bluuebunny/crossref_metadata_2025_split huggingface dataset:
Innovative Practice of Physical Education Teaching in Colleges and Universities Based on Artificial Intelligence Technology
Authors: Guo Jun 
Published: February 2024

Abstract
With the development and improvement of artificial intelligence technology, the teaching innovation mode of combining college sports courses with artificial intelligence has gradually received widespread attention. This paper is based on artificial intelligence technology for the design of intelligent sports detection wearable devices, through which students’ sports data are collected, low-pass filters are used to reduce the noise of the collected data, normalization is carried out, and the AlphaPose algorithm is combined with the assessment and extraction of the human movement posture of college sports. The artificial intelligence sports teaching framework is built to innovate college sports teaching based on artificial intelligence. Finally, the impact of sports recognition is examined, and a comparison experiment is carried out to examine the practical implications of this teaching method. The four experimental targets had sports recognition errors that were less than 10% on average according to the results. The two classes under the experimental control have a P-value of less than 0.05 in the comparison of physical skills and physical fitness test data, and there is an improvement of 5-20 in all scores, which indicates that the experimental class has a higher teaching effect and is significantly helpful in performance improvement. Based on the above, this paper researches the practice of artificial intelligence technology in college sports teaching to provide an innovative path for the transformation of traditional sports teaching to artificial intelligence sports teaching.
Exploration of Innovative Teaching Models of Civics in College Programs with Big Data Analytics
Authors: Hu Yanhua , Jiang Huan 
Published: February 2024

Abstract
Curriculum Civics is a key educational concept for colleges and universities to implement the fundamental task of cultivating people with moral character, and the innovative teaching mode of curriculum Civics is conducive to promoting the quality of work in colleges and universities. Based on ADDIE, this paper constructs the innovative teaching mode of “network+classroom+practice”. By improving the learning behavior cluster analysis method of the K-Means algorithm, the learning state of students’ course Civics is carefully classified and the regression model is used to analyze the interrelationship between the dimensions of students’ Civics thinking and the constructed teaching model. Based on the effectiveness of the model proposed in this paper, we take X college as the research object and conduct empirical analysis from three aspects of students’ learning performance, learning behavior, and level of Civic and Political thinking. The results show that the F-statistics of critical thinking, creative thinking, value thinking, spiritual thinking, and conscious thinking in students’ civic thinking are 148.923, 241.125, 112.561, 83.254, and 84.968, respectively, and the significance is less than 0.05. There is a significant linear relationship between the elements of the innovative teaching model of the civic thinking of the college curriculum and the dimensions of civic thinking, which can improve the level of students’ Civic and Political Thinking.
Intelligent Design of Home Products Based on Digital Intelligence Technology
Authors: Huang Linshi 
Published: February 2024

Abstract
Aiming at the problems of high cost and too much reliance on the creator’s inspiration in traditional home product design, this paper combines digital technology to design home products. Specifically, the attention mechanism is utilized to improve the YOLOv5 network, and the home products are identified through the improved technique to obtain the home product dataset. The generative adversarial network is trained using the dataset, the new design scheme is output through the trained generative adversarial network, and the generative model is evaluated using the IoU metrics to realize the intelligent design of home products. After the model design is completed, the home products are intelligently designed according to the customer’s requirements. The IoU values of the 3D voxel model are 0.6858, 0.6872, 0.7834, and 0.6268, which are more accurate than those of other methods with contours. The European furniture IoU value is 0.534, which is higher than the generation effect of other methods and the CE value of noise floats up and down at 0.110. The 3D voxel reconstruction works best when the projection view angle K is 6, and the table works best at K=8 with 0.65. Overall, the model generated in this paper modeled 3D home products with high definition, good quality, and design.
Data-driven innovation in university library management and service models
Authors: Li Yan , Wu Shaoqun , Zhu Zhengang 
Published: February 2024

Abstract
With the rapid development of the data and information age, the digital-driven library has become an inevitable trend of library development. In this paper, through the Apriori association rule algorithm, the digital-driven library model for the influence factors of information mining, combined with data mining influence factor information to build a data-driven library management system, through the data library lending system optimization and book scheduling optimization to optimize and improve the overall optimization. Finally, it is verified through empirical analysis of association rule analysis and the scheduling effects of data-driven libraries. Through empirical analysis, it can be seen that the staff management efficiency of the management system lending system, and library circulation scheduling enhancement degree are 5.103 and 6.103, both greater than 1. The length of the reader queue and the percentage of reader loss of the data-driven library are between 5~15 and 0%~17%, respectively, and the efficiency of the data-driven library is superior to that of traditional libraries. Combined with the above, this paper based on the data-driven university library management service model can effectively solve the book scheduling problem, improve the management and service efficiency, so that readers have a better experience, and provide a guarantee for the innovative development path of the data-driven library management service model.
Artificial Intelligence-Based Comfort Assessment and Simulation of Architectural Sound Environments
Authors: Wang Weiling , Zhang Yu 
Published: February 2024

