bluuebunny/crossref_metadata_2025_split huggingface dataset:
Innovation of Marketing Supply Chain Management Model Based on SICAS Modeling
Authors: Mao Rui , Liu Youwei , Yang Yida 
Published: February 2024

Abstract
The marketing service system is not perfect enough to highlight the competitive advantages of enterprises, and improving the marketing supply chain management mode is an inevitable trend under the change of the market economic environment. The marketing supply chain management model proposed in this paper is based on the SICAS model to respond quickly to market and customer demand. A collaborative optimization model of the supply chain based on virtual inventory management is constructed to ensure the normal operation of the whole supply chain by deploying flexible inventory in the hands of customers, and the constructed model is solved by using an evolutionary algorithm based on indexes and an optimal solution sorting method based on regret theory. The feasibility and scientificity of the proposed management model are verified by analyzing the effect of applying the management model to J and S e-commerce companies and analyzing consumer evaluation. The results show that from 2014 to 2022, the purchasing cost of J e-commerce enterprises decreased by 0.0307 as a proportion of operating income, the inventory turnover ratio increased by 0.0869, the marketing cost and logistics cost increased by 189 million yuan and 3,878 million yuan, respectively, and the supply chain cost was effectively managed. At the same time, the consumer evaluation score of the marketing supply chain management model based on SICAS model is 3.608±0.043 points; the user experience is good, to a certain extent, to enhance the competitive advantage of the enterprise.
Financial investment risk analysis and countermeasures research based on CVaR-GARCH model
Authors: Wang Yongsheng , Yu Wanrong 
Published: February 2024

Abstract
In this paper, based on the vector autoregressive algorithm, the conditional value-at-risk algorithm is used to compute the optimal portfolio, and the mean-CVaR model oriented to portfolio optimization is established based on the mean-variance model. To explain the volatility accumulation characteristics of financial asset return series, the autoregressive conditional heteroskedasticity model with CvaR is designed. After the design and optimization of the algorithm are completed, the daily closing price of a commodity futures contract, CSI 300 and the stock situation of different companies, and the daily closing index data of the financial index of a city are collected, and the three major groups of data are tested for the model of this paper. The results show that the maximum value of the CVaR-GARCH model at 95% and 90% confidence levels is generally 4000~6000, which is higher than that of the VaR model alone at 1000~2000. The difference between the actual loss and the loss predicted by the model in this paper is 88.618~279.181. The number of failures at 90% confidence level is 44. The number of failures at 95% confidence level is 31, while the number of failures at 99% confidence level is 1,000~1,000. The number of failures at 99% confidence level is 1,000~1,000. Number of times is 31. At a 99% confidence level, the number of failures is 11. This results in a generalized failure rate of 6.03%. Investors can make program adjustments with more accuracy due to the model in this paper’s ability to predict stock market risk.
Precision Management of Agricultural Products Wholesale Platform Based on Big Data Technology
Authors: Liu Xiaoxiao 
Published: February 2024

Abstract
In today’s big data-driven information technology development, the use of algorithms for platform management to achieve more accurate and efficient user services has become a trend. In this paper, from the two aspects of platform recommendation and route delivery of agricultural products wholesale, combining platform recommendation algorithms and delivery route optimization algorithms, the accurate management of the agricultural products wholesale platform is studied. Taking the dataset collected from the X agricultural products wholesale platform as the experimental sample, it can be seen by comparing the experimental results of this paper’s recommendation algorithm and the traditional collaborative filtering algorithm that this paper’s platform recommendation algorithm is more effective. Among them, the recommendation algorithm based on user similarity performs better than the recommendation algorithm based on user location in terms of accuracy, coverage, and recall, with optimal values of 36.42%, 50.84%, and 17.17%, respectively. Taking the route distribution study of 10 customers on the X agricultural products wholesale platform as an example, comparing the original planned distribution routes and the optimized routes, the total distance of the optimized routes is 84.97km, which is 21.29% less than that of the original planned routes under the condition of meeting the customer’s demand volume, distribution time and truck loading capacity, which verifies the effectiveness of the distribution route optimization algorithm. Effect validation shows that customer stickiness, relationship quality, and conversion cost are significantly correlated with platform recommendations and delivery route optimization.
Innovative Teaching of Japanese Language in Colleges and Universities with the Aid of Natural Language Processing Technology
Authors: Shi Liangliang , He Xiaoting 
Published: February 2024

