Pub Date : 2017-05-01DOI: 10.1109/DDCLS.2017.8068159
Qing Guo, Qilei Wu, Juan Chen
The grade transition operation of the polymerization process needs to simultanously satisfy the requirements of safe operation, short transition time, low operating cost, and so on, and therefore it is a multi-objective optimization problem(MOP) with constraints. Usually, a linear weighted sum method is used to transform a multi-objective optimization problem into a single objective problem. In this work, based on the study of the grade transition operation of a continuous styrene polymerization process, two objective functions are constructed focusing on the product quality and the raw material consumption respectively. The constrained multi-objective particle swarm optimization (CMOPSO) approach using control vector parameterization is proposed to solve this multi-objective optimization problem. The process can meet the target quality specification at the end of grade transition operation by adding endpoint constraints on the quality index of the polystyrene. The simulation results confirm that the optimization method can reduce fluctuations of variables, shorten the transition time, reduce the raw materials consumption, and provide multiple grade transition strategies.
{"title":"A constrained multi-objective particle swarm optimization approach for polystyrene grade transition","authors":"Qing Guo, Qilei Wu, Juan Chen","doi":"10.1109/DDCLS.2017.8068159","DOIUrl":"https://doi.org/10.1109/DDCLS.2017.8068159","url":null,"abstract":"The grade transition operation of the polymerization process needs to simultanously satisfy the requirements of safe operation, short transition time, low operating cost, and so on, and therefore it is a multi-objective optimization problem(MOP) with constraints. Usually, a linear weighted sum method is used to transform a multi-objective optimization problem into a single objective problem. In this work, based on the study of the grade transition operation of a continuous styrene polymerization process, two objective functions are constructed focusing on the product quality and the raw material consumption respectively. The constrained multi-objective particle swarm optimization (CMOPSO) approach using control vector parameterization is proposed to solve this multi-objective optimization problem. The process can meet the target quality specification at the end of grade transition operation by adding endpoint constraints on the quality index of the polystyrene. The simulation results confirm that the optimization method can reduce fluctuations of variables, shorten the transition time, reduce the raw materials consumption, and provide multiple grade transition strategies.","PeriodicalId":419114,"journal":{"name":"2017 6th Data Driven Control and Learning Systems (DDCLS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116894215","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 : 2017-05-01DOI: 10.1109/DDCLS.2017.8068103
Yin Zhang, Xiaohua Zhou, Yuwei Zhang, Xi-sheng Dai
In this paper, by analyzing the relationship between rotor position and phase back electromotive forces (PB-EMFs) of brushless DC motor (BLDCM), a novel rotor position detection method based on morphological filter algorithm (MFA) for BLDCM is proposed. MFA is applied to identify the signal turning points (STPs) of the input stator PB-EMFs, which provides technical support for the current commutations of PWM control system. In addition, accurate current commutation point detection of BLDCM promises rotor field to keep perpendicularity with armature magnetic field, to achieve accurate detection of rotor position and position sensorless control of BLDCM. Results of simulation studies proved that, the proposed detection method can realize the position sensorless control for BLDCM by obtaining the STPs of PB-EMFs in BLDCM, which greatly improves the static and dynamic performance of speed regulation system of BLDCM, and obtaining a outstanding control effect.
{"title":"A novel rotor position detection method using morphological filter algorithm for brushless DC motor","authors":"Yin Zhang, Xiaohua Zhou, Yuwei Zhang, Xi-sheng Dai","doi":"10.1109/DDCLS.2017.8068103","DOIUrl":"https://doi.org/10.1109/DDCLS.2017.8068103","url":null,"abstract":"In this paper, by analyzing the relationship between rotor position and phase back electromotive forces (PB-EMFs) of brushless DC motor (BLDCM), a novel rotor position detection method based on morphological filter algorithm (MFA) for BLDCM is proposed. MFA is applied to identify the signal turning points (STPs) of the input stator PB-EMFs, which provides technical support for the current commutations of PWM control system. In addition, accurate current commutation point detection of BLDCM promises rotor field to keep perpendicularity with armature magnetic field, to achieve accurate detection of rotor position and position sensorless control of BLDCM. Results of simulation studies proved that, the proposed detection method can realize the position sensorless control for BLDCM by obtaining the STPs of PB-EMFs in BLDCM, which greatly improves the static and dynamic performance of speed regulation system of BLDCM, and obtaining a outstanding control effect.","PeriodicalId":419114,"journal":{"name":"2017 6th Data Driven Control and Learning Systems (DDCLS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122989407","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 : 2017-05-01DOI: 10.1109/DDCLS.2017.8068143
Jiaqi Zheng, Le Zhou, Zhiqiang Ge, Zhihuan Song
The characteristics of dynamic, uncertainty and time variant are very common in the industrial processes and should be paid enough attention for process control and monitoring purposes. As a high-order Bayesian network model, autoregressive dynamic latent variable (AR-DLV) is able to effectively extract both auto-correlations and cross-correlations in data for a dynamic process. However, the operating conditions is frequently changed in a real production line, which indicates that the measurements cannot be described using a single steady-state model. In this paper, a set of switching AR-DLV models are proposed in the probabilistic framework, which extends the original single model to its multimode form. Based on this, a hierarchical fault detection method is developed for fault detection in multimode dynamic processes. Finally, the proposed method is demonstrated by a simulated case study.
