Fusion of Global Navigation Satellite System (GNSS) with eLoran can greatly improve the coverage and availability of Positioning Navigation and Timing (PNT) services. However, due to the strong nonlinearity in the eLoran pseudorange equations, traditional methods may fail to converge or converge incorrectly when solving the fused pseudorange equation system. In this paper, an interval shrinking trust region algorithm (ISTR) is proposed to solve the pseudorange-based eLoran/GNSS fusion positioning problem, especially when no reliable initial values are available. Simulation and measured data verify that the ISTR algorithm can help the receiver to complete reliable positioning initialization without reliable initial values, and the initialization success rate is 100%.
{"title":"An Interval Shrinking Trust Region Algorithm for GNSS/eLoran Pseudorange Fusion Positioning Initialization","authors":"Kai Liu, Wenhe Yan, Jiangbin Yuan, Zaihui Xiao, Chaozhong Yang, Yu Hua","doi":"10.1109/ICARCE55724.2022.10046591","DOIUrl":"https://doi.org/10.1109/ICARCE55724.2022.10046591","url":null,"abstract":"Fusion of Global Navigation Satellite System (GNSS) with eLoran can greatly improve the coverage and availability of Positioning Navigation and Timing (PNT) services. However, due to the strong nonlinearity in the eLoran pseudorange equations, traditional methods may fail to converge or converge incorrectly when solving the fused pseudorange equation system. In this paper, an interval shrinking trust region algorithm (ISTR) is proposed to solve the pseudorange-based eLoran/GNSS fusion positioning problem, especially when no reliable initial values are available. Simulation and measured data verify that the ISTR algorithm can help the receiver to complete reliable positioning initialization without reliable initial values, and the initialization success rate is 100%.","PeriodicalId":416305,"journal":{"name":"2022 International Conference on Automation, Robotics and Computer Engineering (ICARCE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125881675","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 : 2022-12-16DOI: 10.1109/ICARCE55724.2022.10046470
Feng Yao, Huailin Zhao, Huaping Liu
Human-Robot collaboration as a challenging task has received great attention in the academic research field. Many existing search models are aimed at single agent or multi-agent, but there are some defects in the search efficiency of their task targets. Therefore, we propose a human-computer cooperative search algorithm in the indoor scene, where people and agents cooperate to complete the search of related objects. We have developed a platform for human-robot collaboration, and designed a set of algorithms for agent to integrate scene prior knowledge, target recognition, and path planning. The experimental results that the H-R cooperative search model proposed by us shows good efficiency in target search tasks.
{"title":"Human-Robot Collaboration using Monte Carlo Tree Search","authors":"Feng Yao, Huailin Zhao, Huaping Liu","doi":"10.1109/ICARCE55724.2022.10046470","DOIUrl":"https://doi.org/10.1109/ICARCE55724.2022.10046470","url":null,"abstract":"Human-Robot collaboration as a challenging task has received great attention in the academic research field. Many existing search models are aimed at single agent or multi-agent, but there are some defects in the search efficiency of their task targets. Therefore, we propose a human-computer cooperative search algorithm in the indoor scene, where people and agents cooperate to complete the search of related objects. We have developed a platform for human-robot collaboration, and designed a set of algorithms for agent to integrate scene prior knowledge, target recognition, and path planning. The experimental results that the H-R cooperative search model proposed by us shows good efficiency in target search tasks.","PeriodicalId":416305,"journal":{"name":"2022 International Conference on Automation, Robotics and Computer Engineering (ICARCE)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124804426","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 : 2022-12-16DOI: 10.1109/ICARCE55724.2022.10046635
Yerui Fan, Jianbo Yuan, Yaxiong Wu, Shuai Gan
In this study, a sliding muscle surface controller (SMSC) is designed to suppress disturbances and to reduce uncertainty in the muscle-driven musculoskeletal system (MDMS). When performing manipulation tasks in unstructured environments, bio-inspired robots are able to exhibit more flexibility and safety. Although the model of MDMS can be solved by combining the muscle model and the joint-link dynamics, the influence of unknown external disturbances and dynamic uncertainties makes it difficult to describe the system perfectly in practice. In order to solve the problems, a sliding muscle surface controller with an integral power reaching law is designed to suppress the chattering problem in the control and improve the anti-interference ability of the system and reduce the integrates error between expected and simulation. Subsequently, the stability of musculoskeletal system was ensured using the principle of Lyapunov synthesis. Finally, the simulation results showed that the proposed design techniques could effectively improve the robustness of muscle model.
