bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Utilization of Virtual Reality Technology in the Scientific and Technological Protection and Cultural Inheritance of Clarke Porcelain--Taking Clarke Porcelain in the Collection of the City University of Macau as an Example
Authors: Huang Guang , Zhao Qiang 
Published: March 2024

Abstract
Virtual Reality (VR) technology heralds a transformative era for the safeguarding and disseminating cultural heritage. This paper examines its application through the lens of the Clark Porcelain collection at the City University of Macau, highlighting VR’s pivotal role in the scientific preservation and cultural transmission of these artifacts. By delving into the ornamental intricacies of Clark Porcelain, we evaluate VR’s effectiveness in protecting and showcasing these treasures. The study employs advanced techniques, including 3D virtual scene modeling, texture mapping, and collision detection, to replicate a museum setting, thus elevating the user’s interactive experience. An audience satisfaction survey indicates positive feedback, with relaxation and aesthetic satisfaction scores averaging 4.65 and 4.53, respectively. Moreover, ANOVA results reveal significant technological acceptance disparities across age groups. The Analysis further underscores VR’s substantial impact on cultural heritage promotion, noting the potential for better integration of Clark Porcelain with contemporary technologies. Virtual reality emerges as a formidable tool in the scientific conservation and cultural legacy of Clark Porcelain, offering fresh insights and technical backing for the modernization of traditional cultural heritage preservation.
Design and Innovation of English Teaching Methods in Colleges and Universities Based on Topological Number Theory
Authors: Li Nan , Wang Lei , Gao Mingli 
Published: March 2024

Abstract
This research delves into the innovative application of topological number theory to reform English language teaching methodologies in higher education. We introduce and assess a novel approach to English teaching in colleges and universities, inspired by the principles of topological number theory. Our methodology leverages a unique model for recognizing handwritten English based on visual topological cognition, applying the insights of topological cognition theory to enhance English language instruction. The empirical analysis reveals a low word error rate of just 9.42% for our model, outperforming traditional models like the CRNN, which exhibits a 15.12% error rate. In a 10-week instructional experiment, students taught using the topological approach demonstrated significant improvements across all dimensions of English learning compared to their peers in a control group. The findings underscore the substantial potential of topological number theory in elevating English language teaching in colleges, offering significant benefits in teaching effectiveness and student motivation.
Innovation and Evaluation Analysis of English Teaching Mode in Colleges and Universities Based on Wavelet Packet Decomposition
Authors: Wang Lei , Gao Mingli , Li Nan 
Published: March 2024

Abstract
The surge in information technology has catalyzed a pivotal shift towards innovative English teaching methodologies in higher education, garnering significant attention in educational research. This study introduces wavelet packet decomposition as a novel approach to both the innovation and evaluation of English teaching methods in colleges and universities, aiming to enhance teaching efficacy and scientific rigor. By employing wavelet packet decomposition for data analysis and utilizing a cloud-based evaluation model for teaching assessments, we investigate the impact of a new teaching mode at College M. Results reveal that students exposed to this innovative teaching strategy outperformed their counterparts in the control group on English cognitive tests, particularly in foundational areas such as grammar, where the experimental group achieved an impressive average success rate of 86.73%, compared to the 25%-50% range of the control group. These findings highlight the substantial benefits of the innovative teaching mode in elevating students’ English learning outcomes, particularly in grasping basic concepts. Furthermore, integrating a cloud evaluation model offers a comprehensive and scientific framework for assessing teaching effectiveness. This research validates the efficacy of the novel teaching model and introduces an innovative evaluation methodology for English education in tertiary institutions.
The Construction of Wisdom Teaching Mode of Physical Education and Training in Colleges and Universities in the Internet Era
Authors: Qian Yahui 
Published: March 2024

Abstract
The rise of the intelligent teaching model, relying on artificial intelligence and digital information technology, provides students with personalized and autonomous learning pathways. The model encourages students to learn independently and develop personally by integrating online and offline learning resources, enhancing their innovation and practical skills. Educational innovation has focused on exploring how to effectively incorporate competent teaching resources to improve teaching efficiency and students’ physical education skills. This study designed a new smart teaching mode for physical training science using blended learning theory and artificial intelligence technology. The differences in students’ physical education performance, participation, and satisfaction between the traditional and intelligent teaching modes were analyzed by comparison. The students who used innovative teaching methods in the study were better than those who used conventional teaching methods in 100-meter sprint and basketball shooting accuracy, with an average improvement rate of 15%. According to the study, the intelligent teaching mode can effectively enhance students’ physical education learning efficiency and mastery of movement skills, paving the way for a new development direction in college physical education.
Exploring the Methods and Paths of Integrating Entrepreneurship and Innovation Education into Applied Undergraduate Education
Authors: Wu Yuefeng 
Published: March 2024

