Pub Date : 2019-08-01DOI: 10.1109/COASE.2019.8843205
Peng Peng, Jiaxin Zhao, Yi Zhang, Heming Zhang
Data-driven techniques become increasingly popular in the field of industrial fault detection. Regarding the complex nonlinear industrial process accompanied by multiple operational monitoring modes, conventional multivariate monitoring techniques such as kernel principal component analysis (KPCA) are not suitable. In this paper, a novel hidden Markov model (HMM) combined with kernel principal component analysis is proposed for nonlinear multimode process fault detection. Firstly, the HMM is built from the measurement data of different modes so as to estimate the dynamic mode sequence. Furthermore, a local KPCA model is developed to detect the fault of each mode. The effectiveness of the proposed method is shown through a numerical nonlinear multimode simulation example and Tennessee Eastman (TE) Chemical benchmark process. The comparison results demonstrate that the proposed HMM-KPCA method precedes the conventional KPCA method due to the high fault detection rate (FDR) and low false alarm rate (FAR).
{"title":"Hidden Markov Model Combined with Kernel Principal Component Analysis for Nonlinear Multimode Process Fault Detection","authors":"Peng Peng, Jiaxin Zhao, Yi Zhang, Heming Zhang","doi":"10.1109/COASE.2019.8843205","DOIUrl":"https://doi.org/10.1109/COASE.2019.8843205","url":null,"abstract":"Data-driven techniques become increasingly popular in the field of industrial fault detection. Regarding the complex nonlinear industrial process accompanied by multiple operational monitoring modes, conventional multivariate monitoring techniques such as kernel principal component analysis (KPCA) are not suitable. In this paper, a novel hidden Markov model (HMM) combined with kernel principal component analysis is proposed for nonlinear multimode process fault detection. Firstly, the HMM is built from the measurement data of different modes so as to estimate the dynamic mode sequence. Furthermore, a local KPCA model is developed to detect the fault of each mode. The effectiveness of the proposed method is shown through a numerical nonlinear multimode simulation example and Tennessee Eastman (TE) Chemical benchmark process. The comparison results demonstrate that the proposed HMM-KPCA method precedes the conventional KPCA method due to the high fault detection rate (FDR) and low false alarm rate (FAR).","PeriodicalId":6695,"journal":{"name":"2019 IEEE 15th International Conference on Automation Science and Engineering (CASE)","volume":"42 1","pages":"1586-1591"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82517476","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 : 2019-08-01DOI: 10.1109/COASE.2019.8843188
Xiaodong Jia, Shiming Duan, C. Lee, P. Radecki, Jay Lee
Torque converters (TC) are widely used in automatic transmissions and continuous variation transmissions (CVT) to transfer the engine power to the transmission through fluid and mechanical coupling. The degradation of the TC Clutch (TCC) may result in excessive vibrations in the TC and driveline, elevated transmission temperature, and transmission shudder. The present study develops a systematic approach to detect TCC system degradation utilizing both machine learning techniques and domain expertise. The validation using vehicle data demonstrates the effectiveness of the approach. The early detection of TCC degradation may help to prolong the lifespan of TC, protect transmission components from further damage, and avoid limp-home and walk-home incidents.
