Pub Date : 2017-07-10DOI: 10.1109/ICAR.2017.8023493
M. Durner, Simon Kriegel, Sebastian Riedel, Manuel Brucker, Zoltán-Csaba Márton, Ferenc Bálint-Benczédi, Rudolph Triebel
As the performance of key perception tasks heavily depends on their parametrization, deploying versatile robots to different application domains will also require a way to tune these changing scenarios by their operators. As many of these tunings are found by trial and error basically by experts as well, and the quality criteria change from application to application, we propose a Pipeline Optimization Framework that helps overcoming lengthy setup times by largely automating this process. When deployed, fine-tuning optimizations as presented in this paper can be initiated on pre-recorded data, dry runs, or automatically during operation. Here, we quantified the performance gains for two crucial modules based on ground truth annotated data. We release our challenging THR dataset, including evaluation scenes for two application scenarios.
{"title":"Experience-based optimization of robotic perception","authors":"M. Durner, Simon Kriegel, Sebastian Riedel, Manuel Brucker, Zoltán-Csaba Márton, Ferenc Bálint-Benczédi, Rudolph Triebel","doi":"10.1109/ICAR.2017.8023493","DOIUrl":"https://doi.org/10.1109/ICAR.2017.8023493","url":null,"abstract":"As the performance of key perception tasks heavily depends on their parametrization, deploying versatile robots to different application domains will also require a way to tune these changing scenarios by their operators. As many of these tunings are found by trial and error basically by experts as well, and the quality criteria change from application to application, we propose a Pipeline Optimization Framework that helps overcoming lengthy setup times by largely automating this process. When deployed, fine-tuning optimizations as presented in this paper can be initiated on pre-recorded data, dry runs, or automatically during operation. Here, we quantified the performance gains for two crucial modules based on ground truth annotated data. We release our challenging THR dataset, including evaluation scenes for two application scenarios.","PeriodicalId":198633,"journal":{"name":"2017 18th International Conference on Advanced Robotics (ICAR)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125579775","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 : 2017-07-01DOI: 10.1109/ICAR.2017.8023625
Abeer Imdoukh, A. Shaker, Aya Al-Toukhy, Darin Kablaoui, Mohammed El-Abd
Fire is one of the critical problems that have not been solved yet despite the technological development. Human losses are the most important aspect related to fires. Since it may be impossible to prevent fire from occurring, it would be helpful to minimize its impact in terms of human losses. The fact that unmanned aerial vehicles (UAVs) can handle dangerous and risky tasks as well as their fast and efficient performance allows them to be used in fire related problems such as entering and exploring disastrous zones. Hence, an indoor fireproof unmanned aerial vehicle that enables searching for survivors and locating them in minimal time is developed. The UAV is designed such that it can fly while carrying a fire extinguisher. Cameras are mounted on the UAV such that the person in control of the UAV is able to view the environment. In this way, the safety of firemen is ensured, since they know exactly where to go.
