bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on innovative methods of virtual reality course content for tourism education
Authors: Zhu Zhu 
Published: October 2024

Abstract
Tourism practice teaching is an important means to cultivate high-quality skilled tourism talents. When virtual reality is in tourism practice, teaching undoubtedly shows a beautiful blueprint for modern tourism education. The article demonstrates the advantages of the application of VR technology, designs a VR practical training system for tourism education, and develops VR resources and interface interaction design for tourism education. Based on the binocular stereo imaging model to obtain maximum and minimum parallax, and combined with the adaptive weight PSO algorithm for optimizing tourism virtual scene viewpoints. Then, a comparison test for teaching was designed using the VR training system for tourism education. By analyzing students’ eye movement data to understand the viewpoint optimization effect of the AW-PSO algorithm, we also verified their learning performance, learning experience, and academic mood changes. The edge strength and clarity of the virtual scene obtained by the AW-PSO algorithm were 67.06 and 14.71, respectively, and the theoretical score of the experimental class students was 83.15, which was 9.06% higher than that of the control class students. Based on tourism education, VR practical training systems can effectively enhance students’ learning interest and academic mood for tourism education courses and help develop high-quality tourism education courses in colleges and universities.
A model for the application of big data analytics in cost prediction and control in construction projects
Authors: Sun Wenbo 
Published: October 2024

Abstract
Construction project cost control is an important aspect of project management. This paper aims to provide an effective cost control management mode for the construction industry by studying the application of big data technology in cost prediction and control management of construction projects. The standard particle swarm algorithm is optimized by establishing a particle object element model, performing iterative and hierarchical updating of particles, and introducing the Tent mapping strategy. Then it is used in the optimization of the Extreme Learning Machine algorithm to design a construction project cost prediction and control model based on APSO-LLM. The index system of the construction project cost prediction and control model is constructed, and the convergence effect, prediction effect, and case application of the model are analyzed. The APSO-LLM model enhances the convergence speed and search accuracy, boosts the optimal fitness by 0.037, and maintains a construction cost prediction error below 3%. The study proves the APSO-LLM model’s applicability, accuracy, and good prediction effect in cost prediction and construction project control.
A Study on Personalized Digital Marketing Content Creation Based on Consumer Psychoanalysis
Authors: Zhan Huina 
Published: October 2024

Abstract
At present, personalized recommendation technology is widely used in digital marketing. In this paper, on the basis of the existing personalized recommendation algorithm based on commodity characteristics, from the perspective of consumer psychology, we propose a multiple attitude recommendation algorithm under the apparent awareness of the customer. In this recommendation algorithm, the user’s recent and historical interest weights are added, and personalized digital marketing content recommendations are made based on consumer psychology. The MT algorithm designed in this paper has a higher recommendation accuracy when compared to other recommendation algorithms. A questionnaire survey is conducted to examine the influence of marketing content on consumers’ purchase intentions on shopping websites using the personalized recommendation system designed in this paper. The correlation analysis results indicate that the variables and the willingness to buy have a positive correlation at a significance level of 0.01. The final regression equation: willingness to buy = 0.065+0.126*information orchestration+0.113*pop-up ads+0.109*social channel recommendation+0.158*web system recommendation+0.152*user trust, which indicates that the variable of web system recommendation has the greatest effect on willingness to buy.
A Language Modeling-Based Approach to Real-Time Language Translation Quality Enhancement in ESL Education
Authors: Zhou Hong 
Published: October 2024

Abstract
With the development of ESL education in recent years, real-time language translation has gradually become a research hotspot in the field of natural language communication. In this paper, the data processing technology of real-time translation is introduced, and then a Transducer (RNN-T) model based on real-time language translation is constructed based on the BPE subword segmentation method under the condition of probability gradient calculation algorithm and transcription network. Secondly, this model determines and tests the content involved in the process of real-time language translation and finally obtains results to improve the quality of real-time language translation. The experimental results show that the accuracy of character translation among the six language models is 85.8%, 86.2%, 88%, 93.4%, 94.03%, and 94.36%, respectively. In addition, the error rate of inserting, deleting, and replacing characters is < 20%. Compared with the other four models, the word error rate of the RNN-Transducer algorithm is reduced by 1.59%, 3.94%, 3.86%, and 9.01%, and the RTF is reduced by 3.91%, 10.96%, 10.09%, and 7.94%, respectively, which reflects the superiority of the RNN-Transducer method proposed in this paper.
A Practical Study on the Teaching Reform of Civic and Political Integration of Economics Courses in Colleges and Universities Supported by Information Technology
Authors: Li Xiaolu , Wu Yuchuan 
Published: October 2024

