This study explores the application of virtual reality technology and traditional offline hybrid teaching mode for the specialized course “Animation Laws of Motion”. Through the improved ORB algorithm, this paper effectively combines the BRIEF and ORB image feature and matching algorithms to optimize capturing and matching image features. Two classes of animation majors in a school were selected for experiments in the study, and the effects of the two teaching modes were compared through half-term tests, pre- and post-test question analyses, and questionnaire surveys. The results show that after the teaching assisted by VR animation technology, students’ acceptance and emotional attitudes are significantly improved, and the students in the experimental class better mastered the six motion methods in the animation motion course and completed the animation design tasks with high quality. In the animation modeling course, the proportion of low-quality works in the experimental class is only 4%, showing significant teaching effects. The Research in this paper provides empirical support for the application of virtual reality technology in animation education. It demonstrates the potential of combining VR technology with traditional teaching in enhancing teaching effectiveness.
{"title":"Practice and Exploration of Blended Teaching Based on VR Animation Laws of Motion Course","authors":"Jiansong Zhao, Intan Khasumarlina binti Mohd Khalid, Fangfang Wan, Pingfei Zhang","doi":"10.2478/amns-2024-0418","DOIUrl":"https://doi.org/10.2478/amns-2024-0418","url":null,"abstract":"\u0000 This study explores the application of virtual reality technology and traditional offline hybrid teaching mode for the specialized course “Animation Laws of Motion”. Through the improved ORB algorithm, this paper effectively combines the BRIEF and ORB image feature and matching algorithms to optimize capturing and matching image features. Two classes of animation majors in a school were selected for experiments in the study, and the effects of the two teaching modes were compared through half-term tests, pre- and post-test question analyses, and questionnaire surveys. The results show that after the teaching assisted by VR animation technology, students’ acceptance and emotional attitudes are significantly improved, and the students in the experimental class better mastered the six motion methods in the animation motion course and completed the animation design tasks with high quality. In the animation modeling course, the proportion of low-quality works in the experimental class is only 4%, showing significant teaching effects. The Research in this paper provides empirical support for the application of virtual reality technology in animation education. It demonstrates the potential of combining VR technology with traditional teaching in enhancing teaching effectiveness.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140519357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, a large amount of data related to the teaching of ideological and political courses is collected using information technology and preprocessed in the four dimensions of data cleaning, missing value processing, sample labeling, and expert sample data. Aiming at the problem of underfitting of traditional neural network algorithm in the evaluation of digital teaching effect of ideological and political courses, the RBF neural network is improved and optimized by combining radial basis function and radial basis interpolation, and a teaching evaluation model based on the enhanced RBF network is constructed. The combination of statistical and simulation analysis is used to analyze the learning behavior of digitally empowered ideological and political courses. The results show that among the five types of teaching activities, participation in after-class discussion (-1.6443) performs better compared to the other four types of teaching activities (-1.7541, -1.6815, 1.7331, -1.8265), indicating that the neural network algorithm based on the Improved RBF accurately reflects the learning behavior of the group in the teaching of Digital Empowerment Ideology and Politics Course. This study realizes the scientific, modern and intelligent development of digitally empowered ideological and political course teaching. It promotes digital ideological and political course teaching to be more and more scientific and philosophical.