{"title":"Semi-autonomous indoor firefighting UAV","authors":"Abeer Imdoukh, A. Shaker, Aya Al-Toukhy, Darin Kablaoui, Mohammed El-Abd","doi":"10.1109/ICAR.2017.8023625","DOIUrl":"https://doi.org/10.1109/ICAR.2017.8023625","url":null,"abstract":"Fire is one of the critical problems that have not been solved yet despite the technological development. Human losses are the most important aspect related to fires. Since it may be impossible to prevent fire from occurring, it would be helpful to minimize its impact in terms of human losses. The fact that unmanned aerial vehicles (UAVs) can handle dangerous and risky tasks as well as their fast and efficient performance allows them to be used in fire related problems such as entering and exploring disastrous zones. Hence, an indoor fireproof unmanned aerial vehicle that enables searching for survivors and locating them in minimal time is developed. The UAV is designed such that it can fly while carrying a fire extinguisher. Cameras are mounted on the UAV such that the person in control of the UAV is able to view the environment. In this way, the safety of firemen is ensured, since they know exactly where to go.","PeriodicalId":198633,"journal":{"name":"2017 18th International Conference on Advanced Robotics (ICAR)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123698316","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 : 2017-07-01DOI: 10.1109/ICAR.2017.8023650
Fatemah Taqi, Fatima Al-Langawi, H. Abdulraheem, Mohammed El-Abd
The harvesting robot is a robot that is created for harvesting cherry tomatoes in households and greenhouses. For households, the project aims to protect the privacy of people who have their own gardens at home, and do not prefer to have workers coming to their home gardens to harvest the fruits. In addition, the weather in Kuwait is very hot, which makes it difficult for harvesters to work for long periods of time. This creates a problem because if the gardener does not finish harvesting on time; the fruits become rotten causing wastage and loss. Therefore, using a harvesting robot provides an excellent solution for harvesting in such conditions. The developed robot picks out the cherry tomatoes that are ripe enough without causing any damage to the surroundings, and leaves the ones that are not ripe enough. Moreover, the robot identifies the ripe cherry tomatoes by image sensing using a camera. After that, the robot picks the ripe cherry tomato and places it in a basket. The robot repeats the previous steps until there are no cherry tomatoes left on the trees. The robot has additional features, such as picking the rotten cherry tomatoes and placing them in a separate basket. In this paper, we present the design and implementation of this harvesting robot.
{"title":"A cherry-tomato harvesting robot","authors":"Fatemah Taqi, Fatima Al-Langawi, H. Abdulraheem, Mohammed El-Abd","doi":"10.1109/ICAR.2017.8023650","DOIUrl":"https://doi.org/10.1109/ICAR.2017.8023650","url":null,"abstract":"The harvesting robot is a robot that is created for harvesting cherry tomatoes in households and greenhouses. For households, the project aims to protect the privacy of people who have their own gardens at home, and do not prefer to have workers coming to their home gardens to harvest the fruits. In addition, the weather in Kuwait is very hot, which makes it difficult for harvesters to work for long periods of time. This creates a problem because if the gardener does not finish harvesting on time; the fruits become rotten causing wastage and loss. Therefore, using a harvesting robot provides an excellent solution for harvesting in such conditions. The developed robot picks out the cherry tomatoes that are ripe enough without causing any damage to the surroundings, and leaves the ones that are not ripe enough. Moreover, the robot identifies the ripe cherry tomatoes by image sensing using a camera. After that, the robot picks the ripe cherry tomato and places it in a basket. The robot repeats the previous steps until there are no cherry tomatoes left on the trees. The robot has additional features, such as picking the rotten cherry tomatoes and placing them in a separate basket. In this paper, we present the design and implementation of this harvesting robot.","PeriodicalId":198633,"journal":{"name":"2017 18th International Conference on Advanced Robotics (ICAR)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114143370","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 : 2017-07-01DOI: 10.1109/ICAR.2017.8023503
A. W. Li, G. S. Bastos
The purpose of this paper is to present a hybrid method of a particle filter for localization in mobile robotics. The main references are the particle filter based on Kullback-Leibler divergence and a self-adaptive particle filter using grid-energy. Gains and drawbacks of each method are discussed and compared with the developed algorithm. This hybrid particle filter explores the best quality of each method and the final result brings a solution to the localization problem: position tracking, global localization and kidnapping in a deterministic environment. This work was developed using the ROS framework (Robot Operating System) and tested with a Pioneer 3DX robot in real and simulation environments.
