bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on the digital cultivation form of “double-qualified” teachers team in higher vocational colleges and universities under the perspective of industry-teaching integration
Authors: Dai Jingjing 
Published: February 2024

Abstract
The insufficiency of the training mechanism for the construction of “double-qualified” teachers in higher vocational colleges and universities restricts the high-quality development of higher vocational education in the future. This paper takes the four dimensions of digital cultivation of teachers in higher vocational colleges as the entry point, constructs a four-dimensional co-creation cultivation model of higher vocational teachers based on the UMU digital platform, and designs the cultivation process and evaluation scale of “double-qualified” teachers based on this model. Using the convenience of the digital platform, a convolutional neural network is combined with the probability matrix distribution to establish the CUPMF model to realize the personalized recommendation of digital teaching resources for higher vocational teachers. This paper uses example verification to validate the effectiveness of the four-dimensional co-creation cultivation model proposed in this paper based on teachers’ classroom performance and work evaluation. The results show that the NDCG scores of the CUPMF model range from 0.7 to 0.9, the classroom performance shows a significant difference at the 1% level before and after the development of the training model, and the content scores of the teachers’ works increase by 1.129 points, and the correlation coefficients of the dimensions and the teachers’ level of digital application are all more than 0.6. The “double-qualified” higher vocational colleges and universities in the field of industry-education fusion The digital cultivation of “double-qualified” teacher team should rely on the digital platform, establish a four-dimensional co-creation cultivation model, and provide a solid foundation for promoting the digitalization level of higher vocational teachers.
Analysis of the moderating effect of music therapy on autism in the context of big data
Authors: Zou Hongmin , He Yupeng 
Published: February 2024

Abstract
In this paper, in the process of analyzing the response of music therapeutic method to emotion regulation, eye movement data, cognitive data, and EEG signal data were collected to clarify the criteria for the selection of indicators. The wavelet transform algorithm is used to decompose the original EEG signal, extract the features of the EEG signal based on the power spectrum, and improve its coherence. The behavioral intervention for autistic children was specifically addressed through the use of Orff music therapy following the pre-investigation of the subjects. The moderating effect of the music therapy method on the children’s four-eye-relative behavior was analyzed in conjunction with the number of occurrences of the children’s target behaviors in the baseline, intervention, and tracking periods. To explore the cumulative acquisition number and generalization maintenance effects of children’s responses to medium- versus fast-speed music at different teaching sessions in conjunction with the convergence and stability values of response behaviors within the phases. The combination of the music therapy method and the Go/No-go task method was used to analyze the effect of the number of music training sessions on response inhibition in autism. The data showed that the mean of correctness of responses for the second medium-speed music instruction for subject W was 0.495. The highest mean for the three fast music instruction was 0.801. All three subjects maintained a high level of correctness during the maintenance period after the intervention was withdrawn. It has been suggested that music training has a significant impact on improving inhibitory control in children with autism.
Exploring the Teaching Reform of Middle School Ideological and Political Classroom Based on the Background of Internet
Authors: Deng Gang , Chen Qian 
Published: February 2024

Abstract
The combination of Internet technology and education will continue to promote the change of the traditional education model, and will inevitably have a far-reaching impact on the reform of the education field. The wisdom classroom vector model is used to establish a secondary school classroom for ideological and political wisdom in this paper. In the smart classroom, students can recognize facial expressions by using GAN and tripartite consistency loss function. The ANM-CFM action recognition model is formed by the combination of the adaptive normalization module and covariance matrix fusion. For the effectiveness of the intelligent classroom of secondary school ideology and politics proposed in this paper with the related classroom behavior intelligent recognition method, the validation is carried out using example data. The results show that the first 200 frames in the smart classroom are dominated by the teacher’s lecture, and the students’ hand-raising interaction moments are mainly distributed between 200 and 400 frames. At the end of the teaching experiment, the classroom engagement level of the students in the experimental class was 9.037±0.532 points, the thinking level score of the experimental class exceeded 0.5 points compared with that of the control class, and the student’s satisfaction scores for the learning environment of the smart classroom were all over 2.4 points. The adoption of smart classrooms in the background of the Internet can realize the innovative reform of secondary school ideological and political classroom teaching and provide a new guarantee for improving the level of students’ thinking literacy.
Exploration of Cultural and Creative Product Design Thinking in the Age of Artificial Intelligence
Authors: Zhang Shanlin 
Published: February 2024