{"title":"Switching autoregressive dynamic latent variable model for fault detection in multimode processes","authors":"Jiaqi Zheng, Le Zhou, Zhiqiang Ge, Zhihuan Song","doi":"10.1109/DDCLS.2017.8068143","DOIUrl":"https://doi.org/10.1109/DDCLS.2017.8068143","url":null,"abstract":"The characteristics of dynamic, uncertainty and time variant are very common in the industrial processes and should be paid enough attention for process control and monitoring purposes. As a high-order Bayesian network model, autoregressive dynamic latent variable (AR-DLV) is able to effectively extract both auto-correlations and cross-correlations in data for a dynamic process. However, the operating conditions is frequently changed in a real production line, which indicates that the measurements cannot be described using a single steady-state model. In this paper, a set of switching AR-DLV models are proposed in the probabilistic framework, which extends the original single model to its multimode form. Based on this, a hierarchical fault detection method is developed for fault detection in multimode dynamic processes. Finally, the proposed method is demonstrated by a simulated case study.","PeriodicalId":419114,"journal":{"name":"2017 6th Data Driven Control and Learning Systems (DDCLS)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122808949","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 : 2017-05-01DOI: 10.1109/DDCLS.2017.8068072
Xiaoe Ruan, Yan Liu, Yaoyu Li
The paper exploits the convergence characteristics of the first- and second-order PI-type iterative learning control (ILC) schemes for linear time-invariant (LTI) systems with direct-through terms. The aim is to investigate the effects of the integration embedments into the conventional P-type ILC rule. In the exploitation, the tracking errors are assessed in the form of the Lebesgue-p norm and the convergences are derived in virtue of the generalized Young inequality of convolution integral. The derivations convey that the convergence monotonicities are guaranteed for the first-order PI-type ILC. At the same time, the convergence is ensured for the case when the second-order PI-type ILC is implemented on the systems. Numerical simulations testify the validity and of the proposed schemes.
{"title":"Convergence characteristics of PI-type iterative learning control for linear time-invariant systems","authors":"Xiaoe Ruan, Yan Liu, Yaoyu Li","doi":"10.1109/DDCLS.2017.8068072","DOIUrl":"https://doi.org/10.1109/DDCLS.2017.8068072","url":null,"abstract":"The paper exploits the convergence characteristics of the first- and second-order PI-type iterative learning control (ILC) schemes for linear time-invariant (LTI) systems with direct-through terms. The aim is to investigate the effects of the integration embedments into the conventional P-type ILC rule. In the exploitation, the tracking errors are assessed in the form of the Lebesgue-p norm and the convergences are derived in virtue of the generalized Young inequality of convolution integral. The derivations convey that the convergence monotonicities are guaranteed for the first-order PI-type ILC. At the same time, the convergence is ensured for the case when the second-order PI-type ILC is implemented on the systems. Numerical simulations testify the validity and of the proposed schemes.","PeriodicalId":419114,"journal":{"name":"2017 6th Data Driven Control and Learning Systems (DDCLS)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122887035","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 : 2017-05-01DOI: 10.1109/DDCLS.2017.8068048
Xuefang Li, Deqing Huang, D. Shen, Jian-xin Xu
This work addresses the boundary tracking control of a class of MIMO PDE-ODE cascade systems via learning control approach. Due to the temporal-, spatial- and iteration-varying properties, one of the key steps before the controller design is to reduce the variation of the systems. Therefore, frequency domain analysis techniques are adopted in this work, which can be used to remove the time domain impact and then facilitate the learning controller design. The convergence analysis is derived rigorously based on contraction mapping methodology. Moreover, the effect of input and measurement disturbances to the ILC performance is also discussed. In the end, an numerical example is illustrated to present to effectiveness of the proposed controller.