{"title":"A hybrid self-adaptive particle filter through KLD-sampling and SAMCL","authors":"A. W. Li, G. S. Bastos","doi":"10.1109/ICAR.2017.8023503","DOIUrl":"https://doi.org/10.1109/ICAR.2017.8023503","url":null,"abstract":"The purpose of this paper is to present a hybrid method of a particle filter for localization in mobile robotics. The main references are the particle filter based on Kullback-Leibler divergence and a self-adaptive particle filter using grid-energy. Gains and drawbacks of each method are discussed and compared with the developed algorithm. This hybrid particle filter explores the best quality of each method and the final result brings a solution to the localization problem: position tracking, global localization and kidnapping in a deterministic environment. This work was developed using the ROS framework (Robot Operating System) and tested with a Pioneer 3DX robot in real and simulation environments.","PeriodicalId":198633,"journal":{"name":"2017 18th International Conference on Advanced Robotics (ICAR)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131293892","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 : 2017-07-01DOI: 10.1109/ICAR.2017.8023632
Z. Dong, X. Ye, Jiacai Hong, Zhiwei Liu, Fan Yang
In order to solve the problem of harsh operating condition of the space manipulator, and the problem of not being able to afford great collision Momentum, this paper proposes a new technical method, namely soft-contact technology. According to the proposed method, the dynamic model of space flexible manipulator is built up based on Kane's equations. Then this paper makes a comparison simulation between dynamic models designed by ADAMS using same dynamic parameters. Simulation show that the curves obtained by Kane's equations and ADAMS are basically the same, so the correctness of the dynamic model of the space flexible manipulator based on Kane's equation has been proved.
{"title":"Research on dynamic modeling of soft-contact technology based on Kane's equations","authors":"Z. Dong, X. Ye, Jiacai Hong, Zhiwei Liu, Fan Yang","doi":"10.1109/ICAR.2017.8023632","DOIUrl":"https://doi.org/10.1109/ICAR.2017.8023632","url":null,"abstract":"In order to solve the problem of harsh operating condition of the space manipulator, and the problem of not being able to afford great collision Momentum, this paper proposes a new technical method, namely soft-contact technology. According to the proposed method, the dynamic model of space flexible manipulator is built up based on Kane's equations. Then this paper makes a comparison simulation between dynamic models designed by ADAMS using same dynamic parameters. Simulation show that the curves obtained by Kane's equations and ADAMS are basically the same, so the correctness of the dynamic model of the space flexible manipulator based on Kane's equation has been proved.","PeriodicalId":198633,"journal":{"name":"2017 18th International Conference on Advanced Robotics (ICAR)","volume":"232 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130837500","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 : 2017-07-01DOI: 10.1109/ICAR.2017.8023669
R. Raja, A. Dutta
This paper proposes a path planning method for a wheeled mobile robot operating in rough terrain dynamic environments using a combination of A∗ search algorithm and potential field method. In this method, the mobile robot uses the structured light system to extract real terrain data as a discrete points to generate a b-spline surface. The terrain is classified based on the slope and elevation using a fuzzy logic controller and a user defined cost function is generated. A combination of A∗ and potential field method has been introduced to find the path from the start location to goal location according to the cost function. The A∗ algorithm determines the path that globally optimizes terrain roughness, curvature and length of the path, and the potential field method has been used as a local planner which performs an on-line planning to avoid the newly detected obstacles by the sensory information. The developed potential function is found to be able to avoid local minima in the work space. The results shows the effectiveness of the proposed algorithm.
