Pub Date : 2018-08-01DOI: 10.1109/CCTA.2018.8511483
A. Subramaniam, Tushar Jain
In this paper, we present a novel integrated fault-diagnosis and fault-tolerant control approach based on the nonlinear model-predictive control (NMPC) technique for heating, ventilation, and air conditioning systems in commercial buildings, which addresses the economic objectives while maintaining the thermal comfort of users possibly under the event of faults. The fault diagnosis system uses a full order nonlinear observer to detect and estimate multiple stuck faults in VAV dampers. Based on the complete information received about the occurred fault, the NMPC is reconfigured to accommodate the aftereffects of faults. The effectiveness of the proposed control and monitoring approach is demonstrated on a one floor, three-zone building constructed using SIMulation of Building and Devices (SIMBAD) toolbox.
{"title":"Fault Tolerant Economic Model Predictive Control for Energy Efficiency in a Multi-Zone Building","authors":"A. Subramaniam, Tushar Jain","doi":"10.1109/CCTA.2018.8511483","DOIUrl":"https://doi.org/10.1109/CCTA.2018.8511483","url":null,"abstract":"In this paper, we present a novel integrated fault-diagnosis and fault-tolerant control approach based on the nonlinear model-predictive control (NMPC) technique for heating, ventilation, and air conditioning systems in commercial buildings, which addresses the economic objectives while maintaining the thermal comfort of users possibly under the event of faults. The fault diagnosis system uses a full order nonlinear observer to detect and estimate multiple stuck faults in VAV dampers. Based on the complete information received about the occurred fault, the NMPC is reconfigured to accommodate the aftereffects of faults. The effectiveness of the proposed control and monitoring approach is demonstrated on a one floor, three-zone building constructed using SIMulation of Building and Devices (SIMBAD) toolbox.","PeriodicalId":358360,"journal":{"name":"2018 IEEE Conference on Control Technology and Applications (CCTA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131815046","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 : 2018-08-01DOI: 10.1109/CCTA.2018.8511399
Qinling Zheng, Zhan Ping, S. Soares, Yu Hu, Zhiqiang Gao
As more and more massive data storage drives are used in super high density, the power used to cool the servers has become an increasingly large component of the total power consumption. Therefore, improving server cooling efficiency has become an essential requirement in data centers. However, because the thermal dynamics of the server system has characteristics such as nonlinearity, significant inter-loop coupling, and continuously fast changing/unknown workload disturbances, these pose huge challenges to control engineers and data center architect engineers. To address the above concerns, this paper presents an active disturbance rejection control (ADRC) based temperature control solution to realize the thermal regulation in a one-unit (1U) server to simultaneously improve fan power consumption efficiency and regulate the server components' temperature to avoid downgraded performance caused by overheating. In this study, an experimental testbed is built and modeled to capture the thermal dynamics of a typical 1U blade server where the thermal characteristics and existing solutions are both systematically evaluated. Performance of the design concept is proved both in simulation and hardware testbed. Experimental results show that, with the proposed control solution, temperature overshoot is greatly eliminated, temperatures are more tightly controlled and the server components' throttling rate are greatly decreased. Furthermore, the proposed method is shown to be able to save up to 22% energy when the temperature set-point is increased.
