bluuebunny/crossref_metadata_2025 huggingface dataset:
An Empirical Study on Improving Mathematics Application Skills of Engineering Students Using MATLAB Tools
Authors: Yan Junna
Published: May 2024

This paper discusses the implementation and application of MATLAB tools in the teaching of engineering majors so as to improve the quality of education and students’ mathematical application ability. Using the programming and GUI graphical interface design functions of MATLAB, the method of establishing the graphical user interface of the mathematical experiment module closely links the experimental content with the practical teaching of mathematical modeling. With the help of the operation functions provided by the system, we can set the experiment parameters and design the experiment interface ourselves to deepen our intuitive understanding of the mathematical content learned. After the pilot teaching in the mechanism major of University Z, 22 individuals failed to reach course objective 1, and 40 individuals were unable to reach course objective 2. The number of individuals passing the three lab reports increased continuously, from 40 to 57 in Class 1 and from 34 to 56 in Class 2. The math scores in the three exams improved significantly, and the distribution of the scores went from concentrating on scores below 60 to focusing on scores between 70–89. As a result, the teaching method for MATLAB tools application was effective.
Quantification of ecosystem service value and its guidance to land use strategy in Loess Plateau region: A case study of Qingyang City
Authors: Yang Yongchong , Bai Tieyan
Published: May 2024

Alterations in land use strategies significantly influence regional sustainable development, affecting ecosystem service functions, surface energy balance, and biodiversity. This study explores the impact of ecosystem service values on land use within Qingyang City, situated in the Loess Plateau. We employ an index system to assess ecosystem services at the Loess Plateau across four dimensions—supply, regulation, culture, and support. Utilizing physical and ecological value equivalent factors, we quantify these indices and the value of Qingyang City’s ecological service system. Specifically, the ecosystem equivalent factors for sloped cropland and terraced fields in Qingyang City are quantified as 1.1545 and 1.9788, respectively. Our findings reveal that ecosystem services significantly influence land use; notably, cropland and grassland, which collectively provide approximately 98% of climate regulation services, have experienced a reduction in their total climate regulation capacity by −14.19% and −9.42%, respectively, from 2010 to 2020. This reduction highlights a marked weakening in the climate regulatory capabilities of these land types, underscoring the need for Qingyang City to reassess and adjust its land use strategies to enhance the climate regulation service capacities of cropland and grassland.
Research on Graphic Visual Communication Design for User Perception Experience
Authors: Yuan Feng , Li Sen , Yang Bo , Liu Jianye
Published: May 2024

With the advancement of technologies such as big data, machine learning, and human-computer interaction, there has been a notable increase in the expectations for the perceptual experience offered by graphic visual communication design. This study builds upon existing research to define six principal layout features specific to graphic visual communication design and presents a formula for calculating these features. Employing HSV color space theory, we quantify color perception features and utilize a generative adversarial network to establish a model for generating graphic layouts. An example analysis is conducted to validate the model. Notably, except for Q3 (warm color percentage), where the significance level was not below 0.01, all other variables showed significance levels under 0.01. The seven perceptual features that emerged as most influential on user experience include cold color percentage (0.088), color contrast (0.223), color vibrancy (0.188), hierarchical richness (0.267), number of colors (0.088), number of color palettes (0.212), and number of patches (0.081). This research not only enhances the efficiency and quality of graphic visual communication design layouts but also significantly enriches the perceptual experience of users.
Reform and Effectiveness Assessment of Accounting Teaching in Colleges and Universities Based on Multi-source Data Mining
Authors: Zhang Mengwei
Published: May 2024

The growing discrepancy between the supply and demand of new accounting professionals underscores an urgent need for reform in the educational paradigms within higher education accounting programs. This paper introduces a comprehensive proposal for educational reform in accounting at the collegiate level, using ‘A school’ as a pilot site for our experimental teaching reform. Central to our methodology is the design of a multi-source data mining process, utilizing characteristics of educational information data. Employing the K-means clustering algorithm as a foundation, we further develop a Fuzzy C-Means (FCM) clustering algorithm to evaluate the impact of these pedagogical reforms. Subsequent to the reform, we collected and analyzed teaching data, establishing specific assessment metrics. The analysis, conducted via clustering, revealed significant improvements. Prior to the reform, the experimental class scored an average of 62.89, compared to the control class’s 63.05. Post-reform, the experimental class’s performance elevated to 74.57, while the control class saw a more modest increase to 65.14. This marked enhancement in the experimental class’s performance underscores the efficacy of the reform, aligning with our educational objectives, which anticipate an 80% qualification rate and a 42% excellence rate among accounting majors. This study not only advances the theoretical framework but also refines the practical approaches to cultivating accounting talent in collegiate settings. It offers valuable insights and serves as a reference for future reforms in accounting education at universities.
Research on Fuzzy Logic Approach to Cost-Benefit Analysis of Multimodal Transportation for China-Europe Liner Game
Authors: Zhang Mengmeng , Xu Maozeng
Published: May 2024

