Pub Date : 2020-10-18DOI: 10.1109/IECON43393.2020.9254982
R. Malet, J. Oliver, R. Aragonés, Ramon Voces, C. Ferrer
It is proven that the effects of the carbon footprint in the global planet is steadily increasing the temperature. In the EU28 it is estimated that 70% of the energy used in industry is used for thermal processes, and more than the 21% is lost as waste heat. It is a need to invest in the construction of waste heat recovery systems as guarantors of energy return systems.Focusing in it, this paper presents a new DC/DC converter with Maximum Power Point Tracker (MPPT) without the need to sense current for thermoelectricity harvesting systems. Multiple converters can be also directly connected in systems composed of cells working at different temperature, as it is usually the case in systems that use thermoelectric generator modules (TGM). The MPPT described in this paper is intended to be used in a multichannel high-efficiency thermoelectric generating system.
{"title":"Power electronics for Waste Heat Recovery Unit with MPPT and Without Current Sensing","authors":"R. Malet, J. Oliver, R. Aragonés, Ramon Voces, C. Ferrer","doi":"10.1109/IECON43393.2020.9254982","DOIUrl":"https://doi.org/10.1109/IECON43393.2020.9254982","url":null,"abstract":"It is proven that the effects of the carbon footprint in the global planet is steadily increasing the temperature. In the EU28 it is estimated that 70% of the energy used in industry is used for thermal processes, and more than the 21% is lost as waste heat. It is a need to invest in the construction of waste heat recovery systems as guarantors of energy return systems.Focusing in it, this paper presents a new DC/DC converter with Maximum Power Point Tracker (MPPT) without the need to sense current for thermoelectricity harvesting systems. Multiple converters can be also directly connected in systems composed of cells working at different temperature, as it is usually the case in systems that use thermoelectric generator modules (TGM). The MPPT described in this paper is intended to be used in a multichannel high-efficiency thermoelectric generating system.","PeriodicalId":13045,"journal":{"name":"IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society","volume":"69 1","pages":"5197-5202"},"PeriodicalIF":0.0,"publicationDate":"2020-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84984393","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 : 2020-10-18DOI: 10.1109/IECON43393.2020.9254603
Andres F. Lopez-Chavarro, Juan F. Patarroyo-Montenegro, Enrique A. Sanabria-Torres, Daniel D. Campo-Ossa, Jesus D. Vasquez-Plaza, Fabio Andrade-Rengifo
This paper presents a voltage control design algorithm for a three-phase voltage source converter (VSC) connected to a linear load using a passive LCL filter. The controller is based on an optimal regulator, combined with the integral of the voltage error, which is called LQI that achieves null tracking of the error. The main objective of this paper is to present an algorithm to design a voltage controller through frequency analysis of the singular values of the system, the weight of the states involved in the system, the movement of the closed poles and their respective step response to evaluate performance and robustness against load changes. The simulation results show a satisfactory operation of the voltage controller with fast recovery after a resistive load change.
{"title":"A Design Algorithm for Multivariable Linear Quadratic Integral Controllers in Voltage-Source Converters","authors":"Andres F. Lopez-Chavarro, Juan F. Patarroyo-Montenegro, Enrique A. Sanabria-Torres, Daniel D. Campo-Ossa, Jesus D. Vasquez-Plaza, Fabio Andrade-Rengifo","doi":"10.1109/IECON43393.2020.9254603","DOIUrl":"https://doi.org/10.1109/IECON43393.2020.9254603","url":null,"abstract":"This paper presents a voltage control design algorithm for a three-phase voltage source converter (VSC) connected to a linear load using a passive LCL filter. The controller is based on an optimal regulator, combined with the integral of the voltage error, which is called LQI that achieves null tracking of the error. The main objective of this paper is to present an algorithm to design a voltage controller through frequency analysis of the singular values of the system, the weight of the states involved in the system, the movement of the closed poles and their respective step response to evaluate performance and robustness against load changes. The simulation results show a satisfactory operation of the voltage controller with fast recovery after a resistive load change.","PeriodicalId":13045,"journal":{"name":"IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society","volume":"5 1","pages":"4025-4030"},"PeriodicalIF":0.0,"publicationDate":"2020-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85479115","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 : 2020-10-18DOI: 10.1109/IECON43393.2020.9255330
M. G. Zarch, Mohsen N. Soltani
An effective fault diagnosis scheme can improve system’s safety and reliability. Artificial Intelligence (AI) provides a good framework to deal with this issue. Deep learning is a successful implementation of AI that its superior isolation performance find its way in fault diagnosis area. In this study, based on feature extraction abilities of Convolutional Neural Network (CNN), a deep network have been developed in order to isolate different kinds of faults in Tennessee Eastman process. This network has an end-to-end structure with 13 layers that takes raw sensor’s data and has isolation performance of more than 98 percent. A comparison between our proposed method and a linear classifier that uses Principal Component Analysis(PCA) for feature extraction and a Neural Network (NN) with 2 hidden layers as nonlinear classifier have been conducted to show the performance of the proposed fault isolation scheme.
