Pub Date : 2010-12-17DOI: 10.1109/ICCAS.2010.5669881
Hocheol Shin, Kyungmin Jeong, J. Kwon
This paper presents a snake robot moving in a small diameter pipe. A snake robot is a multi-linked modular robot. The snake robot, KAEROT-snake IV consists of 11 2-DOF actuator modules, a head, and a tail module. Each of the 2-DOF actuator modules has two small DC motors and worm gear boxes to increase the torque output and an embedded motor controller. The snake robot can move in a small diameter pipe with a sequence of holding motion as well as with a sinusoidal motion. Some modules holds the robot itself by pressing outward to induce friction while the other modules move forward/backward and hold the robot at a more front/rear position. A sequence of holding moves the robot forward/backward in a small diameter pipe.
{"title":"Development of a snake robot moving in a small diameter pipe","authors":"Hocheol Shin, Kyungmin Jeong, J. Kwon","doi":"10.1109/ICCAS.2010.5669881","DOIUrl":"https://doi.org/10.1109/ICCAS.2010.5669881","url":null,"abstract":"This paper presents a snake robot moving in a small diameter pipe. A snake robot is a multi-linked modular robot. The snake robot, KAEROT-snake IV consists of 11 2-DOF actuator modules, a head, and a tail module. Each of the 2-DOF actuator modules has two small DC motors and worm gear boxes to increase the torque output and an embedded motor controller. The snake robot can move in a small diameter pipe with a sequence of holding motion as well as with a sinusoidal motion. Some modules holds the robot itself by pressing outward to induce friction while the other modules move forward/backward and hold the robot at a more front/rear position. A sequence of holding moves the robot forward/backward in a small diameter pipe.","PeriodicalId":158687,"journal":{"name":"ICCAS 2010","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131239614","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 : 2010-12-17DOI: 10.1109/ICCAS.2010.5669671
H. Ahn, Kwang‐Kyo Oh
This paper addresses possible benefits and potential utilities of Euclidean distance matrix (EDM) in multi-agent formation systems. Using interval concept, this paper considers range variation, measurement uncertainties, and possible disturbances in the distances; and then using this result, we address a realization problem of partial interval matrices, a rigidity problem of corresponding graph, and a unique realization of partial interval distance matrices. This paper also outlines some specific applications of Euclidean distance matrix in command coordination. The central contribution of this paper is to propose of using Euclidean distance matrix in generating a command for multi-agent coordination.
{"title":"Command coordination in multi-agent formation: Euclidean distance matrix approaches","authors":"H. Ahn, Kwang‐Kyo Oh","doi":"10.1109/ICCAS.2010.5669671","DOIUrl":"https://doi.org/10.1109/ICCAS.2010.5669671","url":null,"abstract":"This paper addresses possible benefits and potential utilities of Euclidean distance matrix (EDM) in multi-agent formation systems. Using interval concept, this paper considers range variation, measurement uncertainties, and possible disturbances in the distances; and then using this result, we address a realization problem of partial interval matrices, a rigidity problem of corresponding graph, and a unique realization of partial interval distance matrices. This paper also outlines some specific applications of Euclidean distance matrix in command coordination. The central contribution of this paper is to propose of using Euclidean distance matrix in generating a command for multi-agent coordination.","PeriodicalId":158687,"journal":{"name":"ICCAS 2010","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130742135","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 : 2010-12-17DOI: 10.1109/ICCAS.2010.5670189
Baifan Chen, Z. Cai, Zhirong Zou
Data association is critical for the simultaneous localization and mapping (SLAM) of mobile robots. The classic data association algorithms have their own advantages and disadvantages, such as individual compatibility nearest neighbor (ICNN) algorithm and joint compatibility branch and bound (JCBB) algorithm. In this paper, we present a hybrid approach of data association based on local maps by combining them. ICNN is firstly used to do data association in the local map whose arrange is determined by the preset threshold. In order to overcome the problem of low reliability of ICNN, the errors detection in the data association results is necessary. If there are mismatchings, JCBB will be used to correct them in the local area around mismatched measurements to enhance the correct rate. The experimental results show that the proposed method performance of the speed and accuracy is satisfactory, even in the complex environments.
