Pub Date : 2009-07-08DOI: 10.1109/CCA.2009.5281082
H. Priyadarshan, H. Pillai
Unlike linear dynamical systems the existence and uniqueness of solutions (wellposedness) for linear complementarity systems (LCS) is not trivial. It has been shown in literature that the consistent and jump space of an LCS (with zero input) plays an important role in establishing the wellposedness. In this paper we apply state and port feedback to an LCS to reorient these spaces. Sometimes it is desirable to increase the consistent space which means enlarging the set of states having continuous extension. At the same time it may be desirable to shrink the set of states which may have discontinuous extension, in other words, to decrease the jump space. Sufficient conditions in this direction are obtained in terms of feedback matrices.
{"title":"Reorienting linear complementarity systems using feedback","authors":"H. Priyadarshan, H. Pillai","doi":"10.1109/CCA.2009.5281082","DOIUrl":"https://doi.org/10.1109/CCA.2009.5281082","url":null,"abstract":"Unlike linear dynamical systems the existence and uniqueness of solutions (wellposedness) for linear complementarity systems (LCS) is not trivial. It has been shown in literature that the consistent and jump space of an LCS (with zero input) plays an important role in establishing the wellposedness. In this paper we apply state and port feedback to an LCS to reorient these spaces. Sometimes it is desirable to increase the consistent space which means enlarging the set of states having continuous extension. At the same time it may be desirable to shrink the set of states which may have discontinuous extension, in other words, to decrease the jump space. Sufficient conditions in this direction are obtained in terms of feedback matrices.","PeriodicalId":294950,"journal":{"name":"2009 IEEE Control Applications, (CCA) & Intelligent Control, (ISIC)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127651891","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 : 2009-07-08DOI: 10.1109/CCA.2009.5281072
Md. Jahangir Hossain, H. Pota, V. Ugrinovskii, R. Ramos
In this paper, a novel robust controller for a Static Synchronous Compensator (STATCOM) is presented to enhance the fault ride-through (FRT) capability of fixed speed induction generators (FSIGs), the most common type of generators that can be found in wind farms. The effects of STATCOM rating and wind farm integration on FRT capability of FSIGs are studied analytically using the power-voltage and torque-slip relationships as well as through simulations. The wind generator is a highly nonlinear system, which is modelled in this work as a linear part plus a nonlinear part, the nonlinear term being the Cauchy remainder term in the Taylor series expansion and of the equations used to model the wind farm. Bounds derived for this Cauchy remainder term are used to define an uncertain linear model for which a robust control design is performed. The controller resulting from this robust design provides an acceptable performance over a wide range of conditions needed to operate the wind farm during severe faults. The performance of the designed controller is demonstrated by large disturbance simulations on a test system.
{"title":"Robust STATCOM control for the enhancement of fault ride-through capability of fixed speed wind generators","authors":"Md. Jahangir Hossain, H. Pota, V. Ugrinovskii, R. Ramos","doi":"10.1109/CCA.2009.5281072","DOIUrl":"https://doi.org/10.1109/CCA.2009.5281072","url":null,"abstract":"In this paper, a novel robust controller for a Static Synchronous Compensator (STATCOM) is presented to enhance the fault ride-through (FRT) capability of fixed speed induction generators (FSIGs), the most common type of generators that can be found in wind farms. The effects of STATCOM rating and wind farm integration on FRT capability of FSIGs are studied analytically using the power-voltage and torque-slip relationships as well as through simulations. The wind generator is a highly nonlinear system, which is modelled in this work as a linear part plus a nonlinear part, the nonlinear term being the Cauchy remainder term in the Taylor series expansion and of the equations used to model the wind farm. Bounds derived for this Cauchy remainder term are used to define an uncertain linear model for which a robust control design is performed. The controller resulting from this robust design provides an acceptable performance over a wide range of conditions needed to operate the wind farm during severe faults. The performance of the designed controller is demonstrated by large disturbance simulations on a test system.","PeriodicalId":294950,"journal":{"name":"2009 IEEE Control Applications, (CCA) & Intelligent Control, (ISIC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128148302","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 : 2009-07-08DOI: 10.1109/CCA.2009.5281126
Wen-June Wang, Cheng-Hao Huang
This paper presents a fuzzy parallel distributed compensation (PDC) control design for balancing a two-wheeled inverted pendulum (TWIP). A Takagi-Sugeno (T-S) fuzzy model can be firstly constructed from the nonlinear system model of the TWIP. Based on the T-S fuzzy model, a PDC controller is designed with the aid of linear matrix inequality (LMI) concept. The stability of the fuzzy balance control can be guaranteed by solving the inequalities of LMI. Finally, one simulation and its equivalent experiment are given to demonstrate the effectiveness and feasibility of the control scheme.