The implementation of the “Belt and Road” initiative provides unprecedented development opportunities for China-Europe liner multimodal transportation. In this paper, we constrain the cost-effectiveness of multimodal transportation between China and Europe using linear games from three perspectives: transportation cost, transportation time, and cargo time value. We also establish a cost-effective decision-making model. At the same time, a simulated annealing algorithm is introduced on the basis of a genetic algorithm, an adaptive genetic algorithm based on simulated annealing is designed to solve the model, and the optimal cost-benefit path assessment of China-Europe liner multimodal transportation is carried out based on the fuzzy logic method. Example analysis is carried out with three demands, and the advantages and disadvantages of the set of transportation route schemes are obtained. The optimal cost-effective scheme is selected as Scheme III, which has the highest scheme sticker schedule of 0.841, which verifies the feasibility of the model. The sensitivity analysis of transportation costs and transportation time shows that different transportation costs and times have certain influences on the transportation route selection of other goods. The cost-benefit analysis method for China-European liner multimodal transportation constructed in this paper provides scientific and reasonable guidance for multimodal transportation operators on path selection, which is of certain practical significance.
Construction and Optimization of Dynamic Assessment Indicators for Distribution Grid Carrying Capacity with High Proportion of Distributed Resource Connections
Authors: Zhou Zhongqiang , Wen Yuan , Jiang Dan , Deng Ruifeng , Ma Jianwei , Meng Jingrong
Published: May 2024

In this study, we evaluate the enhanced carrying capacity of the modified IEEE 33-node distribution system, which incorporates a high percentage of distributed resource (DR) integration, utilizing the whale optimization algorithm. The evaluation employs a fuzzy comprehensive evaluation (FCE) method, wherein we construct FCE indices for factors influencing the distribution network’s carrying capacity. These indices involve calculating weight coefficients and establishing an affiliation function, culminating in the output of the final fuzzy evaluation result vector. The analysis identifies three nodes—11, 18, and 31—within the IEEE 33-node system for decentralized DR installation. Based on initial scenario data, the maximum carrying capacity of the distribution network is determined to be 40.68 MW. The analysis further reveals that the utilization rate of distributed resources reaches 100% at specific times, specifically at 2:00 AM and 6:00 AM. During the 3:00 to 5:00 AM interval, both the system voltage excursion index and the composite score for distribution network losses are calculated to be low. These findings suggest the feasibility of integrating a single regional distribution network with other energy networks, thereby facilitating multi-regional resource interconnection and enhancing the flexibility of system operations. This approach offers significant implications for improving the robustness and efficiency of electrical distribution systems.
A refined decision-making method for orderly power consumption in virtual power plants considering load characteristics
Authors: Guo Hao , Yang Junhong , Wang Weirong
Published: May 2024

In recent years, electricity consumption has been increasing, while the supply of electricity is relatively lagging, and power shortages often occur. Therefore, the management of organized power consumption is an urgent task for the current power industry. Based on the characteristics of power load, this paper constructs a decision-making management framework for orderly power consumption by considering four aspects: generation, grid side, demand side, and social benefit. Through the various types of flexible load resources aggregated within the virtual power plant, it participates in regulating its power, effectively reduces the peak-valley difference, and realizes refined, orderly power consumption management. Finally, based on the multi-objective optimization model, refined decision-making for orderly power consumption with the participation of virtual power plants is constructed and compared to traditional decision-making for orderly power consumption. The results show that compared with conventional decision-making, the peak-to-valley difference is reduced by 8.7789 WM, the economic benefit of the power enterprise is improved by 228,300 yuan, and customer satisfaction is enhanced by 0.1613, which verifies the effectiveness of the decision-making method of the sequential power consumption in this paper.
Exploring the Strategies of Civic Education in Higher Vocational Colleges and Universities Based on Deep Learning
Authors: Huang Jiping
Published: May 2024