{"title":"Boundary tracking control for MIMO PDE-ODE cascade systems via learning control approach","authors":"Xuefang Li, Deqing Huang, D. Shen, Jian-xin Xu","doi":"10.1109/DDCLS.2017.8068048","DOIUrl":"https://doi.org/10.1109/DDCLS.2017.8068048","url":null,"abstract":"This work addresses the boundary tracking control of a class of MIMO PDE-ODE cascade systems via learning control approach. Due to the temporal-, spatial- and iteration-varying properties, one of the key steps before the controller design is to reduce the variation of the systems. Therefore, frequency domain analysis techniques are adopted in this work, which can be used to remove the time domain impact and then facilitate the learning controller design. The convergence analysis is derived rigorously based on contraction mapping methodology. Moreover, the effect of input and measurement disturbances to the ILC performance is also discussed. In the end, an numerical example is illustrated to present to effectiveness of the proposed controller.","PeriodicalId":419114,"journal":{"name":"2017 6th Data Driven Control and Learning Systems (DDCLS)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125046161","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 : 2017-05-01DOI: 10.1109/DDCLS.2017.8068042
Xingyu Zhou, X. Dai, Senping Tian, S. Mei
This paper addresses iterative learning control problem for singular distributed parameter systems with parabolic type. Owing to singular value decomposition theory, the singular distributed parameter systems are transformed into its dynamic decomposition standard form. Then, in virtue of the Bellman-Gronwall inequality and contraction mapping approach, the learning convergence of L2 norm of output errors has been guaranteed through rigorous analysis. Sufficient convergence conditions are provided under two cases. In the end, numerical simulations are presented to validate the effectiveness of P-type ILC scheme.
{"title":"Iterative learning control for a class of singular distributed parameter systems","authors":"Xingyu Zhou, X. Dai, Senping Tian, S. Mei","doi":"10.1109/DDCLS.2017.8068042","DOIUrl":"https://doi.org/10.1109/DDCLS.2017.8068042","url":null,"abstract":"This paper addresses iterative learning control problem for singular distributed parameter systems with parabolic type. Owing to singular value decomposition theory, the singular distributed parameter systems are transformed into its dynamic decomposition standard form. Then, in virtue of the Bellman-Gronwall inequality and contraction mapping approach, the learning convergence of L2 norm of output errors has been guaranteed through rigorous analysis. Sufficient convergence conditions are provided under two cases. In the end, numerical simulations are presented to validate the effectiveness of P-type ILC scheme.","PeriodicalId":419114,"journal":{"name":"2017 6th Data Driven Control and Learning Systems (DDCLS)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127904344","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 : 2017-05-01DOI: 10.1109/DDCLS.2017.8068122
Ying-mao Fu, Dazhong Ma, Huaguang Zhang, Li Zheng
This paper designs an algorithm for the moving object recognition based on support vector machine (SVM) in order to identify and classify the moving objects accurately. In view of the advantages of support vector machine in small sample, nonlinear, and high dimensional pattern recognition, a classifier is constructed based on support vector machine (SVM) is constructed. A feature vector is presented to train and classify support vector machines, which is composed of shape features and used to classify the samples. Furthermore, the support vector machine and binary decision tree are combined to form the multi class classifier. The object feature vector is used as the input of SVM, and the classifier is used to classify the detected moving objects. Finally, the experimental results show that the proposed algorithm can identify and classify different objects in video images accurately.
{"title":"Moving object recognition based on SVM and binary decision tree","authors":"Ying-mao Fu, Dazhong Ma, Huaguang Zhang, Li Zheng","doi":"10.1109/DDCLS.2017.8068122","DOIUrl":"https://doi.org/10.1109/DDCLS.2017.8068122","url":null,"abstract":"This paper designs an algorithm for the moving object recognition based on support vector machine (SVM) in order to identify and classify the moving objects accurately. In view of the advantages of support vector machine in small sample, nonlinear, and high dimensional pattern recognition, a classifier is constructed based on support vector machine (SVM) is constructed. A feature vector is presented to train and classify support vector machines, which is composed of shape features and used to classify the samples. Furthermore, the support vector machine and binary decision tree are combined to form the multi class classifier. The object feature vector is used as the input of SVM, and the classifier is used to classify the detected moving objects. Finally, the experimental results show that the proposed algorithm can identify and classify different objects in video images accurately.","PeriodicalId":419114,"journal":{"name":"2017 6th Data Driven Control and Learning Systems (DDCLS)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117096168","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 : 2017-05-01DOI: 10.1109/DDCLS.2017.8068152
Yan Li, Yundong Sun, Wenchao Wang
This paper discusses a novel strategy of dynamic modeling of clarithromycin against Helicobacter pylori. A nonlinear fractional order equivalent circuit model is proposed to describe kill-time curves for different concentrations of antibiotics and different ages of bacteria. The efficiency of the time domain analysis method has been proved by plenty of tested data. All model parameters and variables, which come from external data, are closely related to the internal characteristics of antibiotics against bacterium. It provides a group of quantified indices of bactericidal mechanism in spite of knowledge of complex micro-scale mechanisms. A number of conjectures are presented to extend possible applications of this paper.