{"title":"Path planning in dynamic environment for a rover using A∗ and potential field method","authors":"R. Raja, A. Dutta","doi":"10.1109/ICAR.2017.8023669","DOIUrl":"https://doi.org/10.1109/ICAR.2017.8023669","url":null,"abstract":"This paper proposes a path planning method for a wheeled mobile robot operating in rough terrain dynamic environments using a combination of A∗ search algorithm and potential field method. In this method, the mobile robot uses the structured light system to extract real terrain data as a discrete points to generate a b-spline surface. The terrain is classified based on the slope and elevation using a fuzzy logic controller and a user defined cost function is generated. A combination of A∗ and potential field method has been introduced to find the path from the start location to goal location according to the cost function. The A∗ algorithm determines the path that globally optimizes terrain roughness, curvature and length of the path, and the potential field method has been used as a local planner which performs an on-line planning to avoid the newly detected obstacles by the sensory information. The developed potential function is found to be able to avoid local minima in the work space. The results shows the effectiveness of the proposed algorithm.","PeriodicalId":198633,"journal":{"name":"2017 18th International Conference on Advanced Robotics (ICAR)","volume":"52 18","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133655851","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 : 2017-07-01DOI: 10.1109/ICAR.2017.8023666
Zhongnan Qu
This paper describes an adaptive robust moving hands recognition algorithm using Kinect V2, which can detect the bare hands or hands with gloves in the real-time image stream under complex lighting condition. Firstly, according to the Bayes criterion, a novel skin color classification is built on the best separation plane in color space, which is found through linear discriminant analysis (LDA). Secondly, an adaptive learning rate and connected component theory are added to the traditional background subtraction. Finally, this new background subtraction and LDA skin color classification are combined together with an adaptive updated skin color look-up-table. In experiment results, this algorithm presents a satisfactory performance in hand detection under complex lighting condition.
{"title":"Adaptive robust moving hands recognition under complex lighting condition","authors":"Zhongnan Qu","doi":"10.1109/ICAR.2017.8023666","DOIUrl":"https://doi.org/10.1109/ICAR.2017.8023666","url":null,"abstract":"This paper describes an adaptive robust moving hands recognition algorithm using Kinect V2, which can detect the bare hands or hands with gloves in the real-time image stream under complex lighting condition. Firstly, according to the Bayes criterion, a novel skin color classification is built on the best separation plane in color space, which is found through linear discriminant analysis (LDA). Secondly, an adaptive learning rate and connected component theory are added to the traditional background subtraction. Finally, this new background subtraction and LDA skin color classification are combined together with an adaptive updated skin color look-up-table. In experiment results, this algorithm presents a satisfactory performance in hand detection under complex lighting condition.","PeriodicalId":198633,"journal":{"name":"2017 18th International Conference on Advanced Robotics (ICAR)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132260548","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 : 2017-07-01DOI: 10.1109/ICAR.2017.8023622
W. Reis, G. S. Bastos
This paper aims to analyze the Multi-Robot Task Allocation (MRTA) problem from the perspective of Social Choice Theory. More specifically taking into account the conditions of Arrow's Impossibility Theorem in a robot collective preference aggregation. The scalar utility comparison between two robots becomes impractical with an inexact estimate. As argued by Arrow, the cardinal utility comparison can be replaced by an ordinal comparison. The work also examines two different MRTA problems from this Arrovian view, while establishing Multi-Robot Social Choice and Multi-Robot Social Welfare functions.
{"title":"An Arrovian view on the multi-robot task allocation problem","authors":"W. Reis, G. S. Bastos","doi":"10.1109/ICAR.2017.8023622","DOIUrl":"https://doi.org/10.1109/ICAR.2017.8023622","url":null,"abstract":"This paper aims to analyze the Multi-Robot Task Allocation (MRTA) problem from the perspective of Social Choice Theory. More specifically taking into account the conditions of Arrow's Impossibility Theorem in a robot collective preference aggregation. The scalar utility comparison between two robots becomes impractical with an inexact estimate. As argued by Arrow, the cardinal utility comparison can be replaced by an ordinal comparison. The work also examines two different MRTA problems from this Arrovian view, while establishing Multi-Robot Social Choice and Multi-Robot Social Welfare functions.","PeriodicalId":198633,"journal":{"name":"2017 18th International Conference on Advanced Robotics (ICAR)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133194526","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 : 2017-07-01DOI: 10.1109/ICAR.2017.8023653
M. Salameh, A. Abdullah, S. Sahran
In this paper, we describe a novel extension of the real-time appearance-based mapping (RTAB-Map), called the Ensemble of Real-Time Appearance-Based Mapping (ERTAB-Map). The original RTAB-Map calculates the probabilities of multiple beliefs for loop closure detection based on a single descriptor model. However, the ERTAB-Map can use an arbitrary number of descriptor models, in which a set of probability belief models are evaluated using an ensemble learning approach. The probability values are extracted from the active working memory and the passive long term memory of RTAB-Map. We have performed experiments on 388 images from the Lib6Indoor and 1063 images from Lib6Outdoor datasets. The results show that our ensemble of active and passive outperforms the original RTAB-Map. Furthermore, the ensemble achieves a recall of 91.59% and 98.65% on the Lib6Indoor and Lib6Outdoor respectively, with a corresponding precision of 100%.