Deep learning significantly enhances Civic and Political Education in higher vocational colleges and universities by facilitating a nuanced understanding of students’ cognition of learning content, engagement in the learning process, and perceptions of the educational environment. This study involved collecting behavioral data from students in Civic and Political Education classes and applying the YOLOv5s algorithm—an advancement in deep learning networks—to extract and detect student behavioral features. Additionally, the enhanced ShuffleNetV2 algorithm was employed to classify and identify these features. Based on these methodologies, a student behavior recognition system was developed for Civics classrooms, and its practical application was evaluated. The findings indicate that the implementation of this recognition system resulted in increased classroom activity and engagement, with 70% of the participants demonstrating hand-raising and speaking behaviors. There was a statistically significant enhancement in students’ Civic learning behaviors following the system’s application in teaching (P<0.05). This study underscores the potential of digital intelligence technology to foster precise and intelligent educational practices in Civics education.
A Study of Chinese Peking Opera Arithmetic Coding in Tan Dun’s Opera Marco Polo and the Art of Mixed Sexuality
Authors: He Man , Li Ying
Published: May 2024

Opera is an important part of Western music culture. Chinese Peking Opera and Western opera are a kind of art style focusing on expressiveness. Both of them are isomorphic to a certain extent, and they are different due to cultural differences. This paper takes Tan Dun’s opera “Marco Polo,” a hybrid work of art containing elements of Chinese Peking Opera and Western Opera, as the object of study and quantitatively analyzes the artistic characteristics and expressive forms of the work by means of arithmetic coding technology of audio signals and terminology acquisition and labeling model. According to the results, there are 15 labeled Beijing Opera singing tune fields in the work and 12 labeled locations, which indicate the destinations of Marco Polo’s travel process. The feasibility of the arithmetic coding quantization method, which was employed in the study of Tan Dun’s opera Marco Polo, is confirmed by the results.
The Path of Cultivating College Students’ Sense of Social Responsibility under the IMB Model--Taking Some Private Colleges and Universities in Anhui Province as an Example
Authors: Liu Jiang
Published: May 2024

In recent years, the sense of social responsibility among college students has garnered significant scholarly interest due to its impact on individual development and its implications for national modernization and strength. This study introduces the Information-Motivation-Behavioral Skills (IMB) model as an innovative approach to fostering social responsibility in students at private colleges in Anhui Province. By employing a questionnaire, we assessed the current state of social responsibility cultivation among these students. Subsequently, an intervention study was conducted to evaluate the effectiveness of the IMB model. The intervention group received a social responsibility intervention based on the IMB model, while the control group continued with traditional methods. The findings indicate that the intervention group outperformed the control group across various dimensions—information, motivation, behavioral skills, and social responsibility behaviors. Notably, the overall sense of social responsibility in the intervention group increased by 13.13% post-intervention, which is 14.87% higher than that observed in the control group. These results suggest that the IMB model is a potent strategy for enhancing social responsibility among college students.
Regression analysis of the effect of social support on rural teachers’ willingness to stay in the profession
Authors: Du Chenglin , Sun Ning , Yu Pei
Published: May 2024

The retention of rural teachers is crucial not only for enhancing the quality of education in rural areas but also for the cultivation of talent and broader social development. This article conducts a detailed analysis of rural teachers’ willingness to remain in their positions by constructing and comparing various statistical models, including multi-level linear models and logistic regression models. Based on the results of model fitting, it specifically derives a logistic regression model that identifies the factors influencing rural teachers’ intentions to stay at the conclusion of their terms. Finally, 250 rural teachers as a survey research object, using the research method of this paper to analyze and explore. After the study, it is concluded that social support will have a significant positive impact on the willingness to stay when B = 0.121, 95% confidence interval is [0.298, 0.434], β = 0.532, t = 18.326, p < 0.001. Work pressure and working hours negatively predicted rural teachers’ willingness to stay in the profession, while social support positively predicted rural teachers’ desire to remain in the profession. The higher the level of social support, the higher the degree of recognition of rural teachers’ profession in the family, school, and society.
Evaluation of the double-cycle benefits of international engineering cooperation and the Western economy - based on the SFA methodology
Authors: Li Yanfang , Bian Yuzhu
Published: May 2024

In the era of globalization and development, international engineering cooperation is crucial to the improvement of economic efficiency in the West. This paper selects panel data from six regions in the West from 2019-2022 and selects reasonable input-output indicators and environmental variable indicators. At the first stage of the three-stage DEA model, the static measurement of Western economic efficiency is first measured using the variable scale compensation (BCC) model. The SFA model is utilized to decompose the slack variables during the first stage and adjust the input variables without affecting environmental variables. In addition, the Malmquist index model is used to analyze the efficiency of the Western economy dynamically in order to have a more comprehensive evaluation of the double-cycle efficiency of the Western economy from the perspective of dynamic and static. The results of the study show that after removing the effects of environmental factors and random errors, the average values of technical efficiency, pure technical efficiency, and scale efficiency in the third stage of all western regions have increased by 0.0175, 0.0193, and 0.0194 compared with those in the first stage, and the annual average total factor productivity index has shown a decreasing and then increasing trend. The SFA method used in the study can effectively eliminate the influence of environmental factors and random factors and evaluate the double-cycle efficiency situation of international engineering cooperation and the Western economy more comprehensively.
A Study of Systemic Financial Risk Prediction Models in the Insurance Industry
Authors: Wang Haifei , Chen Xiaoxin
Published: May 2024