{"title":"A Methodology for the Early Diagnosis of Vehicle Torque Converter Clutch Degradation","authors":"Xiaodong Jia, Shiming Duan, C. Lee, P. Radecki, Jay Lee","doi":"10.1109/COASE.2019.8843188","DOIUrl":"https://doi.org/10.1109/COASE.2019.8843188","url":null,"abstract":"Torque converters (TC) are widely used in automatic transmissions and continuous variation transmissions (CVT) to transfer the engine power to the transmission through fluid and mechanical coupling. The degradation of the TC Clutch (TCC) may result in excessive vibrations in the TC and driveline, elevated transmission temperature, and transmission shudder. The present study develops a systematic approach to detect TCC system degradation utilizing both machine learning techniques and domain expertise. The validation using vehicle data demonstrates the effectiveness of the approach. The early detection of TCC degradation may help to prolong the lifespan of TC, protect transmission components from further damage, and avoid limp-home and walk-home incidents.","PeriodicalId":6695,"journal":{"name":"2019 IEEE 15th International Conference on Automation Science and Engineering (CASE)","volume":"23 1","pages":"529-534"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82984922","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 : 2019-08-01DOI: 10.1109/COASE.2019.8842989
Yuqian Lu, Huiyue Huang, Chao Liu, X. Xu
Manufacturing is becoming smart with capabilities of self-awareness, autonomous decision-making, and adaptive excitation and collaboration. Standardization is a crucial enabler for achieving the required intelligence for smart manufacturing. Though a large number of efforts have been made to the development of manufacturing standards, there is still a significant research gap to be fulfilled. This paper reviews the landscape of existing standards in the context of smart manufacturing and offers guidance on the selection of the standards for different smart manufacturing applications.
{"title":"Standards for Smart Manufacturing: A review","authors":"Yuqian Lu, Huiyue Huang, Chao Liu, X. Xu","doi":"10.1109/COASE.2019.8842989","DOIUrl":"https://doi.org/10.1109/COASE.2019.8842989","url":null,"abstract":"Manufacturing is becoming smart with capabilities of self-awareness, autonomous decision-making, and adaptive excitation and collaboration. Standardization is a crucial enabler for achieving the required intelligence for smart manufacturing. Though a large number of efforts have been made to the development of manufacturing standards, there is still a significant research gap to be fulfilled. This paper reviews the landscape of existing standards in the context of smart manufacturing and offers guidance on the selection of the standards for different smart manufacturing applications.","PeriodicalId":6695,"journal":{"name":"2019 IEEE 15th International Conference on Automation Science and Engineering (CASE)","volume":"33 1","pages":"73-78"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87007512","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The increasing rate of vehicle population leads to traffic congestion and gas emission. Frequent traffic congestion increases commuting time and affects efficiency in work. Raising the proportion of public transportation is a solution to the issue. Compared with conventional transportation, Individualized Public Transportation System (IPTS) is more flexible and can be customized for every passenger. This paper proposes a four-stage system design method. Scheduling, dispatching and order responding algorithm are design to meet the demand of IPTS. We define the concept of Available Area for each bus, in order to recognize whether a new passenger order can be added to the bus without detour. We present the results in two scenarios: uniform distributed passengers and commuting passengers. IPTS reduces total travel time and waiting time compared to conventional transportation.
{"title":"A Multi-Stage Dispatching and Scheduling Algorithm for Individualized Public Transportation System","authors":"Zhenming Yang, Xuetao Wang, Chenghao Li, Qianchuan Zhao","doi":"10.1109/COASE.2019.8843019","DOIUrl":"https://doi.org/10.1109/COASE.2019.8843019","url":null,"abstract":"The increasing rate of vehicle population leads to traffic congestion and gas emission. Frequent traffic congestion increases commuting time and affects efficiency in work. Raising the proportion of public transportation is a solution to the issue. Compared with conventional transportation, Individualized Public Transportation System (IPTS) is more flexible and can be customized for every passenger. This paper proposes a four-stage system design method. Scheduling, dispatching and order responding algorithm are design to meet the demand of IPTS. We define the concept of Available Area for each bus, in order to recognize whether a new passenger order can be added to the bus without detour. We present the results in two scenarios: uniform distributed passengers and commuting passengers. IPTS reduces total travel time and waiting time compared to conventional transportation.","PeriodicalId":6695,"journal":{"name":"2019 IEEE 15th International Conference on Automation Science and Engineering (CASE)","volume":"13 1","pages":"745-750"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90040797","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 : 2019-08-01DOI: 10.1109/COASE.2019.8842930
Yihui Hu, Ziyue Ma, Zhiwu Li
In this paper we study the active diagnosis problem in Petri nets with quiescence. We first generalize the notion of diagnosability to Petri nets that may contain deadlocks. To avoid enumerating the reachability space, we introduce a structure called the Quiescent Basis Reachability Graph, based on which a structure called the Q-diagnoser is computed. Finally, a supervisor is designed based on Q-diagnoser such that the closed-loop system is diagnosable.