{"title":"Ensemble of Bayesian filter with active and passive nodes for loop closure detection","authors":"M. Salameh, A. Abdullah, S. Sahran","doi":"10.1109/ICAR.2017.8023653","DOIUrl":"https://doi.org/10.1109/ICAR.2017.8023653","url":null,"abstract":"In this paper, we describe a novel extension of the real-time appearance-based mapping (RTAB-Map), called the Ensemble of Real-Time Appearance-Based Mapping (ERTAB-Map). The original RTAB-Map calculates the probabilities of multiple beliefs for loop closure detection based on a single descriptor model. However, the ERTAB-Map can use an arbitrary number of descriptor models, in which a set of probability belief models are evaluated using an ensemble learning approach. The probability values are extracted from the active working memory and the passive long term memory of RTAB-Map. We have performed experiments on 388 images from the Lib6Indoor and 1063 images from Lib6Outdoor datasets. The results show that our ensemble of active and passive outperforms the original RTAB-Map. Furthermore, the ensemble achieves a recall of 91.59% and 98.65% on the Lib6Indoor and Lib6Outdoor respectively, with a corresponding precision of 100%.","PeriodicalId":198633,"journal":{"name":"2017 18th International Conference on Advanced Robotics (ICAR)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116315052","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 : 2017-07-01DOI: 10.1109/ICAR.2017.8023664
Guang-ming Xiong, Hao Li, Y. Jin, Jian-wei Gong, Huiyan Chen
Although efforts have been done to solve collision avoidance using either environment recognition sensors or vehicle-to-vehicle (V2V) communication information, it is still a challenging problem in some specific scene, e.g. highway entrance ramp. In this paper, we propose a new cooperative adaptive cruise control (CACC) method which combines information of environment recognition sensors and V2V communication. A collision detection system of CACC will work based on the information of V2V communication before environment recognition sensors detecting obstacles accurately. Co-simulation experiment using PreScan and Simulink is conducted. The experimental results show that the intelligent vehicle with our method can pass the freeway entrance ramp more safely.
{"title":"Collision avoidance system with cooperative adaptive cruise control in highway entrance ramp environment","authors":"Guang-ming Xiong, Hao Li, Y. Jin, Jian-wei Gong, Huiyan Chen","doi":"10.1109/ICAR.2017.8023664","DOIUrl":"https://doi.org/10.1109/ICAR.2017.8023664","url":null,"abstract":"Although efforts have been done to solve collision avoidance using either environment recognition sensors or vehicle-to-vehicle (V2V) communication information, it is still a challenging problem in some specific scene, e.g. highway entrance ramp. In this paper, we propose a new cooperative adaptive cruise control (CACC) method which combines information of environment recognition sensors and V2V communication. A collision detection system of CACC will work based on the information of V2V communication before environment recognition sensors detecting obstacles accurately. Co-simulation experiment using PreScan and Simulink is conducted. The experimental results show that the intelligent vehicle with our method can pass the freeway entrance ramp more safely.","PeriodicalId":198633,"journal":{"name":"2017 18th International Conference on Advanced Robotics (ICAR)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115267951","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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