{"title":"An artificial intelligence approach to fault isolation based on sensor data in Tennessee Eastman process","authors":"M. G. Zarch, Mohsen N. Soltani","doi":"10.1109/IECON43393.2020.9255330","DOIUrl":"https://doi.org/10.1109/IECON43393.2020.9255330","url":null,"abstract":"An effective fault diagnosis scheme can improve system’s safety and reliability. Artificial Intelligence (AI) provides a good framework to deal with this issue. Deep learning is a successful implementation of AI that its superior isolation performance find its way in fault diagnosis area. In this study, based on feature extraction abilities of Convolutional Neural Network (CNN), a deep network have been developed in order to isolate different kinds of faults in Tennessee Eastman process. This network has an end-to-end structure with 13 layers that takes raw sensor’s data and has isolation performance of more than 98 percent. A comparison between our proposed method and a linear classifier that uses Principal Component Analysis(PCA) for feature extraction and a Neural Network (NN) with 2 hidden layers as nonlinear classifier have been conducted to show the performance of the proposed fault isolation scheme.","PeriodicalId":13045,"journal":{"name":"IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society","volume":"16 1","pages":"417-422"},"PeriodicalIF":0.0,"publicationDate":"2020-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85631505","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}
Connected devices generate large amount of data for IoT applicatons. Assisted by edge computing, caching IoT data at the edge nodes is considered as a promising technique for its advantage in reducing network traffic and service delay of cloud platform. However, the IoT data is characterized by transient lifetime and cache capacity that is limited by the edge nodes. As a consequence, caching policy should consider both data transiency and storage capacity of edge nodes. Inspired by the success of deep reinforcement learning (DRL) in deal with Markov Decision Process (MDP) problem in unknown environment, A DRL-based algorithm for edge caching problem is proposed in this paper. The proposed Advantage Actor Critic (A2C)-based algorithm is aimed at maximizing the long-term energy saving without knowledge of the IoT data popularity profiles. Simulation results demonstrate that the proposed DRL-based algorithm can achieve higher energy saving and cache hit ratio compared with the baseline algorithms.
