bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research and optimization of cross-border e-commerce logistics model based on big data technology
Authors: Liu Qian , Yao Xuesong , Pei Lei , Lin Mei 
Published: December 2024

Abstract
Cross-border e-commerce is a powerful embodiment of the digital development of foreign trade transactions, but the cross-border logistics model constrains the development of cross-border e-commerce. The article outlines the cross-border e-commerce business process and proposes a smart logistics system for cross-border e-commerce that combines blockchain technology. The transportation cost, cargo damage cost, penalty cost, distribution center cost and information technology cost of cross-border e-commerce logistics transportation are taken as the objective function to construct a logistics distribution path optimization model. Then a genetic algorithm is introduced to solve the model and obtain a cost-effective cross-border e-commerce logistics distribution path optimization scheme. The optimal transportation time obtained in the simulation of the GA algorithm-solving model is only 34.76h, and the total distribution cost of the optimal distribution scheme obtained by the model after 160 iterations is 1068.7 yuan. The cross-border e-commerce logistics path optimization model can obtain the optimal logistics and distribution scheme under the consideration of time window constraints, and combined with the verification of the intelligent logistics system, it can be seen that the total logistics and distribution cost of 10 customers in the distribution area is 10956.02 yuan. The optimization of the cross-border e-commerce logistics model can be realized based on big data technology and blockchain technology, which lay the foundation for high-quality cooperation and the development of international foreign trade transactions.
Exploring and Practicing the Integration of Scientist Spirit into the Cultivation of Young Scientific and Technological Talents in the Era of Big Data
Authors: Tu Shengxue 
Published: December 2024

Abstract
The spirit of a scientist carries rich connotations and important values of the times. The study focuses on integrating the spirit of scientists into the cultivation of young scientific and technological talents. For the cultivation of young scientific and technological talents, relevant input and output indicators are selected and screened using the GRA model, and then the cultivation of young scientific and technological talents in a certain place is taken as an example to be empirically analyzed by combining the DEA model. On this basis, the conceptual model framework of scientists’ spirit and young scientific and technological talent cultivation is constructed; research hypotheses are put forward; and the PLS-SEM model is applied to verify the hypotheses and explore the influence of scientists’ spirit on young scientific and technological talent cultivation. The comprehensive efficiency value of the sample’s young scientific and technological talent cultivation is 0.716, placing it in the upper middle category. 32% of young scientific and technological talent cultivates DEA effectiveness. There is a significant positive effect of the spirit of scientists on the cultivation of young scientific and technological talents at the 1% level, with an influence degree of 0.573, and the most obvious promotion effect of the spirit of innovation on the cultivation of young scientific and technological talents (0.624). In the cultivation of young scientific and technological talents, we must guide young people to practice the spirit of scientists, enhance the cultivation of scientific ethics, foster their ability to seek truth and innovation, and foster the inheritance and development of the spirit of scientists among young scientific and technological talents.
A Modeling Study of Business English Students’ Intercultural Competitiveness and Strategies in the Belt and Road Initiative
Authors: Xi Xiaoxue 
Published: December 2024

Abstract
Intercultural competitiveness is an important guarantee for Business English majors to show their advantages and grasp the opportunities of the times in the Belt and Road Initiative. This paper evaluates the cross-cultural competitiveness of business English majors by constructing the CFCS-TOPSIS model and proposes strategies to improve the cross-cultural competitiveness of business English majors in the Belt and Road Initiative based on the evaluation results. The evaluation system of cross-cultural competitiveness of business English students is constructed, while the CFCS algorithm is used to denazify the fuzzy-valued indexes, and the obtained indexes are used as input factors to calculate the TOPSIS model. The research is conducted on students who major in business English at a university and the current level of their intercultural competitiveness is measured and analyzed using statistical analysis methods. The results indicate that business English majors in this university have a good level of intercultural competitiveness, but their intercultural skills and values still require improvement. Cross-sectional comparison of the cross-cultural competitiveness of business English majors in 15 colleges and universities focusing on the construction of the Belt and Road, the P
i values of U2, U5, U12, and U15 colleges and universities are 0.493, 0.536, 0.748, and 0.645, respectively. The indexes of understanding the international business environment (X1), cross-cultural communication theory (X2), and openness (X7) have the most significant influence on the cross-cultural competitiveness of business English majors. The most significant effect is caused by intercultural competitiveness.
A data-driven evaluation of student health impacts in teaching higher education physical education and health programs
Authors: Xue Jianxin , Zhang Jin 
Published: December 2024

