Abstract In this article, the authors propose a method to identify the bridge damage using a backpropagation (BP) neural network. It uses bridge vibration response to solve the accuracy of bridge damage. A particle swarm optimization algorithm based on chaotic mutation is adopted to perform chaotic mutation operations and make the group jump out of the local optimum. CPSO (particle swarm optimization algorithm based on chaotic variation) algorithm can make up for the BP neural network model, easy to fall into the shortcomings of local optima, so the author will combine the two algorithms and discuss the environmental data of the bridge. Establishing a finite element model of the bridge through actual analysis, through data comparison, comparing the frequencies of the intact stages with the frequencies of the damaged stages, and verifying the neural network with random samples, for the degree of bridge damage, we get the root mean square error m s e mse and the correlation coefficient r. The result shows that the root mean square error m s e = 0.003196 mse=0.003196 , and the correlation coefficient r = 0.9654 r=0.9654 . There are only a few individual points; it seems that the relative error is relatively large. The rest of the fit is basically the same; it can meet the factors of vibration through the environment and perform damage identification for the structural damage monitoring of the bridge. Using the BP neural network model optimized by chaotic particle swarms, combined with the modal analysis of environmental vibration, it can be used in the monitoring of the health structure of the bridge, plays a certain recognition effect, and provides a new technical idea.
摘要本文提出了一种基于BP神经网络的桥梁损伤识别方法。利用桥梁振动响应来解决桥梁损伤的精度问题。采用基于混沌突变的粒子群优化算法进行混沌突变操作，使群体跳出局部最优。CPSO(基于混沌变异的粒子群优化算法)算法可以弥补BP神经网络模型容易陷入局部最优的缺点，因此笔者将两种算法结合起来，对桥梁的环境数据进行讨论。建立一个桥的有限元模型通过实际分析,通过数据的比较,比较完整的频率阶段和破坏阶段的频率,并与随机抽样验证神经网络,对桥梁损伤的程度,我们得到均方根误差m s e mse和相关系数r。结果表明,均方根误差m s e = 0.003196 mse = 0.003196,和相关系数r = 0.9654 r = 0.9654。只有几个单独的点;看来相对误差比较大。其余的贴合基本相同;它能通过环境满足振动因素，对桥梁结构损伤监测进行损伤识别。利用混沌粒子群优化的BP神经网络模型，结合环境振动的模态分析，可用于桥梁健康结构的监测，起到一定的识别效果，并提供了新的技术思路。
{"title":"Analysis of bridge vibration response for identification of bridge damage using BP neural network","authors":"Rui Wu, Chong Zhang","doi":"10.1515/nleng-2022-0273","DOIUrl":"https://doi.org/10.1515/nleng-2022-0273","url":null,"abstract":"Abstract In this article, the authors propose a method to identify the bridge damage using a backpropagation (BP) neural network. It uses bridge vibration response to solve the accuracy of bridge damage. A particle swarm optimization algorithm based on chaotic mutation is adopted to perform chaotic mutation operations and make the group jump out of the local optimum. CPSO (particle swarm optimization algorithm based on chaotic variation) algorithm can make up for the BP neural network model, easy to fall into the shortcomings of local optima, so the author will combine the two algorithms and discuss the environmental data of the bridge. Establishing a finite element model of the bridge through actual analysis, through data comparison, comparing the frequencies of the intact stages with the frequencies of the damaged stages, and verifying the neural network with random samples, for the degree of bridge damage, we get the root mean square error m s e mse and the correlation coefficient r. The result shows that the root mean square error m s e = 0.003196 mse=0.003196 , and the correlation coefficient r = 0.9654 r=0.9654 . There are only a few individual points; it seems that the relative error is relatively large. The rest of the fit is basically the same; it can meet the factors of vibration through the environment and perform damage identification for the structural damage monitoring of the bridge. Using the BP neural network model optimized by chaotic particle swarms, combined with the modal analysis of environmental vibration, it can be used in the monitoring of the health structure of the bridge, plays a certain recognition effect, and provides a new technical idea.","PeriodicalId":37863,"journal":{"name":"Nonlinear Engineering - Modeling and Application","volume":null,"pages":null},"PeriodicalIF":8.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87158674","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}
D. V. Ramana Reddy, K. T. Balaram Padal, Jagadish Babu Gunda
Abstract In this work, an application of two noded beam finite element methodology, which is demonstrated in the previous research work for vibration analysis of beam with a flexible joint problem, has been further extended here to investigate the buckling behaviour of free–free beam subjected to an in-plane compressive load. Joint is modelled as rotational spring, where the rotational spring stiffness governs the behaviour of the flexible joint. Variation of first five non-dimensional buckling loads of free–free beam with reference to the joint location as well as joint stiffness parameters are briefly presented. It is understood that looseness of the joint can significantly influence the buckling behaviour of free–free beam and plays an important role in accurately determining the buckling behaviour of jointed beams subjected to an in-plane compressive loads.