Abstract
In this paper, the Japanese sentences are processed by using the participle technology for participle and syntactic analysis, on the basis of which different weight values are assigned to different Japanese sentence components, and at the same time, the optimal sentence tree searching calculation method is applied in the process of calculating the maximum semantic conformity of the discourse linkage. According to the results of Japanese sentence segmentation processing, the weights of keywords in the Japanese teaching content are set, the synonyms and near-synonyms of each keyword are found, and the binary tree with weighted paths is used to compute the similarity between Japanese interrogative sentences and Japanese title sentences. Combining natural language processing technology with Japanese language teaching, we develop an assisted Japanese language teaching system based on natural language processing technology and analyze examples of unfolding Japanese language teaching. The results show that on the basis of high-level anxiety level, the average value of Japanese language teaching based on natural language technology are the lowest, and their values are (23.57), followed by medium anxiety group (45.56), low anxiety group (68.45), based on the assisted Japanese language teaching system in order of increasing, which indicates that the lower the anxiety state of the students, the effect of the application of the assisted Japanese language teaching system based on natural language processing technology is The higher the level of anxiety. This study provides theoretical analysis and experimental basis for assisted Japanese language teaching with natural language processing technology, which is of great significance for promoting the development of innovative Japanese language teaching in colleges and universities.
Emotion Appreciation Strategy in College Music Teaching Based on Improved Multimodal RCNN
Authors: Jin Fenglin 
Published: February 2024

Abstract
People’s judgment of music emotion is highly subjective; how to quantify the music emotion characteristics is the key to solving the music emotion recognition problem. This paper utilizes the Fourier transform method to preprocess the input music sample signal. A digital filter accomplishes the pre-emphasis operation, and the number of frames in the music signal is determined by splitting and windowing through a convolution operation. By utilizing the Mel frequency cepstrum coefficient and cochlear frequency, emotional features of music can be extracted. Improve the multimodal model based on the RCNN algorithm, propose the TWC music emotion framework, and construct a music emotion recognition model that incorporates the improved multimodal RCNN. The proposed model’s impact on music emotion appreciation is evaluated through experiments to identify music emotions and an analysis of college music teaching practices that emphasize emotion appreciation. The results show that 1376 songs belonging to the category of “relaxation” are assigned to the category of “healing”, which is only 4 songs short of the target, and the labeling of the songs is not homogeneous, and the emotional recognition of the model is consistent with the cognition. The mean value of the empathy ability of college students in music emotion appreciation is 69.13, which is in the middle-upper level, indicating that the model proposed in this paper has a good effect on the cultivation of students’ music emotion appreciation.
The application of information fusion technology in the cultivation of talents in fine arts majors
Authors: Wang Zuochuan 
Published: February 2024

Abstract
In this paper, we use information fusion technology to describe the problem formalization of art major talent cultivation and obtain the similarity coefficients and probability matrices of art major talent cultivation by calculating the ability level of art majors. On this basis, the art major talent cultivation path is proposed from two aspects: the planning of the art major cultivation path and the recommendation of a personalized art major academic talent cultivation path. The data set is selected, the experimental environment is determined, and the data analysis software is used to analyze the example of the ant colony optimization algorithm-based talent cultivation path planning for fine arts majors and the CNN-based talent cultivation path recommendation for fine arts majors. The results show that the teaching effect of mastering knowledge points is poor, and the duration has a more obvious change (598s), which confirms that the ant colony optimization algorithm can optimize the teaching duration of video knowledge points according to the situation of talent cultivation path of fine arts majors. CNN, in solving the problem of recommending the talent cultivation path of fine arts majors, compares with the genetic algorithm GA (0.662) and the original ant colony algorithm ACO (0.665); the most personalized learning path recommended is not only more suitable for the user’s learning style, but also in line with the actual learning sequence, and thus can help users efficiently achieve their career goals.
Research on the application of virtual reality technology in the teaching of art sketching
Authors: Tan Zongbin 
Published: February 2024