Abstract
In the field of physical education in the 21st century, with the rapid development of information technology, data-driven decision modeling has become an important means to improve the quality of teaching and promote the healthy development of students. The accurate assessment of students’ physical fitness levels and mental health is achieved through the use of fuzzy judgment and clustering algorithms in this paper. A data-driven platform for student health sports has been created by modeling sports users and sports and using the UB-CF recommendation algorithm, which includes personalized recommendations. The platform’s impact on students’ health is evaluated using a university as an example. The platform in this paper can provide students with different physical fitness courses with content that meets their own needs. After the experiment, students in the physical education and health course group saw a decrease in weight and hip circumference, respectively, by 2.59kg and 2.81cm, and their physical health improved further. And the platform presented in this paper can enhance the muscle fitness of students. In the experimental group, the standing long jump distance improved by about 10.25% compared with the preexperiment. The MAE of this paper’s method on the identification of psychological emotion “Depression” is only 0.296, which is much lower than the baseline method. Moreover, the method presented in this paper can accurately classify students according to their psychological problems. The purpose of this paper is to provide practical guidance for the innovative development of physical education in colleges and universities.
Exploring the Teaching Reform of Computer Operating System Course Based on Deep Learning
Authors: Zhao Hui 
Published: December 2024

Abstract
This paper reforms the teaching of an existing computer operating system course based on the deep learning route DELC model and evaluates the teaching effect of the reform by means of empirical research. According to the loop framework of the DELC model, design innovative teaching objectives, teaching environments, and other aspects for the computer operating system course. We selected the control class and the experimental class in the School of Computer as research subjects for our teaching practice. The statistical analysis of the pre-test and post-test questionnaire data collected during the teaching practice was used to compare the questionnaire results of the control and experimental classes. Based on the test scores of the computer operating system course of the 10 classes of 2019–2023, cluster analysis and discriminative information were used to explore the teaching effect after the course reform in depth. The paper concludes that the average post-test scores of the experimental classes are significantly higher than those of the control classes, and they are 17.39% higher in the course recognition dimension compared to the control classes. Students of 2019-2022 are clustered into the “common” category, while students of 2023 who adopted the reform strategy in this paper are clustered into the “better” category. This fully demonstrates the feasibility and effectiveness of the proposed computer operating system course reform based on the DELC model.
Simulation study of the dynamics of carbon storage in a forest ecosystem model
Authors: Zhao Hongfei , Lu Haifei , Zhong Tailin , Cao Zhihua , Wan Guowei 
Published: December 2024

Abstract
Changes in the waxing and waning of carbon pools in forest ecosystems have a profound impact on the global carbon cycle. The study takes forests in a city as an example, uses sample plot survey data and Sentinel-2 and GF-1 satellite remote sensing data as data sources, and after multiple feature extraction, the RBF neural network optimized by the PSO algorithm is used for modeling the dynamic estimation of carbon storage, assessing the accuracy of the model and inverting the estimation of carbon storage in the sample area. The results show that the PSO-RBF model in this paper has the best fit and prediction accuracy for carbon storage estimation, with the highest R² of 0.644 and the smallest RRMSE and MAE of 0.287 and 15.368 in the combination of the two data sources, and the estimated value of forest carbon storage in 2022 in the sample area is 6809451.80t, which differs from the actual value by 0.04% and the difference of predicted and actual values in each subarea is 0.04%. The predicted and measured values in subregions had a difference of less than 0.34%. The forest carbon storage model that utilizes PSO-RBF has a good estimation effect overall. The technical support provided by this study enables accurate monitoring of carbon storage in forest ecosystems.
The classroom interaction and learning effect are enhanced by the intelligent teaching system in the high-quality development of colleges and universities
Authors: Sun Liyan 
Published: December 2024

Abstract
In recent years, Artificial Intelligence (AI) technology has developed rapidly, bringing new opportunities for the innovation of education. This paper adopts Bayesian network and Agent technology to construct an intelligent teaching system, which can formulate and implement guided learning strategies according to the individual, actively collect the most interesting information for the learners through the intelligent Agent proxy server, automatically generate a variety of questions and exercises, and reasonably plan and adjust the learning content and progress. Introducing knowledge points as the foundation of teaching resources, establishing connections between them, constructing dynamic knowledge tree models, and implementing intelligent interactive teaching strategies in the teaching system. Teaching research shows that with the empowerment of the intelligent teaching system, the effective interactive behavior of teachers and students covers up to 92.75% of the classroom time, which is significantly higher than the traditional coverage rate of 78.89%, effectively improving the effect of teacher-student interactions in the university classroom, while the academic performance of the experimental class has also been significantly improved. The intelligent teaching system is more effective in enhancing the high-quality development of universities.
Algorithmic Innovation and Visual Communication Strategies in Digital Visual Effects
Authors: Yan Kuan , Liu Gangtian , Zhang Hui , Zhu Danjun 
Published: December 2024