Abstract
In the context of a global enthusiasm for innovation and entrepreneurship, this study explores practical strategies for incorporating entrepreneurship and innovation education into applied undergraduate curricula, marking a pivotal shift in educational reform. Utilizing a PEST analysis, cloud computing for resource allocation, and decision tree algorithms, we comprehensively examine the innovation and entrepreneurship education landscape in applied educational institutions. Our study demonstrates that strategic resource allocation can substantially improve both the utilization efficiency of resources and the overall impact of education. Establishing a resource allocation system enhances the alignment between educational resources and specific tasks, leading to marked improvements in resource efficiency. Comparative assessments indicate that applied institutions are particularly adept at fostering students’ entrepreneurial and innovative capacities, with student-led ventures in these institutions generating an average net profit of 210,000 to 500,000 yuan and capturing a market share of 58.88%. The research underscores the necessity of constructing a supportive framework for innovation and entrepreneurship education, advocating for an interdisciplinary stance and stronger school-business partnerships as essential components for optimizing educational effectiveness in applied undergraduate programs.
Identification of English Teaching Effectiveness and Students’ English Proficiency Development in Colleges and Universities Combining Refined Bilinear Attention Networks
Authors: Xi Lihong 
Published: March 2024

Abstract
With the current application of artificial intelligence in education, English teaching methods in colleges and universities are developing rapidly. In this paper, we explore the application of the streamlined bilinear attention network to enhance students’ English proficiency and evaluate teaching effectiveness to improve teaching efficiency and improve students’ English proficiency. The study applies the bilinear attention mechanism to effectively process visual information during college English teaching using computerized visual learning methods to improve the accuracy of classroom teaching quality assessment. The methodology includes implementing a bilinear attention mechanism and applying a deformable convolution module to extract more accurate image features and optimize model performance. The model achieves 98.89% accuracy in facial expression recognition on the CK+ dataset, and 88.5% and 78.9% on the RAF-DB and Fer2013 datasets, respectively. Through online emotion evaluation experiments, the model performed well in recognizing emotional activity in teaching videos, which is highly consistent with the manual evaluation results. In analyzing students’ English proficiency development, the model-assisted teaching method can significantly improve students’ listening, grammar, phonetics, and many other abilities, with a mean value of self-evaluation reaching 4.09576 points. It shows the effectiveness of the streamlined bilinear attention network in assessing the teaching effectiveness of English teaching in colleges and universities and improving students’ abilities. Not only does the model accurately identify emotional activity in the classroom, but it also enhances students’ English learning.
Speech Recognition Enhancement and Compression Perception in Russian Translation Teaching Cooperative System Application
Authors: Xu Di 
Published: March 2024

Abstract
In the digital age, characterized by the ubiquity of big data and artificial intelligence, Russian translation education is poised for transformative change. This study explores the integration of advanced speech recognition and compressed perception technologies into Russian translation instruction, highlighting their potential to elevate educational quality and translator training. Utilizing the Spring Boot framework, we developed a comprehensive Russian translation teaching system, incorporating a Russian-Chinese speech translation model that leverages the RNN Transducer model and an N-gram language model, alongside compressed perception theory for efficient speech signal processing. Our findings reveal a notable enhancement in Russian speech recognition accuracy and processing speed, with a 4.73% improvement in endto-end speech detection accuracy and a significant reduction in word error rate, outperforming CTC and CTC-LM models by 14.79% to 24.85%. Furthermore, speech quality and intelligibility scores experienced marked improvements. The application of speech recognition enhancement and compressed perception technologies emerges as a vital strategy for enriching Russian translation pedagogy and fostering the development of proficient translators.
Strategic Analysis of Informatization of International Trade Enterprises’ Economic Management Models Based on Game Theory Models
Authors: Yang Xinran 
Published: March 2024

Abstract
Exploring the economic management models of international trade enterprises, this research highlights the significant role of informatization strategies informed by game theory. Through the prism of game theory, we analyze the interplay among various stakeholders, including risk takers, managers, and executors. Our study reveals that appropriate risk-taking can drastically lower operational risks. A case in point is Company A, which witnessed a notable improvement in financial stability, with its Z-score rising from 2.6785 in 2005 to 4.6314 in 2022. As theAnalysis shows, effective risk management plays a pivotal role in boosting economic efficiency, evident through enhanced total asset turnover and gross operating margins. This study underscores the utility of a game theory-based economic management model in improving risk management and financial efficiency, thereby advancing the implementation and refinement of informatization strategies within enterprises.
Construction of Local Fiscal Revenue Forecasting Model Based on SVR Model
Authors: Yu Xianghui 
Published: March 2024