Abstract
In this paper, we use Bayesian model to calculate color probability, train Bayesian classifier using a skin color training set of different gestures, and realize full skin color foreground object segmentation. The rendering of depth texture is established throughout to realize the unified scene rendering of art sketching teaching space and combined with a deep convolutional neural network to realize the interactive operation of virtual reality sketching teaching. Sampled students of T1 and T2 groups of art majors in Q College were analyzed for the acceptance of the virtual teaching scene of art sketching and explored the usability of virtual teaching of art sketching. Analyze and test the application effect of virtual teaching of art sketching from the two aspects of student’s learning motivation and the results of sketching work innovation assessment. The virtual simulation course of art sketching is designed to meet demand innovation by combining the total score of SUS and the application results. Based on the total SUS score of 62.325 for virtual teaching of art sketching, we added expert scoring data in the course design and obtained the difference between student scoring and expert scoring in terms of ease of operation, R42, and smoothness of operation and interaction, R23, which are only 0.01 and 0.06 respectively, which indicates that the virtual simulation course of art sketching should pay more attention to ease of operation and smoothness of operation. It shows that the virtual simulation course for art sketching should pay more attention to the ease of teaching and smoothness of operation and interaction.
Construction of Ideological and Political Education Innovation and Development Platform of Colleges and Universities Based on Big Data Technology under the Concept of Green Ecological Development
Authors: Hao Wenjia , Zeng Honghu , Pan Hongxu 
Published: February 2024

Abstract
This paper combines association rules and collaborative filtering algorithms to build a course recommendation method that considers personalized learning characteristics on the innovative development platform of Civic and Political Education in colleges and universities. The related algorithms in the association rules are used to visualize and analyze the association of the 10 main contents of the Civic and Political courses and give the combination of the contents of the Civic and Political courses. By analyzing the mastery and interest of students on the platform, we push the combination of courses that meet the personalized needs of students according to their knowledge, ability and interest. The constructed personalized teaching platform is used in actual teaching, and the application of association rules in course analysis and personalized push function is analyzed to prove the effectiveness of the platform. The impact of the platform on teaching is evaluated by comparing the students’ performance under platform learning to that under traditional teaching. The results show that the average scores of the Civics course content of group D1 are all above 80, and the significance value of the difference between group D1 and D2 is 4.21% < less than 5%, indicating that there is an obvious achievement difference between the two groups. In the recommended course content of Student 2, the score of the combination course A4 and A7 was 8.2158, and the learning interest rating was 17.326, which was 0.769 higher than the sum of the interest ratings of the two courses alone.
Psychological Needs Analysis of Urban Tall Building Landscape Design Based on Affective Computing
Authors: Qin Wenyong 
Published: February 2024

Abstract
Landscape design is a human-centered service industry, which is bound to be improved according to the psychological needs of users. This paper starts from the graphical emotion dictionary, constructs the dictionary containing a three-part graph structure, calculates the positive and negative probability of the emotional tendency of <attribute, emotion word>, and judges the emotional extreme value of the text. According to the emotional extreme value to establish a theoretical model of implicit psychological needs of urban high-rise landscape design, combined with natural language processing and causal inference theory, to identify the causal relationship and psychological needs of the user’s emotional expression obtained, and to utilize the emotional correlation to weight the distance calculation, to ensure the relevance of the sample. Using the constructed emotional calculation model, calculate the psychological needs of users for urban high-rise landscape design, compare the emotional value of the design needs of different high-rise landscapes, and select the landscape design program that best meets the needs of users. Users’ psychological emotional needs are taken into account in the adjustment of their existing landscape design, and the impact of the improved design is evaluated. According to the findings, the landscape lake has the highest degree of aggregation for six psychological behaviors, with a degree of more than 80, and it reaches 93 when walking. Among the 21 subdivided psychological demand elements, only the quality grades of spatial sequence construction, maneuverability, and architectural involvement are other than average and poor, and the remaining 18 of them are all over good, which is a good effect of analyzing the psychological demand of users.
Parametric Modeling Applied to the Construction of a Competency Hierarchy Model for Teaching Early Childhood Gymnastics
Authors: Hao Shengli , Zhao Ling 
Published: February 2024