{"title":"An Active Disturbance Rejection Control Approach to Fan Control in Servers","authors":"Qinling Zheng, Zhan Ping, S. Soares, Yu Hu, Zhiqiang Gao","doi":"10.1109/CCTA.2018.8511399","DOIUrl":"https://doi.org/10.1109/CCTA.2018.8511399","url":null,"abstract":"As more and more massive data storage drives are used in super high density, the power used to cool the servers has become an increasingly large component of the total power consumption. Therefore, improving server cooling efficiency has become an essential requirement in data centers. However, because the thermal dynamics of the server system has characteristics such as nonlinearity, significant inter-loop coupling, and continuously fast changing/unknown workload disturbances, these pose huge challenges to control engineers and data center architect engineers. To address the above concerns, this paper presents an active disturbance rejection control (ADRC) based temperature control solution to realize the thermal regulation in a one-unit (1U) server to simultaneously improve fan power consumption efficiency and regulate the server components' temperature to avoid downgraded performance caused by overheating. In this study, an experimental testbed is built and modeled to capture the thermal dynamics of a typical 1U blade server where the thermal characteristics and existing solutions are both systematically evaluated. Performance of the design concept is proved both in simulation and hardware testbed. Experimental results show that, with the proposed control solution, temperature overshoot is greatly eliminated, temperatures are more tightly controlled and the server components' throttling rate are greatly decreased. Furthermore, the proposed method is shown to be able to save up to 22% energy when the temperature set-point is increased.","PeriodicalId":358360,"journal":{"name":"2018 IEEE Conference on Control Technology and Applications (CCTA)","volume":"176 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131855519","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 : 2018-08-01DOI: 10.1109/CCTA.2018.8511466
Jafar Abbaszadeh Chekan, Saeid Bashash, S. Taheri
This paper presents a novel data-driven control strategy for the computationally efficient power management of plug-in hybrid electric vehicles (PHEVs). The proposed method relies on a set of real-time control policies trained through a linear regression process based on a large set of optimal powertrain decisions obtained from dynamic programming. The control policies receive the real-time powertrain system information such as the demanded propulsion force, vehicle speed, battery state-of-charge, etc. to compute the required torque values for the engine and the electric drivetrain system. The proposed controller makes near-optimal decisions when it is evaluated for the same test conditions as trained. When the test and training settings are different, however, the controller decisions deviate from optimality. We show that this deviation can be mitigated by including future drive cycle information such as trip length in the control computations.
{"title":"A Data-Driven Control Strategy for Trip Length-Conscious Power Management of Plug-In Hybrid Electric Vehicles","authors":"Jafar Abbaszadeh Chekan, Saeid Bashash, S. Taheri","doi":"10.1109/CCTA.2018.8511466","DOIUrl":"https://doi.org/10.1109/CCTA.2018.8511466","url":null,"abstract":"This paper presents a novel data-driven control strategy for the computationally efficient power management of plug-in hybrid electric vehicles (PHEVs). The proposed method relies on a set of real-time control policies trained through a linear regression process based on a large set of optimal powertrain decisions obtained from dynamic programming. The control policies receive the real-time powertrain system information such as the demanded propulsion force, vehicle speed, battery state-of-charge, etc. to compute the required torque values for the engine and the electric drivetrain system. The proposed controller makes near-optimal decisions when it is evaluated for the same test conditions as trained. When the test and training settings are different, however, the controller decisions deviate from optimality. We show that this deviation can be mitigated by including future drive cycle information such as trip length in the control computations.","PeriodicalId":358360,"journal":{"name":"2018 IEEE Conference on Control Technology and Applications (CCTA)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134403258","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 : 2018-08-01DOI: 10.1109/CCTA.2018.8511387
Minh-Duc Hua, Guillaume Allibert
This paper revisits the problem of estimating the pose (i.e. position and attitude) of a robotic vehicle by combining landmark position measurements provided by a stereo camera with measurements of an Inertial Measurement Unit. The distinguished features with respect to similar works on the topic are two folds: First, the vehicle's linear velocity is not measured neither in the body frame nor in the inertial frame; Second, no prior knowledge on the gravity direction expressed in the inertial frame is required. Instead both the linear velocity and the gravity direction are estimated together with the pose. Another innovative feature of the paper relies on the idea of over-parametrizing the gravity direction vector evolving on the unit 2-sphere $S^{2}$ by an element of SO(3) so that the error system in first order approximations can be written in an “elegant” linear time-varying form. The proposed deterministic observer is accompanied with an observability analysis that points out an explicit observability condition under which local exponential stability is granted. Reported simulation results further indicate that the observer's domain of convergence is large.