{"title":"A hybrid data association approach for mobile robot SLAM","authors":"Baifan Chen, Z. Cai, Zhirong Zou","doi":"10.1109/ICCAS.2010.5670189","DOIUrl":"https://doi.org/10.1109/ICCAS.2010.5670189","url":null,"abstract":"Data association is critical for the simultaneous localization and mapping (SLAM) of mobile robots. The classic data association algorithms have their own advantages and disadvantages, such as individual compatibility nearest neighbor (ICNN) algorithm and joint compatibility branch and bound (JCBB) algorithm. In this paper, we present a hybrid approach of data association based on local maps by combining them. ICNN is firstly used to do data association in the local map whose arrange is determined by the preset threshold. In order to overcome the problem of low reliability of ICNN, the errors detection in the data association results is necessary. If there are mismatchings, JCBB will be used to correct them in the local area around mismatched measurements to enhance the correct rate. The experimental results show that the proposed method performance of the speed and accuracy is satisfactory, even in the complex environments.","PeriodicalId":158687,"journal":{"name":"ICCAS 2010","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133670762","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 : 2010-12-17DOI: 10.1109/ICCAS.2010.5670211
Youngrae Jo, Sungho Jo
This work addresses the problem of behavioral performance of multi-robots corresponding to human drawing inputs in the sense of friendly human-robot interaction. We propose a drawing interface algorithm with multi-robots based on the centroidal Voronoi tessellation and the continuous-time Lloyd algorithms which have popularly been used for sensing and coverage control of multi-robots. Multi-robots can perform some meaningful behaviors through the realtime density functional update which reflects human drawings. Three drawing modes (distribution, following, and dancing modes) are implemented. Simulation tests verify the feasibility of the proposed algorithm.
{"title":"Behavioral performance of multi-robots driven by human drawing","authors":"Youngrae Jo, Sungho Jo","doi":"10.1109/ICCAS.2010.5670211","DOIUrl":"https://doi.org/10.1109/ICCAS.2010.5670211","url":null,"abstract":"This work addresses the problem of behavioral performance of multi-robots corresponding to human drawing inputs in the sense of friendly human-robot interaction. We propose a drawing interface algorithm with multi-robots based on the centroidal Voronoi tessellation and the continuous-time Lloyd algorithms which have popularly been used for sensing and coverage control of multi-robots. Multi-robots can perform some meaningful behaviors through the realtime density functional update which reflects human drawings. Three drawing modes (distribution, following, and dancing modes) are implemented. Simulation tests verify the feasibility of the proposed algorithm.","PeriodicalId":158687,"journal":{"name":"ICCAS 2010","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115210716","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 : 2010-12-17DOI: 10.1109/ICCAS.2010.5670175
Seh-Chan Oh, Hanmin Lee
Common safeguards have limited capability to maintain safety because they are a kind of passive systems, i.e. a station operator or someone should monitor and detect the event when an emergency occurs. It is very difficult to deal with the accidents instantly. Vision based Monitoring System detects possible accidents on railway platform, and effectively manages that situation. The system monitors all of the track area by using multiple stereo cameras, and immediately reports detection results with alarm to operator. Besides, the system automatically stops train, and broadcasts for passenger's safety because train stop by manual operation has a limit to emergency stop because of operator's reaction time. In this paper, we present the test results and analyze the detection performance of the system.
