Pub Date : 2023-12-02DOI: 10.2478/amns.2023.2.01321
Guanglei Zhang
Abstract In this paper, the TR graph is constructed by combining the advantages of the tree diagram and Nightingale’s rose diagram, followed by the use of the LR+GBDT fusion model for predicting students’ performance. For the shortcomings of the K-prototypes algorithm in the application of educational data, an improved K-prototypes algorithm for student group division and feature labeling, and finally, user portrait as a pivot will be the fusion of the three to solve the problem of multi-chart linkage and the integration of charts constructed the student portrait, assisting teachers to make scientific decisions to develop personalized learning strategies. Through the integration of social resources and the curriculum content of the ideological and political discipline, a project-based learning model is established to realize the goal of cultivating students’ core qualities in the discipline of the ideological and political discipline. After the project-based learning mode, the difference between the pre-test and post-test scores of the experimental class’ ideological and political character was −6.83, p=0.000<0.001, the difference between the pre-test and post-test scores of cultural literacy was −7.12, p=0.000<0.001, and the difference between the pre-test and post-test scores of the value concept dimension was −3.54, p=0.027<0.05. There was a significant difference between the pre-test and post-test scores of the three dimensions, and there was a significant difference in the pre-test and post-test scores of all three dimensions. Scores between the pre-and post-tests were significantly different. Therefore, the application of project-based learning in the teaching of Civics and Political Science plays an important role in promoting.
{"title":"Application of Project-based Learning Model Based on GBDT Model in Higher Vocational Civics Classes at the Time of Innovation","authors":"Guanglei Zhang","doi":"10.2478/amns.2023.2.01321","DOIUrl":"https://doi.org/10.2478/amns.2023.2.01321","url":null,"abstract":"Abstract In this paper, the TR graph is constructed by combining the advantages of the tree diagram and Nightingale’s rose diagram, followed by the use of the LR+GBDT fusion model for predicting students’ performance. For the shortcomings of the K-prototypes algorithm in the application of educational data, an improved K-prototypes algorithm for student group division and feature labeling, and finally, user portrait as a pivot will be the fusion of the three to solve the problem of multi-chart linkage and the integration of charts constructed the student portrait, assisting teachers to make scientific decisions to develop personalized learning strategies. Through the integration of social resources and the curriculum content of the ideological and political discipline, a project-based learning model is established to realize the goal of cultivating students’ core qualities in the discipline of the ideological and political discipline. After the project-based learning mode, the difference between the pre-test and post-test scores of the experimental class’ ideological and political character was −6.83, p=0.000<0.001, the difference between the pre-test and post-test scores of cultural literacy was −7.12, p=0.000<0.001, and the difference between the pre-test and post-test scores of the value concept dimension was −3.54, p=0.027<0.05. There was a significant difference between the pre-test and post-test scores of the three dimensions, and there was a significant difference in the pre-test and post-test scores of all three dimensions. Scores between the pre-and post-tests were significantly different. Therefore, the application of project-based learning in the teaching of Civics and Political Science plays an important role in promoting.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":"77 9","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138606021","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}
Pub Date : 2023-12-02DOI: 10.2478/amns.2023.2.01329
Qiang Zhen, Ling Shen
Abstract Once the failure of rotating machinery occurs, it may cause the whole system to paralyze and cause great economic losses, or it may cause casualties. Therefore, the prediction of the remaining life of bearings is of great significance. The purpose of this paper is to analyze the approximate modeling technology and develop a framework for combined approximate modeling technology. A multi-strategy radial-based approximate model optimization model is proposed based on the limitations of radial-based approximate model technology. Utilizing the weight coefficient solving technique, the variable confidence RBF model, i.e., RBF-LSTM model, is established. Propose the remaining methods for life prediction using the bearing life prediction process. The RBF-LSTM combined approximation model is used to construct the evaluation index for rolling bearing remaining life prediction. Using the empirical analysis method, the optimization effects of different models and the accuracy of bearing remaining life prediction are analyzed, respectively. Experiments show that the data range of the RBF-LSTM combined approximation model is between [23,52], the overall fluctuation range of the data is not large, and the time taken is only 31 s. After 230 calculations, the model optimization effect is better. In the remaining life validation, the starting values of 132h and 148h are less different from real life, only 1.53h and 1.3h, respectively, and the model prediction accuracy is high.