Abstract
The issue of strengthening the construction of economics courses, enhancing the moral development of economics professionals, and cultivating professionals with firm and lofty economics ideals is of utmost urgency. In this paper, we model the potential relationship prediction and global correspondence of economics curriculum civics in colleges and universities and then use the sequence markers specific to the subset of relationships to deal with the overlap between entities and entities to complete the ternary extraction work and to realize the joint curriculum civics element entity relationship extraction. Fusion of entity attributes and structural features can be achieved by utilizing the dual attention mechanism, and hyperbolic spatial embedding in graph structure feature extraction can be utilized for entity alignment. The economics program at a university in Guangzhou implements classroom civics integration teaching reform after completing the named entity recognition task test on the dataset. It was found that compared to LEBRT, the current state-of-the-art method for incorporating lexicon information, the model in this paper achieved a performance improvement of 2.53%, 2.26%, and 3.47% in the three metrics, respectively. After one semester of teaching reform and model application, the four scores of Economics Interest, Economics Habit, Economics Confidence, and Economics Autonomous Learning Ability increased by 28.13, 28.65, 18.39, and 26.68 points, respectively, compared with the pre-test, and professionalism also improved by more than 10 points in all cases. This paper provides a useful exploration for optimizing classroom civics teaching methods and efficiency, as well as combining implicit civics with cutting-edge information technology.
Exploring Innovative Practices and Challenges in the Ecological Development of Art Industry Driven by Digital Technology
Authors: Chen Liyan 
Published: October 2024

Abstract
The essence of the ecological development of the art industry, when viewed through the lens of digital technology, is precisely the development of regional economies within the framework of sustainable development strategies. This paper determines the first-level and second-level indicators of the three subsystems of industrial economy, ecology, and society according to relevant references and experts’ suggestions. Using the entropy weight method to calculate the weights of evaluation indicators, combining the weight values and normalized data, we construct the economic-ecological-social composite system evaluation model and make a detailed expression of the coupling degree and the coupling coordination degree calculation formula and process. This paper utilizes the model of this paper to evaluate and analyze the ecological development of the art industry influenced by digital technology by selecting the research object. The weight values of the ecosystem, social system, and economic system are 0.4277, 3064, and 0.2659, respectively. The index of the coupling coordination degree of the ecological-economic-social system falls between 0.6 and 0.7 in the years 2013 to 2015, indicating that the composite system is currently in the primary coordination stage. By evaluating and analyzing the results, we summarize the challenges that need to be faced by the ecological development of the art industry in the context of digitization, and for this reason, we propose innovative practices for the art industry.
Research on Cultural and Creative Design Based on Modal Theory and AIGC Technology
Authors: Xie Xueying , Tang Boyun 
Published: October 2024

Abstract
Modal theory is an important basis for studying cultural inheritance and dissemination. This paper combines modal theory and AIGC technology to innovate the cultural and creative design method. Through the calculation and analysis of modal recognition degree and other indicators, the modal factors that should be applied or innovated in cultural and creative design are identified. Using this paper’s cultural and creative design method, the analysis of Liangzhu culture and Shu brocade patterns is conducted separately. In the Liangzhu culture modal recognition, the higher recognition is pattern representation, morphological representation, and artifact function, and the lower recognition is color representation, aesthetic concept, material representation, and philosophical thought. The order of the popularity of the modal elements of pattern representations is from high to low: abstract pattern > animal pattern > geometric pattern. The traditional patterns of Shu brocade are in the order of color expression: A (0.209) > subject matter content, D (0.206) > surface features, C (0.162) > organization, B (0.148) > aesthetic meaning, F (0.138) > symbolic meaning E (0.137). When using AIGC to assist cultural and creative design, it is necessary to take into account the modal factors with smaller weight values to ensure that the final design can be loved by the public and achieve the dual goals of cultural heritage and economic benefits.
Comparison of Digital Literacy Education Strategies for Chinese and Foreign Youth in the Digital Media Era
Authors: Zhang Qian , Yang Di , Bai Ben 
Published: October 2024