{"title":"Performance analysis of vision based monitoring system for passenger's safety on railway platform","authors":"Seh-Chan Oh, Hanmin Lee","doi":"10.1109/ICCAS.2010.5670175","DOIUrl":"https://doi.org/10.1109/ICCAS.2010.5670175","url":null,"abstract":"Common safeguards have limited capability to maintain safety because they are a kind of passive systems, i.e. a station operator or someone should monitor and detect the event when an emergency occurs. It is very difficult to deal with the accidents instantly. Vision based Monitoring System detects possible accidents on railway platform, and effectively manages that situation. The system monitors all of the track area by using multiple stereo cameras, and immediately reports detection results with alarm to operator. Besides, the system automatically stops train, and broadcasts for passenger's safety because train stop by manual operation has a limit to emergency stop because of operator's reaction time. In this paper, we present the test results and analyze the detection performance of the system.","PeriodicalId":158687,"journal":{"name":"ICCAS 2010","volume":"126 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115628770","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 : 2010-12-17DOI: 10.1109/ICCAS.2010.5669778
S. Hettiarachchi
The ability for a swarm of mobile agents to quickly adapt in unknown environments and reach a goal while avoiding obstacles and maintaining a formation is extremely important in time critical tasks. We utilize a physics-based autonomous agent framework combined with our DAEDALUS paradigm which allows the agents to learn from the neighboring agents. In traditional approaches, a swarm of agents learn the task in simulation(offline) combined with an evolutionary/genetic algorithm, and a global observer optimizes the swarm performance. In real world(online), the swarm of agents may have to rapidly adapt in unfamiliar environments. When there is no global observer and the online(real world) environment is dense with obstacles compared to offline environment, the performance feedback may be delayed or perturbed by noise, and the rules learned in simulation(offline) may not be sufficient to overcome the navigational difficulties, leaving the swarm to rapidly adapt in new environment. DAEDALUS is a paradigm designed to address these issues, by mimicking more closely the actual dynamics of populations of agents moving and interacting in a task environment. This paper presents an analysis of swarm adaptation using DAEDALUS in high obstacle density environments where agent interactions could be obstructed by obstacles.
{"title":"An evolutionary approach to swarm adaptation in dense environments","authors":"S. Hettiarachchi","doi":"10.1109/ICCAS.2010.5669778","DOIUrl":"https://doi.org/10.1109/ICCAS.2010.5669778","url":null,"abstract":"The ability for a swarm of mobile agents to quickly adapt in unknown environments and reach a goal while avoiding obstacles and maintaining a formation is extremely important in time critical tasks. We utilize a physics-based autonomous agent framework combined with our DAEDALUS paradigm which allows the agents to learn from the neighboring agents. In traditional approaches, a swarm of agents learn the task in simulation(offline) combined with an evolutionary/genetic algorithm, and a global observer optimizes the swarm performance. In real world(online), the swarm of agents may have to rapidly adapt in unfamiliar environments. When there is no global observer and the online(real world) environment is dense with obstacles compared to offline environment, the performance feedback may be delayed or perturbed by noise, and the rules learned in simulation(offline) may not be sufficient to overcome the navigational difficulties, leaving the swarm to rapidly adapt in new environment. DAEDALUS is a paradigm designed to address these issues, by mimicking more closely the actual dynamics of populations of agents moving and interacting in a task environment. This paper presents an analysis of swarm adaptation using DAEDALUS in high obstacle density environments where agent interactions could be obstructed by obstacles.","PeriodicalId":158687,"journal":{"name":"ICCAS 2010","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123988725","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 : 2010-12-17DOI: 10.1109/ICCAS.2010.5669890
B. Suksawat
In this paper classification of chip form and main cutting force prediction of cast nylon in turning operation by using artificial neural network (ANN) are described. The multi-layer perceptron of back-propagation neural network (BPNN) was employed as a tool to classify a chip form following ISO 3685-1977(E) and predicted the tangential cutting force. The turning operation was performed by a conventional form of high speed steel cutting tool with various cutting speeds, feed rates and depths of cutting. The BPNN structure had two models consisting of classification and prediction model. Each model composes of an input layer, two hidden layers and one output layer. Input layer composes of three input parameters, including cutting speed, feed rate and cutting depth. Hidden layer contains twenty nodes on each layer. A node of output layer was determined for obtaining the results. The sixty data from the experiments were used for neural network training with optimum parameters equal 0.6 of training rate and 0.6 of momentum. A set of data from the fifteen turning operation experiments were employed for prediction. The results revealed that the classification accuracy for classification chip form was 86.67%; and the main cutting force prediction was 91.130% of accuracy. Therefore, the chip form and main cutting force in cast nylon turning operation can be classified and predicted with reasonable accuracy for a given set of machining conditions using ANN model.