{"title":"Residual life prediction of bearings based on RBF approximation models","authors":"Qiang Zhen, Ling Shen","doi":"10.2478/amns.2023.2.01329","DOIUrl":"https://doi.org/10.2478/amns.2023.2.01329","url":null,"abstract":"Abstract Once the failure of rotating machinery occurs, it may cause the whole system to paralyze and cause great economic losses, or it may cause casualties. Therefore, the prediction of the remaining life of bearings is of great significance. The purpose of this paper is to analyze the approximate modeling technology and develop a framework for combined approximate modeling technology. A multi-strategy radial-based approximate model optimization model is proposed based on the limitations of radial-based approximate model technology. Utilizing the weight coefficient solving technique, the variable confidence RBF model, i.e., RBF-LSTM model, is established. Propose the remaining methods for life prediction using the bearing life prediction process. The RBF-LSTM combined approximation model is used to construct the evaluation index for rolling bearing remaining life prediction. Using the empirical analysis method, the optimization effects of different models and the accuracy of bearing remaining life prediction are analyzed, respectively. Experiments show that the data range of the RBF-LSTM combined approximation model is between [23,52], the overall fluctuation range of the data is not large, and the time taken is only 31 s. After 230 calculations, the model optimization effect is better. In the remaining life validation, the starting values of 132h and 148h are less different from real life, only 1.53h and 1.3h, respectively, and the model prediction accuracy is high.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":"42 2","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138606758","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}
Pub Date : 2023-12-02DOI: 10.2478/amns.2023.2.01336
Jianhua Du
Abstract This paper starts with the application of hyper-convergence technology, builds the framework of a university smart campus based on it, and gives the framework description of the smart campus. In order to analyze the network security for the smart campus, the Markov model is used as the basis combined with the reinforced Q learning algorithm for network node security detection, and a specific simulation analysis is given. The encryption performance and defense performance of the elliptic curve cryptosystem are analyzed through the elliptic curve cryptosystem to formulate the encryption scheme for students’ private data in the smart campus. The results indicate that the Markov model node detection combined with reinforcement Q-learning in this paper takes a maximum time of about 5.75s when the network node size reaches 150. When the number of nodes in the smart campus network is 30, under brute force attack, the whole network is captured only when the number of malicious nodes increases to more than 22, while under random attack, it takes as many as 30 malicious nodes to join before the network completely falls. This illustrates that the use of the Markov model can be realized to analyze the network security of the smart campus and that student privacy protection needs to further improve the awareness of student data privacy protection and develop the habit of assessing the privacy risk beforehand in their daily network behavior.
{"title":"Optimization of Smart Campus Cybersecurity and Student Privacy Protection Paths Based on Markov Models","authors":"Jianhua Du","doi":"10.2478/amns.2023.2.01336","DOIUrl":"https://doi.org/10.2478/amns.2023.2.01336","url":null,"abstract":"Abstract This paper starts with the application of hyper-convergence technology, builds the framework of a university smart campus based on it, and gives the framework description of the smart campus. In order to analyze the network security for the smart campus, the Markov model is used as the basis combined with the reinforced Q learning algorithm for network node security detection, and a specific simulation analysis is given. The encryption performance and defense performance of the elliptic curve cryptosystem are analyzed through the elliptic curve cryptosystem to formulate the encryption scheme for students’ private data in the smart campus. The results indicate that the Markov model node detection combined with reinforcement Q-learning in this paper takes a maximum time of about 5.75s when the network node size reaches 150. When the number of nodes in the smart campus network is 30, under brute force attack, the whole network is captured only when the number of malicious nodes increases to more than 22, while under random attack, it takes as many as 30 malicious nodes to join before the network completely falls. This illustrates that the use of the Markov model can be realized to analyze the network security of the smart campus and that student privacy protection needs to further improve the awareness of student data privacy protection and develop the habit of assessing the privacy risk beforehand in their daily network behavior.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":"19 2","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138607088","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}
Pub Date : 2023-12-02DOI: 10.2478/amns.2023.2.01320
Yingnan Xiao
Abstract This paper mainly investigates the attitude control method of the quadrotor against unknown external interference and improves the control accuracy for the subsequent design of the control algorithm by establishing a more accurate mathematical model of the quadrotor. The extended Kalman filtering algorithm is used to obtain the real-time attitude state of the vehicle for attitude solving. The inertial guidance fusion uses the Kalman filter algorithm with delay correction to estimate the vehicle’s position and velocity information. Finally, the attitude control method of serial linear self-immunity control is proposed, which estimates and compensates for the external perturbation and internal uncertainty in real-time by linear expansion observer, while the position controller is designed by using PIV control. The simulation study analyzes that this paper’s method reduces the UAV attitude angle maximum error magnitude between about 1.04° and 4.07°compared with the traditional ADRC and serial PID. The maximum tracking error of pitch angle under white noise interference is only 0.37°using the control method of this paper, and the fluctuation amplitude is reduced by 0.81 on average, which shows a stronger anti-interference ability.