{"title":"Fractional order dynamics for clarithromycin against helicobacter pylori","authors":"Yan Li, Yundong Sun, Wenchao Wang","doi":"10.1109/DDCLS.2017.8068152","DOIUrl":"https://doi.org/10.1109/DDCLS.2017.8068152","url":null,"abstract":"This paper discusses a novel strategy of dynamic modeling of clarithromycin against Helicobacter pylori. A nonlinear fractional order equivalent circuit model is proposed to describe kill-time curves for different concentrations of antibiotics and different ages of bacteria. The efficiency of the time domain analysis method has been proved by plenty of tested data. All model parameters and variables, which come from external data, are closely related to the internal characteristics of antibiotics against bacterium. It provides a group of quantified indices of bactericidal mechanism in spite of knowledge of complex micro-scale mechanisms. A number of conjectures are presented to extend possible applications of this paper.","PeriodicalId":419114,"journal":{"name":"2017 6th Data Driven Control and Learning Systems (DDCLS)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124361651","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 : 2017-05-01DOI: 10.1109/DDCLS.2017.8068083
Ruikun Zhang, R. Chi, Z. Hou
In the technical note, consensus tracking is studied for multi-agents system (MAS) with state time-delays. Every agent of the MAS has homogeneous dynamic function, which is described by a nonlinearly parameterized functions with unknown state time-delays. Moreover, it is assumed that the virtual leader (regarded as the desired trajectory) can be accessible to at least one agent. Based on several necessary assumptions, a distributed adaptive ILC is designed. In order to prove the convergence of tracking error, a composite energy function is designed. The result of convergence analysis shows that the designed control strategy can guarantee the agents track virtual leader along the iteration axis. A numerical simulation is provided to illustrate the effectiveness of the adaptive iterative learning controller.
{"title":"Consensus tracking of multi-agent systems with time-delays using adaptive iterative learning control","authors":"Ruikun Zhang, R. Chi, Z. Hou","doi":"10.1109/DDCLS.2017.8068083","DOIUrl":"https://doi.org/10.1109/DDCLS.2017.8068083","url":null,"abstract":"In the technical note, consensus tracking is studied for multi-agents system (MAS) with state time-delays. Every agent of the MAS has homogeneous dynamic function, which is described by a nonlinearly parameterized functions with unknown state time-delays. Moreover, it is assumed that the virtual leader (regarded as the desired trajectory) can be accessible to at least one agent. Based on several necessary assumptions, a distributed adaptive ILC is designed. In order to prove the convergence of tracking error, a composite energy function is designed. The result of convergence analysis shows that the designed control strategy can guarantee the agents track virtual leader along the iteration axis. A numerical simulation is provided to illustrate the effectiveness of the adaptive iterative learning controller.","PeriodicalId":419114,"journal":{"name":"2017 6th Data Driven Control and Learning Systems (DDCLS)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127213639","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 : 2017-05-01DOI: 10.1109/DDCLS.2017.8068132
Xiaoyue Ji, Xiaojia Xiang, Tianjiang Hu
The commonly used 2D Display is limited in aiding operators to control unmanned aerial vehicles (UAVs) within complex environments, due to its weak immersion. This paper proposes a data-driven 3D augmented reality approach. Pre-known data and experience can be integrated into to constructing a 3D virtual scenario. Furthermore, the on-board sensor data is continuously updated to this scenario during the task process. Under such circumstance, the static scenario and dynamic data are fused together by using the UAV's position and orientation. Task-associated information, e.g. route points and flying status, is simultaneously imported into the scenario to augment the virtual reality and to support the operator as well. Eventually, the AR ground station prototype is designed and implemented. Experimental results of quad rotors demonstrate that the developed system is feasible and effective to strengthen immersion with the virtual reality glasses.
{"title":"Data-driven augmented reality display and operations for UAV ground stations","authors":"Xiaoyue Ji, Xiaojia Xiang, Tianjiang Hu","doi":"10.1109/DDCLS.2017.8068132","DOIUrl":"https://doi.org/10.1109/DDCLS.2017.8068132","url":null,"abstract":"The commonly used 2D Display is limited in aiding operators to control unmanned aerial vehicles (UAVs) within complex environments, due to its weak immersion. This paper proposes a data-driven 3D augmented reality approach. Pre-known data and experience can be integrated into to constructing a 3D virtual scenario. Furthermore, the on-board sensor data is continuously updated to this scenario during the task process. Under such circumstance, the static scenario and dynamic data are fused together by using the UAV's position and orientation. Task-associated information, e.g. route points and flying status, is simultaneously imported into the scenario to augment the virtual reality and to support the operator as well. Eventually, the AR ground station prototype is designed and implemented. Experimental results of quad rotors demonstrate that the developed system is feasible and effective to strengthen immersion with the virtual reality glasses.","PeriodicalId":419114,"journal":{"name":"2017 6th Data Driven Control and Learning Systems (DDCLS)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130619821","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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