The influence of the stability of the insurance industry on the strength of the financial market cannot be ignored, and the healthy and strong growth of the insurance industry plays an indispensable role in maintaining the stability of the whole society. To fully analyze the influence of the stability of the insurance industry on the strength of the financial market, this paper proposes a prediction model of systemic financial risk. The insurance industry’s systemic financial risk prediction indicators are determined based on the principle of selecting systemic risk factors and indicators. After preprocessing the collected relevant research data, relevant research variables are determined, a Logit prediction model for the systemic risk of the insurance industry is constructed, and a case study is conducted. The data show that the average value of GDP during these 21 years is 379642.64, and it reaches about 2.4 times the average value in 2023. The insurance industry’s economy grows steadily and rapidly. It reached the maximum response in the 10th period (0.04616), i.e., the development of China’s life insurance industry, which has a more obvious role in promoting the development of the economy. It is predicted that China’s financial risk in the insurance industry in the second half of 2024 will have a great probability of being in a low-risk state. Its predicted probability value is close to 1. The insurance industry’s healthy development has a positive impact on economic development, and the insurance industry’s stable development is of great importance to economic development, as evidenced by this study.
Application and Implications of Artificial Intelligence Technology in Basketball Coaching Decision Making
Authors: Wang Bingyang , HoKun Yi , Xu Hua , Huang Yufei , Niu Yonggang
Published: May 2024

The proliferation of artificial intelligence (AI) technologies is significantly enhancing the precision and efficacy of decision-making in basketball. This study focuses on players from the men’s basketball team at School A, employing AI to model their sports postures, collect athletic performance data, and analyze physiological metrics in real time. By utilizing fuzzy gray correlation analysis, the research aims to identify the factors influencing basketball game outcomes, thereby informing tactical decisions for coaches. Moreover, this paper compares the proposed analysis method with other correlation techniques to evaluate its relative superiority. The findings indicate that post-training, the serum levels of all ten athletes exceeded 400 U/L. Yet, the creatine kinase (CK) levels remained below 6.8 mmol/L, and the urine specific gravity surpassed 1.05, suggesting that the training intensity was high but within the athletes’ physiological tolerances. With a correlation coefficient of 0.4, the study confirms a positive impact of game outcomes on the coach’s tactical adaptations. This underscores the utility of integrating AI systems into basketball to facilitate timely and effective decision-making by coaches.
Analysis of Factors Influencing the Quality of Teaching Mathematics and Applied Mathematics under the Orientation of OBE Philosophy
Authors: Wei Jinling , Zhang Tiecheng
Published: May 2024

Mathematics, recognized as a foundational subject, is marked by its high level of abstraction, rigorous logic, and extensive applicability, necessitating effective reforms. This article proposes a results-based teaching model for mathematics by integrating the Outcome-Based Education (OBE) concept with fundamental mathematical principles. The study utilizes a university in GD province as a case study to implement this OBE-based teaching model. Employing factor analysis and structural equation modeling, the research explores factors influencing the quality of teaching. Descriptive and correlational analyses were conducted on the variables involved, followed by structural equation modeling to test the proposed hypotheses. The findings revealed significant positive relationships among study habits, learning ability, interest motivation, learning resistance, teaching environment, and learning environment, with correlation coefficients positive at a 0.01 confidence level. The standardized path coefficients were 0.241, 0.143, 0.255, 0.153, 0.175, and 0.124 for learning habits, learning ability, interest motivation, learning resistance, teaching environment, and learning environment, respectively. These influences significantly and positively impact the effectiveness of the mathematics teaching model, demonstrating their beneficial effects on educational outcomes.
Modeling Personalized Smart Teaching for Learner Needs
Authors: Wu Juanjuan
Published: May 2024