{"title":"Machine learning-based design of a linear self-resistant attitude control system for UAV string level","authors":"Yingnan Xiao","doi":"10.2478/amns.2023.2.01320","DOIUrl":"https://doi.org/10.2478/amns.2023.2.01320","url":null,"abstract":"Abstract This paper mainly investigates the attitude control method of the quadrotor against unknown external interference and improves the control accuracy for the subsequent design of the control algorithm by establishing a more accurate mathematical model of the quadrotor. The extended Kalman filtering algorithm is used to obtain the real-time attitude state of the vehicle for attitude solving. The inertial guidance fusion uses the Kalman filter algorithm with delay correction to estimate the vehicle’s position and velocity information. Finally, the attitude control method of serial linear self-immunity control is proposed, which estimates and compensates for the external perturbation and internal uncertainty in real-time by linear expansion observer, while the position controller is designed by using PIV control. The simulation study analyzes that this paper’s method reduces the UAV attitude angle maximum error magnitude between about 1.04° and 4.07°compared with the traditional ADRC and serial PID. The maximum tracking error of pitch angle under white noise interference is only 0.37°using the control method of this paper, and the fluctuation amplitude is reduced by 0.81 on average, which shows a stronger anti-interference ability.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":"117 48","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138607561","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}
Pub Date : 2023-12-02DOI: 10.2478/amns.2023.2.01331
Liping Xiang
Abstract Re-employment of the mobile elderly population is an important factor in promoting the development of social integration, and the study of the interaction between the two can further realize re-employment. This paper evaluates the level of social integration from four dimensions: economic integration, behavioral integration, cultural integration, and psychological integration, and explains different integration indicators. The indicator factors and their weights of the social integration measurement model were identified through the use of factor analysis and principal component analysis. At the same time, categorical variables were used to set up the re-employment mode of the migrant elderly population, which led to the formulation of three research hypotheses on the impact of social integration. In the description of the overall characteristics of the re-employment of the mobile elderly population, with the help of the multiple covariance test to confirm the accuracy of the estimation of the impact effect, binary logistic regression is used to verify the relationship between the impact of social integration on the re-employment of the mobile elderly population. The test results show that the minimum value of tolerance is 0.804, and the maximum value is 0.954. The maximum value of VIF is 1.199, and the minimum value is 1.009. Model 1 shows that social integration has a negative effect on re-employment of the mobile elderly population, and the value of EXP(B) is 0.541. This study verifies the relationship of the effect of social integration on re-employment and guides the re-employment of the mobile elderly population.
{"title":"An Exploration of the Impact of Social Integration on the Re-employment Patterns of the Mobile Elderly Population in the Context of Informatization","authors":"Liping Xiang","doi":"10.2478/amns.2023.2.01331","DOIUrl":"https://doi.org/10.2478/amns.2023.2.01331","url":null,"abstract":"Abstract Re-employment of the mobile elderly population is an important factor in promoting the development of social integration, and the study of the interaction between the two can further realize re-employment. This paper evaluates the level of social integration from four dimensions: economic integration, behavioral integration, cultural integration, and psychological integration, and explains different integration indicators. The indicator factors and their weights of the social integration measurement model were identified through the use of factor analysis and principal component analysis. At the same time, categorical variables were used to set up the re-employment mode of the migrant elderly population, which led to the formulation of three research hypotheses on the impact of social integration. In the description of the overall characteristics of the re-employment of the mobile elderly population, with the help of the multiple covariance test to confirm the accuracy of the estimation of the impact effect, binary logistic regression is used to verify the relationship between the impact of social integration on the re-employment of the mobile elderly population. The test results show that the minimum value of tolerance is 0.804, and the maximum value is 0.954. The maximum value of VIF is 1.199, and the minimum value is 1.009. Model 1 shows that social integration has a negative effect on re-employment of the mobile elderly population, and the value of EXP(B) is 0.541. This study verifies the relationship of the effect of social integration on re-employment and guides the re-employment of the mobile elderly population.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":"75 24","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138606212","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}
Pub Date : 2023-12-02DOI: 10.2478/amns.2023.2.01327
Junli Feng, Xiaojie Lian
Abstract In this paper, the feature increment can be regarded as a learning mapping function, and a non-equilibrium incremental learning (WILS) method for the academic warning is proposed, and the academic warning model of the non-equilibrium incremental learning method is constructed. The learning factor is regulated by introducing the Focal loss function, and the learned knowledge is integrated into the Focal loss as the final loss function. Finally, the three-dimensional indicators of social characteristics, personal characteristics, and student behavior were used to explore the influencing factors of academic performance and academic support strategies were explored in this way. The results show that the average value of the accuracy of the academic early warning model is 0.857, and the F1-Measure is 0.891, which indicates that the model can reasonably and efficiently provide prior warning of students’ learning situations and behavioral performance. This paper proposes countermeasure suggestions for managing academic early warning and academic support work, which enhances the purpose of talent cultivation quality.