Abstract
The healthy development of physical quality in the growth process of young children is an important prerequisite for their happy learning, and the effective teaching of gymnastics for young children can realize the effective improvement of young children’s physical quality and various functions. This paper constructs a hierarchical structure model to assess the teaching ability of early childhood gymnastics using the hierarchical analysis method. In order to effectively analyze the degree of influence of each index in the hierarchical structure of gymnastics teaching ability of young children, the quantile regression model under the parametric model is used for verification, and the model parameters are estimated by penalized regression and two-stage regression. Taking the teachers of ten public kindergartens in S city as an example, the relevant influencing factors of the hierarchical structure model of early childhood gymnastics teaching competence were analyzed in depth. The results show that under the τ = 0.5 quartile, instructional design ability has the most significant effect on the hierarchical structure of young children’s gymnastics teaching ability, and its coefficient value fluctuates around 0.45, whereas the degree of influence of teaching research ability teaches and the coefficient estimate fluctuates between [0,0.15]. The ability to teach gymnastics to young children is related to the healthy development of young children’s physical fitness, and early childhood teachers need to strengthen their teaching-related skills with a view to better ensuring the happy growth of young children.
Construction and practical research on the model of college students’ psychology education and training based on PBL theory
Authors: Song Yingjia 
Published: February 2024

Abstract
Improving the mental health of young people is an important task in the construction of spiritual civilization in the new era. The main purpose of this paper is to construct a psychology education and training model for college students that is based on PBL theory. Then, the subjective perception of students under this teaching mode was studied through statistical analysis and significance test, and the impact of psychology education on students’ communication ability, self-efficacy and emotion regulation ability was analyzed based on the analysis. Finally, the regression analysis model was used to test the intervention effect of psychology education on students’ psychological crises and explore the influence factors of each dimension of psychology education. The results showed that the standardized regression coefficients of the dimensions of psychology education and the level of students’ mental health were −0.013, −0.155, −0.34, −0.113, and −0.022, respectively, and the significance test result of the regression equation was F=35.757, P<0.05, which indicated that psychology education had a significant effect on students’ mental health. This study holds great significance in enhancing the quality of school education and establishing a comprehensive and diverse psychology curriculum system in schools.
The application of multivariate data chain network in the design of innovation and entrepreneurship teaching and learning in colleges and universities
Authors: Yan Lijuan , Wang Yanlei 
Published: February 2024

Abstract
At present, although colleges and universities are actively exploring the construction of innovative and entrepreneurial teaching classrooms, they do not have the expected effect in practice. In this paper, based on the compressed perception technology, the complex data in the multivariate data chain network is sparsely represented, and multiple linear subsets in the data matrix are calculated by similarity. Statistical inference is used to generate the recommendation module after describing the encoding of innovation and entrepreneurship information packages in the data. Acquire the characteristics of students’ interest in innovation and entrepreneurial learning, create an interest graph module, and integrate the multi-perspective attention network to overcome the issue of recommendation bias. The analysis of teachers’ competence and students’ learning effectiveness involves the use of empirical testing methods. The results showed that among the 20 teachers, the teacher numbered 11 had a good performance with a competency of 0.8632 on entrepreneurship resources. The students’ 4 dimensions of innovation and entrepreneurship competence improved by more than 2 points, and the standard deviation was within the acceptable range. In the effect of the teaching model application, the mean value of students’ scores after improvement is more than 28. Teachers’ competence and students’ innovation and entrepreneurship ability are improved according to the model constructed in this paper.
Design of Neural Network-based Intelligent Extraction Method for Key Electronic Information
Authors: Wang Boye , Yang Zi 
Published: February 2024

Abstract
At present of rapid development of information technology, it is of great practical significance to extract and analyze electronic information. This paper combines ORB features and an improved convolutional neural network, establishes ORB feature extraction by fast key point extraction and rBRIEF, and also improves the data layer, convolutional layer and loss layer of convolutional neural network to construct the information extraction network model, and images the electronic information to obtain more key information. Taking the forest resources of land M as an example for application research, remote sensing data are collected, and the research is carried out in terms of the dynamic changes of different levels of forest resource information extraction. The results can be obtained that the forests in the middle and eastern parts of Land M have a low degree of depression, with an average diameter at breast height (DBH) of less than 18 cm and a stock volume of less than 100 m3/ha, while in the western part, the degree of depression and the average diameter at breast height (DBH) are higher, and the density of the forest stands in each region is concentrated at 500-1000 plants/ha. The overall forest cover of the land showed an increasing trend from 2016 to 2020. In general, from 2019 to 2020, the area of broadleaf forests, coniferous forests, and non-forested land increased, while the area of bamboo forests decreased. Broadleaf and coniferous forests saw an increase of 14.25% and 3.11% respectively. The area of bamboo forest decreased by 15.42%. The effectiveness of the constructed method for intelligent extraction of key electronic information was verified through application analysis.