With the deep integration of the Internet and education, the personalized development of education has become a new trend in education, and it also increasingly emphasizes the learner’s subject position in learning. In this study, a smart teaching model for learners’ individuality is developed by integrating WEB data mining technology, SOM neural network, and multiple recommendation mechanisms. The model achieves personalized recommendations for learning resources through the collection of user characteristics and then according to the recommendation algorithm. Then, using college English courses at Zhengzhou Shengda University as an example, the SOM neural network is utilized to diagnose the teaching cognition of the experiment. The experimental results show that the SOM neural network cognitive diagnosis results in a high judgment rate, with a high judgment rate of 84.842%. It has certain feasibility in teaching small sample diagnostics. In terms of efficiency, the time of cognitive diagnosis can be controlled within 1 second, which is real-time in teaching applications. The significance test of students’ performance after the experiment shows that the personalized wisdom teaching model constructed in this paper has a significant effect on improving teaching performance.
Kinematics and biomechanics analysis of classic 24-style taijiquan
Authors: Xia Hongwu
Published: May 2024

Inheriting and promoting Taijiquan, most of the process of oral teaching and teaching by words, the lack of scientific data support, there is an urgent need to standardize the interpretation level measurement standards. In this paper, based on the high-speed infrared motion capture technology, the HelenHayes method is used to select the bony landmarks of human anatomy, establish the coordinate system, and optimize the traditional posture-solving algorithm by using Mahony to design the kinematic and biomechanical analytical model used for the movements of the classical 24-step Taijiquan. The analytical model was used to analyze the kinematics and biomechanics of a total of 6 taijiquan practitioners in both professional and amateur groups. It was finally found that the center of gravity of the taijiquan champion was 0.077, 0.080, and 0.034 during the white crane bright wing movement, and the center of gravity of the three stages of the single whip was 0.062, 0.075, and 0.059, without excessive undulating movements, and basically remained at the same height. In the four stages of the movement, the left hip joint angle of the amateur group has been deviating from the standard, with a maximum deviation of 22.98 degrees, which is significantly different from that of the professional group. This study provides a theoretical basis for the improvement, rationalization, and simplification of Taijiquan movements and scientific experimental data for the standardized teaching and training of these movements.
Research on international trade flow analysis based on potential clustering network
Authors: Yi Pan
Published: May 2024

International trade is an important part of the world economy, and the rapid development of big data and complex network theory provides the possibility of an in-depth study of international trade networks. This study constructs the international trade flow gravity model and international trade flow index system on the basis of the clustered dynamic panel gravity model. It explores the influencing factors of national trade flow and the fitting effect of the international trade gravity model through factor analysis and regression analysis of variables in the system. The sample data’s KMO value is 0.834, according to the results, and there is a significant correlation between the variables. The degree of explanation of the public factors to the original variables is more than 0.5, and the variance contribution rate of trade structure, marketized structure, population and macroeconomics, international capital, and exchange rate reaches 71.832%, which makes the factor analysis more effective. The R² value of the trade gravity model reaches 0.837, with a remarkable effect. Among the sample countries, the highest trade flow potential is the United States (125,467.0), while the lowest is Portugal (512.4). The national GDP and population have a significant effect on international trade flows. The volume of each trading country should be used as a reference basis for conducting trade transactions when conducting international trade.
Intelligent Recognition and Classification of 3D Animation Styles - Based on AIGC Technology Application
Authors: Jiang Xinqu , Sun Jian
Published: May 2024

The study of style identification in 3D animation not only enhances the artistry of animation scenes but also has a profound significance on the development of 3D animation works. In this paper, we first sorted out the art style expressions of 3D animation and explored the innovation path of 3D animation art style and related influencing factors. Based on the generative adversarial network in AIGC technology, the discriminator and generator are trained. The 3D animation style intelligent recognition and classification model is established by combining the GAN network and SoftMax classifier, and the loss function of the model is optimized. Using crawler technology to obtain 3D animation-related images and crop them to 128*128 size for dataset construction, 3D animation style recognition and classification experiments were designed to verify the application effectiveness of the 3D-GAN model. It is found that the 3D-GAN model reaches the peak of IS index 9.222 after 60*103 iterations, which is 12.85% higher than the ALGAN model. The average classification accuracy of the 3D-GAN model is 91.42%, which is 6.01 percentage points higher than that of the sub-optimal CycleGAN model. Conducting intelligent recognition and classification of 3D animation styles based on AIGC technology can provide a new direction for innovating 3D animation styles and optimizing scene design.
Stereoscopic Image Enabled Animation Art Design Exploration
Authors: Cui Baoli
Published: May 2024