{"title":"Edge Caching for IoT Transient Data Using Deep Reinforcement Learning","authors":"Shuran Sheng, Peng Chen, Zhimin Chen, Lenan Wu, Hao Jiang","doi":"10.1109/IECON43393.2020.9255111","DOIUrl":"https://doi.org/10.1109/IECON43393.2020.9255111","url":null,"abstract":"Connected devices generate large amount of data for IoT applicatons. Assisted by edge computing, caching IoT data at the edge nodes is considered as a promising technique for its advantage in reducing network traffic and service delay of cloud platform. However, the IoT data is characterized by transient lifetime and cache capacity that is limited by the edge nodes. As a consequence, caching policy should consider both data transiency and storage capacity of edge nodes. Inspired by the success of deep reinforcement learning (DRL) in deal with Markov Decision Process (MDP) problem in unknown environment, A DRL-based algorithm for edge caching problem is proposed in this paper. The proposed Advantage Actor Critic (A2C)-based algorithm is aimed at maximizing the long-term energy saving without knowledge of the IoT data popularity profiles. Simulation results demonstrate that the proposed DRL-based algorithm can achieve higher energy saving and cache hit ratio compared with the baseline algorithms.","PeriodicalId":13045,"journal":{"name":"IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society","volume":"183 1","pages":"4477-4482"},"PeriodicalIF":0.0,"publicationDate":"2020-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85643664","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 : 2020-10-18DOI: 10.1109/IECON43393.2020.9254422
Kazutaka Matsuzaki, Naota Sawabe, Ryo Maeda, Dai Suzuki, Takahiro Matsuura, H. Hamada
With the widespread integration of renewable energy resources, the occurrence of electric power output control is increasing in Japan, especially for photovoltaic (PV) power plants. The practical application of smart inverters that can perform electric power output control more flexibly over the network has gradually progressed. Still, there is a remaining issue regarding how to determine the implementation method and scope of the cybersecurity evaluation for distributed energy resources (DER), including smart inverters. Therefore, we generated a set of security evaluation items, tools, and supporting environments. We validated these with academics, manufacturers, and electric power companies in realistic settings, after which we were finally able to arrange evaluation methods. In this paper, we describe how we performed the industrial demonstration experiments and what we learned through the trials.
{"title":"Cybersecurity Evaluation Methodology for Distributed Energy Resources: Industrial Demonstration","authors":"Kazutaka Matsuzaki, Naota Sawabe, Ryo Maeda, Dai Suzuki, Takahiro Matsuura, H. Hamada","doi":"10.1109/IECON43393.2020.9254422","DOIUrl":"https://doi.org/10.1109/IECON43393.2020.9254422","url":null,"abstract":"With the widespread integration of renewable energy resources, the occurrence of electric power output control is increasing in Japan, especially for photovoltaic (PV) power plants. The practical application of smart inverters that can perform electric power output control more flexibly over the network has gradually progressed. Still, there is a remaining issue regarding how to determine the implementation method and scope of the cybersecurity evaluation for distributed energy resources (DER), including smart inverters. Therefore, we generated a set of security evaluation items, tools, and supporting environments. We validated these with academics, manufacturers, and electric power companies in realistic settings, after which we were finally able to arrange evaluation methods. In this paper, we describe how we performed the industrial demonstration experiments and what we learned through the trials.","PeriodicalId":13045,"journal":{"name":"IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society","volume":"30 1","pages":"2169-2174"},"PeriodicalIF":0.0,"publicationDate":"2020-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86010160","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 : 2020-10-18DOI: 10.1109/IECON43393.2020.9255379
Xiaoqing Lu, Qianxiong Li
Discrete-time control for interconnected microgrids (MGs) is critical in promoting the energy flow balance among distributed generations (DGs) and loads due to the converters’ discrete system characteristic. We propose a two-layer discrete-time iterative cooperative (TDIC) framework for multiple dc MGs, in which a two-layer iterative voltage estimator is designed. Based on this, the TDIC strategy allows all slave-DGs’ current outputs and estimated voltage to track that of their respective master-DGs, which are then guided to achieve consensus current output ratio and reference voltage synchronization. As long as the sampling period of the lower-cyber layer is less than that of the upper-cyber layer, all DGs’ weighted average voltages can be regulated to the reference voltage, meanwhile the accurate current sharing can be realized within each MG and among multiple MGs. Compared with most continuous communication approaches, the designed control inputs, supported by intermittent communication across sparse two-layer cyber networks, are merely updated at the end of each round of discrete-time iteration, which can significantly reduce the communication pressure as well as ensure a faster convergence speed.