{"title":"Riccati Observer Design for Pose, Linear Velocity and Gravity Direction Estimation Using Landmark Position and IMU Measurements","authors":"Minh-Duc Hua, Guillaume Allibert","doi":"10.1109/CCTA.2018.8511387","DOIUrl":"https://doi.org/10.1109/CCTA.2018.8511387","url":null,"abstract":"This paper revisits the problem of estimating the pose (i.e. position and attitude) of a robotic vehicle by combining landmark position measurements provided by a stereo camera with measurements of an Inertial Measurement Unit. The distinguished features with respect to similar works on the topic are two folds: First, the vehicle's linear velocity is not measured neither in the body frame nor in the inertial frame; Second, no prior knowledge on the gravity direction expressed in the inertial frame is required. Instead both the linear velocity and the gravity direction are estimated together with the pose. Another innovative feature of the paper relies on the idea of over-parametrizing the gravity direction vector evolving on the unit 2-sphere $S^{2}$ by an element of SO(3) so that the error system in first order approximations can be written in an “elegant” linear time-varying form. The proposed deterministic observer is accompanied with an observability analysis that points out an explicit observability condition under which local exponential stability is granted. Reported simulation results further indicate that the observer's domain of convergence is large.","PeriodicalId":358360,"journal":{"name":"2018 IEEE Conference on Control Technology and Applications (CCTA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130339090","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 : 2018-08-01DOI: 10.1109/CCTA.2018.8511431
Ion Ghita, P. Kvieska, E. Godoy, D. Beauvois
The charging of electric cars is an open field of innovation for power converters control. Different hardware (e.g active filters) and software solutions (e.g. non-linear control law) are used to mitigate on the one hand the constrains of the connection to the electric distribution network and on the other hand the power demands of the battery. In this paper a non-linear back-stepping based control is proposed for an industrial charger. A comparative study of the performances for the proposed control architecture is presented in respect with the existing control strategy currently integrated in the electric cars. The comparison is realised for imperfect charging conditions: presence of inductive line impedance and harmonic disturbed network voltage.
{"title":"Nonlinear Control of an Industrial Charger","authors":"Ion Ghita, P. Kvieska, E. Godoy, D. Beauvois","doi":"10.1109/CCTA.2018.8511431","DOIUrl":"https://doi.org/10.1109/CCTA.2018.8511431","url":null,"abstract":"The charging of electric cars is an open field of innovation for power converters control. Different hardware (e.g active filters) and software solutions (e.g. non-linear control law) are used to mitigate on the one hand the constrains of the connection to the electric distribution network and on the other hand the power demands of the battery. In this paper a non-linear back-stepping based control is proposed for an industrial charger. A comparative study of the performances for the proposed control architecture is presented in respect with the existing control strategy currently integrated in the electric cars. The comparison is realised for imperfect charging conditions: presence of inductive line impedance and harmonic disturbed network voltage.","PeriodicalId":358360,"journal":{"name":"2018 IEEE Conference on Control Technology and Applications (CCTA)","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122899466","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 : 2018-08-01DOI: 10.1109/CCTA.2018.8511534
J. Ebegbulem, M. Guay, J. House, T. Salsbury
This paper considers the application of decentralized extremum seeking control to heating, ventilation and air conditioning (HVAC) systems in residential, commercial and industrial buildings. The HVAC system considered comprises two rooftop units that each provide cool air to two zones. The compressor, fan and expansion valve of each rooftop unit are controlled by three inner loop proportional-integral (PI) controllers to meet specified control requirements. The objective is to determine the optimal supply air temperature setpoint for each rooftop unit that minimizes the overall power consumption of the units. In addition, each setpoint must satisfy the control objectives of the three inner loop PI controllers. To tackle this problem, a decentralized proportional-integral extremum seeking control technique that avoids the need for communication between the units is employed. A simulation result is included to show the effectiveness of this technique.