With the emergence of movie art, many related art forms were born. Animation art has gained a large number of audiences due to its exaggerated expression. In order to improve the problems of character image overlapping and scene distortion that may occur in the original two-dimensional space, this paper constructs a semi-global stereo image matching algorithm based on the use of point cloud matching in the animation screen for the determination of the screen position and the morphology of the animated character. To compensate for the radiation difference in the stereo image matching algorithm, object-square geometric constraints are proposed to improve the matching cost calculation process. After calculating the matching cost, the original animation model is optimized or rebuilt by creating a depth space image. Taking Disney animation characters as an example, the number of joints required for the reconstruction of the “Snow White” character is 2.9 times more than that of the “Mickey” character, but the reconstruction time of the skeleton is only 12 times longer than that of the “Mickey” character. However, the skeleton reconstruction time is only 12.1 seconds longer than that of the “Mickey” character, which indicates that the algorithm proposed in this paper does not produce a large difference in reconstruction time due to the difference in characters. For the construction of animated indoor scenes, in the eight experimental scenes, the maximum number of grids can be divided into 42365412, and the processing time required is 276.413 seconds. It shows that the algorithm in this paper is capable of subregionally refining the indoor space of the animation. The proposed semi-global stereo image matching-based pan can quickly reconstruct animated character models and animated scenes, as can be seen.
Multi-featured Emotional Expressions in English and American Literature - Based on the Application of Thinking Operations Modeling
Authors: Cui Xiaoke
Published: May 2024

Emotional analysis of English and American literary works constitutes a significant facet of literary scholarship. This study employs a cognitive operation model for analyzing emotional expressions in English and American literature, constructing a multi-featured method for emotion recognition and analysis, which serves as the principal analytical tool of the cognitive operation model. The research involves collecting and processing textual data from English and American literary works, followed by the application of the Senti-BERT model for vectorized representation. Subsequently, a bidirectional Long Short-Term Memory (LSTM) network is used to extract emotional vectors. Furthermore, a softmax function equipped with a multi-attention mechanism facilitates the classification and recognition of emotions. The efficacy of this model was evaluated using a pertinent dataset, with four literary works selected for empirical analysis. Results indicate that the predominant emotional tone across these works is negative. Specifically, the emotion of “anger” in Charles Dickens’s “Bleak House” was predominantly observed in chapters 0-2200, with an emotion value ranging between 20-30. This study provides a robust methodological framework for dissecting the complex emotional expressions in English and American literary texts, thereby enhancing readers’ comprehension of the nuanced meanings embedded within these works.
Principles of AIGC technology and its application in new media micro-video creation
Authors: Di Juan
Published: May 2024

AIGC, as a new generation of intelligent generation technology, provides new ideas for the progress and development of the new media field. This study constructs a communication model for new media micro-video creation based on the information communication model, analyzing the communication and development of new media micro-video creation. Combining the application characteristics of AIGC technology in new media micro-video creation and the needs of new media micro-video creation, it proposes the information hiding improvement method based on the GAN model and diffusion model. It constructs the AIGC optimization system based on new media micro-video creation. The model’s application effect in new media micro-video creation is explored after it passes the performance test. The results show that the average scores of all the indicators of the sense of using experience are above 3.5, the overall average score of micro-video creation is 4.12, and the peak traffic and cumulative traffic of the works created by utilizing this method have been improved by 17,000 and 1,910,000, respectively. The efficiency and quality of micro-video creation can be enhanced by using this study as a feasible reference.
Spatial Intelligent Design and Innovation for Indoor Environment - Visualization and Analysis of Web3D Technology
Authors: Sui Lili
Published: May 2024

Along with the popularization and expanding influence of Internet applications, Web 3D is born from various mature technologies driven by the demand for commercial interests in the Internet. This study designs an interactive intelligent design method for indoor environment space based on Web 3D, which has cross-platform and high-performance graphic drawing capability and covers indoor lighting material transformation, smooth switching of viewpoints, zooming of areas, and other interactive modes. It has cross-platform and high-performance graphic drawing capabilities and covers indoor lighting material change, smooth switching of viewpoints, area zoom, and other features. Based on the visual perception characteristics of the human eye, we obtain the user’s most realistic experience of the color of the indoor space and then construct the virtual indoor environmental space through the Web 3D system, and carry out a visual analysis of the indoor space under different materials and colors. The results show that under the visual analysis of Web 3D, the optimal distribution of color luminance values affecting the visual psychology of indoor environmental space is between 30.5 and 68.9nit, with a mean value of 49.59nit. The results can establish a favorable basis for the later indoor color configuration, which is in line with the visual characteristics of the human eye in indoor color configuration design practice.
Social Emotional Learning Modeling for Enhancement in Preschool Education
Authors: Wang Yexin , Zhang Mingyue
Published: May 2024