{"title":"Active Diagnosis of Petri Nets Using Q-Diagnoser","authors":"Yihui Hu, Ziyue Ma, Zhiwu Li","doi":"10.1109/COASE.2019.8842930","DOIUrl":"https://doi.org/10.1109/COASE.2019.8842930","url":null,"abstract":"In this paper we study the active diagnosis problem in Petri nets with quiescence. We first generalize the notion of diagnosability to Petri nets that may contain deadlocks. To avoid enumerating the reachability space, we introduce a structure called the Quiescent Basis Reachability Graph, based on which a structure called the Q-diagnoser is computed. Finally, a supervisor is designed based on Q-diagnoser such that the closed-loop system is diagnosable.","PeriodicalId":6695,"journal":{"name":"2019 IEEE 15th International Conference on Automation Science and Engineering (CASE)","volume":"77 1","pages":"203-208"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83864005","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 : 2019-08-01DOI: 10.1109/COASE.2019.8843122
Qixing Wang, Fei Miao, Jie Wu, Yuanfang Niu, Chengliang Wang, N. Lownes
As Autonomous Vehicles (AVs) become possible for E-hailing services operate, especially when telecom companies start deploying next-generation wireless networks (known as 5G), many new technologies may be applied in these vehicles. Dynamic-route-switching is one of these technologies, which could help vehicles find the best possible route based on real-time traffic information. However, allowing all AVs to choose their own optimal routes is not the best solution for a complex city network, since each vehicle ignores its negative effect on the road system due to the additional congestion it creates. As a result, with this system, some of the links may become over-congested, causing the whole road network system performance to degrade. Meanwhile, the travel time reliability, especially during the peak hours, is an essential factor to improve the customers’ ride experience. Unfortunately, these two issues have received relatively less attention. In this paper, we design a link-based dynamic pricing model to improve the road network system and travel time reliability at the same time. In this approach, we assume that all links are eligible with the dynamic pricing, and AVs will be perfect informed with update traffic condition and follow the dynamic road pricing. A heuristic approach is developed to address this computationally difficult problem. The output includes link-based surcharge, new travel demand and traffic condition which would improve the system performance close to the System Optimal (SO) solution and maintain the travel time reliability. Finally, we evaluate the effectiveness and efficiency of the proposed model to the well-known test Sioux Falls network.
{"title":"Dynamic Pricing for Autonomous Vehicle E-hailing Services Reliability and Performance Improvement","authors":"Qixing Wang, Fei Miao, Jie Wu, Yuanfang Niu, Chengliang Wang, N. Lownes","doi":"10.1109/COASE.2019.8843122","DOIUrl":"https://doi.org/10.1109/COASE.2019.8843122","url":null,"abstract":"As Autonomous Vehicles (AVs) become possible for E-hailing services operate, especially when telecom companies start deploying next-generation wireless networks (known as 5G), many new technologies may be applied in these vehicles. Dynamic-route-switching is one of these technologies, which could help vehicles find the best possible route based on real-time traffic information. However, allowing all AVs to choose their own optimal routes is not the best solution for a complex city network, since each vehicle ignores its negative effect on the road system due to the additional congestion it creates. As a result, with this system, some of the links may become over-congested, causing the whole road network system performance to degrade. Meanwhile, the travel time reliability, especially during the peak hours, is an essential factor to improve the customers’ ride experience. Unfortunately, these two issues have received relatively less attention. In this paper, we design a link-based dynamic pricing model to improve the road network system and travel time reliability at the same time. In this approach, we assume that all links are eligible with the dynamic pricing, and AVs will be perfect informed with update traffic condition and follow the dynamic road pricing. A heuristic approach is developed to address this computationally difficult problem. The output includes link-based surcharge, new travel demand and traffic condition which would improve the system performance close to the System Optimal (SO) solution and maintain the travel time reliability. Finally, we evaluate the effectiveness and efficiency of the proposed model to the well-known test Sioux Falls network.","PeriodicalId":6695,"journal":{"name":"2019 IEEE 15th International Conference on Automation Science and Engineering (CASE)","volume":"17 1","pages":"948-953"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86348963","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 : 2019-08-01DOI: 10.1109/COASE.2019.8843300
H. Wind, Anton Renner, O. Sawodny
Assistance functions are applied in many areas. For material handling excavators, these functions have not been introduced yet. In this paper, an optimization based trajectory generation which minimizes the travel time of a taught trajectory is presented. This playback optimization considers actuator constraints such as velocity, acceleration, jerk and maximum flow rate of the hydraulic pump. A position and velocity controller is designed based on a simplified dynamic model of the actuator in a two-degree-of-freedom control structure. Experimental results on a material handling excavator are presented. The results show the ability of the playback optimization to generate a time-optimal trajectory, considering the given constraints, and the controller to track the reference values.