Abstract
In order to realize the quantitative analysis of the digital literacy education strategies of Chinese and foreign youth, this paper constructs the evaluation index system with the help of a hierarchical analysis algorithm and comprehensive fuzzy evaluation to explore the differences between the digital literacy of Chinese and foreign youth, and to compare the differences between the digital literacy education strategies of Chinese and foreign youth. After analyzing and discussing, this paper identifies 10 expert panelists, conducts two rounds of the Delphi method survey on the preliminary expert consultation questionnaire, and finally determines the evaluation index system based on the standard of arithmetic mean and coefficient of variation. The evaluation indexes are divided into a hierarchical analysis structure. The judgment matrix of evaluation indexes is constructed according to the 1-9 scale method. The hierarchical single sorting and consistency tests are carried out to derive the weight value of each evaluation index. Based on the system of evaluation indexes, the evaluation factors are composed into a collection of factors, and the semi-trapezoidal distribution function is used to determine the subordination degree of the indexes. The principle of calculation of fuzzy comprehensive evaluation is given to realize the fuzzy comprehensive evaluation model. Construction. Using the above model to evaluate the digital literacy of Chinese and foreign youths, the evaluation result of the digital literacy of youths in country M is strong, with an affiliation degree of 3.9444, and the evaluation result of the digital literacy of youths in China is medium, with an affiliation degree of 3.1581. The difference between the digital literacy of Chinese youths and that of youths in country M is large. The education strategy determines the digital literacy of youths to a large extent. The results of the analysis of the evaluation are summarized in terms of three dimensions of distance education, feedback and communication, and evaluation system to explore the difference between Chinese and foreign youth digital literacy education strategies.
A study on eye movement test and visuospatial optimization of wayfinding perception in large-scale comprehensive transportation hubs
Authors: Zhai Leilei , Xia Haishan , Xu Ran , Shao Jinyan , Zhai Jianye , Nie Jiamin 
Published: October 2024

Abstract
The integration of rail transit stations and the surrounding underground space presents volume scale and functional complexity, and it has gradually formed a complex integrated transportation hub. Wayfinding inside its space is also more difficult, and the behavioral phenomena of passengers stopping, wandering, and getting lost are common. This paper uses station A of a large transportation hub as an example. It combines target detection technology and the optical flow method, designs the traffic space guidance system, tests how well passengers can find their way by moving their eyes, and then looks at how the visual space can be improved in terms of color, comfort, and subjective comfort after getting feedback. The data from the passenger eye-movement test reveals that during the sub-processes of information perception and elevator path selection, the logo is the primary focus, with attention ratios of 72.35% and 61.28%. Orange, yellow, and green were the three colors that received the highest ratings for subjective spatial comfort from passengers, with ratings of 0.58, 0.55, and 0.35, respectively, which are data-supported for visuospatial optimization.
A study of strong convergence of differential equations based on Euler’s algorithm
Authors: Ji Tianfu 
Published: October 2024

Abstract
Differential equations have important applications in many fields, such as chemistry, biology, epidemiology, and finance. Most analytic solutions of differential equations are difficult to obtain. Therefore numerical solutions of differential equations become an important tool. The truncated Euler method is proposed in this paper, and we investigate how the truncated EM solution of the derived SDDE converges strongly under the local Lipschitz condition and the one-sided linear growth condition after relaxation. The basic strong convergence theorem is set up and the new notation X(t,x;s) is introduced as an analytic solution of the stochastic differential equation. Establish the assumption that the coefficients of the drift term and the coefficients of the diffusion term of the stochastic differential equation satisfy a contractionary monotonicity condition in order to prove, by induction, that the exact solution of this stochastic differential equation is bounded for a long time. Different examples are given to compare the simulated deviations between the numerical and analytical solutions of Euler’s algorithm and the modified Euler’s algorithm for the initial value problem of fractional order differential equations and to analyze the convergence of the two numerical solutions. The truncated Euler method is applied to highly nonlinear time-transformed stochastic differential equations by means of the dyadic principle, and it is proved that the order of convergence of the strong convergence of the truncated Euler-Maruyama method for time-transformed stochastic differential equations is

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Application of Artificial Intelligence-based Visual Arts Pedagogy in Traditional Painting Education
Authors: Wu Qiang 
Published: October 2024

Abstract
Traditional art has a deep cultural heritage and rich connotation, combining artificial intelligence technology with traditional aesthetics as a way to realize the innovation of traditional painting education mode. In this paper, starting from the performance of traditional painting’s aesthetic value, a personalized intelligent painting teaching mode is constructed based on the visual art teaching method and combined with artificial intelligence. The CCME-GAN model is introduced for the construction of a personalized painting learning generation model, and the BERT-LDA model is established by combining the BERT model and the LDA model for the intelligent evaluation of personalized painting works. Xinjiang folk artworks were selected as the research data source to carry out the validation of personalized painting work generation and assessment, and teaching comparison experiments were designed to analyze the teaching effect of the personalized intelligent teaching mode. The subjective evaluation score of Xinjiang folk art paintings generated by the CCME-GAN model was 9.11, and among the nine clustering results of painting work assessment, the eigenvalues of the theme of painting evaluation of Cluster 1 range between [0,5.5]. At the end of the teaching experiment, students’ creativity scores increased from 2.74±0.37 before the experiment to 4.63±0.26. Relying on artificial intelligence technology can enhance the teaching effect of traditional painting methods and improve students’ painting levels.
Research on Key Technologies and Eco-Innovation Strategies for Digital Transformation of Art Industry
Authors: Chen Liyan 
Published: October 2024