Abstract
This paper determines the influencing factors of architectural acoustic environment comfort assessment from the perspective of green building acoustic environment comfort, and constructs a two-by-two comparison judgment matrix for each questionnaire survey result. Through the consistency test of the judgment matrix, the weights of the factors influencing the comfort of the building sound environment are obtained, and the construction of the assessment model of the comfort of the building sound environment is completed. Based on the architectural acoustic environment comfort assessment model, optimization variables are selected and multi-objective optimization is used to determine the objective function and constraints of architectural acoustic environment comfort. The comfort of the acoustic environment of the campus building is evaluated and analyzed through simulation analysis. The results show that the two measurement points, point 8 and point 15, located on the north side of the library and information building and the center courtyard, respectively, have relatively low continuous sound pressure levels L
eq of 51.7 dB and 44.4 dB, respectively, which are relatively favorable for the creation of a comfortable acoustic environment. Improving the building arrangement through the multi-objective optimization method under the acoustic environment assessment model can provide good environmental protection for people’s daily lives and work.
The Construction of Interactive Teaching Platform for College English Based on Digital Intelligence Technology
Authors: Chen Qian 
Published: February 2024

Abstract
In the teaching platform, providing students with personalized learning solutions by tracking their learning status is the current trend in the development and research of digital intelligence teaching. In this paper, a Bayesian knowledge tracking model based on multiple interactions is used to construct a knowledge point tracking module, and students’ learning behaviors and memory forgetting factors are simultaneously integrated into the IBKT model to construct the PRL-PLP algorithm, and then a Bayesian knowledge tracking model integrating the behaviors and previous factors is obtained, and real-time prediction of students’ mastery is realized using the extended model. Putting the platform into use, it was observed that the total number of student logins to the platform in two days was 680, with an average of 340 logins per day. After using this educational platform for half a month, the students of class A showed an overall improvement in their English test scores compared to their scores before using the platform, with the number of students scoring less than 60 narrowing down from 5 to 0, and an increase of 5 students between the subsections of 91-100, and an increase in the subsections of 81-90, also from 26 to 43 students. By using the IBKT model in the online teaching platform, teachers and students can receive timely feedback on prediction results, teaching efficiency can be improved, and personalized learning guidance can be provided to students.
The Dilemma and Breakthrough of Professional Ethics Education for Higher Vocational Accounting Professionals in the Internet Era
Authors: Chen Xuemei , Wu Jian , Wang Hui , Zhang Yuan 
Published: February 2024

Abstract
With the development of the Internet, people are more and more pursuing the high-quality development of society, and the cultivation of high-quality talents is also more and more important. Aiming at the dilemma of professional ethics of senior accounting professionals, this paper introduces generator and discriminator structure based on a deep clustering algorithm and constructs a double autocoding deep embedded clustering model, i.e. DADEC model. After completing the model construction, iterative optimization of the clustering center is carried out by combining the small batch stochastic gradient descent and backpropagation algorithms to reduce the clustering loss. The optimized model is utilized in the professional ethics education of senior accounting professionals to categorize their dilemmas and explore breakthrough strategies. The results show that the perceptions of accounting majors in 15 higher vocational colleges and universities in terms of ethical knowledge, sense of professional dedication, professional ethical will, and professional ethical conduct are below 0.6 points. The mean value of the classroom effect of professional ethics education is 0.588, and there is a dilemma between a single teaching form and outdated teaching content. The scores of students in honesty, trustworthiness, love, and dedication are below 60 points. Although there are certain challenges in the current training of senior accounting professionals, the combination of this study points out the direction for overcoming these challenges.
Research and practical application of a bilinear integration learning model for a college psychology course
Authors: Yang Shengxue , Zheng Susheng 
Published: February 2024