{"title":"Influence of joint flexibility on buckling analysis of free–free beams","authors":"D. V. Ramana Reddy, K. T. Balaram Padal, Jagadish Babu Gunda","doi":"10.1515/nleng-2022-0274","DOIUrl":"https://doi.org/10.1515/nleng-2022-0274","url":null,"abstract":"Abstract In this work, an application of two noded beam finite element methodology, which is demonstrated in the previous research work for vibration analysis of beam with a flexible joint problem, has been further extended here to investigate the buckling behaviour of free–free beam subjected to an in-plane compressive load. Joint is modelled as rotational spring, where the rotational spring stiffness governs the behaviour of the flexible joint. Variation of first five non-dimensional buckling loads of free–free beam with reference to the joint location as well as joint stiffness parameters are briefly presented. It is understood that looseness of the joint can significantly influence the buckling behaviour of free–free beam and plays an important role in accurately determining the buckling behaviour of jointed beams subjected to an in-plane compressive loads.","PeriodicalId":37863,"journal":{"name":"Nonlinear Engineering - Modeling and Application","volume":null,"pages":null},"PeriodicalIF":8.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87734362","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}
Abstract This article develops duality principles, a related convex dual formulation and primal dual formulations suitable for the local and global optimization of non convex primal formulations for a large class of models in physics and engineering. The results are based on standard tools of functional analysis, calculus of variations and duality theory. In particular, we develop applications to a Ginzburg–Landau type equation. Other applications include primal dual variational formulations for a Burger’s type equation and a Navier–Stokes system. We emphasize the novelty here is that the first dual variational formulation developed is convex for a primal formulation which is originally non-convex. Finally, we also highlight the primal dual variational formulations presented have a large region of convexity around any of their critical points.