{"title":"Reflections on and Exploration of Academic Early Warning Management and Support for Students in Colleges and Universities","authors":"Junli Feng, Xiaojie Lian","doi":"10.2478/amns.2023.2.01327","DOIUrl":"https://doi.org/10.2478/amns.2023.2.01327","url":null,"abstract":"Abstract In this paper, the feature increment can be regarded as a learning mapping function, and a non-equilibrium incremental learning (WILS) method for the academic warning is proposed, and the academic warning model of the non-equilibrium incremental learning method is constructed. The learning factor is regulated by introducing the Focal loss function, and the learned knowledge is integrated into the Focal loss as the final loss function. Finally, the three-dimensional indicators of social characteristics, personal characteristics, and student behavior were used to explore the influencing factors of academic performance and academic support strategies were explored in this way. The results show that the average value of the accuracy of the academic early warning model is 0.857, and the F1-Measure is 0.891, which indicates that the model can reasonably and efficiently provide prior warning of students’ learning situations and behavioral performance. This paper proposes countermeasure suggestions for managing academic early warning and academic support work, which enhances the purpose of talent cultivation quality.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":"10 2","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138606957","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}
Pub Date : 2023-12-02DOI: 10.2478/amns.2023.2.01315
Heyuan Ma, Xue Yang, Kaiyue Qi
Abstract In today’s society, under the demand for high-quality talents, the professionals cultivated in colleges and universities should not only master professional skills but also need to have the spirit of innovation and entrepreneurial ability in professional aspects. In this paper, firstly, the multivariate statistical analysis method is explained, and the basic principles of the factor analysis model, principal component analysis method and systematic clustering method are given to analyze the data in the following article. Secondly, starting from the necessity of the integration of bi-initiative education and professional education of teacher training majors in colleges and universities, we constructed the 4344 specialized and innovative integrated talent cultivation model of teacher training majors and constructed an evaluation system to evaluate the effectiveness. Finally, based on the evaluation system, the data analysis of the specialized and creative integrated talent cultivation model was carried out using factor analysis, principal component analysis and systematic clustering method. The results show that in the factor analysis, the highest loading value of the first principal factor is 0.917, the contribution rate of the first principal factor is 39.67%, and the loading value of the principal component factor reaches the highest value of 0.925. The clustering analysis is based on the results of the factor analysis, and the respondents are divided into 4 clusters. The number of people in the 2nd category is more than 30 people, which accounts for about 31.41% of the total number of people. The method of multivariate statistical analysis can be used to analyze the data effectively for the specialized and integrated personnel training mode of teacher training in colleges and universities and also gives the path of specialized and integrated personnel training for teacher training.
