on expanding the foreign communication of local culture in Shaanxi.
The role of LightGBM model in management efficiency enhancement of listed agricultural companies
Authors: Xi Xi 
Published: September 2023

Abstract
This paper first explores the principle of the the LightGBM model, which uses a gradient-based one-sided sampling GOSS procedure to sample the sample data to ensure the accuracy of the procedure in information gain evaluation. The mutually exclusive feature bundling Histogram procedure is used to bind the feature variables of the data and the Leaf-wise strategy for differential splitting to enhance the training speed of the model. Then the steps of the LightGBM procedure are discussed, using a a decision tree as the base learner, then iterative training in sequence, and greedy learning using forward distributed procedure and the original feature fetches must be identified from the bundled features to reduce the training complexity. Finally, the LightGBM procedure is associated and investigated with the other four procedures in terms of discriminative accuracy and discriminative time of the factors affecting the efficiency of enterprise management. In terms of level discrimination accuracy, the level discrimination rate of the LightGBM model is basically above 0.7, and the discrimination rate reaches 0.9 at level 6, which is better than other procedures. The discriminatory time of the LightGBM model is only 28 seconds, which is about 16 times faster than the CART model and 20 times faster than the support vector machine model.
A study of investment decision behavior based on risk analysis
Authors: Zhu Jie 
Published: September 2023

Abstract
Risk analysis of investment decision-making behavior is to improve the ability to prevent investment risks in order to guarantee the success rate of investment decisions. In this paper, the risk evaluation level is determined by calculating the correlation degree of risk indicators through the establishment of the material topology matrix, and the gray evaluation coefficients are determined by using the gray correlation analysis of the whitening weight function to construct the gray evaluation model. The risk index factors and the overall gray evaluation were analyzed by using the material topology model and the gray evaluation model. From the physical topology evaluation, the market risk correlation is −0.00825, which means the special level risk. From the grey comprehensive evaluation score, the overall evaluation score is 6.884 overall risk level is medium grade line. This shows that using the model constructed in this paper can effectively realize the risk analysis of investment decisions and provide a guidance basis for investors to take effective measures for different types of risks.
Analysis of factors influencing social responsibility in private education industry based on multimodal discourse analysis model of big data
Authors: Guo Shengqing 
Published: September 2023

Abstract
The analysis of factors influencing social responsibility in the private education industry is to promote better implementation of social responsibility in the private education industry. In this paper, a multimodal depth quantization algorithm is constructed by using a convolutional neural network and deep denoising self-coding network, and a multimodal discourse analysis model is jointly constructed based on the MDQS algorithm and multimodal semantic space. For the model constructed in this paper, quantitative analysis of the data is carried out by examples and performance evaluation experiments. From the performance evaluation, the average accuracy of the model is improved by 22.52%, 27.19% and 7.87% compared with the CCQ algorithm, SEPH algorithm and CDQ algorithm, respectively. In terms of the influencing factors, the highest frequency of the word “interest” is 20.43% and the lowest frequency of the word “culture” is 13.72%. This shows that the multimodal discourse analysis model can effectively analyze the factors influencing the fulfillment of social responsibility in the private education industry and help the private education industry to make targeted improvements to implement social responsibility.
A Markov Chain Prediction Model Based on Rural Tourism Supply and Demand Matching Governance Model from the Perspective of Cultural Tourism Integration
Authors: Xu Lingyun 
Published: September 2023

Abstract
Exploring rural tourism supply and demand matching to promote high-quality rural tourism development. In this paper, we start from the Markov chain model, use the gray GM(1,1) model to divide the state of the Markov chain model and correct the relative error for the weighted Markov chain prediction. The corrected errors are used to construct the gray-weighted Markov chain model, and the arithmetic tests and example data analysis are conducted for the model. In terms of the model accuracy, it was improved by 12.75%, 9.28%, and 7.98% compared with the ARIMA model, ES model, and W-Markov model, respectively. From the perception of supply-demand matching, four demands are in low perception, and three demands are in high perception. This indicates that the use of the gray-Markov chain model can effectively realize the analysis of rural tourism supply and demand matching and also provides theoretical support for rural tourism to realize the supply and demand matching with tourists.
An empirical analysis of the evolution of piano performance skills based on big data
Authors: Zhang Yuyu 
Published: September 2023

Abstract
The current hotspots of empirical analysis of piano performance skills mainly focus on the recognition of single notes, and there are some limitations in recognition accuracy and noise resistance performance. In this paper, to address this problem, firstly, on the basis of big data, we propose to realize the segmentation of the music section and noise section based on the single-port limit energy difference method and perform note onset and stop detection for the music section based on LMS adaptive filtering algorithm, using the musical characteristics of piano to identify the energy jumping point, which effectively improves the accuracy of note onset and stop detection and avoids the situation of missing and wrong diagnosis. Then the piano piece was played as an example, and the scientific evaluation of the piano performance skills was made based on the results of the determination of note types. The results showed that the errors of the eight notes of the piece were 0.9%, 0.30%, 0.24%, 0.28%, 0.34%, 0.11%, 0.63% and 0.28%. The correct rate of determining the types of notes in the performance technique of the music was 100%, and the error of determining all notes was controlled within 1%. This study provides a reference standard for evaluating the quality of music performance and has broad application prospects in the fields of family leisure, music tutoring, etc.
The application of communication art in tea packaging design under the modern aesthetic perspective
Authors: Wen Zhiyong 
Published: September 2023

Abstract
This paper first explores the color emotion analysis of visual communication art, using linear equations and correlations to analyze the correlation between color emotion and image color space and classifying the degree of warmth and coldness and emotional expression of various colors. Then a multi-model hybrid color emotion calculation method is proposed, using positive-negative attribute values to get color positivity-taking values, using heavy-light to get color weight-taking values, and using warm-cold to get color heat-taking values, respectively. And the global color emotion feature of the image is calculated by using the extraction algorithm of central area weighted features. Finally, the influence of visual communication art on tea packaging is analyzed in terms of graphic design, color and layout of the packaging. In terms of packaging focus, 64 people think that they should focus on the embodiment of humanistic customs and culture, 87 people think they should focus on aesthetic aesthetics, and 75 people think they should highlight the characteristics of the product. In terms of the cultural and emotional orientation of packaging, 70.9% of people think that packaging diversity is the main tendency, and 50.9% think that retro style can better reflect the cultural characteristics of tea. The art of visual communication makes tea packaging design more design and aesthetic.
Research on standardization and quantitative extraction of information of ancient building components based on BIM
Authors: Deng Hua 
Published: September 2023

Abstract
The standardization and quantitative extraction of component information are accomplished by establishing an information model of ancient buildings. Based on BIM technology, i.e., model visualization, virtual simulation and BIM-related software, this paper combines the dimensional types of components to realize the parameterization settings of components and further designs the information structure of ancient building components. The standardization rate, repetition rate, repeatability coefficient, and standardization coefficient of the components were calculated by quantitative methods, followed by the determination of standardized components and the quantitative extraction of component attribute features based on the BIM model map. Based on the standardization of the information of the five-room, nine-purlin-hipped ancient building members based on BIM, the spatial location of the ancient building members was determined with the following parameters: bucket size 32.5 mm, eaves height 2180 mm, net height 1802.8 mm, and side legs 23.1 mm. BIM application provides a new way of thinking for archiving and protecting ancient architectural data.