{"title":"Sliding Muscle Surface Control of the Muscle-Driven Musculoskeletal System","authors":"Yerui Fan, Jianbo Yuan, Yaxiong Wu, Shuai Gan","doi":"10.1109/ICARCE55724.2022.10046635","DOIUrl":"https://doi.org/10.1109/ICARCE55724.2022.10046635","url":null,"abstract":"In this study, a sliding muscle surface controller (SMSC) is designed to suppress disturbances and to reduce uncertainty in the muscle-driven musculoskeletal system (MDMS). When performing manipulation tasks in unstructured environments, bio-inspired robots are able to exhibit more flexibility and safety. Although the model of MDMS can be solved by combining the muscle model and the joint-link dynamics, the influence of unknown external disturbances and dynamic uncertainties makes it difficult to describe the system perfectly in practice. In order to solve the problems, a sliding muscle surface controller with an integral power reaching law is designed to suppress the chattering problem in the control and improve the anti-interference ability of the system and reduce the integrates error between expected and simulation. Subsequently, the stability of musculoskeletal system was ensured using the principle of Lyapunov synthesis. Finally, the simulation results showed that the proposed design techniques could effectively improve the robustness of muscle model.","PeriodicalId":416305,"journal":{"name":"2022 International Conference on Automation, Robotics and Computer Engineering (ICARCE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128888529","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 : 2022-12-16DOI: 10.1109/ICARCE55724.2022.10046593
Jiamei Jiang, Xuhan Li, Xingyu Hao, Tao Liu, R. Qiu, Qunfeng Miao
To explore the subclass types of ancient glass artifacts, first we combined the features provided in the dataset with the data on whether the artifacts were weathered or not, constructed a random forest model, and calculated the relative importance of each chemical component by the VIM (Variable Importance Measures) to give the important factors influencing the classification of major classes. Subsequently, we innovatively extracted the important components by improving the coefficient of variation to give the important factors influencing the classification of subclasses. Then, we construct a K-means clustering model for subclassification and give specific criteria for subclassification. Finally, we conducted the rationality analysis from two perspectives of chemical composition and heritage characteristics; we repeated the experiment to test the sensitivity of the large class division model for the random forest model normally distributed white noise sequence; we introduced Dunn index and contour coefficient for sensitivity analysis of the clustering model.
{"title":"A Study on the Classification of Subclasses of Glass Artifacts Based on Feature Selection","authors":"Jiamei Jiang, Xuhan Li, Xingyu Hao, Tao Liu, R. Qiu, Qunfeng Miao","doi":"10.1109/ICARCE55724.2022.10046593","DOIUrl":"https://doi.org/10.1109/ICARCE55724.2022.10046593","url":null,"abstract":"To explore the subclass types of ancient glass artifacts, first we combined the features provided in the dataset with the data on whether the artifacts were weathered or not, constructed a random forest model, and calculated the relative importance of each chemical component by the VIM (Variable Importance Measures) to give the important factors influencing the classification of major classes. Subsequently, we innovatively extracted the important components by improving the coefficient of variation to give the important factors influencing the classification of subclasses. Then, we construct a K-means clustering model for subclassification and give specific criteria for subclassification. Finally, we conducted the rationality analysis from two perspectives of chemical composition and heritage characteristics; we repeated the experiment to test the sensitivity of the large class division model for the random forest model normally distributed white noise sequence; we introduced Dunn index and contour coefficient for sensitivity analysis of the clustering model.","PeriodicalId":416305,"journal":{"name":"2022 International Conference on Automation, Robotics and Computer Engineering (ICARCE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125458757","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}
Temperature prediction is a task involving agriculture, military, industry and other aspects, and it is related to daily life and production tasks. Therefore, accurate temperature prediction is an important research topic at present. In this paper, a neural network-based maximum temperature prediction method is proposed. Combined with the Precipitable Water Vapor (PWV) data calculated from GPS satellite data, it achieves high precision, high time granularity prediction under the condition of low computing power requirements.