{"title":"On duality principles and related convex dual formulations suitable for local and global non-convex variational optimization","authors":"Fabio Silva Botelho","doi":"10.1515/nleng-2022-0343","DOIUrl":"https://doi.org/10.1515/nleng-2022-0343","url":null,"abstract":"Abstract This article develops duality principles, a related convex dual formulation and primal dual formulations suitable for the local and global optimization of non convex primal formulations for a large class of models in physics and engineering. The results are based on standard tools of functional analysis, calculus of variations and duality theory. In particular, we develop applications to a Ginzburg–Landau type equation. Other applications include primal dual variational formulations for a Burger’s type equation and a Navier–Stokes system. We emphasize the novelty here is that the first dual variational formulation developed is convex for a primal formulation which is originally non-convex. Finally, we also highlight the primal dual variational formulations presented have a large region of convexity around any of their critical points.","PeriodicalId":37863,"journal":{"name":"Nonlinear Engineering - Modeling and Application","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135310741","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}
Rashid Jan, Normy Norfiza Abdul Razak, Salah Boulaaras, Ziad Ur Rehman, Salma Bahramand
Abstract It is well known that viral infections have a high impact on public health in multiple ways, including disease burden, outbreaks and pandemic, economic consequences, emergency response, strain on healthcare systems, psychological and social effects, and the importance of vaccination. Mathematical models of viral infections help policymakers and researchers to understand how diseases can spread, predict the potential impact of interventions, and make informed decisions to control and manage outbreaks. In this work, we formulate a mathematical model for the transmission dynamics of COVID-19 in the framework of a fractional derivative. For the analysis of the recommended model, the fundamental concepts and results are presented. For the validity of the model, we have proven that the solutions of the recommended model are positive and bounded. The qualitative and quantitative analyses of the proposed dynamics have been carried out in this research work. To ensure the existence and uniqueness of the proposed COVID-19 dynamics, we employ fixed-point theorems such as Schaefer and Banach. In addition to this, we establish stability results for the system of COVID-19 infection through mathematical skills. To assess the influence of input parameters on the proposed dynamics of the infection, we analyzed the solution pathways using the Laplace Adomian decomposition approach. Moreover, we performed different simulations to conceptualize the role of input parameters on the dynamics of the infection. These simulations provide visualizations of key factors and aid public health officials in implementing effective measures to control the spread of the virus.
{"title":"Mathematical analysis of the transmission dynamics of viral infection with effective control policies via fractional derivative","authors":"Rashid Jan, Normy Norfiza Abdul Razak, Salah Boulaaras, Ziad Ur Rehman, Salma Bahramand","doi":"10.1515/nleng-2022-0342","DOIUrl":"https://doi.org/10.1515/nleng-2022-0342","url":null,"abstract":"Abstract It is well known that viral infections have a high impact on public health in multiple ways, including disease burden, outbreaks and pandemic, economic consequences, emergency response, strain on healthcare systems, psychological and social effects, and the importance of vaccination. Mathematical models of viral infections help policymakers and researchers to understand how diseases can spread, predict the potential impact of interventions, and make informed decisions to control and manage outbreaks. In this work, we formulate a mathematical model for the transmission dynamics of COVID-19 in the framework of a fractional derivative. For the analysis of the recommended model, the fundamental concepts and results are presented. For the validity of the model, we have proven that the solutions of the recommended model are positive and bounded. The qualitative and quantitative analyses of the proposed dynamics have been carried out in this research work. To ensure the existence and uniqueness of the proposed COVID-19 dynamics, we employ fixed-point theorems such as Schaefer and Banach. In addition to this, we establish stability results for the system of COVID-19 infection through mathematical skills. To assess the influence of input parameters on the proposed dynamics of the infection, we analyzed the solution pathways using the Laplace Adomian decomposition approach. Moreover, we performed different simulations to conceptualize the role of input parameters on the dynamics of the infection. These simulations provide visualizations of key factors and aid public health officials in implementing effective measures to control the spread of the virus.","PeriodicalId":37863,"journal":{"name":"Nonlinear Engineering - Modeling and Application","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135262267","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}
Abstract Multimedia and mobile learning are effective teaching tools because of their many useful characteristics. Transmission of educational material to students is facilitated by technology in both multimedia and mobile learning environments. A more interesting and engaging learning experience may be achieved by combining text, graphics, music, video, and animation. Media-rich classrooms are often referred to as “multimedia learning.” In contrast, students who use mobile learning may access their courses from any place with an internet connection and a mobile device such as a smartphone or a tablet. Whenever this involves commonplace technological needs, its cellular gadget and notably its clever telephone take the cake. Smartphone gadgets have a very wide range of potential applications and uses. Some ethical considerations are preventing media from reinforcing stereotypes or prejudice in the communities where they are utilized. Student information are gathered and used in a way that protects their privacy, with materials required for students to engage in mobile learning, and respecting intellectual property and copyright regulations while using multimedia language-learning tools. This importance of learning cannot be overstated but when such results come, mobile devices have increasingly been used in schools. This question of whether mobile devices have an impact on education remains open. Because of such “mobile gaining knowledge,” along with an overall phrase describing researching where different devices could be utilized in combination to enhance schooling, mobile devices had become more popular. Because today’s kids utilize their mobile devices frequently, studies on their effect on word learning are immediately required. This pilot research seeks to understand why school learners think via smartphone-based L2 exercises. In particular, this study collects data about several plenty applications using cell phones in linguistic research. Two hundred and ninety-four college children from one top Turkish institution participated in this research. This project uses some hybrid reporting models and relies on description analysis over its methodology. Their results show that users place one high value on obtaining ready accessibility to materials while studying some foreign language. Respondents not only remarked about their cellphone’s portability but also proposed new applications for enhancing their learning in other countries.