{"title":"Model-based fuzzy control application to a self-balancing two-wheeled inverted pendulum","authors":"Wen-June Wang, Cheng-Hao Huang","doi":"10.1109/CCA.2009.5281126","DOIUrl":"https://doi.org/10.1109/CCA.2009.5281126","url":null,"abstract":"This paper presents a fuzzy parallel distributed compensation (PDC) control design for balancing a two-wheeled inverted pendulum (TWIP). A Takagi-Sugeno (T-S) fuzzy model can be firstly constructed from the nonlinear system model of the TWIP. Based on the T-S fuzzy model, a PDC controller is designed with the aid of linear matrix inequality (LMI) concept. The stability of the fuzzy balance control can be guaranteed by solving the inequalities of LMI. Finally, one simulation and its equivalent experiment are given to demonstrate the effectiveness and feasibility of the control scheme.","PeriodicalId":294950,"journal":{"name":"2009 IEEE Control Applications, (CCA) & Intelligent Control, (ISIC)","volume":"372 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133346963","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 : 2009-07-08DOI: 10.1109/CCA.2009.5280709
R. Colbaugh, K. Glass
This two-part paper presents a new approach to predictive analysis for social processes. In Part I, we begin by identifying a class of social processes which are simultaneously important in applications and difficult to predict using existing methods. It is shown that these processes can be modeled within a multi-scale, stochastic hybrid system framework that is sociologically sensible, expressive, illuminating, and amenable to formal analysis. Among other advantages, the proposed modeling framework enables proper characterization of the interplay between the intrinsic aspects of a social process (e.g., the “appeal” of a political movement) and the social dynamics which are its realization; this characterization is key to successful social process prediction. The utility of the modeling methodology is illustrated through a case study involving the global SARS epidemic of 2002–2003. Part II of the paper then leverages this modeling framework to develop a rigorous, computationally tractable approach to social process predictive analysis.
{"title":"Predictive analysis for social processes I: Multi-scale hybrid system modeling","authors":"R. Colbaugh, K. Glass","doi":"10.1109/CCA.2009.5280709","DOIUrl":"https://doi.org/10.1109/CCA.2009.5280709","url":null,"abstract":"This two-part paper presents a new approach to predictive analysis for social processes. In Part I, we begin by identifying a class of social processes which are simultaneously important in applications and difficult to predict using existing methods. It is shown that these processes can be modeled within a multi-scale, stochastic hybrid system framework that is sociologically sensible, expressive, illuminating, and amenable to formal analysis. Among other advantages, the proposed modeling framework enables proper characterization of the interplay between the intrinsic aspects of a social process (e.g., the “appeal” of a political movement) and the social dynamics which are its realization; this characterization is key to successful social process prediction. The utility of the modeling methodology is illustrated through a case study involving the global SARS epidemic of 2002–2003. Part II of the paper then leverages this modeling framework to develop a rigorous, computationally tractable approach to social process predictive analysis.","PeriodicalId":294950,"journal":{"name":"2009 IEEE Control Applications, (CCA) & Intelligent Control, (ISIC)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134030723","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 : 2009-07-08DOI: 10.1109/CCA.2009.5280998
R. García-Hernández, E. Sánchez, V. Santibáñez, M. Llama, E. Bayro-Corrochano
This paper deals with adaptive trajectory tracking for discrete-time MIMO nonlinear systems. A high order neural network (HONN) is used to approximate a decentralized control law designed by the backstepping technique as applied to a block strict feedback form (BSFF). The HONN learning is performed online by an Extended Kalman Filter (EKF) algorithm. The proposed scheme is implemented in real-time to control a two DOF robot manipulator.