{"title":"Research on the enhancement path of talent cultivation in the integration of dual-creation education and professional education for teacher training majors in colleges and universities based on multivariate statistical analysis","authors":"Heyuan Ma, Xue Yang, Kaiyue Qi","doi":"10.2478/amns.2023.2.01315","DOIUrl":"https://doi.org/10.2478/amns.2023.2.01315","url":null,"abstract":"Abstract In today’s society, under the demand for high-quality talents, the professionals cultivated in colleges and universities should not only master professional skills but also need to have the spirit of innovation and entrepreneurial ability in professional aspects. In this paper, firstly, the multivariate statistical analysis method is explained, and the basic principles of the factor analysis model, principal component analysis method and systematic clustering method are given to analyze the data in the following article. Secondly, starting from the necessity of the integration of bi-initiative education and professional education of teacher training majors in colleges and universities, we constructed the 4344 specialized and innovative integrated talent cultivation model of teacher training majors and constructed an evaluation system to evaluate the effectiveness. Finally, based on the evaluation system, the data analysis of the specialized and creative integrated talent cultivation model was carried out using factor analysis, principal component analysis and systematic clustering method. The results show that in the factor analysis, the highest loading value of the first principal factor is 0.917, the contribution rate of the first principal factor is 39.67%, and the loading value of the principal component factor reaches the highest value of 0.925. The clustering analysis is based on the results of the factor analysis, and the respondents are divided into 4 clusters. The number of people in the 2nd category is more than 30 people, which accounts for about 31.41% of the total number of people. The method of multivariate statistical analysis can be used to analyze the data effectively for the specialized and integrated personnel training mode of teacher training in colleges and universities and also gives the path of specialized and integrated personnel training for teacher training.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":"1 4","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138606964","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}
Pub Date : 2023-12-02DOI: 10.2478/amns.2023.2.01330
Li Hai Yan
Abstract The traditional music teaching method in the informationization era has been difficult to adapt to the needs of modern teaching and must be reformed in the direction of informationization. In this paper, based on the closure, inflection point and outer enclosing box features of the stroke line element, the recognition of handwritten notes is carried out from the three categories of straight line segments, folded line segments and quadratic curves. Meanwhile, for the binarized music score image, the multi-directional LBP features for spectral line detection are improved, and the computation method of multi-scale spectral line detection LBP features is established. The Manhattan distance is used to evaluate and select the features, which are inputted into XGBoost for classification and recognition training based on the statistical distribution characteristics of the features. Note recognition and spectral line recognition are applied to college music teaching, and the effectiveness of teaching is explored. In the rhythm-recognition path, the recognition teaching based on multi-scale and multi-directional LBP features led to an increase in students’ mastery of the musical score by 2.8 and in the phrasing and segmentation path by 3.5. Informational teaching led to a deepening of students’ mastery of the notes and musical scores.
{"title":"Construction of college music information teaching mode under the background of Internet","authors":"Li Hai Yan","doi":"10.2478/amns.2023.2.01330","DOIUrl":"https://doi.org/10.2478/amns.2023.2.01330","url":null,"abstract":"Abstract The traditional music teaching method in the informationization era has been difficult to adapt to the needs of modern teaching and must be reformed in the direction of informationization. In this paper, based on the closure, inflection point and outer enclosing box features of the stroke line element, the recognition of handwritten notes is carried out from the three categories of straight line segments, folded line segments and quadratic curves. Meanwhile, for the binarized music score image, the multi-directional LBP features for spectral line detection are improved, and the computation method of multi-scale spectral line detection LBP features is established. The Manhattan distance is used to evaluate and select the features, which are inputted into XGBoost for classification and recognition training based on the statistical distribution characteristics of the features. Note recognition and spectral line recognition are applied to college music teaching, and the effectiveness of teaching is explored. In the rhythm-recognition path, the recognition teaching based on multi-scale and multi-directional LBP features led to an increase in students’ mastery of the musical score by 2.8 and in the phrasing and segmentation path by 3.5. Informational teaching led to a deepening of students’ mastery of the notes and musical scores.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":"115 15","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138607503","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}
Pub Date : 2023-12-02DOI: 10.2478/amns.2023.2.01322
Zengqiang Kong, Lingling Chen, Qiaoran Jia
Abstract In this paper, the multivariate data chain network is used to obtain the lexical sequence of Civics and Political Education, which needs to be labeled considering the convenience of research and analysis. According to the C-RTT algorithm can reduce the number of synchronization time slots required for fine synchronization of Civic and Political Network Teaching, use the Transformer encoder to assign and define the model parameters, and then construct the automatic scoring model with the theme of Civic and Political Work and Student Management. Starting from the content of the research and evaluation of the Civics and Political Science Program, the research variables and measurements are determined, and the research on the evaluation of the Civics and Political Science Program in colleges and universities is designed. Initial data for research and analysis are obtained by distributing questionnaires, and simulation analysis and statistical analysis are used to empirically analyze the Civics education combined with a multivariate data chain network. The results show that on the model analysis, the P value of the model in this paper can be up to 80.6, the R value can be up to 85.7%, the F1 value can be up to 83.2%, and the accuracy rate can be up to 82.4%, and the automatic scoring model with the theme of Civic and Political Work and Student Management has achieved good results. On the analysis of the Civics course, the mean values of the seven topics of student management are in the range of 3.78-4.18, and the standard deviations are all greater than 0.84. This study skillfully applies the theory of Civics to student management and ultimately helps the students to establish the correct three views.