{"title":"Maximum Temperature Prediction Based on GPS and Meteorological Data by Using Neural Network","authors":"Shenzheng Zuo, Renjie Cai, Yan Wang, Enrui Hu, Lingzhi Liu, Yibo Guo","doi":"10.1109/ICARCE55724.2022.10046621","DOIUrl":"https://doi.org/10.1109/ICARCE55724.2022.10046621","url":null,"abstract":"Temperature prediction is a task involving agriculture, military, industry and other aspects, and it is related to daily life and production tasks. Therefore, accurate temperature prediction is an important research topic at present. In this paper, a neural network-based maximum temperature prediction method is proposed. Combined with the Precipitable Water Vapor (PWV) data calculated from GPS satellite data, it achieves high precision, high time granularity prediction under the condition of low computing power requirements.","PeriodicalId":416305,"journal":{"name":"2022 International Conference on Automation, Robotics and Computer Engineering (ICARCE)","volume":"238 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120949202","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 : 2022-12-16DOI: 10.1109/ICARCE55724.2022.10046500
Xiao Su Zhang, Qing Li, Zhong Su, Guodong Fu
Aiming at the problem of inaccurate statistical characteristics of system model noise within initial alignment of inertial pedestrian navigation, a novel heterogeneous hybrid correlation entropy Kalman filter (NHMCC-KF) alignment method is proposed considering inertial devices and human soft shortcuts. Firstly, the lever arm error is expanded as a state quantity to establish the initial alignment model of the inertial coordinate system. Then, on this basis, the covariance of the measurement noise is adjusted by combining the fast robust Kalman filter (FRKF) and the heterogenous mixture correntropy criterion, using a mixture of Laplace kernel and Gaussian kernel as the adjustment factor of the correntropy, and introducing the prior error covariance feedback adaptive Kalman filtering (NKF) to adjust the process noise. By comparing the alignment effect of NHMCC-KF and FRKF under different conditions through designed experiments, the azimuthal alignment accuracy is improved by more than 23%. The experimental findings demonstrate that the approach described in this research has superior alignment accuracy and speed.