{"title":"Real-time decentralized neural backstepping controller for a robot manipulator","authors":"R. García-Hernández, E. Sánchez, V. Santibáñez, M. Llama, E. Bayro-Corrochano","doi":"10.1109/CCA.2009.5280998","DOIUrl":"https://doi.org/10.1109/CCA.2009.5280998","url":null,"abstract":"This paper deals with adaptive trajectory tracking for discrete-time MIMO nonlinear systems. A high order neural network (HONN) is used to approximate a decentralized control law designed by the backstepping technique as applied to a block strict feedback form (BSFF). The HONN learning is performed online by an Extended Kalman Filter (EKF) algorithm. The proposed scheme is implemented in real-time to control a two DOF robot manipulator.","PeriodicalId":294950,"journal":{"name":"2009 IEEE Control Applications, (CCA) & Intelligent Control, (ISIC)","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132290450","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 : 2009-07-08DOI: 10.1109/CCA.2009.5281183
E. Olofsson, P1er Brunsell, J. Drake
The reversed-field pinch (RFP) EXTRAP-T2R (T2R) is a plasma physics experiment with particular relevance for magnetic confinement fusion (MCF) research. T2R is very well equipped for investigations of magnetohydrodynamic (MHD) instabilities known as resistive-wall modes (RWMs), growing on a time-scale set by a surrounding non-perfectly conducting shell. The RWM instability is also subject of intense research in tokamak experiments (another MCF configuration). Recently, multiple RWMs have been stabilized in T2R using arrays of active (current-carrying) and sensor (voltage-measuring) coils equidistributed on the shell. In this paper, the MHD normal modes dynamics is probed in the required feedback operation by simultaneously, and pseudo-randomly, exciting the spectrum in the spatial sense. Spectra are then extracted by predictionerror minimization based on an observer that tracks dynamically aliased modes and the results thus obtained are related, and compared, to established linear MHD stability theory. This pioneer study at T2R is, arguably, appealling both to plasma physicists and automatic control staff.
{"title":"Closed-loop direct parametric identification of magnetohydrodynamic normal modes spectra in EXTRAP-T2R reversed-field pinch","authors":"E. Olofsson, P1er Brunsell, J. Drake","doi":"10.1109/CCA.2009.5281183","DOIUrl":"https://doi.org/10.1109/CCA.2009.5281183","url":null,"abstract":"The reversed-field pinch (RFP) EXTRAP-T2R (T2R) is a plasma physics experiment with particular relevance for magnetic confinement fusion (MCF) research. T2R is very well equipped for investigations of magnetohydrodynamic (MHD) instabilities known as resistive-wall modes (RWMs), growing on a time-scale set by a surrounding non-perfectly conducting shell. The RWM instability is also subject of intense research in tokamak experiments (another MCF configuration). Recently, multiple RWMs have been stabilized in T2R using arrays of active (current-carrying) and sensor (voltage-measuring) coils equidistributed on the shell. In this paper, the MHD normal modes dynamics is probed in the required feedback operation by simultaneously, and pseudo-randomly, exciting the spectrum in the spatial sense. Spectra are then extracted by predictionerror minimization based on an observer that tracks dynamically aliased modes and the results thus obtained are related, and compared, to established linear MHD stability theory. This pioneer study at T2R is, arguably, appealling both to plasma physicists and automatic control staff.","PeriodicalId":294950,"journal":{"name":"2009 IEEE Control Applications, (CCA) & Intelligent Control, (ISIC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114385147","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 : 2009-07-08DOI: 10.1109/CCA.2009.5280702
S. García-Nieto, J. V. Salcedo, D. Laurí, Miguel A. Martínez
An extension of the model predictive control philosophy to the field of fuzzy control design is discussed. The main goal is to bring together the best features from both techniques. The basic idea is to divide the initial optimization problem in a set of recursive optimization subproblems or decision stages. Each subproblem is raised as a fuzzy LQR design where the goal is to define the set of feedback gains of a fuzzy Parallel Distributed Compensator (PDC) that minimizes the function cost using Linear Matrix Inequalities (LMIs). Therefore, the global controller is a set of PDC controllers that satisfies the Bellman optimality principle, minimizing the cost function both locally and globally, and guarantees stability and satisfies the control action constraints.