{"title":"An innovative model of digitally empowered teaching of ideological and political courses for university students","authors":"Han Yang","doi":"10.2478/amns-2024-0326","DOIUrl":"https://doi.org/10.2478/amns-2024-0326","url":null,"abstract":"\u0000 In this paper, a large amount of data related to the teaching of ideological and political courses is collected using information technology and preprocessed in the four dimensions of data cleaning, missing value processing, sample labeling, and expert sample data. Aiming at the problem of underfitting of traditional neural network algorithm in the evaluation of digital teaching effect of ideological and political courses, the RBF neural network is improved and optimized by combining radial basis function and radial basis interpolation, and a teaching evaluation model based on the enhanced RBF network is constructed. The combination of statistical and simulation analysis is used to analyze the learning behavior of digitally empowered ideological and political courses. The results show that among the five types of teaching activities, participation in after-class discussion (-1.6443) performs better compared to the other four types of teaching activities (-1.7541, -1.6815, 1.7331, -1.8265), indicating that the neural network algorithm based on the Improved RBF accurately reflects the learning behavior of the group in the teaching of Digital Empowerment Ideology and Politics Course. This study realizes the scientific, modern and intelligent development of digitally empowered ideological and political course teaching. It promotes digital ideological and political course teaching to be more and more scientific and philosophical.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140527365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Establishing a teaching resource base for English in higher vocational education is one of the effective informatization reform measures. In this paper, the basic framework of English teaching resource base based on a knowledge graph is firstly designed to semantically describe and organize the existing teaching resource organization structure and storage method in the form of a graph based on text semantic coding. Using entity linking technology and knowledge point automated association method, the entity vocabulary in the text is identified and linked to the corresponding entities in the knowledge base to realize the association between teaching resources and knowledge points. Then, the cosine similarity between historical learning resources and teaching resources in terms of semantic features is calculated, and resource recommendation is carried out based on the knowledge connectivity between user interests and resources. The evaluation of the teaching resource library’s performance and its effect on students’ English learning and teachers’ teaching ability is concluded. The results show that users’ evaluations of the indicators of the teaching resource library are concentrated between (3.9-4.4), the p-values of the dimensions of students’ English knowledge in the two cases of yes/no use of the resource library are 0.010, 0.047, 0.038, 0.035, 0.018, and 0.026, and there is a significant variability of the teacher’s teaching ability at the level of 5 percent. This study offers guidance on how to promote the reform of English curriculum construction, optimize teaching resources, and enhance teachers’ overall teaching ability.
{"title":"The Construction of English Teaching Resource Base in Colleges and Universities Based on Knowledge Graphs","authors":"Xiaohua Liang","doi":"10.2478/amns-2024-0039","DOIUrl":"https://doi.org/10.2478/amns-2024-0039","url":null,"abstract":"\u0000 Establishing a teaching resource base for English in higher vocational education is one of the effective informatization reform measures. In this paper, the basic framework of English teaching resource base based on a knowledge graph is firstly designed to semantically describe and organize the existing teaching resource organization structure and storage method in the form of a graph based on text semantic coding. Using entity linking technology and knowledge point automated association method, the entity vocabulary in the text is identified and linked to the corresponding entities in the knowledge base to realize the association between teaching resources and knowledge points. Then, the cosine similarity between historical learning resources and teaching resources in terms of semantic features is calculated, and resource recommendation is carried out based on the knowledge connectivity between user interests and resources. The evaluation of the teaching resource library’s performance and its effect on students’ English learning and teachers’ teaching ability is concluded. The results show that users’ evaluations of the indicators of the teaching resource library are concentrated between (3.9-4.4), the p-values of the dimensions of students’ English knowledge in the two cases of yes/no use of the resource library are 0.010, 0.047, 0.038, 0.035, 0.018, and 0.026, and there is a significant variability of the teacher’s teaching ability at the level of 5 percent. This study offers guidance on how to promote the reform of English curriculum construction, optimize teaching resources, and enhance teachers’ overall teaching ability.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140519403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study focuses on the innovative teaching mode of design aesthetics education in the information age, and builds a flipped classroom and blended teaching mode of design aesthetics based on MOOC+SPOC platform. The study points out that traditional design aesthetics education needs to integrate modern technology to enhance students’ aesthetic ability and innovation literacy. By conducting teaching experiments in 10 colleges and universities, the results show that students using the blended teaching mode significantly outperform the traditional teaching mode in terms of design aesthetics performance, interest and cognitive learning effects. The study also proposes a personalized recommendation method to effectively promote students’ in-depth learning of design aesthetics. The conclusion emphasizes that design aesthetics education in the information age should focus on technology integration and teaching mode innovation to improve the teaching effect and cultivate design aesthetics talents adapted to the development of the times.
{"title":"The Value and Significance of Design Aesthetics Education in the Information Age","authors":"Ximei Gao, Yuhwa Wang","doi":"10.2478/amns-2024-0650","DOIUrl":"https://doi.org/10.2478/amns-2024-0650","url":null,"abstract":"\u0000 This study focuses on the innovative teaching mode of design aesthetics education in the information age, and builds a flipped classroom and blended teaching mode of design aesthetics based on MOOC+SPOC platform. The study points out that traditional design aesthetics education needs to integrate modern technology to enhance students’ aesthetic ability and innovation literacy. By conducting teaching experiments in 10 colleges and universities, the results show that students using the blended teaching mode significantly outperform the traditional teaching mode in terms of design aesthetics performance, interest and cognitive learning effects. The study also proposes a personalized recommendation method to effectively promote students’ in-depth learning of design aesthetics. The conclusion emphasizes that design aesthetics education in the information age should focus on technology integration and teaching mode innovation to improve the teaching effect and cultivate design aesthetics talents adapted to the development of the times.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140516473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Information technology, as the driving force of a new round of technological and industrial changes, brings new opportunities to sports training. In this paper, a dynamic threshold step monitoring strategy based on sinusoidal waveform curve of acceleration change is designed, and blood oxygen saturation content is monitored by near-infrared spectroscopy. By mining the high-frequency exercise load monitoring information, the intelligent sports training model is discussed in depth. In the application effect study at X University of S Province, the model successfully measured the average heart rate of students to be 160.91 beats/minute and the average energy consumption to be 137.27 Kcal, which provided a critical decision-making basis for physical education teaching. This finding offers a scientific implementation program for reforming physical education in colleges and universities, ensuring that physical training is accomplished efficiently and highly.