{"title":"Initial Alignment Method of Human Soft Strapdown Base Based on NKF-FRKF","authors":"Xiao Su Zhang, Qing Li, Zhong Su, Guodong Fu","doi":"10.1109/ICARCE55724.2022.10046500","DOIUrl":"https://doi.org/10.1109/ICARCE55724.2022.10046500","url":null,"abstract":"Aiming at the problem of inaccurate statistical characteristics of system model noise within initial alignment of inertial pedestrian navigation, a novel heterogeneous hybrid correlation entropy Kalman filter (NHMCC-KF) alignment method is proposed considering inertial devices and human soft shortcuts. Firstly, the lever arm error is expanded as a state quantity to establish the initial alignment model of the inertial coordinate system. Then, on this basis, the covariance of the measurement noise is adjusted by combining the fast robust Kalman filter (FRKF) and the heterogenous mixture correntropy criterion, using a mixture of Laplace kernel and Gaussian kernel as the adjustment factor of the correntropy, and introducing the prior error covariance feedback adaptive Kalman filtering (NKF) to adjust the process noise. By comparing the alignment effect of NHMCC-KF and FRKF under different conditions through designed experiments, the azimuthal alignment accuracy is improved by more than 23%. The experimental findings demonstrate that the approach described in this research has superior alignment accuracy and speed.","PeriodicalId":416305,"journal":{"name":"2022 International Conference on Automation, Robotics and Computer Engineering (ICARCE)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127779266","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 : 2022-12-16DOI: 10.1109/ICARCE55724.2022.10046516
Jingjing Li, Yi Xu, Yapeng Li, Kepei Qi, Feiyong Yu, Shaohua Sun
In order to improve the recognition accuracy of tobacco diseases, improve the recognition efficiency and convenience, and reduce the recognition cost, this project carried out the research on the recognition technology of tobacco diseases based on deep learning. First, the data set was established. The data set is consisted of several kinds of common tobacco diseases images which were labeled according to the experts’ diagnosis results. Second, the YOLOv7 network model was studied and pruned considering the recognition rate and accurate. Third, the pruned model was trained using the established training dataset. Then, the trained model is ported to Android system. Finally, an experimental testing was carried out, and the results show that the model can run efficiently in Android system with the detection accuracy above 90%.
{"title":"Research on Intelligent Recognition Solution of Tobacco Disease on Android Platform","authors":"Jingjing Li, Yi Xu, Yapeng Li, Kepei Qi, Feiyong Yu, Shaohua Sun","doi":"10.1109/ICARCE55724.2022.10046516","DOIUrl":"https://doi.org/10.1109/ICARCE55724.2022.10046516","url":null,"abstract":"In order to improve the recognition accuracy of tobacco diseases, improve the recognition efficiency and convenience, and reduce the recognition cost, this project carried out the research on the recognition technology of tobacco diseases based on deep learning. First, the data set was established. The data set is consisted of several kinds of common tobacco diseases images which were labeled according to the experts’ diagnosis results. Second, the YOLOv7 network model was studied and pruned considering the recognition rate and accurate. Third, the pruned model was trained using the established training dataset. Then, the trained model is ported to Android system. Finally, an experimental testing was carried out, and the results show that the model can run efficiently in Android system with the detection accuracy above 90%.","PeriodicalId":416305,"journal":{"name":"2022 International Conference on Automation, Robotics and Computer Engineering (ICARCE)","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133656663","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 : 2022-12-16DOI: 10.1109/ICARCE55724.2022.10046468
Jing An, Wei Liu, Wanting Rong, Haoliang Qi
To ensure the feasibility and effectiveness of exploratory simulation experiments, it is necessary to take the simulation scenario sample space with acceptable scale and typical representative as input. In this paper, a method of generating simulation scenario sample space combining qualitative and quantitative analysis is proposed. This method constructs a machine learning meta-model based on simulation pre-experiment, and screens the key experimental factors based on sensitivity analysis of meta-model to determine the factor levels. Finally, the space is sampled and compressed to complete the generation of the hypothetical sample space.
{"title":"The Generation Method of Simulation Scenario Sample Space Based on Sensitivity Analysis of Meta-model","authors":"Jing An, Wei Liu, Wanting Rong, Haoliang Qi","doi":"10.1109/ICARCE55724.2022.10046468","DOIUrl":"https://doi.org/10.1109/ICARCE55724.2022.10046468","url":null,"abstract":"To ensure the feasibility and effectiveness of exploratory simulation experiments, it is necessary to take the simulation scenario sample space with acceptable scale and typical representative as input. In this paper, a method of generating simulation scenario sample space combining qualitative and quantitative analysis is proposed. This method constructs a machine learning meta-model based on simulation pre-experiment, and screens the key experimental factors based on sensitivity analysis of meta-model to determine the factor levels. Finally, the space is sampled and compressed to complete the generation of the hypothetical sample space.","PeriodicalId":416305,"journal":{"name":"2022 International Conference on Automation, Robotics and Computer Engineering (ICARCE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130368344","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 considers a multi-agent pursuit-evasion game in a bounded domain with multiple exits and obstacles. First, the problem modeling is performed, and the control strategy of the evaders is assumed. Then, based on Voronoi partition and potential field gradient, a pursuit strategy for N-pursuer/M-evader in the non-closed bounded domain is proposed, where the pursuers are classified into three autonomous switchable categories: the goalkeeper, the striker and the defender. The proposed strategy is a low-dimensional algorithm, which can greatly reduce computational costs. Finally, the feasibility and effectiveness are demonstrated by numerical case studies.