{"title":"Discrete Forward-Backward Fuzzy Predictive Control","authors":"S. García-Nieto, J. V. Salcedo, D. Laurí, Miguel A. Martínez","doi":"10.1109/CCA.2009.5280702","DOIUrl":"https://doi.org/10.1109/CCA.2009.5280702","url":null,"abstract":"An extension of the model predictive control philosophy to the field of fuzzy control design is discussed. The main goal is to bring together the best features from both techniques. The basic idea is to divide the initial optimization problem in a set of recursive optimization subproblems or decision stages. Each subproblem is raised as a fuzzy LQR design where the goal is to define the set of feedback gains of a fuzzy Parallel Distributed Compensator (PDC) that minimizes the function cost using Linear Matrix Inequalities (LMIs). Therefore, the global controller is a set of PDC controllers that satisfies the Bellman optimality principle, minimizing the cost function both locally and globally, and guarantees stability and satisfies the control action constraints.","PeriodicalId":294950,"journal":{"name":"2009 IEEE Control Applications, (CCA) & Intelligent Control, (ISIC)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115408981","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 : 2009-07-08DOI: 10.1109/CCA.2009.5280996
C. C. Hernández, E. Sánchez, A. Loukianov, B. Castillo-Toledo
This paper presents a discrete-time direct current (DC) motor torque tracking controller, based on a recurrent high order neural network (RHONN) to identify the plant model. Using this model, a control law is derived, which combines block control and sliding modes techniques. The applicability of the scheme is illustrated via real time implementation for a DC motor with separate winding excitation.
{"title":"Real-time torque control for a DC motor using recurrent high order neural networks","authors":"C. C. Hernández, E. Sánchez, A. Loukianov, B. Castillo-Toledo","doi":"10.1109/CCA.2009.5280996","DOIUrl":"https://doi.org/10.1109/CCA.2009.5280996","url":null,"abstract":"This paper presents a discrete-time direct current (DC) motor torque tracking controller, based on a recurrent high order neural network (RHONN) to identify the plant model. Using this model, a control law is derived, which combines block control and sliding modes techniques. The applicability of the scheme is illustrated via real time implementation for a DC motor with separate winding excitation.","PeriodicalId":294950,"journal":{"name":"2009 IEEE Control Applications, (CCA) & Intelligent Control, (ISIC)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125070504","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 : 2009-07-08DOI: 10.1109/CCA.2009.5281133
K. Glass, R. Colbaugh, M. Planck
The Internet occasionally experiences large disruptions, arising from both natural and manmade disturbances, and it is of significant interest to develop methods for locating within the network the source of a given disruption (i.e., the network element(s) whose perturbation initiated the event). This paper presents a new approach to realizing this logical localization objective. The proposed methodology consists of three steps: 1.) data preprocessing, in which publicly available measurements of Internet activity are acquired, “cleaned”, and assembled into a format suitable for computational analysis, 2.) event characterization via tensor factorization-based time series analysis, and 3.) localization of the source of the disruption through graph theoretic analysis. This procedure provides a principled, automated approach to identifying the root causes of network disruptions at “whole-Internet” scale. The considerable potential of the proposed analytic method is illustrated through both computer simulation studies and empirical.