{"title":"Analysis of multimedia technology and mobile learning in English teaching in colleges and universities","authors":"Ruixia Liu","doi":"10.1515/nleng-2022-0300","DOIUrl":"https://doi.org/10.1515/nleng-2022-0300","url":null,"abstract":"Abstract Multimedia and mobile learning are effective teaching tools because of their many useful characteristics. Transmission of educational material to students is facilitated by technology in both multimedia and mobile learning environments. A more interesting and engaging learning experience may be achieved by combining text, graphics, music, video, and animation. Media-rich classrooms are often referred to as “multimedia learning.” In contrast, students who use mobile learning may access their courses from any place with an internet connection and a mobile device such as a smartphone or a tablet. Whenever this involves commonplace technological needs, its cellular gadget and notably its clever telephone take the cake. Smartphone gadgets have a very wide range of potential applications and uses. Some ethical considerations are preventing media from reinforcing stereotypes or prejudice in the communities where they are utilized. Student information are gathered and used in a way that protects their privacy, with materials required for students to engage in mobile learning, and respecting intellectual property and copyright regulations while using multimedia language-learning tools. This importance of learning cannot be overstated but when such results come, mobile devices have increasingly been used in schools. This question of whether mobile devices have an impact on education remains open. Because of such “mobile gaining knowledge,” along with an overall phrase describing researching where different devices could be utilized in combination to enhance schooling, mobile devices had become more popular. Because today’s kids utilize their mobile devices frequently, studies on their effect on word learning are immediately required. This pilot research seeks to understand why school learners think via smartphone-based L2 exercises. In particular, this study collects data about several plenty applications using cell phones in linguistic research. Two hundred and ninety-four college children from one top Turkish institution participated in this research. This project uses some hybrid reporting models and relies on description analysis over its methodology. Their results show that users place one high value on obtaining ready accessibility to materials while studying some foreign language. Respondents not only remarked about their cellphone’s portability but also proposed new applications for enhancing their learning in other countries.","PeriodicalId":37863,"journal":{"name":"Nonlinear Engineering - Modeling and Application","volume":null,"pages":null},"PeriodicalIF":8.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82487851","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}
Mohamed Moustafa, Youssri Hassan Youssri, A. G. Atta
Abstract In this research, a compact combination of Chebyshev polynomials is created and used as a spatial basis for the time fractional fourth-order Euler–Bernoulli pinned–pinned beam. The method is based on applying the Petrov–Galerkin procedure to discretize the differential problem into a system of linear algebraic equations with unknown expansion coefficients. Using the efficient Gaussian elimination procedure, we solve the obtained system of equations with matrices of a particular pattern. The L ∞ {L}_{infty } and L 2 {L}_{2} norms estimate the error bound. Three numerical examples were exhibited to verify the theoretical analysis and efficiency of the newly developed algorithm.