{"title":"Cooperative Pursuit in a Non-closed Bounded Domain","authors":"Yahong Xing, Gangqi Dong, Zhiqiang Ma, Panfeng Huang","doi":"10.1109/ICARCE55724.2022.10046568","DOIUrl":"https://doi.org/10.1109/ICARCE55724.2022.10046568","url":null,"abstract":"This paper considers a multi-agent pursuit-evasion game in a bounded domain with multiple exits and obstacles. First, the problem modeling is performed, and the control strategy of the evaders is assumed. Then, based on Voronoi partition and potential field gradient, a pursuit strategy for N-pursuer/M-evader in the non-closed bounded domain is proposed, where the pursuers are classified into three autonomous switchable categories: the goalkeeper, the striker and the defender. The proposed strategy is a low-dimensional algorithm, which can greatly reduce computational costs. Finally, the feasibility and effectiveness are demonstrated by numerical case studies.","PeriodicalId":416305,"journal":{"name":"2022 International Conference on Automation, Robotics and Computer Engineering (ICARCE)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114184503","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 : 2022-12-16DOI: 10.1109/ICARCE55724.2022.10046476
Rong Ma, Meiju Zhang, Zhongkai Zhang, Manguo Huang, Xiaobo Liang, Jiangjiang Liu, Zhaojun Liu, B. Tian
The design, fabrication, testing and implementation of a new high-performance tungsten-rhenium thin film thermocouple are introduced. In this paper, tungsten-rhenium TFTCs are taken as the research object, after simulation analysis in COMSOL software and design, it is made by screen-printing technology and magnetron sputtering. This kind of thin film thermocouple primarily utilizes two kinds of electrode materials with varying composition combination, mainly tungsten with 5% rhenium and tungsten with 26% rhenium. Furthermore, high-temperature annealing is performed to maintain the mechanical properties and thus improve thermoelectric performance. The results demonstrate that the performance is reliable in the temperature range of 150-600 C° with a repeatability of 2.02%, providing application value for high-temperature in-situ sensing.
{"title":"A Double Node Thin-Film Thermocouples for In-Situ Measurement","authors":"Rong Ma, Meiju Zhang, Zhongkai Zhang, Manguo Huang, Xiaobo Liang, Jiangjiang Liu, Zhaojun Liu, B. Tian","doi":"10.1109/ICARCE55724.2022.10046476","DOIUrl":"https://doi.org/10.1109/ICARCE55724.2022.10046476","url":null,"abstract":"The design, fabrication, testing and implementation of a new high-performance tungsten-rhenium thin film thermocouple are introduced. In this paper, tungsten-rhenium TFTCs are taken as the research object, after simulation analysis in COMSOL software and design, it is made by screen-printing technology and magnetron sputtering. This kind of thin film thermocouple primarily utilizes two kinds of electrode materials with varying composition combination, mainly tungsten with 5% rhenium and tungsten with 26% rhenium. Furthermore, high-temperature annealing is performed to maintain the mechanical properties and thus improve thermoelectric performance. The results demonstrate that the performance is reliable in the temperature range of 150-600 C° with a repeatability of 2.02%, providing application value for high-temperature in-situ sensing.","PeriodicalId":416305,"journal":{"name":"2022 International Conference on Automation, Robotics and Computer Engineering (ICARCE)","volume":"266 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116241677","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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