{"title":"Logical localization of large Internet events","authors":"K. Glass, R. Colbaugh, M. Planck","doi":"10.1109/CCA.2009.5281133","DOIUrl":"https://doi.org/10.1109/CCA.2009.5281133","url":null,"abstract":"The Internet occasionally experiences large disruptions, arising from both natural and manmade disturbances, and it is of significant interest to develop methods for locating within the network the source of a given disruption (i.e., the network element(s) whose perturbation initiated the event). This paper presents a new approach to realizing this logical localization objective. The proposed methodology consists of three steps: 1.) data preprocessing, in which publicly available measurements of Internet activity are acquired, “cleaned”, and assembled into a format suitable for computational analysis, 2.) event characterization via tensor factorization-based time series analysis, and 3.) localization of the source of the disruption through graph theoretic analysis. This procedure provides a principled, automated approach to identifying the root causes of network disruptions at “whole-Internet” scale. The considerable potential of the proposed analytic method is illustrated through both computer simulation studies and empirical.","PeriodicalId":294950,"journal":{"name":"2009 IEEE Control Applications, (CCA) & Intelligent Control, (ISIC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123935778","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 : 2009-07-08DOI: 10.1109/CCA.2009.5280999
J. Chang, Jia-Jie Shyu, Chien-Wen Cho
Human activity recognition plays an essential role in e-health applications, such as automatic nursing home systems, human-machine interface, home care system, and smart home applications. Many of human activity recognition systems only used the posture of an image frame to classify an activity. But transitional relationships of postures embedded in the temporal sequence are important information for human activity recognition. In this paper, we combine temple posture matching and fuzzy rule reasoning to recognize an action. Firstly, a fore-ground subject is extracted and converted to a binary image by a statistical background model based on frame ratio, which is robust to illumination changes. For better efficiency and separability, the binary image is then trans-formed to a new space by eigenspace and canonical space transformation, and recognition is done in canonical space. A three image frame sequence, 5:1 down sampling from the video, is converted to a posture sequence by template matching. The posture sequence is classified to an action by fuzzy rules inference. Fuzzy rule approach can not only combine temporal sequence information for recognition but also be tolerant to variation of action done by different people. In our experiment, the proposed activity recognition method has demonstrated higher recognition accuracy of 91.8% than the HMM approach by about 5.4 %.
{"title":"Fuzzy rule inference based human activity recognition","authors":"J. Chang, Jia-Jie Shyu, Chien-Wen Cho","doi":"10.1109/CCA.2009.5280999","DOIUrl":"https://doi.org/10.1109/CCA.2009.5280999","url":null,"abstract":"Human activity recognition plays an essential role in e-health applications, such as automatic nursing home systems, human-machine interface, home care system, and smart home applications. Many of human activity recognition systems only used the posture of an image frame to classify an activity. But transitional relationships of postures embedded in the temporal sequence are important information for human activity recognition. In this paper, we combine temple posture matching and fuzzy rule reasoning to recognize an action. Firstly, a fore-ground subject is extracted and converted to a binary image by a statistical background model based on frame ratio, which is robust to illumination changes. For better efficiency and separability, the binary image is then trans-formed to a new space by eigenspace and canonical space transformation, and recognition is done in canonical space. A three image frame sequence, 5:1 down sampling from the video, is converted to a posture sequence by template matching. The posture sequence is classified to an action by fuzzy rules inference. Fuzzy rule approach can not only combine temporal sequence information for recognition but also be tolerant to variation of action done by different people. In our experiment, the proposed activity recognition method has demonstrated higher recognition accuracy of 91.8% than the HMM approach by about 5.4 %.","PeriodicalId":294950,"journal":{"name":"2009 IEEE Control Applications, (CCA) & Intelligent Control, (ISIC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123943129","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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