Abstract
With the popularization of digital mobile devices, the development of new media technology and the Internet, visual media presentation becomes more and more diversified and gradually transforms to digitalization. The article optimizes the digital halftone algorithm using visual model and printer model, and proposes an adaptive digital halftone algorithm for enhancing digital images. The enhanced digital image is input into the dual-tree complex wavelet transform for feature dimensionality reduction and noise processing, and then combined with the HSV color model to establish the optimization algorithm for visual communication effect. The average PSNR of the adaptive digital halftone algorithm is 2.31% higher than that of the Floyd-Steinberg error diffusion method, and the information entropy of the visual communication optimization can be up to 9.29 bits, and when the number of digital images is 100, the optimization time of the proposed method for the visual communication optimization is only 30.71 s. The visual communication design works can be attracted to the audience through the optimization of the visual communication effect. The visual communication design works obtained through digital visual effect optimization can attract more attention from the audience and can also effectively trigger positive emotions from the audience. From the optimization of digital visual effect, it is necessary to further introduce the integration of digital technology and visual communication design, combine cross-border resource sharing and improve the dynamic effect of visual communication design, and then improve the effect of visual communication design works.
Research on the Integration of Innovation and Entrepreneurship and Civic and Political Education in the Context of High-Quality Education in the Internet Era
Authors: Hao Binbin , Guo Yanping , Wang Chunhong 
Published: December 2024

Abstract
This paper first studied the feasibility of the integration of civic education and innovation and entrepreneurship education and constructed the integration pathway of innovation and entrepreneurship education and civic education from three aspects, namely, value leadership, theoretical integration as well as practical integration. A regression analysis model was created, the parameters of the model were evaluated using least squares estimation, and the model was tested for its significance. Finally, based on the regression model, the correlation between entrepreneurship education and ideological and political education in colleges and universities was explored, and the influence of ideological and political education on the self-efficacy of college students’ innovation and entrepreneurship and their values of innovation and entrepreneurship was analyzed. The study shows that ideological and political education, classroom channel, daily education and self-efficacy are significantly positively correlated at the level of 0.05, and the correlation coefficients on students’ entrepreneurial values are 0.722, 0.673, and 0.696, respectively. This study has a reference to the healthy development of innovation and entrepreneurship education, and provides a reference to the reform of innovation and entrepreneurship education undertakings for other local colleges and universities of the same type.
Surface Defect Detection of Mining Automation Equipment Based on Convolutional Neural Networks
Authors: Bian Zeyu 
Published: December 2024

Abstract
Surface defect detection of mining automation equipment is crucial for creating a safe operating environment. This paper analyzes the commonly used target detection techniques and selects a target detection algorithm based on Faster-RCNN to construct a model for surface defect detection in mining automation equipment. In the acquisition of surface defects, the Laplace operator and homomorphic filtering are used to enhance and sharpen the image. The texture defect dataset and metal surface defect dataset are also selected to make the VOC2007 dataset, and the Faster-RCNN network model is utilized for training to obtain the surface defect detection model of mining automation equipment. The model defect detection comparison results show that the Faster-RCNN model has an mAP value of 76.1%, which is the model with the highest detection accuracy. The result confirms the effectiveness of the method presented in this paper and enhances the accuracy of the model’s detection.
A Practical Study of Biological Big Data Base Assisting the Reformed Teaching of Probability Theory and Mathematical Statistics Course
Authors: Zeng Xiang 
Published: December 2024

Abstract
Under the background of the large-scale popularization of “Internet + Education”, personalized education mode based on artificial intelligence and other information technologies has become the trend of teaching reform development. In this paper, we have collected and pre-processed students’ learning behaviors during the teaching of Probability Theory and Mathematical Statistics courses, and established a large biological database based on these behaviors. The features of learning behaviors are extracted using the SHAP method, and the features are fused and processed by the MFCNN module. The Bi-LSTM method is used to warn students of academic risks. Finally, we construct a visualization system to assist in teaching Probability Theory and Mathematical Statistics. The results of practical application show that with the assistance of the system, the average grade of the students’ Probability Theory and Mathematical Statistics course progresses quite obviously, the post-test grade is significantly higher than the pre-test grade, and the student’s ability of critical reflection also improves. In addition, a significant difference (p<0.05) was observed between the students of the experimental class and those of the control class in the learning motivation posttest. This paper provides new ideas for research related to the big database of biology and academic early warning in teaching, which contributes to the further promotion of teaching reform.
Characteristic Development of Teaching Ideology and Politics Courses in Colleges and Universities Based on Convex Optimization
Authors: Chen Chen 
Published: December 2024

