Pub Date : 2018-12-04DOI: 10.1109/COASE.2018.8560698
Kaiyan Yu, J. Yi, J. Shan
We present an integrated, electric-field-based method for Automated Characterization, Manipulation, and Assembly of Nanowires (ACMAN) into nanodevices by selectable electrical conductivities with precisely controlled positions and orientations. We combine electrophoresis-based motion-control, planning and manipulation strategies and contactless and solution-based electro-orientation spectroscopy (EOS) to simultaneously characterize and manipulate multiple individual nanowires. The ACMAN is a complete automated and online process to form functional nanodevice with desired electrical properties. We validate the ACMAN design by assembling field-effect transistors (FETs) with silicon nanowires of selected electrical conductivities. The results confirm the high performance of the FET by the ACMAN process.
{"title":"Automated Electric-Field-Based Nanowire Characterization, Manipulation, and Assembly","authors":"Kaiyan Yu, J. Yi, J. Shan","doi":"10.1109/COASE.2018.8560698","DOIUrl":"https://doi.org/10.1109/COASE.2018.8560698","url":null,"abstract":"We present an integrated, electric-field-based method for Automated Characterization, Manipulation, and Assembly of Nanowires (ACMAN) into nanodevices by selectable electrical conductivities with precisely controlled positions and orientations. We combine electrophoresis-based motion-control, planning and manipulation strategies and contactless and solution-based electro-orientation spectroscopy (EOS) to simultaneously characterize and manipulate multiple individual nanowires. The ACMAN is a complete automated and online process to form functional nanodevice with desired electrical properties. We validate the ACMAN design by assembling field-effect transistors (FETs) with silicon nanowires of selected electrical conductivities. The results confirm the high performance of the FET by the ACMAN process.","PeriodicalId":6518,"journal":{"name":"2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)","volume":"22 1","pages":"1612-1617"},"PeriodicalIF":0.0,"publicationDate":"2018-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72968053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/COASE.2018.8560518
Shuai Wang, Shaofeng Du, Tao Ma, Dongni Li
To solve intercell scheduling problem in industrial environments, heuristic rules are becoming popular due to the simplicity and efficiency. Grouping decisions in decision blocks is an efficient way to make the use of heuristic rules. A decision block generation algorithm based on grouping genetic algorithm (DBGA) is proposed in this paper. In DBGA, both the size and the constitution of each decision block are evolved together. Non-sequential entities are grouped into decision blocks and rules are assigned to decision blocks simultaneously. Comparative experiments are conducted with different structures of decision blocks. The results verify the effectiveness of DBGA.
{"title":"A Grouping Genetic Algorithm for the Intercell Scheduling Problem","authors":"Shuai Wang, Shaofeng Du, Tao Ma, Dongni Li","doi":"10.1109/COASE.2018.8560518","DOIUrl":"https://doi.org/10.1109/COASE.2018.8560518","url":null,"abstract":"To solve intercell scheduling problem in industrial environments, heuristic rules are becoming popular due to the simplicity and efficiency. Grouping decisions in decision blocks is an efficient way to make the use of heuristic rules. A decision block generation algorithm based on grouping genetic algorithm (DBGA) is proposed in this paper. In DBGA, both the size and the constitution of each decision block are evolved together. Non-sequential entities are grouped into decision blocks and rules are assigned to decision blocks simultaneously. Comparative experiments are conducted with different structures of decision blocks. The results verify the effectiveness of DBGA.","PeriodicalId":6518,"journal":{"name":"2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)","volume":"50 1","pages":"956-961"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73433787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/COASE.2018.8560338
Adnan Khan, M. Dahl, P. Falkman, Martin Fabian
In this paper, an approach to incorporate a digital twin for legacy production systems is presented. Hardware-in-the-loop setups are routinely used by manufacturing companies to carry out virtual commissioning. However, manufacturing companies having online legacy production systems are still struggling to incorporate a digital twin due to the absence of verified and validated simulation models. Companies that use virtual commissioning as a part of their engineering tool chain, usually perform offline verification of the simulation model. This approach is typically based on visual inspection and is a tedious task as each aspect of the model has to be visually validated. For legacy systems, only assessing the behavior visually in the absence of updated documents can result in an incorrect simulation model, i.e. simulating incorrect behavior with respect to the specification. Due to this, such simulation models cannot be incorporated in the engineering tool chain, as the simulated results can lead to improper decisions and can even cause equipment damage. This paper presents a platform and an approach, based on model-based testing, that is a first step for manufacturing companies to incorporate a validated simulation model for existing online production systems that will serve as a digital twin.