信息技术作为新一轮科技和产业变革的驱动力，为体育训练带来了新的机遇。本文设计了基于加速度变化正弦波形曲线的动态阈值阶跃监测策略，并利用近红外光谱监测血氧饱和度含量。通过对高频运动负荷监测信息的挖掘，深入探讨了智能运动训练模型。在 S 省 X 大学的应用效果研究中，该模型成功测得学生的平均心率为 160.91 次/分钟，平均能量消耗为 137.27 千卡，为体育教学提供了重要的决策依据。这一研究成果为高校体育教学改革提供了科学的实施方案，确保体育训练高效、高质地完成。
{"title":"The Innovative Development Path of Intelligent Sports Training in Colleges and Universities under the Perspective of National Fitness","authors":"De-an Tian, Bo Liu","doi":"10.2478/amns-2024-0331","DOIUrl":"https://doi.org/10.2478/amns-2024-0331","url":null,"abstract":"\u0000 Information technology, as the driving force of a new round of technological and industrial changes, brings new opportunities to sports training. In this paper, a dynamic threshold step monitoring strategy based on sinusoidal waveform curve of acceleration change is designed, and blood oxygen saturation content is monitored by near-infrared spectroscopy. By mining the high-frequency exercise load monitoring information, the intelligent sports training model is discussed in depth. In the application effect study at X University of S Province, the model successfully measured the average heart rate of students to be 160.91 beats/minute and the average energy consumption to be 137.27 Kcal, which provided a critical decision-making basis for physical education teaching. This finding offers a scientific implementation program for reforming physical education in colleges and universities, ensuring that physical training is accomplished efficiently and highly.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140526320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The article establishes the objective function of distributed electronic and electrical architecture from three dimensions of economy, quantization and loadability, and constructs a mathematical model for multi-objective optimization based on the satisfaction of constraints. The model was applied and tested in the intelligent control system of automotive industrial equipment. In practical applications, the intelligent control system can automatically reduce the speed to 16km/h to maintain a safe distance and prevent collision when the target vehicle is monitored to enter the lane it is in and the distance between the two cars is less than 30 meters. Under 1500 pcu/h traffic flow conditions, the average delays of vehicles at the intersection through intelligent control were only 8.06 seconds and 8.02 seconds, compared to 20.58 seconds and 23.29 seconds for vehicles under conventional control. Vehicle intelligent control systems based on distributed electronic and electrical architectures have great potential for development and significant safety performance improvement in automotive industrial equipment manufacturing. The research in this paper provides a new perspective and adequate technical support for the intelligent control of future industrial equipment.