Abstract
In this paper, we use the inference rules and reasoning rules in the shape grammar to extract the elements of the cultural and creative product design, obtain the graphical elements of the cultural and creative product, import the determined graphical elements of the cultural and creative product of the inference object into Illustrator, use the pen tool to outline the morphological curves of the ornaments into paths, and at the same time organize the outlined morphological curves into the gallery. Aiming at the problem that it is difficult to obtain the optimal cultural and creative product design works in the cultural and creative product design based on shape grammar and using genetic algorithm to optimize the cultural and creative product design model. The optimization model of cultural and creative product design is empirically analyzed using simulation analysis based on research data and parameter settings. The results show that the scaling values (tx

d

1, tx

d

2) of the first layer in the optimal design parameters of the cultural and creative products are approximated to be the maximum value, and the optimal solutions in the samples are (3.61, 0.437) and (3.61, 0.268), respectively, which confirms that the optimization model of the cultural and creative product design can provide theoretical knowledge and reference value for the research of the cultural and creative product design.
An innovative development model for combining visual communication and art design based on the integration of multilevel features
Authors: Zhang Yanli 
Published: February 2024

Abstract
Art design for visual communication is an innovative model that combines art, design and communication, aiming to present artworks through visual elements and design principles. This paper utilizes level 5 features extracted from pillar networks as a rough unimodal feature to extract saliency targets in art design images. Improving their performance can be achieved by cascading different unimodal features. Design the multi-branch group fusion module, which is divided into multi- and single-branch fusion branches according to the number of groups to extract different numbers of image features. Determine the classification of art images by their original and stroke information features. Design a quantitative analysis scheme for image data to analyze the role of art design from the perspective of RGB, HSV, and image visual information communication effect. In the image HSV analysis, the hue distribution region of the sample original image is mainly concentrated in [0,0.1] and [0.5,0.6], the distribution is more concentrated, and 1/3 of the maximum value of the saturation is under 0.8, which shows the visual characteristics mainly through the hue component. A better communication effect can be attributed to the mean value of the color conciseness score reaching 4.212 in the image visual communication effect.
Innovative Research on the Quality Evaluation Method of English Translation Teaching in Colleges and Universities Based on Neural Network Modeling
Authors: Dou Weiwei , Yang Kaiye 
Published: February 2024

Abstract
This paper presents BP neural network as an evaluation tool for English translation instruction in colleges and universities. It does this by analyzing and combing the structure of BP neural networks, combining the five first-level indices with the assessment of indexes data preprocessing method, and building an evaluation system based on BP neural networks. We get sample data for the teaching quality assessment indexes based on the example teaching, evaluate it, and confirm that the BP neural network is feasible to use in the evaluation model. Two randomly selected college English language teaching classrooms are used as an example for the class, and the teaching quality rating method is utilized and analyzed. The teaching quality evaluation system’s findings are used to investigate the influencing factors that affect the quality of English translation teaching in higher education institutions. The teaching effect is also discussed about the impact of course time and content arrangements. According to the analysis, the English translation teaching evaluation index system built around the BP neural network model has a substantial amount of credibility because Kendall’s harmony coefficient W = 0.756 χ
2 = 7.687 χ
2 (p − 0.025) = 7.249 indicates that the consistency credibility of the instructional quality evaluation system goes to the test at a significant level of P = 0.025 and the opinions are very uniform.
Optimization of Color Matching and Conveyance of Picture Information in Chinese Oil Painting under the Background of Big Data
Authors: Jia Changjuan 
Published: February 2024

Abstract
Color, as the first element affecting human vision, is particularly important in the process of oil painting art creation. This paper constructs a color-matching optimization algorithm using convolutional neural network and generative adversarial network algorithms to optimize the four optimization factors of Chinese oil painting: color brightness, hue, contrast and orderliness. Color beauty is used to measure the color matching and design effect of Chinese oil paintings, and the order factor and complexity factor between each color of the color matching scheme are calculated. Finally, the effectiveness of the color matching optimization scheme is verified by taking the Chinese oil painting ‘Eight Nine Geese Coming’ as the research object. The results show that the harmonies of the four color-matching optimization schemes are 3.53, 2.86, 3.43 and 2.34, respectively, with an overall average improvement of 5.1175 percentage points compared with that before optimization. The color matching of Chinese oil paintings is based on a theoretical basis provided by this study, and it also introduces a new line of thought.
Modeling Research on Quality Evaluation of Talent Cultivation for Industry-Teaching Integration in College Education Based on IPO Modeling
Authors: Liu Xuhao , Wang Jiali 
Published: February 2024