{"title":"Explicit Chebyshev Petrov–Galerkin scheme for time-fractional fourth-order uniform Euler–Bernoulli pinned–pinned beam equation","authors":"Mohamed Moustafa, Youssri Hassan Youssri, A. G. Atta","doi":"10.1515/nleng-2022-0308","DOIUrl":"https://doi.org/10.1515/nleng-2022-0308","url":null,"abstract":"Abstract In this research, a compact combination of Chebyshev polynomials is created and used as a spatial basis for the time fractional fourth-order Euler–Bernoulli pinned–pinned beam. The method is based on applying the Petrov–Galerkin procedure to discretize the differential problem into a system of linear algebraic equations with unknown expansion coefficients. Using the efficient Gaussian elimination procedure, we solve the obtained system of equations with matrices of a particular pattern. The L ∞ {L}_{infty } and L 2 {L}_{2} norms estimate the error bound. Three numerical examples were exhibited to verify the theoretical analysis and efficiency of the newly developed algorithm.","PeriodicalId":37863,"journal":{"name":"Nonlinear Engineering - Modeling and Application","volume":null,"pages":null},"PeriodicalIF":8.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79296076","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}
Abstract A fully fledged face recognition system consists of face detection, face alignment, and face recognition. Facial recognition has been challenging due to various unconstrained factors such as pose variation, illumination, aging, partial occlusion, low resolution, etc. The traditional approaches to face recognition have some limitations in an unconstrained environment. Therefore, the task of face recognition is improved using various deep learning architectures. Though the contemporary deep learning techniques for face recognition systems improved overall efficiency, a resilient and efficacious system is still required. Therefore, we proposed a hybrid ensemble convolutional neural network (HE-CNN) framework using ensemble transfer learning from the modified pre-trained models for face recognition. The concept of progressive training is used for training the model that significantly enhanced the recognition accuracy. The proposed modifications in the classification layers and training process generated best-in-class results and improved the recognition accuracy. Further, the suggested model is evaluated using a self-created criminal dataset to demonstrate the use of facial recognition in real-time. The suggested HE-CNN model obtained an accuracy of 99.35, 91.58, and 95% on labeled faces in the wild (LFW), cross pose LFW, and self-created datasets, respectively.
{"title":"A novel hybrid ensemble convolutional neural network for face recognition by optimizing hyperparameters","authors":"Shahina Anwarul, T. Choudhury, Susheela Dahiya","doi":"10.1515/nleng-2022-0290","DOIUrl":"https://doi.org/10.1515/nleng-2022-0290","url":null,"abstract":"Abstract A fully fledged face recognition system consists of face detection, face alignment, and face recognition. Facial recognition has been challenging due to various unconstrained factors such as pose variation, illumination, aging, partial occlusion, low resolution, etc. The traditional approaches to face recognition have some limitations in an unconstrained environment. Therefore, the task of face recognition is improved using various deep learning architectures. Though the contemporary deep learning techniques for face recognition systems improved overall efficiency, a resilient and efficacious system is still required. Therefore, we proposed a hybrid ensemble convolutional neural network (HE-CNN) framework using ensemble transfer learning from the modified pre-trained models for face recognition. The concept of progressive training is used for training the model that significantly enhanced the recognition accuracy. The proposed modifications in the classification layers and training process generated best-in-class results and improved the recognition accuracy. Further, the suggested model is evaluated using a self-created criminal dataset to demonstrate the use of facial recognition in real-time. The suggested HE-CNN model obtained an accuracy of 99.35, 91.58, and 95% on labeled faces in the wild (LFW), cross pose LFW, and self-created datasets, respectively.","PeriodicalId":37863,"journal":{"name":"Nonlinear Engineering - Modeling and Application","volume":null,"pages":null},"PeriodicalIF":8.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79063725","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}
Abstract In this study, we show a new way for a small unmanned aerial vehicle (UAV) to move around on its own in the plantations of the tree using a single camera only. To avoid running into trees, a control plan was put into place. The detection model looks at the image heights of the trees it finds to figure out how far away they are from the UAV. It then looks at the widths of the image between the trees without any obstacles to finding the largest space. The purpose of this research is to investigate how virtual reality (VR) may improve student engagement and outcomes in the classroom. The emotional consequences of virtual reality on learning, such as motivation and enjoyment, are also explored, making this fascinating research. To investigate virtual reality’s potential as a creative and immersive tool for boosting educational experiences, the study adopts a controlled experimental method. This study’s most significant contributions are the empirical evidence it provides for the efficacy of virtual reality in education, the illumination of the impact VR has on various aspects of learning, and the recommendations it offers to educators on how to make the most of VR in the classroom.