{"title":"Decentralized Proportional-Integral Extremum Seeking Control for Heating, Ventilation and Air Conditioning (HVAC) Systems","authors":"J. Ebegbulem, M. Guay, J. House, T. Salsbury","doi":"10.1109/CCTA.2018.8511534","DOIUrl":"https://doi.org/10.1109/CCTA.2018.8511534","url":null,"abstract":"This paper considers the application of decentralized extremum seeking control to heating, ventilation and air conditioning (HVAC) systems in residential, commercial and industrial buildings. The HVAC system considered comprises two rooftop units that each provide cool air to two zones. The compressor, fan and expansion valve of each rooftop unit are controlled by three inner loop proportional-integral (PI) controllers to meet specified control requirements. The objective is to determine the optimal supply air temperature setpoint for each rooftop unit that minimizes the overall power consumption of the units. In addition, each setpoint must satisfy the control objectives of the three inner loop PI controllers. To tackle this problem, a decentralized proportional-integral extremum seeking control technique that avoids the need for communication between the units is employed. A simulation result is included to show the effectiveness of this technique.","PeriodicalId":358360,"journal":{"name":"2018 IEEE Conference on Control Technology and Applications (CCTA)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122175500","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 : 2018-08-01DOI: 10.1109/CCTA.2018.8511090
Donald J. Docimo, H. Fathy
This paper develops a balancing algorithm capable of attenuating charge, temperature, and other types of heterogeneity between cells within a lithium-ion battery pack. Cell-to-cell heterogeneity is known to negatively impact pack performance and reduce pack lifespan, and several balancing algorithms exist to mitigate this impact. These algorithms control cell currents and remove state of charge (SOC), state of health (SOH) and temperature imbalances, extending pack lifespan. However, the literature currently lacks a formalized method for removal of multiple types of heterogeneity that is scalable for different pack sizes. This paper addresses this gap by developing a balancing algorithm which is (i) general with respect to battery model selection and heterogeneity types and (ii) easily scalable to different pack sizes without increasing computational complexity. To design the algorithm, a linear time-varying (LTV) model representative of heterogeneity within the battery pack is presented. A linear quadratic regulator (LQR) is applied to this heterogeneity model, providing a systematic method to determine controller gains for the balancing currents. The block diagonal matrices of the LTV model prove advantageous, and allow the LQR problem's solution to be independent of the pack size. The novel balancing algorithm is validated through simulation using a realistic electro-thermal model with heterogeneity in charge, temperature, and other electrochemical states. This case study exemplifies the effectiveness of the balancing algorithm to eliminate multiple types of heterogeneity.
{"title":"Using a Linear Quadratic Regulator to Attenuate Cell-to-Cell Heterogeneity within a Lithium-Ion Battery Pack","authors":"Donald J. Docimo, H. Fathy","doi":"10.1109/CCTA.2018.8511090","DOIUrl":"https://doi.org/10.1109/CCTA.2018.8511090","url":null,"abstract":"This paper develops a balancing algorithm capable of attenuating charge, temperature, and other types of heterogeneity between cells within a lithium-ion battery pack. Cell-to-cell heterogeneity is known to negatively impact pack performance and reduce pack lifespan, and several balancing algorithms exist to mitigate this impact. These algorithms control cell currents and remove state of charge (SOC), state of health (SOH) and temperature imbalances, extending pack lifespan. However, the literature currently lacks a formalized method for removal of multiple types of heterogeneity that is scalable for different pack sizes. This paper addresses this gap by developing a balancing algorithm which is (i) general with respect to battery model selection and heterogeneity types and (ii) easily scalable to different pack sizes without increasing computational complexity. To design the algorithm, a linear time-varying (LTV) model representative of heterogeneity within the battery pack is presented. A linear quadratic regulator (LQR) is applied to this heterogeneity model, providing a systematic method to determine controller gains for the balancing currents. The block diagonal matrices of the LTV model prove advantageous, and allow the LQR problem's solution to be independent of the pack size. The novel balancing algorithm is validated through simulation using a realistic electro-thermal model with heterogeneity in charge, temperature, and other electrochemical states. This case study exemplifies the effectiveness of the balancing algorithm to eliminate multiple types of heterogeneity.","PeriodicalId":358360,"journal":{"name":"2018 IEEE Conference on Control Technology and Applications (CCTA)","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125126182","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 : 2018-08-01DOI: 10.1109/ccta.2018.8511581