Abstract
This study integrates the theory of convex optimization into the teaching of ideology and politics courses in colleges and universities and puts forward the characteristic teaching strategy of constructing the teaching resource management and network teaching platform of ideology and politics courses. It consists of a course resource module, an after-class Q&A module, and my module to compose the function of the Ideological and Political Science course network teaching platform. Model the computational migration resource division problem of the mobile terminal as a convex optimization problem and solve it using the Lagrange multiplier method to optimize energy consumption of the mobile terminal. Design the registration and login, personal center, likes and comments, resource upload, resource recommendation, and platform management modules as the functions of the teaching resource management platform for Ideology and Politics courses. Use the search algorithm to obtain the correspondence of physical nodes, use the time series prediction smoothing exponential model to reduce the probability of hotspot misjudgment, and determine the best form of placing network resources through global search optimization. Teaching practice is being conducted with the 2022 computer science major students at a university in Guangdong Province, China. The overall Ideology and Politics literacy of the subject students increased by 7.02 compared to the pre-experiment, P=0.031<0.05, showing a significant difference. Satisfaction with the teaching of ideology and politics courses also exceeds 3 and is close to 4, making more recognized classrooms for teaching ideology and politics.
Validation of Correlations Between in Situ Investigations and Soil Parameters Using FEM Modeling
Authors: Poenaru Alexandru 
Published: December 2024

Abstract
This paper aims to validate the geotechnical parameters obtained using new proposed correlations [1] with in situ test results by using the finite element method (FEM). To achieve this objective was performed a numerical modelling of a deep excavation built in the Northern area of Bucharest, by using several constitutive models such as Mohr-Coulomb, Hardening Soil and HS-Small. The geotechnical parameters used as input data for the numerical model were determined based on in situ soil investigations and using new proposed correlations described in [1]. The numerical model results in terms of horizontal displacements of the diaphragm walls supporting the deep excavation were compared to the measured displacements obtained from 2 inclinometers. Based on these results useful conclusions regarding the validity of the proposed correlations are drawn. This paper is part of wider doctoral research regarding correlations between in situ tests and geotechnical parameters.
Identification of the Areas at High Pluvial Flood Risk Based on Urban Hydraulic Modelling. Case Study for Tulcea Municipality
Authors: Dan Marinela Teodorescu , Hodson Gavin , Lee Rebecca , Speak Ben , Rădulescu Daniela , Rizea Cristina , Cozma Andrei 
Published: December 2024

Abstract
Pluvial floods are frequent phenomena in Romania occurring during torrential rainfall, causing significant damage. Pluvial floods occur due to extreme rainfall when the natural infiltration of excess water into the ground is artificially reduced and when runoff into urban areas exceeds the capacity of existing drainage systems. In urban areas, pluvial flooding is more frequent due to extended impermeable areas, buildings, and undersized drainage systems. Tulcea municipality is characterized by periodic rainfall flooding events with consequences on properties and communities, infrastructure, and on the economic activities. In the second cycle of implementation of the Floods Directive 2007/60/EC, 17 Areas of Potential Significant Flood Risk (APFSR) pluvial source areas were identified, covering 19 municipalities and towns, for which pluvial hydraulic models were carried out. Tulcea municipality was one of the cities designated as having areas of potential significant pluvial flood risk. Hydraulic modelling results have been used for the construction of pluvial flood hazard and risk maps, these being the first pluvial maps reported by Romania to the European Commission. Based on these maps, critical drainage areas have been identified at the level of Tulcea Municipality and some potential flood risk reduction measures have been recommended.
An Alternative Method for Checking Reinforced Concrete Elements Under Biaxial Bending
Authors: Tudor Marius 
Published: December 2024

Abstract
The article presents an original method for verifying reinforced concrete elements under biaxial bending with axial force, in structures subjected to seismic action. This method was easily implemented in automated calculation programs based on numerical analysis. The nonlinear behavior of the reinforced concrete cross section was considered. More importantly, we propose a new method of presenting the results of numerical analysis. This representation involves a two-dimensional graph that can be printed on paper, and it shows the boundary between the resistance reserve of the analyzed element and the direction of horizontal loading. The described method exhibits a very good convergence, allowing results to be calculated and presented rapidly to the program user. The presented method can be successfully applied to any type of geometry and reinforcement.