{"title":"Convolutional neural network for UAV image processing and navigation in tree plantations based on deep learning","authors":"Shuiqing Xiao","doi":"10.1515/nleng-2022-0299","DOIUrl":"https://doi.org/10.1515/nleng-2022-0299","url":null,"abstract":"Abstract In this study, we show a new way for a small unmanned aerial vehicle (UAV) to move around on its own in the plantations of the tree using a single camera only. To avoid running into trees, a control plan was put into place. The detection model looks at the image heights of the trees it finds to figure out how far away they are from the UAV. It then looks at the widths of the image between the trees without any obstacles to finding the largest space. The purpose of this research is to investigate how virtual reality (VR) may improve student engagement and outcomes in the classroom. The emotional consequences of virtual reality on learning, such as motivation and enjoyment, are also explored, making this fascinating research. To investigate virtual reality’s potential as a creative and immersive tool for boosting educational experiences, the study adopts a controlled experimental method. This study’s most significant contributions are the empirical evidence it provides for the efficacy of virtual reality in education, the illumination of the impact VR has on various aspects of learning, and the recommendations it offers to educators on how to make the most of VR in the classroom.","PeriodicalId":37863,"journal":{"name":"Nonlinear Engineering - Modeling and Application","volume":null,"pages":null},"PeriodicalIF":8.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72702002","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}
Abstract In order to achieve facial object detection and tracking in video, a method based on nonlinear sequence Monte Carlo filtering technology is proposed. The algorithm is simple, effective, and easy to operate, which can solve the problems of scale change and occlusion in the process of online learning tracking, so as to ensure the smooth implementation of learning effect evaluation. Experimental methods should be added to the article summary section. The results show that the algorithm in this study outperforms the basic KCF in terms of evaluation accuracy and success rate, as well as outperforms other tracker algorithms in benchmark, achieving scores of 0.837 and 0.705, respectively. In terms of overlapping accuracy, the reason why this study’s algorithm is higher than KCF is that this study determines the tracking status of the current target by calculating the primary side regulated (PSR) value when the target is obscured or lost, which does not make the tracking error to accumulate. The tracking algorithm in this study is not ranked first in the two attributes of motion blur and low resolution, but the rankings of all other nine attributes belong to the first. Compared with the KCF algorithm, the accuracy plots for the three attributes of scale change, occlusion, and leaving the field of view are improved by 10.26, 13.48, and 13.04%, respectively. Thus, it is proved that the method based on nonlinear sequence Monte Carlo filtering technology can achieve video facial object detection and tracking.