{"title":"Time-Optimal Playback Trajectory Generation for Hydraulic Material Handling Excavator","authors":"H. Wind, Anton Renner, O. Sawodny","doi":"10.1109/COASE.2019.8843300","DOIUrl":"https://doi.org/10.1109/COASE.2019.8843300","url":null,"abstract":"Assistance functions are applied in many areas. For material handling excavators, these functions have not been introduced yet. In this paper, an optimization based trajectory generation which minimizes the travel time of a taught trajectory is presented. This playback optimization considers actuator constraints such as velocity, acceleration, jerk and maximum flow rate of the hydraulic pump. A position and velocity controller is designed based on a simplified dynamic model of the actuator in a two-degree-of-freedom control structure. Experimental results on a material handling excavator are presented. The results show the ability of the playback optimization to generate a time-optimal trajectory, considering the given constraints, and the controller to track the reference values.","PeriodicalId":6695,"journal":{"name":"2019 IEEE 15th International Conference on Automation Science and Engineering (CASE)","volume":"509 1","pages":"1315-1320"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86846687","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 : 2019-08-01DOI: 10.1109/COASE.2019.8843098
A. Dagnino
Process industries use complex control systems to control manufacturing operations. Control systems collect a large variety and volume of sensor data that measure processes and equipment functions. Alarms constitute an integral component of data collected by control systems. These alarms are generated when there is a deviation from normal operating conditions in equipment and processes. With large number of alarms potentially occurring in a plant, it is imperative that operators and plant managers focus on the most important alarms and dismiss un-important alarms. This paper discusses a novel approach on how to reduce unimportant alarms in a control system and how to show operators the most important alarms using Sequence Data Mining and Market Basket Analysis concepts. These approaches help reduce the number of unimportant alarms and highlight alarms that can lead to expensive breakdowns or potential accidents.
{"title":"Data Mining Methods to Analyze Alarm Logs in IoT Process Control Systems","authors":"A. Dagnino","doi":"10.1109/COASE.2019.8843098","DOIUrl":"https://doi.org/10.1109/COASE.2019.8843098","url":null,"abstract":"Process industries use complex control systems to control manufacturing operations. Control systems collect a large variety and volume of sensor data that measure processes and equipment functions. Alarms constitute an integral component of data collected by control systems. These alarms are generated when there is a deviation from normal operating conditions in equipment and processes. With large number of alarms potentially occurring in a plant, it is imperative that operators and plant managers focus on the most important alarms and dismiss un-important alarms. This paper discusses a novel approach on how to reduce unimportant alarms in a control system and how to show operators the most important alarms using Sequence Data Mining and Market Basket Analysis concepts. These approaches help reduce the number of unimportant alarms and highlight alarms that can lead to expensive breakdowns or potential accidents.","PeriodicalId":6695,"journal":{"name":"2019 IEEE 15th International Conference on Automation Science and Engineering (CASE)","volume":"7 1","pages":"323-330"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82965132","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 : 2019-08-01DOI: 10.1109/COASE.2019.8843219
S. Goecke, T. Seefeld, D. Tyralla, A. Krug
Ultra high strength steels UHSS are increasingly used in dynamic highly stressed constructions such as mobile crane booms to realise light weight designs with highest maximum loads. To guaranty sufficient mechanical-technological joint properties in welded joint, the monitoring and control of the cooling times is required. Hence, in this work, a challenging approach is the accurate in-situ and real-time sensing of the energy input in MAG laser hybrid welding of UHSS processed by sophisticated IR thermography sensors for robust “zero-defect manufacturing”.