{"title":"CCTA 2018 Organization","authors":"","doi":"10.1109/ccta.2018.8511581","DOIUrl":"https://doi.org/10.1109/ccta.2018.8511581","url":null,"abstract":"","PeriodicalId":358360,"journal":{"name":"2018 IEEE Conference on Control Technology and Applications (CCTA)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132119169","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 : 2018-08-01DOI: 10.1109/CCTA.2018.8511361
Isao Kimoto, K. Takaba
This paper deals with the fast SLAM algorithm for the line-based SLAM problem with a laser range scanner for a single two-wheeled mobile robot. Since the computational time of the estimation process per each step depends on the number of observed landmarks, and we control the computational time by adaptively tuning the number of particles according to the number of the observed landmarks. First, we review the estimation process of the fast line-based SLAM algorithm. Then, we propose a method for the prediction of the computational time and how to control it by using the number of particles. Finally, we show simulation results of the proposed method in order to verify its effectiveness.
{"title":"Effective Line-Based SLAM with Adaptive Tuning of Particles","authors":"Isao Kimoto, K. Takaba","doi":"10.1109/CCTA.2018.8511361","DOIUrl":"https://doi.org/10.1109/CCTA.2018.8511361","url":null,"abstract":"This paper deals with the fast SLAM algorithm for the line-based SLAM problem with a laser range scanner for a single two-wheeled mobile robot. Since the computational time of the estimation process per each step depends on the number of observed landmarks, and we control the computational time by adaptively tuning the number of particles according to the number of the observed landmarks. First, we review the estimation process of the fast line-based SLAM algorithm. Then, we propose a method for the prediction of the computational time and how to control it by using the number of particles. Finally, we show simulation results of the proposed method in order to verify its effectiveness.","PeriodicalId":358360,"journal":{"name":"2018 IEEE Conference on Control Technology and Applications (CCTA)","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133910007","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 : 2018-08-01DOI: 10.1109/CCTA.2018.8511395
S. Bortoff
In this paper we derive a dynamic model of the Delta robot that is well-suited to an object-oriented modeling framework. The approach uses an augmented Lagrangian or Hamiltonian formulation together with Baumgarte's method of index reduction, and results in a singularity-free dynamic model that is well suited to dynamic analysis, control system synthesis and time-domain simulation. The object-oriented structure enables broad application to problems such as coordinated control and robotic assembly. We present several common control algorithms and conduct a dynamic analysis of the Delta robot that shows that the open-loop system is unstable for large volumes of the reachable workspace, which has fundamental implications on closed-loop performance.
{"title":"Object-Oriented Modeling and Control of Delta Robots","authors":"S. Bortoff","doi":"10.1109/CCTA.2018.8511395","DOIUrl":"https://doi.org/10.1109/CCTA.2018.8511395","url":null,"abstract":"In this paper we derive a dynamic model of the Delta robot that is well-suited to an object-oriented modeling framework. The approach uses an augmented Lagrangian or Hamiltonian formulation together with Baumgarte's method of index reduction, and results in a singularity-free dynamic model that is well suited to dynamic analysis, control system synthesis and time-domain simulation. The object-oriented structure enables broad application to problems such as coordinated control and robotic assembly. We present several common control algorithms and conduct a dynamic analysis of the Delta robot that shows that the open-loop system is unstable for large volumes of the reachable workspace, which has fundamental implications on closed-loop performance.","PeriodicalId":358360,"journal":{"name":"2018 IEEE Conference on Control Technology and Applications (CCTA)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114233361","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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