{"title":"Chip form classification and main cutting force prediction of cast nylon in turning operation using artificial neural network","authors":"B. Suksawat","doi":"10.1109/ICCAS.2010.5669890","DOIUrl":"https://doi.org/10.1109/ICCAS.2010.5669890","url":null,"abstract":"In this paper classification of chip form and main cutting force prediction of cast nylon in turning operation by using artificial neural network (ANN) are described. The multi-layer perceptron of back-propagation neural network (BPNN) was employed as a tool to classify a chip form following ISO 3685-1977(E) and predicted the tangential cutting force. The turning operation was performed by a conventional form of high speed steel cutting tool with various cutting speeds, feed rates and depths of cutting. The BPNN structure had two models consisting of classification and prediction model. Each model composes of an input layer, two hidden layers and one output layer. Input layer composes of three input parameters, including cutting speed, feed rate and cutting depth. Hidden layer contains twenty nodes on each layer. A node of output layer was determined for obtaining the results. The sixty data from the experiments were used for neural network training with optimum parameters equal 0.6 of training rate and 0.6 of momentum. A set of data from the fifteen turning operation experiments were employed for prediction. The results revealed that the classification accuracy for classification chip form was 86.67%; and the main cutting force prediction was 91.130% of accuracy. Therefore, the chip form and main cutting force in cast nylon turning operation can be classified and predicted with reasonable accuracy for a given set of machining conditions using ANN model.","PeriodicalId":158687,"journal":{"name":"ICCAS 2010","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124540866","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 : 2010-12-17DOI: 10.1109/ICCAS.2010.5669898
Reza Sobhani Ahmadgurabi, M. Nekoui, K. Salahshoor
Predictive controller based on model has been known as a reliable and robust controller in the last 20 years. This paper presents a new idea of design and implementing an adaptive model predictive controller on an industrial “dynamic” and “nonlinear” plant in an integrated software environment using Hysys and Matlab packages. The model predictive controller formation is based on an adaptive state-space prediction model of the system response to obtain the control action by minimizing an objective function. The designed MPC controller is utilized to regulate a gaseous industrial plant, simulated in Hysys. The objective of controlling the plant is to compensate for the pressure variations in topside output of the vessel in on-line form. In this paper, the opening value percentage (OP) of a valve in the output is randomly excited in a given interval to identify the output pressure in the plant, called as Process Variable (PV). The predicted and desired outputs are then employed in the designed model predictive controller to determine the control actions in the prediction horizon. The simulation results obtained in the developed integrated Hysys-Matlab environment, demonstrate the capability of the proposed approach to efficiently monitor and control an industrial gaseous plant in a real and practical manner.