{"title":"An Intelligent Control Method for Industrial Equipment Based on Distributed Electrical and Electronic Architecture","authors":"Xiaodong Han","doi":"10.2478/amns-2024-0451","DOIUrl":"https://doi.org/10.2478/amns-2024-0451","url":null,"abstract":"\u0000 The article establishes the objective function of distributed electronic and electrical architecture from three dimensions of economy, quantization and loadability, and constructs a mathematical model for multi-objective optimization based on the satisfaction of constraints. The model was applied and tested in the intelligent control system of automotive industrial equipment. In practical applications, the intelligent control system can automatically reduce the speed to 16km/h to maintain a safe distance and prevent collision when the target vehicle is monitored to enter the lane it is in and the distance between the two cars is less than 30 meters. Under 1500 pcu/h traffic flow conditions, the average delays of vehicles at the intersection through intelligent control were only 8.06 seconds and 8.02 seconds, compared to 20.58 seconds and 23.29 seconds for vehicles under conventional control. Vehicle intelligent control systems based on distributed electronic and electrical architectures have great potential for development and significant safety performance improvement in automotive industrial equipment manufacturing. The research in this paper provides a new perspective and adequate technical support for the intelligent control of future industrial equipment.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140516510","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper is dedicated to exploring the digital design of modern sculpture in the era of new media, addressing the challenges and opportunities encountered by traditional sculpture in digital transformation. Considering the innovation brought by digital technology to artistic creation, the precision and efficiency of sculpture digitization are improved by introducing advanced NURBS method and FCM clustering algorithm through precise analysis and characterization of surface geometric parameters of three-dimensional sculptures. The surface geometric parameters and characteristics of three-dimensional sculptures are analyzed using non-uniform rational B-spline (NURBS) and fuzzy C-mean (FCM) clustering algorithms. The high-order surfaces of the sculptures can be represented effectively by the NURBS method, whereas the FCM clustering algorithms exhibit highly efficient performance in surface partitioning planning. The NURBS-based FCM algorithm can reduce the root-mean-square error of point cloud splicing to 0.0853 mm, reduce the number of iterations to 3, and shorten the algorithm’s running time to 18.46 seconds. The practice of digital sculpture application shows that the method improves work efficiency and reduces production costs. The digital design method proposed in this study provides a new way of producing and creating modern sculpture, which helps develop and preserve traditional sculpture art in the new media era.
{"title":"Research on Digital Design of Modern Sculpture in New Media Era","authors":"Xiaozhong Chen, Chaoyang Zhang","doi":"10.2478/amns-2024-0816","DOIUrl":"https://doi.org/10.2478/amns-2024-0816","url":null,"abstract":"\u0000 This paper is dedicated to exploring the digital design of modern sculpture in the era of new media, addressing the challenges and opportunities encountered by traditional sculpture in digital transformation. Considering the innovation brought by digital technology to artistic creation, the precision and efficiency of sculpture digitization are improved by introducing advanced NURBS method and FCM clustering algorithm through precise analysis and characterization of surface geometric parameters of three-dimensional sculptures. The surface geometric parameters and characteristics of three-dimensional sculptures are analyzed using non-uniform rational B-spline (NURBS) and fuzzy C-mean (FCM) clustering algorithms. The high-order surfaces of the sculptures can be represented effectively by the NURBS method, whereas the FCM clustering algorithms exhibit highly efficient performance in surface partitioning planning. The NURBS-based FCM algorithm can reduce the root-mean-square error of point cloud splicing to 0.0853 mm, reduce the number of iterations to 3, and shorten the algorithm’s running time to 18.46 seconds. The practice of digital sculpture application shows that the method improves work efficiency and reduces production costs. The digital design method proposed in this study provides a new way of producing and creating modern sculpture, which helps develop and preserve traditional sculpture art in the new media era.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140521174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the quest to safeguard and revitalize folk dance heritage, this study explores the transformative potential of virtual reality (VR) technology. We developed an immersive display system using the Unreal game engine, incorporating a dance movement database, virtual reality immersion, and precise inertial motion capture. This innovative approach captivates users with an immersive folk dance experience and boasts a high motion recognition accuracy (99.51%) and an overall accuracy of 96%. Comparative experiments highlight VR’s advantages in making folk dance education more interactive and enjoyable without sacrificing ease of use. Virtual reality emerges as a vital tool in engaging new generations with folk dance, suggesting a vibrant future for intangible cultural heritage preservation.
{"title":"Innovative Strategies of Virtual Reality Technology in Ethnic Dance Inheritance","authors":"Wen Cai, Wenfeng Liu","doi":"10.2478/amns-2024-0844","DOIUrl":"https://doi.org/10.2478/amns-2024-0844","url":null,"abstract":"\u0000 In the quest to safeguard and revitalize folk dance heritage, this study explores the transformative potential of virtual reality (VR) technology. We developed an immersive display system using the Unreal game engine, incorporating a dance movement database, virtual reality immersion, and precise inertial motion capture. This innovative approach captivates users with an immersive folk dance experience and boasts a high motion recognition accuracy (99.51%) and an overall accuracy of 96%. Comparative experiments highlight VR’s advantages in making folk dance education more interactive and enjoyable without sacrificing ease of use. Virtual reality emerges as a vital tool in engaging new generations with folk dance, suggesting a vibrant future for intangible cultural heritage preservation.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140516552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper investigates music education, where an efficient and accurate performance evaluation system in the piano teaching and performance ecosystem is increasingly becoming an essential tool for improving teaching quality and performance level. The objective evaluation of students’ performance skills can be achieved by carefully analyzing piano performances using the network flow optimization technique. This technique optimizes the performance evaluation system’s audio recognition ability by analyzing the piano audio signal and solving the multi-constraint nonlinear optimization problem in a limited time domain. This paper establishes a network flow optimization model, applies the multi-constraint nonlinear optimization technique, and combines the non-negative matrix decomposition and dynamic time regularization algorithm to analyze the piano performance for experiments. After optimization processing, hundreds of piano audio samples were collected, and the audio recognition accuracy was improved by 20%. By optimizing and processing the audio signals from the network stream, the evaluation system could detect polyphony more accurately and track the musical score effectively, improving accuracy and efficiency. Using the non-negative matrix decomposition algorithm, the accuracy of detecting polyphony can reach 85%, while the dynamic temporal regularization algorithm can match the position of the musical score with 95% accuracy. The accuracy of piano performance evaluation is optimized by this network flow optimization method, providing new technical means for music education, and promoting the quality of teaching and performance.