Abstract
Information technology in education has triggered a change in “psychology” learning, and dual-line integrated learning will become an important form of learning in the future. The impact of information technology on education has led to changes in psychological learning, and dual-line integrated learning will become a crucial form of learning in the future. Then, based on the FuzzyCDF model of fuzzy set theory, the students’ psychology cognition, learning ability, and knowledge mastery were tested to assess the student’s cognitive level and learning effectiveness of psychology courses. Then, we analyzed the effect of dual-line integration teaching, evaluated the teaching recognition and cognition of students in different grades, and explored in depth the effects of online and offline integration teaching on students’ learning attitude, learning anxiety, self-efficacy, and academic performance. Comparative analysis was used to analyze the impact of psychology course education on students’ mental health. The results showed that the student’s recognition of the dual-line integration learning mode was all above 3.7, the correlation of the online and offline learning mode on the dimensions of students’ learning attitude, self-efficacy, and academic achievement were all between (0.12,0.65), and the negative correlation on students’ learning anxiety. Psychoeducators in colleges and universities can benefit from this study in developing effective teaching strategies and improving the quality of psychology courses for college students.
Research on the Evaluation of Deeply Intelligent Classroom Teaching and Learning in Colleges and Universities Based on Data Analysis
Authors: Liang Fenglan , Shen Weiwei , Chen Le 
Published: February 2024

Abstract
In the context of the era of modern information technology to promote the digital transformation of education, it is also imperative to explore the intelligence of classroom teaching evaluation. This paper proposes a Bayesian probabilistic model based on PyMC3, weights it, and introduces the principle of incremental learning, which greatly reduces the error of the plain Bayesian algorithm in collecting and processing data teaching evaluation data. The Bayesian algorithm is used to classify and filter original classroom teaching evaluation data. The data analysis part of this paper examines the intelligent classroom, the teacher’s lecture scoring, and the student’s grades. With the help of the weighted plain Bayesian algorithm, the level of student participation in the traditional lecture mode and intelligent classroom were determined respectively, from which the classroom acceptance level and the probability of high or low evaluation of teaching were calculated. From the data collection, it can be seen that the full attendance rate of students in three months reached 54%, and the average satisfaction score of the algorithm on the teacher’s instruction reached 0.53. Therefore, the plain Bayesian algorithm used in this paper can effectively analyze the teaching evaluation data and accurately visualize the data association between student classroom engagement and teaching evaluation.
The Two-Way Feedback of Literary and Artistic Emotional Expression and Aesthetic Nurturing from the Perspective of Poetics in the Age of Mathematical Intelligence
Authors: Liao Kemin , Liang Binghui 
Published: February 2024

Abstract
Combined with the analysis of literary and artistic emotional expression, it helps to better cultivate students’ aesthetic ability by building an effective teaching model. This paper develops a hybrid teaching mode for aesthetic cultivation that depends on an online teaching platform, based on the BOPPPS teaching model. To fully analyze the emotional expression of literature and art in the teaching mode, the multimodal features of literature and artworks were extracted from the three perspectives of text features, voice features, and visual features, and the multimodal emotional expression model of literature and artworks was established. Concerning the effectiveness of the blended teaching model of literary emotional expression and aesthetic education established in this paper, five universities in the university city of S province were selected as examples, and corresponding teaching experiments were designed and verified from various perspectives, such as teaching effect, emotional comprehension, and ability perception. The results show that the difference between the pre-and post-test scores of students’ aesthetic awareness in perceived beauty under the blended teaching mode reaches 5.51 points respectively, and the students in the experimental class improve their understanding of the natural beauty of the emotional expression of literary works by 36.82 percentage points compared with the control class. The blended teaching model can effectively enhance students’ aesthetic awareness and aesthetic concepts, to better understand the embedded emotions of literary and artistic works, and the two complement each other to enhance students’ aesthetic core literacy.
Research on Strategies of English Teaching Reform in Colleges and Universities Supported by Artificial Intelligence Technology
Authors: Ma Shu , Wang Tianxiao 
Published: February 2024

Abstract
The way that artificial intelligence technology is being developed is causing a progressive evolution in college and university teaching methods and systems. This paper presents the design of the English teaching mode in colleges and universities based on artificial intelligence technology. Research on strategies for English teaching reform in colleges and universities supported by artificial intelligence technology. A weighted inference model was used to design an AI expert system, based on which an intelligent assisted learning system based on a neural network was constructed using the law of knowledge forgetting. Based on information acquisition, the random Linsen method was selected as the assessment methodology for the impact of English instruction in colleges and universities. The assessment model’s performance and errors are examined through comparison tests of the teaching evaluation model. In this article, the educational effect evaluation model has an accuracy rate of 91% and a mean square error of less than 0.002. The impact of AI-assisted English instruction on teaching is evaluated based on this. Results from studies conducted both before and following the experimental group show that the overall score increases by 12.33 points and the P-value of the four dimensions’ teaching effect is less than 0.01. The experimental group using artificial intelligence technology for English instruction received an average comprehensive score of 95 points in the actual English assessment, which is 8 points higher than the control group receiving traditional English instruction. This paper’s artificial intelligence teaching mode is believed to have a significant impact on students’ English, which is confirmed by its effectiveness and rationality. It is beneficial for teaching reform and guides enhancing and advancing English instruction in colleges and institutions.
Experimental Validation: Perception and Localization Systems for Autonomous Vehicles using the Extended Kalman Filter Algorithm
Authors: Widjiantoro Bambang Lelono , Indriawati Katherin , Alexander Buyung T. S. N. , Wahyuadnyana Kadek Dwi 
Published: February 2024