{"title":"Design and implementation of an adaptive predictive controller for a nonlinear dynamic industrial plant using Hysys and Matlab simulation packages","authors":"Reza Sobhani Ahmadgurabi, M. Nekoui, K. Salahshoor","doi":"10.1109/ICCAS.2010.5669898","DOIUrl":"https://doi.org/10.1109/ICCAS.2010.5669898","url":null,"abstract":"Predictive controller based on model has been known as a reliable and robust controller in the last 20 years. This paper presents a new idea of design and implementing an adaptive model predictive controller on an industrial “dynamic” and “nonlinear” plant in an integrated software environment using Hysys and Matlab packages. The model predictive controller formation is based on an adaptive state-space prediction model of the system response to obtain the control action by minimizing an objective function. The designed MPC controller is utilized to regulate a gaseous industrial plant, simulated in Hysys. The objective of controlling the plant is to compensate for the pressure variations in topside output of the vessel in on-line form. In this paper, the opening value percentage (OP) of a valve in the output is randomly excited in a given interval to identify the output pressure in the plant, called as Process Variable (PV). The predicted and desired outputs are then employed in the designed model predictive controller to determine the control actions in the prediction horizon. The simulation results obtained in the developed integrated Hysys-Matlab environment, demonstrate the capability of the proposed approach to efficiently monitor and control an industrial gaseous plant in a real and practical manner.","PeriodicalId":158687,"journal":{"name":"ICCAS 2010","volume":"142 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114536665","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 : 2010-12-17DOI: 10.1109/ICCAS.2010.5669940
Chan Wong, C. Montes, L. Mears, J. Ziegert
This paper presents a model-based control algorithm to address the delayed feedback that occurs in a novel two dimensional positioning system. The delayed feedback causes the motion control system unable to track the desire setpoint accurately and at the same time introduce following error. Thus, a Modified Smith Predictor is proposed to address the delayed feedback by having an inner plant model to predict the path during the delay. Furthermore, an online system identification scheme is proposed to improve the accuracy of the model used in Modified Smith Predictor. Simulation and experimental results of the Modified Smith Predictor and online system identification are presented.
{"title":"Model-based control to enhance a novel two dimensional positioning system","authors":"Chan Wong, C. Montes, L. Mears, J. Ziegert","doi":"10.1109/ICCAS.2010.5669940","DOIUrl":"https://doi.org/10.1109/ICCAS.2010.5669940","url":null,"abstract":"This paper presents a model-based control algorithm to address the delayed feedback that occurs in a novel two dimensional positioning system. The delayed feedback causes the motion control system unable to track the desire setpoint accurately and at the same time introduce following error. Thus, a Modified Smith Predictor is proposed to address the delayed feedback by having an inner plant model to predict the path during the delay. Furthermore, an online system identification scheme is proposed to improve the accuracy of the model used in Modified Smith Predictor. Simulation and experimental results of the Modified Smith Predictor and online system identification are presented.","PeriodicalId":158687,"journal":{"name":"ICCAS 2010","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114550408","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 : 2010-12-17DOI: 10.1109/ICCAS.2010.5670101
P. Thumwarin, C. Prasit, K. Yakoompai, T. Matsuura
This paper presents a firearm identification method with rotation invariance. The rotation invariant feature can be extracted by the magnitude of Fourier coefficients of polar image of the cartridge on circles with different radii. Then the fluctuation of the obtained magnitude of Fourier coefficients can be reduced by the FIR(Finite impulse response) Wiener filter. And they are used as the input and the output of the FIR system characterizing the rotation invariant feature of cartridge image. The impulse response of the FIR system is used as the unique feature for firearm identification. Finally, the firearm can be identified by the Fisher's linear discriminant function. The experimental results are given to show the effectiveness of the proposed method.
{"title":"Firearm identification system with rotation invariance","authors":"P. Thumwarin, C. Prasit, K. Yakoompai, T. Matsuura","doi":"10.1109/ICCAS.2010.5670101","DOIUrl":"https://doi.org/10.1109/ICCAS.2010.5670101","url":null,"abstract":"This paper presents a firearm identification method with rotation invariance. The rotation invariant feature can be extracted by the magnitude of Fourier coefficients of polar image of the cartridge on circles with different radii. Then the fluctuation of the obtained magnitude of Fourier coefficients can be reduced by the FIR(Finite impulse response) Wiener filter. And they are used as the input and the output of the FIR system characterizing the rotation invariant feature of cartridge image. The impulse response of the FIR system is used as the unique feature for firearm identification. Finally, the firearm can be identified by the Fisher's linear discriminant function. The experimental results are given to show the effectiveness of the proposed method.","PeriodicalId":158687,"journal":{"name":"ICCAS 2010","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114911234","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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