{"title":"Monitoring and Control of the Heat Input in MAG-Laser-Hybrid Welding of High Strength Steel in Telescopic Crane Booms","authors":"S. Goecke, T. Seefeld, D. Tyralla, A. Krug","doi":"10.1109/COASE.2019.8843219","DOIUrl":"https://doi.org/10.1109/COASE.2019.8843219","url":null,"abstract":"Ultra high strength steels UHSS are increasingly used in dynamic highly stressed constructions such as mobile crane booms to realise light weight designs with highest maximum loads. To guaranty sufficient mechanical-technological joint properties in welded joint, the monitoring and control of the cooling times is required. Hence, in this work, a challenging approach is the accurate in-situ and real-time sensing of the energy input in MAG laser hybrid welding of UHSS processed by sophisticated IR thermography sensors for robust “zero-defect manufacturing”.","PeriodicalId":6695,"journal":{"name":"2019 IEEE 15th International Conference on Automation Science and Engineering (CASE)","volume":"108 1","pages":"1744-1747"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81314486","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 : 2019-08-01DOI: 10.1109/COASE.2019.8842965
Janindu Arukgoda, Ravindra Ranasinghe, G. Dissanayake
This paper presents a novel method for representing an uncertain occupancy map using a “feature vector” and an associated covariance matrix. Input required is a point cloud generated using observations from a sensor captured at different locations in the environment. Both the sensor locations and the measurements themselves may have an associated uncertainty. The output is a set of coefficients and their uncertainties of a cubic spline approximation to the distance function of the environment, thereby resulting in a compact parametric representation of the environment geometry. Cubic spline coefficients are computed by solving a non-linear least squares problem that enforces the Eikonal equation over the space in which the environment geometry is defined, and zero boundary condition at each observation in the point cloud. It is argued that a feature based representation of point cloud maps acquired from uncertain locations using noisy sensors has the potential to open up a new direction in robot mapping, localisation and SLAM. Numerical examples are presented to illustrate the proposed technique.
{"title":"Representation of Uncertain Occupancy Maps with High Level Feature Vectors","authors":"Janindu Arukgoda, Ravindra Ranasinghe, G. Dissanayake","doi":"10.1109/COASE.2019.8842965","DOIUrl":"https://doi.org/10.1109/COASE.2019.8842965","url":null,"abstract":"This paper presents a novel method for representing an uncertain occupancy map using a “feature vector” and an associated covariance matrix. Input required is a point cloud generated using observations from a sensor captured at different locations in the environment. Both the sensor locations and the measurements themselves may have an associated uncertainty. The output is a set of coefficients and their uncertainties of a cubic spline approximation to the distance function of the environment, thereby resulting in a compact parametric representation of the environment geometry. Cubic spline coefficients are computed by solving a non-linear least squares problem that enforces the Eikonal equation over the space in which the environment geometry is defined, and zero boundary condition at each observation in the point cloud. It is argued that a feature based representation of point cloud maps acquired from uncertain locations using noisy sensors has the potential to open up a new direction in robot mapping, localisation and SLAM. Numerical examples are presented to illustrate the proposed technique.","PeriodicalId":6695,"journal":{"name":"2019 IEEE 15th International Conference on Automation Science and Engineering (CASE)","volume":"20 1","pages":"1035-1041"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78750946","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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