Social-emotional learning is an important part of young children’s overall development and has a positive effect on their social development, good emotional and moral character, and the formation of a healthy personality. This paper proposes a social-emotional learning model based on collaborative knowledge construction. It investigates the social-emotional learning ability of 50 toddlers in two large classes of X kindergarten in G city by combining the Peer Interaction Ability Scale, Emotional Understanding Test, and Interpersonal Problem Solving Test. The factors that affect social-emotional learning ability in the activities of the older class were studied to explore the enhancement of the social-emotional learning model in preschool education. The results showed that the social-emotional learning model can significantly (p<0.05) enhance the social-emotional learning level of young children in five dimensions: self-awareness, self-management, social awareness, interpersonal skills, and making responsible decisions. This study enriches the existing theoretical system of social-emotional learning and provides theoretical and practical support.
Intelligent design of cold storage room system based on low temperature process
Authors: Yang Juntong
Published: May 2024

In this study, we address the intelligent design requirements of a cold storage system by developing a monitoring module for operational oversight, setting up the requisite hardware and software operating environment, and establishing a three-dimensional digital twin-based intelligent decision-making system with the digital twin model serving as the core framework. In order to seek the best path for the operation of the refrigeration system and achieve the lowest energy consumption in the refrigeration system, the dynamic planning algorithm is used to configure the refrigeration system power-consuming equipment and analyze the energy consumption of the system unit under different θW values. For the control algorithm of the electronic expansion valve in the application of a low-temperature process in cold storage, the PID algorithm is introduced and optimized using a variable domain fuzzy control algorithm to explore the degree of system energy saving and control accuracy under the two algorithmic control methods. Under the same working conditions, the fluctuation range of the PID control effect is ± 0.8 ℃, the fluctuation range of the fuzzy PID control effect is ± 0.4 ℃, the fluctuation range of fuzzy PID control superheats is smaller, the system superheat maintenance is more stable, which is in line with the design of an intelligent system for cold storage room.
Analysis of clinical outcome risk factors in glioma
Authors: Wang Yuru
Published: May 2024

In this paper, survival curves and Cox regression models were used to form an integrated disease risk factor model. Stepwise Cox regression models using the AIC criterion and the BIC criterion were included in the comparative models, penalties were imposed on the regression parameters for variable selection, and important covariates were selected to analyze censored data so as to analyze the dependence of dichotomous outcome events and survival time on the covariates. Applying the model of this paper to investigate postoperative infection and seizure risk in glioma, the results showed that 104 strains of pathogenic bacteria were detected. Gram-positive bacteria were the most prevalent infection-causing organisms with 67 strains, with Streptococcus grass-green and Staphylococcus epidermidis being the most common. There were 34 strains (32.69%) of gram-negative bacteria, and Acinetobacter baumannii was the most common one. 3 strains (2.88%) of fungi were present. Cox regression analysis was used to screen for five independent risk factors for surgical site infections in patients undergoing glioma surgery: neutrophil ratio, lymphocyte ratio, surgical grade (III), duration of antibiotic use, and postoperative day three temperature. The presence or absence of preoperative epilepsy has an impact on the prognosis of glioma patients, with fluctuating seizures being the most common postoperative condition in patients with grade II-III gliomas, which often recur after 12 months of seizure-free epilepsy. To sum up, the findings of this report are highly instructive in determining the prognosis for glioma treatment.
Computer Simulation of Piano Tones and Design of Virtual Piano System
Authors: Zhang Yuting , Guo Anni , Pan Yu , Shi Wei
Published: May 2024

With the advancement of contemporary technology, there is an increasing demand for sophisticated tone libraries in intelligent and digital pianos. This paper introduces a virtual piano system based on timbre simulation. Drawing upon the articulation principles of the piano, a mathematical model is formulated to derive the equation governing string vibrations. This equation facilitates a comprehensive analysis of the components constituting piano timbre and establishes a model for synthesizing these timbres using a frequency envelope algorithm. The short-time Fourier transform (STFT) is utilized to extract features from the synthesized timbre and to accomplish its digital simulation. Subsequently, the integration of the piano’s timbre features with computer programming facilitates the comprehensive design of the virtual piano system. Performance testing and evaluation of the system reveal promising results: the detection rate for each musical piece exceeds 90%, with an average detection rate of 94.81% across ten pieces and an average deviation (Mean-D) of 3.35 in the scoring of 100 music samples. This research contributes to the flexibility in timbre editing, enhances the expressiveness of intelligent and digital pianos, and aims to elevate the music industry to new heights.
Analysis of the Role of Educational Policies in Promoting Educational Technological Innovation and Policy Networks
Authors: Zou Zenan
Published: May 2024