{"title":"Exploring Collaborative Parenting Strategies for Civics and Student Management in Colleges and Universities Using Multiple Data Chain Networks","authors":"Zengqiang Kong, Lingling Chen, Qiaoran Jia","doi":"10.2478/amns.2023.2.01322","DOIUrl":"https://doi.org/10.2478/amns.2023.2.01322","url":null,"abstract":"Abstract In this paper, the multivariate data chain network is used to obtain the lexical sequence of Civics and Political Education, which needs to be labeled considering the convenience of research and analysis. According to the C-RTT algorithm can reduce the number of synchronization time slots required for fine synchronization of Civic and Political Network Teaching, use the Transformer encoder to assign and define the model parameters, and then construct the automatic scoring model with the theme of Civic and Political Work and Student Management. Starting from the content of the research and evaluation of the Civics and Political Science Program, the research variables and measurements are determined, and the research on the evaluation of the Civics and Political Science Program in colleges and universities is designed. Initial data for research and analysis are obtained by distributing questionnaires, and simulation analysis and statistical analysis are used to empirically analyze the Civics education combined with a multivariate data chain network. The results show that on the model analysis, the P value of the model in this paper can be up to 80.6, the R value can be up to 85.7%, the F1 value can be up to 83.2%, and the accuracy rate can be up to 82.4%, and the automatic scoring model with the theme of Civic and Political Work and Student Management has achieved good results. On the analysis of the Civics course, the mean values of the seven topics of student management are in the range of 3.78-4.18, and the standard deviations are all greater than 0.84. This study skillfully applies the theory of Civics to student management and ultimately helps the students to establish the correct three views.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":"23 6","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138606803","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}
Pub Date : 2023-12-02DOI: 10.2478/amns.2023.2.01323
Xia Liu, Mingwei Liang
Abstract Based on the linear regression algorithm, this paper uses the basic linear regression algorithm and the kernel linear regression algorithm to construct the relationship model between academic input and academic achievement based on linear regression and to determine the independent variables, dependent variables and control variables in the model. The engineering students of East China Normal University are selected as the research object, the research instrument is determined, the research index is determined according to the survey, and the research hypothesis is proposed, and then the research and analysis design of the impact of academic input on academic achievement is completed. Using reliability and validity to test the validity of the questionnaire, the initial data of the study can be obtained by distributing the questionnaire, and correlation analysis and regression analysis are used to carry out an empirical study of academic input and academic achievement based on linear regression. The results show that the correlation coefficient between academic input and academic achievement of master’s degree students is R=0.892 and R2=0.792, indicating that the predictive variance of academic input on academic achievement is 89.2%. The effects of the dimensions under the academic input on the social adjustment dimension under the academic achievement were, in descending order, as follows: active cooperation > teacher-student interaction > educational enrichment > academic challenge > campus support. This study comprehensively analyzes the impact of academic engagement on academic achievement, and colleges and universities should change the test of students’ ability to memorize knowledge and skills to the test of students’ ability to analyze and solve problems by applying what they have learned.
{"title":"An empirical study on the effect of academic engagement on academic achievement of engineering students in colleges and universities","authors":"Xia Liu, Mingwei Liang","doi":"10.2478/amns.2023.2.01323","DOIUrl":"https://doi.org/10.2478/amns.2023.2.01323","url":null,"abstract":"Abstract Based on the linear regression algorithm, this paper uses the basic linear regression algorithm and the kernel linear regression algorithm to construct the relationship model between academic input and academic achievement based on linear regression and to determine the independent variables, dependent variables and control variables in the model. The engineering students of East China Normal University are selected as the research object, the research instrument is determined, the research index is determined according to the survey, and the research hypothesis is proposed, and then the research and analysis design of the impact of academic input on academic achievement is completed. Using reliability and validity to test the validity of the questionnaire, the initial data of the study can be obtained by distributing the questionnaire, and correlation analysis and regression analysis are used to carry out an empirical study of academic input and academic achievement based on linear regression. The results show that the correlation coefficient between academic input and academic achievement of master’s degree students is R=0.892 and R2=0.792, indicating that the predictive variance of academic input on academic achievement is 89.2%. The effects of the dimensions under the academic input on the social adjustment dimension under the academic achievement were, in descending order, as follows: active cooperation > teacher-student interaction > educational enrichment > academic challenge > campus support. This study comprehensively analyzes the impact of academic engagement on academic achievement, and colleges and universities should change the test of students’ ability to memorize knowledge and skills to the test of students’ ability to analyze and solve problems by applying what they have learned.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":"121 10","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138607226","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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