{"title":"Research on Piano Curriculum Education and Its Performance Ecosystem Based on Network Flow Optimization","authors":"Huang Wang","doi":"10.2478/amns-2024-0830","DOIUrl":"https://doi.org/10.2478/amns-2024-0830","url":null,"abstract":"\u0000 This paper investigates music education, where an efficient and accurate performance evaluation system in the piano teaching and performance ecosystem is increasingly becoming an essential tool for improving teaching quality and performance level. The objective evaluation of students’ performance skills can be achieved by carefully analyzing piano performances using the network flow optimization technique. This technique optimizes the performance evaluation system’s audio recognition ability by analyzing the piano audio signal and solving the multi-constraint nonlinear optimization problem in a limited time domain. This paper establishes a network flow optimization model, applies the multi-constraint nonlinear optimization technique, and combines the non-negative matrix decomposition and dynamic time regularization algorithm to analyze the piano performance for experiments. After optimization processing, hundreds of piano audio samples were collected, and the audio recognition accuracy was improved by 20%. By optimizing and processing the audio signals from the network stream, the evaluation system could detect polyphony more accurately and track the musical score effectively, improving accuracy and efficiency. Using the non-negative matrix decomposition algorithm, the accuracy of detecting polyphony can reach 85%, while the dynamic temporal regularization algorithm can match the position of the musical score with 95% accuracy. The accuracy of piano performance evaluation is optimized by this network flow optimization method, providing new technical means for music education, and promoting the quality of teaching and performance.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140518702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The article analyzes the precise teaching reform by applying artificial intelligence technology in English teaching in colleges and universities to improve teaching efficiency and student learning effect. The study establishes an English teaching model based on learner profiling, using artificial intelligence technology for student data analysis to achieve personalized customization of teaching content. Through empirical analysis, this study found that the experimental class adopting this teaching model significantly improved classroom interaction, learner class profile, and English performance. The average score of English assessment of students in the practical class increased from 55.5465 to 78.7267, and the passing rate also increased significantly. In addition, the teaching mode can effectively reduce the degree of dispersion of students’ performance and reduce the performance differences among students. The application of artificial intelligence technology in English teaching in colleges and universities can effectively promote students’ learning interest and performance improvement, providing a new direction for reforming English teaching in colleges and universities.
{"title":"Research on the Reform of English Precision Teaching in Colleges and Universities Facilitated by Artificial Intelligence Technology","authors":"Lirong Wang, Junli Yu","doi":"10.2478/amns-2024-0627","DOIUrl":"https://doi.org/10.2478/amns-2024-0627","url":null,"abstract":"\u0000 The article analyzes the precise teaching reform by applying artificial intelligence technology in English teaching in colleges and universities to improve teaching efficiency and student learning effect. The study establishes an English teaching model based on learner profiling, using artificial intelligence technology for student data analysis to achieve personalized customization of teaching content. Through empirical analysis, this study found that the experimental class adopting this teaching model significantly improved classroom interaction, learner class profile, and English performance. The average score of English assessment of students in the practical class increased from 55.5465 to 78.7267, and the passing rate also increased significantly. In addition, the teaching mode can effectively reduce the degree of dispersion of students’ performance and reduce the performance differences among students. The application of artificial intelligence technology in English teaching in colleges and universities can effectively promote students’ learning interest and performance improvement, providing a new direction for reforming English teaching in colleges and universities.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140517109","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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