{"title":"Two-Layer Discrete-Time Iterative Cooperation for Interconnected DC Microgrids","authors":"Xiaoqing Lu, Qianxiong Li","doi":"10.1109/IECON43393.2020.9255379","DOIUrl":"https://doi.org/10.1109/IECON43393.2020.9255379","url":null,"abstract":"Discrete-time control for interconnected microgrids (MGs) is critical in promoting the energy flow balance among distributed generations (DGs) and loads due to the converters’ discrete system characteristic. We propose a two-layer discrete-time iterative cooperative (TDIC) framework for multiple dc MGs, in which a two-layer iterative voltage estimator is designed. Based on this, the TDIC strategy allows all slave-DGs’ current outputs and estimated voltage to track that of their respective master-DGs, which are then guided to achieve consensus current output ratio and reference voltage synchronization. As long as the sampling period of the lower-cyber layer is less than that of the upper-cyber layer, all DGs’ weighted average voltages can be regulated to the reference voltage, meanwhile the accurate current sharing can be realized within each MG and among multiple MGs. Compared with most continuous communication approaches, the designed control inputs, supported by intermittent communication across sparse two-layer cyber networks, are merely updated at the end of each round of discrete-time iteration, which can significantly reduce the communication pressure as well as ensure a faster convergence speed.","PeriodicalId":13045,"journal":{"name":"IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society","volume":"11 1","pages":"3383-3388"},"PeriodicalIF":0.0,"publicationDate":"2020-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80853976","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 : 2020-10-18DOI: 10.1109/IECON43393.2020.9255053
R. VijuNair, Srinivas Gulur, Ritwik Chattopadhyay, S. Bhattacharya
Triple active bridge converters are an extension of dual active bridge converters and used to combine multiple energy sources. The advantages of using a triple active bridge converter are its high power density, providing isolation along with elimination of low frequency transformer and high efficiency power conversion. To address the intermittent nature of solar energy, it is always appropriate to include a energy storage device along with it. Triple active bridge converter acts a viable option in integrating these two energy sources in the most efficient manner. Further, this energy can be fed to the grid by using a voltage source converter cascaded with this triple active bridge converter. This paper discusses the cascaded converter with its control algorithms and different operating modes. A laboratory prototype of a triple active bridge converter integrated with the grid through a voltage source converter is developed and the different control and operating modes are verified, which are also included in this paper.
{"title":"Integrating Photovoltaics and Battery Energy Storage to Grid Using Triple Active Bridge and Voltage Source Converters","authors":"R. VijuNair, Srinivas Gulur, Ritwik Chattopadhyay, S. Bhattacharya","doi":"10.1109/IECON43393.2020.9255053","DOIUrl":"https://doi.org/10.1109/IECON43393.2020.9255053","url":null,"abstract":"Triple active bridge converters are an extension of dual active bridge converters and used to combine multiple energy sources. The advantages of using a triple active bridge converter are its high power density, providing isolation along with elimination of low frequency transformer and high efficiency power conversion. To address the intermittent nature of solar energy, it is always appropriate to include a energy storage device along with it. Triple active bridge converter acts a viable option in integrating these two energy sources in the most efficient manner. Further, this energy can be fed to the grid by using a voltage source converter cascaded with this triple active bridge converter. This paper discusses the cascaded converter with its control algorithms and different operating modes. A laboratory prototype of a triple active bridge converter integrated with the grid through a voltage source converter is developed and the different control and operating modes are verified, which are also included in this paper.","PeriodicalId":13045,"journal":{"name":"IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society","volume":"46 1","pages":"3691-3696"},"PeriodicalIF":0.0,"publicationDate":"2020-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80985016","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 : 2020-10-18DOI: 10.1109/IECON43393.2020.9254395
K. Takeda, T. Koseki
In dynamic wireless power transfer, power fluctuation occurs due to coupling variation. This paper proposes a design method of compensation network to suppress the variation based on a geometrical interpretation of power transmission characteristics. This paper also shows the theoretical limitation of suppression of power fluctuation by designing compensation circuit. The proposed design is able to suppress the power fluctuation by more than 10 percent as compared to conventional methods. The simulation and experimental results show good agreement.