Abstract
With the development of the economy at hand, local fiscal revenue forecasting is becoming increasingly important for policy making and budgetary management. In this paper, based on SVR (Support Vector Regression) model, the method of building a more accurate local fiscal revenue forecasting model is discussed. The study is constructing a local fiscal revenue forecasting model based on the SVR model to improve forecasting accuracy. The PCA method is applied to preprocess the data to reduce multicollinearity and extract the key influence factors. The SVR model is used to forecast, and the appropriate kernel function and model parameters are chosen. The model’s ability to predict accurately is demonstrated by the average prediction error of 2.47% in the short-term and 3.29% in the medium- and long-term forecasts. The PCA-SVR model is more effective in dealing with seasonal and short-term shocks than traditional time series models. The study proved that the SVR model is an effective and powerful tool for predicting local fiscal revenues.
Research on the Practice of Collaborative Parenting between Mental Health Education and Student Management in Colleges and Universities in the Information Age
Authors: Zhang Tingting 
Published: March 2024

Abstract
In today’s digital era, mental health challenges among college students are escalating. This study investigates how integrating mental health education with student management can foster college students’ comprehensive growth. Employing fuzzy clustering for mental health analysis and leveraging both sample-weighted and feature-weighted algorithms, we assess the mental well-being of students from varied familial backgrounds. Our findings reveal that students from particular family backgrounds exhibit significantly lower mental health scores across personality, emotional stability, behavioral habits, self-awareness, and social interactions, with marked disparities in depression and anxiety levels. The adoption of a collaborative parenting approach markedly improved the mental health outcomes for these students, reducing depression and anxiety scores by 1.815 and 1.436 points, respectively. The study advocates for a concerted effort in mental health education and student management within higher education institutions, emphasizing support for students from challenging family environments to nurture their holistic well-being.
A Spatio-Temporal Network Model of Chinese Ethnic Culture Transmission Paths Cultural
Authors: Zhou Xuefang 
Published: March 2024

Abstract
The current social network analysis method is essential in dealing with massive data on network relationships. By treating individuals, organizations, or countries as nodes and their relationships as connecting lines, the network diagrams provided a new perspective for studying social structure and communication paths. When exploring the path of Chinese national culture, the spatio-temporal network model can better analyze cultural diffusion’s dynamic characteristics and efficiency, and then optimize the diffusion strategy to promote the global diffusion of Chinese culture. In this study, the efficiency and characteristics of cultural diffusion are analyzed in depth using social network analysis, with indicators such as point degree centrality, mediated centrality, proximity centrality, and network flatness. The effectiveness of cultural diffusion is influenced by the identification of critical nodes and the trust propagation mechanism in the normalized model. Estimated by the generalized least squares method, the model demonstrates the increased efficiency of cultural dissemination under specific dissemination attributes and narrative attributes, in which the average number of plays of Chinese cultural content on the TikTok platform reaches 13,585,700, the number of likes reaches 355,123, and the number of comments is 31,398. Enhancing the global communication efficiency of Chinese national culture can be achieved by optimizing the social network structure and content strategy. This study provides a scientific basis and practical guidance for spreading Chinese culture globally, and emphasizes the importance of social platforms in cultural dissemination.
University English Translation Teaching in the Context of Artificial Intelligence: Problems and Countermeasures
Authors: Sun Yanan 
Published: March 2024

Abstract
With the rapid development of artificial intelligence, university English translation teaching faces many challenges and opportunities. This article studies the problems in teaching in this context and proposes effective countermeasures. Diagnostic analysis and factor analysis are used in the article to conduct an in-depth study of the three levels of the teaching process: knowledge skills, autonomy, and emotional development. The students achieved a 70% mastery rate in knowledge and skills, while their independence and emotional development performance was 60% and 50%, respectively. This paper proposes an English speech translation system based on artificial intelligence to enhance teaching effectiveness. After a 14-week teaching experiment, the average grade of the students in the experimental class improved by about 6.82 points compared to the traditional teaching class, proving the system’s effectiveness. The study diagnosed the current problems in university English translation teaching, verified the potential of AI technology in improving teaching quality through empirical research, and combined with AI technology can effectively improve the quality and efficiency of university English translation teaching.
Construction and Research of Aerobics Teaching Evaluation Platform in Colleges and Universities in the Age of Digital Technology
Authors: Wang Haiying , Liu Song 
Published: March 2024