摘要为了实现视频中人脸目标的检测与跟踪，提出了一种基于非线性序列蒙特卡罗滤波技术的人脸目标检测与跟踪方法。该算法简单有效，易于操作，能够解决在线学习跟踪过程中的尺度变化和遮挡问题，从而保证学习效果评估的顺利实施。实验方法应添加到文章摘要部分。结果表明，本研究算法在评估准确率和成功率方面优于基本KCF，在基准测试中优于其他跟踪算法，得分分别为0.837和0.705。在重叠精度方面，本研究算法之所以高于KCF，是因为本研究通过计算目标被遮挡或丢失时的初级侧调节(primary side regulated, PSR)值来确定当前目标的跟踪状态，不会使跟踪误差累积。本研究中的跟踪算法在运动模糊和低分辨率这两个属性上并没有排名第一，但其他九个属性的排名都属于第一。与KCF算法相比，尺度变化、遮挡和离开视场三个属性的精度图分别提高了10.26、13.48和13.04%。从而证明了基于非线性序列蒙特卡罗滤波技术的方法可以实现视频人脸目标的检测与跟踪。
{"title":"Video face target detection and tracking algorithm based on nonlinear sequence Monte Carlo filtering technique","authors":"Yunming Du, Yi Liu, Jing Tian","doi":"10.1515/nleng-2022-0329","DOIUrl":"https://doi.org/10.1515/nleng-2022-0329","url":null,"abstract":"Abstract In order to achieve facial object detection and tracking in video, a method based on nonlinear sequence Monte Carlo filtering technology is proposed. The algorithm is simple, effective, and easy to operate, which can solve the problems of scale change and occlusion in the process of online learning tracking, so as to ensure the smooth implementation of learning effect evaluation. Experimental methods should be added to the article summary section. The results show that the algorithm in this study outperforms the basic KCF in terms of evaluation accuracy and success rate, as well as outperforms other tracker algorithms in benchmark, achieving scores of 0.837 and 0.705, respectively. In terms of overlapping accuracy, the reason why this study’s algorithm is higher than KCF is that this study determines the tracking status of the current target by calculating the primary side regulated (PSR) value when the target is obscured or lost, which does not make the tracking error to accumulate. The tracking algorithm in this study is not ranked first in the two attributes of motion blur and low resolution, but the rankings of all other nine attributes belong to the first. Compared with the KCF algorithm, the accuracy plots for the three attributes of scale change, occlusion, and leaving the field of view are improved by 10.26, 13.48, and 13.04%, respectively. Thus, it is proved that the method based on nonlinear sequence Monte Carlo filtering technology can achieve video facial object detection and tracking.","PeriodicalId":37863,"journal":{"name":"Nonlinear Engineering - Modeling and Application","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135106174","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}
Abstract In order to further improve the prediction accuracy, the network packet loss rate (PLR) prediction mathematical model based on the Internet of Things (IoTs) was proposed. First, the network data transmission module was established, and the network PLR prediction process was developed based on IoTs; second, the prediction framework of PLR was designed to obtain more accurate prior information. The relationship between PLR and user experience quality QoE is univariate and nonlinear. The mapping between PLR and user experience quality QoE is established using univariate nonlinear regression analysis; finally, a mathematical model of network PLR prediction is constructed to further improve the prediction accuracy. Experimental results show that the delays of network nodes are all within 5 s, which can ensure the real-time nature of data transmission. When the total number of packets and the number of lost packets are the same, the PLR predicted by the mathematical model designed by the authors is consistent with the actual PLR. Conclusion: The prediction effect of the model is better and has higher promotion value.
{"title":"Mathematical prediction model construction of network packet loss rate and nonlinear mapping user experience under the Internet of Things","authors":"Bin Fan, B. Nagaraj","doi":"10.1515/nleng-2022-0309","DOIUrl":"https://doi.org/10.1515/nleng-2022-0309","url":null,"abstract":"Abstract In order to further improve the prediction accuracy, the network packet loss rate (PLR) prediction mathematical model based on the Internet of Things (IoTs) was proposed. First, the network data transmission module was established, and the network PLR prediction process was developed based on IoTs; second, the prediction framework of PLR was designed to obtain more accurate prior information. The relationship between PLR and user experience quality QoE is univariate and nonlinear. The mapping between PLR and user experience quality QoE is established using univariate nonlinear regression analysis; finally, a mathematical model of network PLR prediction is constructed to further improve the prediction accuracy. Experimental results show that the delays of network nodes are all within 5 s, which can ensure the real-time nature of data transmission. When the total number of packets and the number of lost packets are the same, the PLR predicted by the mathematical model designed by the authors is consistent with the actual PLR. Conclusion: The prediction effect of the model is better and has higher promotion value.","PeriodicalId":37863,"journal":{"name":"Nonlinear Engineering - Modeling and Application","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135749670","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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