Abstract
The rapid development of the economy makes the social requirements for talent rise, and exploring the quality evaluation of talent cultivation in the integration of university education and industry has become a topic worthy of in-depth study. This paper is based on the IPO model for the construction of a university education industry-teaching integration talent cultivation quality evaluation index system and utilizes CRITIC analysis method to calculate the index weights of the talent cultivation quality evaluation system. The GRA-TOPSIS evaluation model was established by combining the gray correlation analysis method with the ideal sorting TOPSIS method to realize the comprehensive evaluation of the quality of talent cultivation for the integration of education and industry in colleges and universities. To further explore the obstacle factors that hinder the development of talent cultivation quality of university industry-teaching integration, the data were quantitatively analyzed by using the diagnostic model of obstacle factors. The results show that in the evaluation of talent cultivation quality, the weight value of teaching and training is 0.1449, and the relative proximity of talent cultivation quality of colleges and universities has increased by 18.36% from 2015 to 2022, and the obstacle degree of the construction of training bases to the quality of talent cultivation of university-industry-teaching integration has reached 49.93%. The improvement of talent cultivation quality of university industry-industry integration needs to fully implement the strategy of university-enterprise cooperation based on student’s needs and provide more practical training bases to enhance students’ practical ability.
A Practical Approach to the Reform of “Three Teachings” in the Age of Digitalization to Promote the High-Quality Development of Higher Vocational Education
Authors: Cao Wei 
Published: February 2024

Abstract
It has become difficult for conventional higher vocational education to fulfill the needs of the digital era, and reforming the “three teachings” is now a crucial decision to promote the high-quality expansion of higher vocational education. Promoting the high-quality development of higher vocational education by adopting a practical approach to reforming the “Three Teachings” in the age of digitalization. In a composite system model, the sequence parameters for the higher vocational school subsystem are determined by the sequence parameters of the ‘Three Teachings’ reform. The TOPSIS method and Moran’s I were used to assess the rate of growth of China’s higher vocational school system to look into the main factors that have contributeds to the good development of higher vocational education in that nation. The results show that there is weak geographical clustering, with each region’s 2022 Moran’s I for the “Three Teachings” reform and the high-quality development of higher vocational education being just 0.1280. Moreover, Moran’s I show a general downward trend from 2013 to 2022, suggesting that challenges need to be addressed to keep improving higher vocational education in a top-notch way. The ‘Three Teachings’ reform strategy presented in this study may help further sustain the long-term, high-quality expansion of higher vocational education.
Research on Computer Network Security Vulnerabilities and Encryption Technology in Cloud Computing Environment
Authors: Peng Peng 
Published: February 2024

Abstract
Inadequate network security defense measures threaten the information and property security of the state and the public, and how to safeguard network security is of vital practical significance. This paper proposes a dynamic security threat assessment model and a robust optimal control strategy to improve the efficiency of detecting network vulnerabilities and the accuracy of detecting network threats in a cloud computing environment. It also protects the privacy of the user's identity through a multi-factor continuous authentication method, encrypts and protects the user's data using a homomorphic encryption algorithm, and strengthens the ability of computers to resist intrusion. Three case studies are conducted to verify the effectiveness of the proposed technical approach: dynamic assessment of security threats, control policy, authentication, and network encryption. The results show that in the network vulnerability control policy and authentication case study, when adding the control policy Tk
= 40, the percentage of network normal nodes, malicious nodes and restorer nodes are 0.98, 0.02, and 0.009, respectively, and the encrypted plaintext ASCII value is distributed in [0,60] in an unordered manner, and the network is in a very desirable security state. Real-time accurate assessments of network security state can be provided by cloud computing-based network security vulnerability and encryption technology.
Research on the application of digital media technology in dynamic visual communication design
Authors: Zhang Wendi , Shao Lin , Wang Xinmin 
Published: February 2024

Abstract
With the continuous development and improvement of digital media technology, its position in dynamic visual design is also increasing. In this paper, we first combine LCEOPaCH algorithm to extract color features from visual images, use local energy pointing mode to get image color transformation information, optimize the dynamic visual measurement method based on dynamic binocular reconstruction, and construct a dynamic visual communication model combined with visual SLAM. Through the empirical data of the visual communication system, the localization accuracy of different methods in dynamic environments is compared based on the root mean square error value of absolute trajectory error in dynamic datasets A, B, and C. The quantization results of this paper’s algorithm under dynamic visual measurement analysis and color feature extraction data comparison in 6 sets of simulated images, the PSNR value is higher than 30, and the average value of PSNR is as high as 38.11 under 24 feature colors. The SSIM value for 8 feature colors is higher than 0.75 in the same quantization. The study demonstrates the advantages of digital media technology in visual communication design and provides practical design ideas.
Analysis of public resource allocation model based on BP neural network
Authors: Yang Maolin 
Published: February 2024