Abstract
As digital technology advances, college aerobics instruction must evolve to enhance teaching efficiency and quality through tech-based solutions. Traditional aerobics evaluation faces challenges like subjectivity, delayed feedback, and inefficiency, hindering quality improvement and modern teaching management. This study introduces a novel, efficient, scientific evaluation platform for aerobics teaching, focusing on quantitative assessment and refined management. The platform demonstrates significant benefits by developing an evaluation index system, utilizing a genetic algorithm for index weight optimization, and employing a fuzzy comprehensive evaluation method for teacher performance. Results show enhanced student satisfaction, a notable 14.81% increase in assessment scores among the experimental group, and improved skill quality and application. This platform offers a fresh perspective and pathway for elevating aerobics teaching in higher education.
Study on the Construction of Educational Management System to Integrate the Elements of Civic and Political Programs with the Employment and Precision Support for Poor College Students in Colleges and Universities under the Learning Migration Theory
Authors: Xu Gaochao 
Published: March 2024

Abstract
Facing the complex and changing job market, poor students in colleges and universities face severe challenges. This study explores how to construct an educational management system for precise employment support for poor college students in colleges and universities by integrating elements of the Civics and Political Science program under the guidance of the learning transfer theory to enhance employment ability and increase employment opportunities. The entropy weight-TOPSIS method is used in the study to assess the quality of employment help for poor college students in a comprehensive manner. Among the 10 colleges and universities, the evaluation scores of the quality of employment assistance work range from 0.25 to 0.7567, and the average score is 0.4432, which concludes that there is a significant difference between different colleges and universities in the quality of employment assistance work. Through the analysis of the multiple linear regression model, it is found that individual career level, school guidance level, and ability development level are the key factors affecting the satisfaction of employsment precision help for poor college students, and the influence of ability development level is the most significant. To improve the employment quality of poor college students, colleges and universities should prioritize individualized guidance and ability development when providing employment assistance.
Fault Detection and Failure Rate Analysis of New Energy Vehicles Based on Decision Tree Algorithm
Authors: Tan Ping , Gong Lanlan 
Published: March 2024

Abstract
New energy vehicles are vital in promoting environmental protection and technological innovation. Fault detection still faces challenges during its operation, and efficient and accurate methods for fault diagnosis are urgently needed. This paper proposes a fault detection and analysis model based on a decision tree algorithm for the fault detection problem of new energy vehicles. The dataset applicable to the model is prepared by preprocessing in-vehicle network data, including data cleaning, integration, and other steps. Fault prediction can be realized after using C4.5 algorithms to construct a decision tree. With a precision of 82.26% on the test set, this model is highly accurate in fault detection, which is 1.23 percentage points higher than the traditional decision tree algorithm. The model’s effectiveness and efficiency in handling large-scale data were demonstrated by its training and testing on training sets of different sizes. Using the traditional algorithm, a training set of 80,000 data was used to reduce the model’s running time from 274,432 seconds to 249,269 seconds. This study provides a practical methodology for fault diagnosis of new energy vehicles, improving fault detection accuracy while optimizing computational efficiency. Real-time monitoring and timely maintenance of new energy vehicles require this.
Parasites in Wildlife in the Federation of Bosnia and Herzegovina
Authors: Omeragić Jasmin , Kapo Naida , Škapur Vedad , Softić Adis , Goletić Šejla , Šaljić Ermin , Goletić Teufik 
Published: March 2024

Abstract
Parasitic diseases of wild animals represent an important area of research. In addition to the significant impact on wildlife health and fitness, many parasitic diseases have zoonotic implications. Due to limited scientific information, this research aimed to investigate parasitic diseases in wildlife in Bosnia and Herzegovina (B&H), focusing on the Federation of Bosnia and Herzegovina (FB&H), emphasizing zoonotic species. In the period from April 2020 to November 2022, we conducted research on 9 wildlife species. We analyzed fecal samples to detect and identify diagnostic stages (eggs, larvae, cysts, and oocysts) of various animal endoparasites using coprological methods, such as sedimentation, flotation, and the Baermann technique. The MERIFLUOR® Cryptosporidium/Giardia test was also used for the detection of Cryptosporidium oocysts and Giardia cysts. In the case of red foxes, intestinal samples were examined using the intestinal scraping technique to detect adult helminths. All collected muscle samples were subjected to the artificial digestion method for Trichinella detection. From 1,278 samples, 70.9% were positive. Parasitic infections were confirmed in 15.9% (11/69) of bears; 83.7% (262/313) of red foxes; 67.6% (44/65) of wolves; 25% (1/4) of wildcats; 20% (1/5) of badger; 43.7% (7/16) of martens; 39.7% (76/191) of wild boars; 84.5% (350/414) of deer, and 77.1% (155/201) of hares. The finding of zoonotic parasites (Toxocara canis, Uncinaria spp., Trichinella spp., Echinococcus spp. etc.) is particularly important due to their potential detrimental effects on human health, which highlights the need for further investigations.