Adopting the policy network as a theoretical framework, this study constructs an educational policy network based on Roots’ theoretical model. It analyzes the roles and actions of actors within this network, as well as their interactions. Using a structural model, the research employs quantitative methods and empirical analysis to investigate the deployment of policy tools by the intergovernmental network in fostering educational technology innovation. Furthermore, this paper examines the influence of educational policies on promoting technological innovation in pedagogy through an empirical investigation of policy texts from 12 pilot zones dedicated to educational technology innovation. The results show that environment-based policy tools are used most frequently (62.67%), supply-based policy tools (24.26%), and demand-based policy tools (13.07%) are underused, and there are problems of imbalance, generalization, insufficiency, and shortsightedness in the use of tools. In the model hypotheses, performance expectations (P=0.032), enabling conditions (P=0.014), and incentive policies (P=0.009) have a significant effect on teachers’ behavioral intention to engage in 1+X pedagogical technology innovation. In summary, this paper successfully analyzes the use of policy tools in the policy network and concludes that incentive policies can drive innovation in educational technology.
Research on the Path of Improving the Parenting Ability of Teachers of Marxist Civics Classes in Colleges and Universities Based on Bidirectional Recurrent Neural Networks
Authors: Lv Feng
Published: May 2024

Drawing on the insights from the expert consultation form and the current state of parenting ability among teachers of Marxist Civics courses in higher education institutions, this paper initiates the selection of evaluation indicators for these teachers’ pedagogical skills. These indicators undergo reliability and validity testing before finalizing the evaluation system. Subsequently, the indices are quantified, and principal component analysis is employed to reduce the dimensions of these indices, resulting in an index feature matrix. The scores of these evaluation indices serve as inputs to a Bidirectional Recurrent Neural Network (BiRNN), with the comprehensive ability scores of Civics teachers as the outputs. This forms the basis for constructing a BiRNN-based evaluation model for assessing the educational capabilities of Marxist Civics course instructors in colleges and universities. The study then proceeds with an empirical analysis using this model. The results show that BiRNN (RMSE=0.0084, R=0.9948) can effectively improve the evaluation accuracy of the parenting ability of college Civics teachers, and B1 to B10 all show a significant correlation with the parenting ability (Y) of Civics teachers (Sig<0.05). The Person correlation coefficients are 0.607, 0.691, 0.472, 0.785, 0.499, 0.758, 0.437, 0.539 and 0.519 respectively. This study reveals in depth the factors influencing the parenting ability of Marxist Civics teachers, which is of great significance in promoting the enhancement of the parenting ability of Marxist Civics teachers in colleges and universities.
Display and Interaction Design of VR Technology in Environmental Design
Authors: Pang Jianbin
Published: May 2024

VR technology, with its unique interactivity and immersive environment display, has a wide range of application prospects in various industries. In this paper, starting from the display and interaction experience of users for virtual environment design, we propose the optimization experience path of virtual environment user display and interaction and build up the optimization technology framework based on this. AutoCAD modeling software is used to complete three-dimensional modeling, and a three-dimensional display technology based on dual-computer communication is proposed to display the virtual environment in three dimensions. In the interaction design aspect, the virtual hand is optimized for detecting targets and generating grasping gestures. In the application of the optimization technology framework, the hotel apartment of Yuntianlou Intercontinental Plaza in Wenzhou City, Zhejiang Province, China, was selected as the design content for the virtual environment design. In the interactive performance evaluation, the average user rating of the virtual hand interaction method is 0.42 points higher than that of the traditional mouse interaction method, and the average computing time of the interaction is only about 60ms. In the comprehensive evaluation test, the average value of the environment display and interaction experience modules is more than 4 points, which indicates excellent display and interaction experiences.
Optimisation Analysis of Enterprise Environmental Cost Accounting Based on Support Vector Machine Model
Authors: Sun Tongzhen
Published: May 2024

Environmental cost accounting, as a developing field, has been implemented in enterprises for only a brief duration, revealing several areas necessitating enhancements. This paper presents an environmental cost accounting method based on Support Vector Machines (SVM) to address the challenges posed by large and complex data sets in enterprise ecological cost accounting. The technique employs the Radial Basis Function (RBF) kernel to optimize the SVM model, derives the linear regression equation for the Least Squares SVM (LS-SVM) model, and preprocesses enterprise environmental cost data. It integrates Material Flow Cost Accounting (MFCA) to extract essential environmental cost-related data for enterprises. In the empirical application within a tested enterprise, the total cost attributed to resource loss amounted to 1,423,002.55 yuan, representing 4.89% of total expenses, with material costs accounting for the highest share at 86.35%. The analysis suggests that enterprises should prioritize monitoring and managing material costs to minimize resource wastage. Regarding the accounting for external environmental damage, sulfur dioxide and fluoride emissions from material quantity center 1 were identified as the predominant pollutants, exceeding 90% of emissions. This highlights the need for targeted energy-saving and emission-reduction measures for these pollutants to mitigate their environmental impact.