Abstract
This study validates EKF-SLAM for indoor autonomous vehicles by experimentally integrating the MPU6050 sensor and encoder data using an extended Kalman filter. Real-world tests show significant improvements, achieving high accuracy with just 1% and 3% errors in the X and Y axes. RPLiDAR A1M8 is utilized for mapping, producing accurate maps visualized through RViz-ROS. The research demonstrates the novelty and practical utility of EKF-SLAM in real-world scenarios, showcasing unprecedented effectiveness and precision.
Cognitive Modeling as a Forecasting Tool
Authors: Makarenya Tatyana A. , Mannaa Ali Sajae , Kalinichenko Alexey I. , Petrenko Svetlana V. 
Published: February 2024

Abstract
Under the current geopolitical conditions and the economic sanctions imposed on Russia, there is an objective need to formulate a strategic development plan for the economy as a whole and for specific sectors of the economy. Various methods and tools can be used for strategic planning. One of the methods of strategic planning is the program-targeted method of planning, which has proved to be an effective method of foresight. It is possible to speak about failures of planning activities, but these failures were related not only to shortcomings and application of science-based planning methods but also to the efficiency of the managerial apparatus, which took decisions. It should be noted that it was in the period when science-based planning methods were applied that our country managed to form and develop industrial production in various sectors, and the issue of import substitution did not arise then, as all the stages of the product life cycle were represented at all the enterprises. Currently, the country is facing the problem of strategic development in the context of the imposed economic sanctions. The volume of sanctions is increasing day by day and one can only speculate on the future restrictions imposed. Therefore, there is a need to forecast activities at the level of the whole country, individual industries, and enterprises. One such method is cognitive modeling based on fuzzy logic. This approach involves the use of cognitive principles and methods to understand the behavior of individuals in the system, as well as the interactions and feedback loops between the various components. The purpose of this paper is to retrospectively analyze the application of the cognitive method to modeling. Information systems that have been developed in our country to implement the tasks of cognitive modeling are reviewed, and an assessment of existing software products is made. Also, theoretical materials on cognitive approach in modeling are presented in order to understand the application of this toolkit for modeling socioeconomic systems using elements of fuzzy logic.
Adaptive block size selection in a hybrid image compression algorithm employing the DCT and SVD
Authors: Garg Garima , Kumar Raman 
Published: February 2024

Abstract
The rationale behind this research stems from practical implementations in real-world scenarios, recognizing the critical importance of efficient image compression in fields such as medical imaging, remote sensing, and multimedia communication. This study introduces a hybrid image compression technique that employs adaptive block size selection and a synergistic combination of the discrete cosine transform (DCT) and singular value decomposition (SVD) to enhance compression efficiency while maintaining picture quality. Motivated by the potential to achieve significant compression ratios imperceptible to human observers, the hybrid approach addresses the escalating need for real-time image processing. The study pushes the boundaries of image compression by developing an algorithm that effectively combines conventional approaches with the intricacies of modern images, aiming for high compression ratios, adaptive picture content, and real-time efficiency. This article presents a novel hybrid algorithm that dynamically combines the DCT, SVD, and adaptive block size selection to enhance compression performance while keeping image quality constant. The proposed technique exhibits noteworthy accomplishments, achieving compression ratios of up to 60% and a peak signal-to-noise ratio (PSNR) exceeding 35 dB. Comparative evaluations demonstrate the algorithm’s superiority over existing approaches in terms of compression efficiency and quality measures. The adaptability of this hybrid approach makes significant contributions across various disciplines. In multimedia, it enhances data utilization while preserving image integrity; in medical imaging, it guarantees accurate diagnosis with compression-induced distortion (CID) below 1%; and in remote sensing, it efficiently manages large datasets, reducing expenses. The flexibility of this algorithm positions it as a valuable tool for future advancements in the rapidly evolving landscape of technology.