Abstract
The development of digital technology has brought unprecedented opportunities and challenges for the art industry, and seeking transformation and upgrading has become the preferred choice for the development of the art industry in the wave of digitalization that keeps rushing forward. This paper constructs an art design system using image processing technology to provide strong technical support for the core design of the art industry. The method of sparse feature expression and visual communication is used to extract the edge features of artworks, and the chunked feature matching technology is used for spatial sampling of artworks to realize the three-dimensional display of artworks based on virtual reality technology. The application effect of the image processing algorithm used in the art design system of this paper is significantly better than that of the original processing technology and digital signal-based processing technology. At the same time, the feature extraction and matching algorithms in the three-dimensional display of this paper are also significantly better than other algorithms, and the matching and fusion of artworks can realize the effect of high similarity with the original works. Based on the Kano model of display demand research, this paper finally calculated that the SI value is located between 0.1943~0.8120, the DSI value is located between -0.7053~-0.1004, and according to the calculation of the various demand items affecting user satisfaction, which provides a directional guideline for the upgrading and transformation of the display of works of art and the art industry.
Research on optimal path planning technology for industrial robots based on improved IDE algorithm
Authors: Zuo Peiliang 
Published: October 2024

Abstract
Realizing efficient and accurate positional movement of industrial robots is one of the key technologies to accelerate industrial development. In this paper, a four-wheel-drive McNamee mobile robot is selected as the research object, and the improved IPSO-IDE algorithm is proposed, which is combined with a PID controller to realize the accurate positioning and optimal path planning of industrial machines. The experimental results of robot kinematic parameter calibration show that the distance error of the robot calibrated with the algorithm is greatly reduced, and not only that, the IPSO-IDE algorithm reduces the average distance error of the robot to only 0.124 mm, which is much smaller than that of the PSO algorithm and the DE algorithm. The IPSO-IDE algorithm is capable of planning the optimal motion path in a short time, as demonstrated by the results of robot map environment simulation experiments. In the simulated map environment of 10 m × 10 m, the convergence speed of the algorithm’s planning path is 12.69 seconds, and the generated optimal path length is 15.0221 m, which is better than other algorithms. In conclusion, the proposed IPSO-IDE algorithm has an excellent performance in terms of path-planning capabilities for industrial robots.
Mixed-field ABO front typing as an early sign of disease recurrence in ABO-matched stem cell transplantation
Authors: Yurtsever Nalan , Lee Edward S. , Pinatti Lisa , Shah Bhushan , Tormey Christopher A. , Siddon Alexa J. 
Published: October 2024

Abstract
ABO group testing is critical for allogeneic stem cell transplantation because mismatches can cause both transfusion and engraftment challenges. Even with ABO-matched donor-recipient pairs, ABO group determination may provide valuable insight into allograft status. Herein, we report a case of a 76-year-old female patient with myeloid neoplasm who underwent ABO-matched stem cell transplantation and in whom mixed-field ABO antigen expression during routine follow-up testing post-transplantation was the first sign of a change in transplant graft status; the mixed-field findings pre-dated changes in formal chimerism testing. This case underscores the potential of mixed-field ABO typing as an early indicator of disease recurrence in ABO-matched stem cell transplants and suggests that, in such cases, more sensitive forms of chimerism testing and/or closer monitoring for disease recurrence, particularly in the clinical setting of myeloid neoplasms, may be warranted.
The American Rare Donor Program: 25 years supporting rare blood needs
Authors: Keller Margaret A. , Nance Sandra T. , Maurer Joan , Kavitsky Victoria , Babariya Shraddha P. 
Published: October 2024

Abstract
Rare donor programs are critically important for those patients with rare phenotypes who have produced the associated alloantibodies that necessitate the provision of rare blood components. We describe the American Rare Donor Program (ARDP) and its establishment, members, and policies. The specific phenotypes meeting the ARDP criteria for inclusion are described. Data on the number of rare donors registered by year, and the number of requests for rare blood components received and fulfilled over the 25 years of the program (1998–2023) are provided, along with a description of some notable cases and discussion of how the program supports patients with sickle cell disease.