Abstract
Accelerating the rational allocation and optimal integration of urban public resources plays an extremely important role in national and regional development. Based on the public resource allocation model of BP optimization and the analysis method of public resource allocation efficiency, this paper, on the basis of constructing the indicators of the public resource allocation model, calculates and analyzes the data of each indicator from 2012 to 2020 of four cities A, B, C and D in Z, to test the validity of the constructed model and to derive the efficiency of public resource allocation of these four cities. Lastly, the Tobit regression model is employed to explore the factors that influence public resource allocation. In terms of public resource allocation efficiency, 2017, 2018 and 2019 are the concentrated years in which the public resource allocation of the four cities reaches the effective value of 1. The average value of the public resource allocation efficiency of the four cities from 2012 to 2020 is around 0.9, which does not reach the effective value of 1, and the overall allocation efficiency is low. Among the 24 selected influencing factors, 20 influencing factors have a positive effect on public resource allocation efficiency, accounting for 83.3%, of which 11 factors have a significant effect, satisfying P < 0.1.
Research on photovoltaic energy storage unit charge state detection method based on improved limit learning machine
Authors: Ma Xue , Li Fang , Li Xiantao , Ying Zhiping , Gong Siyu , Xiao Yu 
Published: February 2024

Abstract
In order to accurately detect the photovoltaic energy storage unit charge state, this paper selects the parameter charge state as the detection quantity in the equivalent model, establishes the PSO-ELM method to detect the charge state of photovoltaic energy storage unit, optimizes the limit learning machine network using the particle swarm optimization algorithm, and improves the problems such as redundancy of neurons in the implicit layer of the limit learning machine and the poor ability to identify the unknown input parameter, so as to increase the detection accuracy of the PSO-ELM method to improve the detection accuracy of photovoltaic energy storage unit charge state. The relative error between the method established in this paper and the results of the PV storage unit charge state detected by the definition method in the charging state is kept within ±1.9%, and the detection accuracy of the improved method in the dynamic working condition can reach about 97%. The PSO-ELM method established in this paper can accurately detect the charge state of PV energy storage units under various conditions, as demonstrated experimentally.
Optimization and innovation of enterprise finance and accounting supervision system under big data technology
Authors: Liu Guohua , Wang Xiaoyan , Wang Luhui 
Published: February 2024

Abstract
With the continuous development of the social economy, financial and accounting risk control and early warning have become an important part of the sustainable development of enterprises. This paper combines the C4.5 decision tree and Benford law-based random forest audit warning model by constructing enterprise financial risk assessment indicators and audit warning indicators, calculates the indicator data of 100 companies to get the financial risk assessment rule set, and validates it with the financial data of Company A in 2018-2020 as a sample. Our method of obtaining the audit warning interval for 8 indicators and validating it is by using Company B’s indicator data from 2019-2020 as a sample. The assessment results are ‘yes’ when company A is used as an example for empirical analysis, confirming the accuracy of the financial risk assessment model. Early warning intervals are obtained from the Random Forest audit early warning model, in which accounts receivable ledger balance X1 > 5.72, accounts receivable aging X7 > 33.14, accounts payable aging X8 > 4.76, and provision for bad debts X9 > 14.10. The result of the test in the fourth quarter of 2019 for Company B is an early warning status with a probability of 73%. The warning interval is triggered by four indicators, which include the accounts receivable ledger balance X1, accounts receivable aging X7, accounts payable aging X8, and bad debt provision X9.
Effective Application of Smart Logistics Technology in Rural E-commerce Logistics Distribution
Authors: Wei Wenji 
Published: February 2024

Abstract
With the continuous development of smart logistics technology, the status of rural e-commerce logistics and distribution has also increased. This paper combines the intelligent logistics technology framework based on rural e-commerce logistics distribution situation, the selection of rural e-commerce distribution node sites, and distribution path optimization. Furthermore, construct a game model for the rural e-commerce logistics and distribution industry chain with the goal of generating synergy. We examine the traditional rural e-commerce logistics and distribution scheme, distribution node setting, and benefits game based on this basis. The results show that the total cost of the smart logistics distribution program is reduced by 200.7 compared with the traditional distribution program, and the total cost of the smart logistics distribution program saves 5% compared with the traditional distribution program. The average transportation time of smart logistics distribution is 11.22min, which is significantly reduced compared with traditional logistics distribution. The rural smart logistics distribution system for e-commerce that uses benefit sharing and cost sharing profit 1242 is the best program when comparing benefits. To sum up, smart logistics technology plays a significant role in rural e-commerce logistics distribution, which can effectively save logistics distribution costs and enhance distribution efficiency.