{"title":"Geometrical Circuit Design for Dynamic Wireless Power Transfer to Suppress Power Fluctuation to Coupling Variation","authors":"K. Takeda, T. Koseki","doi":"10.1109/IECON43393.2020.9254395","DOIUrl":"https://doi.org/10.1109/IECON43393.2020.9254395","url":null,"abstract":"In dynamic wireless power transfer, power fluctuation occurs due to coupling variation. This paper proposes a design method of compensation network to suppress the variation based on a geometrical interpretation of power transmission characteristics. This paper also shows the theoretical limitation of suppression of power fluctuation by designing compensation circuit. The proposed design is able to suppress the power fluctuation by more than 10 percent as compared to conventional methods. The simulation and experimental results show good agreement.","PeriodicalId":13045,"journal":{"name":"IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society","volume":"33 1","pages":"3895-3900"},"PeriodicalIF":0.0,"publicationDate":"2020-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81989879","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 : 2020-10-18DOI: 10.1109/IECON43393.2020.9255248
Masaya Inukai, D. Yashiro, K. Yubai, S. Komada
Bilateral control systems including propeller-driven systems have been researched for tasks such as swiping motion, cooperative grasping and manipulation. Although some studies have proposed static controllers that do not change the gain of the controller, they are not robust against a modeling error in the stiffness of a contact object. This paper proposes an adaptive controller that estimates the stiffness of a contact object in real time and uses the stiffness for a control gain. The validity of the proposed controller is verified via simulations and experiments.
{"title":"Design of Adaptive Controller for Bilateral Control Systems Including a Propeller-Driven System","authors":"Masaya Inukai, D. Yashiro, K. Yubai, S. Komada","doi":"10.1109/IECON43393.2020.9255248","DOIUrl":"https://doi.org/10.1109/IECON43393.2020.9255248","url":null,"abstract":"Bilateral control systems including propeller-driven systems have been researched for tasks such as swiping motion, cooperative grasping and manipulation. Although some studies have proposed static controllers that do not change the gain of the controller, they are not robust against a modeling error in the stiffness of a contact object. This paper proposes an adaptive controller that estimates the stiffness of a contact object in real time and uses the stiffness for a control gain. The validity of the proposed controller is verified via simulations and experiments.","PeriodicalId":13045,"journal":{"name":"IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society","volume":"20 1","pages":"148-153"},"PeriodicalIF":0.0,"publicationDate":"2020-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85708912","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}
Many overhead lines that run for decades may lead to overload for their aging problem. To ensure overhead transmission line safety, this paper proposes a novel aging risk assessment method integrating aging mechanism analysis and fuzzy logic algorithm. The overhead transmission line tension is determined using a sag-tension model with the measured sag values of the line. According to the tension, the elasticity modulus of the line is calculated based on the Equation of state. By comparing with the elasticity modulus limits, the deformation is calculated based on the Tension-Deformation model. The aging condition of the line is assessed based on fuzzy logic together with the deformation and running time of the line. At last, the proposed method is shown its effectiveness with experiments.
{"title":"Aging Risk Assessment based on Fuzzy logic for overhead transmission line","authors":"Yong Wang, Chigang Peng, Ruchao Liao, Huamin Zhou, Ying Zhang, Tianjin Ke","doi":"10.1109/IECON43393.2020.9254385","DOIUrl":"https://doi.org/10.1109/IECON43393.2020.9254385","url":null,"abstract":"Many overhead lines that run for decades may lead to overload for their aging problem. To ensure overhead transmission line safety, this paper proposes a novel aging risk assessment method integrating aging mechanism analysis and fuzzy logic algorithm. The overhead transmission line tension is determined using a sag-tension model with the measured sag values of the line. According to the tension, the elasticity modulus of the line is calculated based on the Equation of state. By comparing with the elasticity modulus limits, the deformation is calculated based on the Tension-Deformation model. The aging condition of the line is assessed based on fuzzy logic together with the deformation and running time of the line. At last, the proposed method is shown its effectiveness with experiments.","PeriodicalId":13045,"journal":{"name":"IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society","volume":"18 1","pages":"2606-2611"},"PeriodicalIF":0.0,"publicationDate":"2020-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85790476","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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