{"title":"Digital Twin for Legacy Systems: Simulation Model Testing and Validation","authors":"Adnan Khan, M. Dahl, P. Falkman, Martin Fabian","doi":"10.1109/COASE.2018.8560338","DOIUrl":"https://doi.org/10.1109/COASE.2018.8560338","url":null,"abstract":"In this paper, an approach to incorporate a digital twin for legacy production systems is presented. Hardware-in-the-loop setups are routinely used by manufacturing companies to carry out virtual commissioning. However, manufacturing companies having online legacy production systems are still struggling to incorporate a digital twin due to the absence of verified and validated simulation models. Companies that use virtual commissioning as a part of their engineering tool chain, usually perform offline verification of the simulation model. This approach is typically based on visual inspection and is a tedious task as each aspect of the model has to be visually validated. For legacy systems, only assessing the behavior visually in the absence of updated documents can result in an incorrect simulation model, i.e. simulating incorrect behavior with respect to the specification. Due to this, such simulation models cannot be incorporated in the engineering tool chain, as the simulated results can lead to improper decisions and can even cause equipment damage. This paper presents a platform and an approach, based on model-based testing, that is a first step for manufacturing companies to incorporate a validated simulation model for existing online production systems that will serve as a digital twin.","PeriodicalId":6518,"journal":{"name":"2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)","volume":"124 1","pages":"421-426"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73769448","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}
Specialty clinics typically have a critical issue with patient adherence to their appointments, and suffer a huge backlog of patients who need to be seen. The goal of this study is to enhance care providers' productivity and patient access to care through effective clinic appointment scheduling. We introduce a novel discrete-time bulk service queue to model the backlog dynamics, and consider different overbooking strategies to reduce backlog at a minimum risk of working overtime. The modeling framework provides a tool for scheduling template design, and the insights obtained from the models can support clinic operation decision-making, ultimately improving the operational efficiency of clinics, and patient outcomes and satisfaction.
{"title":"Overbooking for Specialty Clinics with Patient No-Shows: A Queueing Approach","authors":"Zhenghao Fan, Xiaolei Xie, Reynerio Sanchez, Xiang Zhong","doi":"10.1109/COASE.2018.8560573","DOIUrl":"https://doi.org/10.1109/COASE.2018.8560573","url":null,"abstract":"Specialty clinics typically have a critical issue with patient adherence to their appointments, and suffer a huge backlog of patients who need to be seen. The goal of this study is to enhance care providers' productivity and patient access to care through effective clinic appointment scheduling. We introduce a novel discrete-time bulk service queue to model the backlog dynamics, and consider different overbooking strategies to reduce backlog at a minimum risk of working overtime. The modeling framework provides a tool for scheduling template design, and the insights obtained from the models can support clinic operation decision-making, ultimately improving the operational efficiency of clinics, and patient outcomes and satisfaction.","PeriodicalId":6518,"journal":{"name":"2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)","volume":"68 1","pages":"396-401"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74618402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/COASE.2018.8560565
Xin-gang Hao, Mingyao Qi
The facility layout problem (FLP) has attracted much attention with abundant research on it. This paper studies the facility layout problem under a new industrial background. As increasing factories produce in full-automation, like chip production companies, which need orbits transmit materials, therefore, we consider a layout scheme that the facility is divided into several columns by vertical orbits, and in each column, there are several horizontal orbits with machines along both sides of them. We consider heterogeneous unequal-area machines, each type with more than one, to minimize the total theoretical material transmission distances. This study proposes a mixed integer linear programming (MILP) model to determine the locations of orbits, layouts of facilities as well as the material transmission routes which could lead to a global optimal solution. Through designed experiments, the results show how the parameter setting can affect the performance of the solution.
{"title":"Solving Unequal-Area Facility Layout Problems with Orbits in Fully Automatic System","authors":"Xin-gang Hao, Mingyao Qi","doi":"10.1109/COASE.2018.8560565","DOIUrl":"https://doi.org/10.1109/COASE.2018.8560565","url":null,"abstract":"The facility layout problem (FLP) has attracted much attention with abundant research on it. This paper studies the facility layout problem under a new industrial background. As increasing factories produce in full-automation, like chip production companies, which need orbits transmit materials, therefore, we consider a layout scheme that the facility is divided into several columns by vertical orbits, and in each column, there are several horizontal orbits with machines along both sides of them. We consider heterogeneous unequal-area machines, each type with more than one, to minimize the total theoretical material transmission distances. This study proposes a mixed integer linear programming (MILP) model to determine the locations of orbits, layouts of facilities as well as the material transmission routes which could lead to a global optimal solution. Through designed experiments, the results show how the parameter setting can affect the performance of the solution.","PeriodicalId":6518,"journal":{"name":"2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)","volume":"47 1","pages":"1183-1188"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78757432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/COASE.2018.8560488
K. Hidaka, N. Kameyama
In this paper, we present a method of effectively creating environment maps on an auto-transport system in logistics and industrial site management applications, e.g., an automobile assembly plant. The key objective of the study is creating a map effectively. Simultaneous Localization and Mapping (SLAM) is established as a general map-generating method. The map is, however, created with ad hoc and manual. Thus, an exploration method in an unknown environment for autonomously generating a map has been studied for decades. The main method is frontier-based exploration. This method presents a problem for an efficient mapping method in a wide environment, and for accuracy of the map depending on the local area. In the backgrounds, an autonomous exploration algorithm using only infrared sensor and odometer information from a robot is proposed as a sensor-based exploration approach without using map information. The proposed method requires only a depth sensor and camera on a robot. Next, we propose a hybrid exploration to decrease unavailable areas in frontier-based exploration. To perform our proposed method, an environment map is created by a mobile robot, and the effectiveness of the hybrid exploration method is demonstrated.
{"title":"Hybrid Sensor-Based and Frontier-Based Exploration Algorithm for Autonomous Transport Vehicle Map Generation","authors":"K. Hidaka, N. Kameyama","doi":"10.1109/COASE.2018.8560488","DOIUrl":"https://doi.org/10.1109/COASE.2018.8560488","url":null,"abstract":"In this paper, we present a method of effectively creating environment maps on an auto-transport system in logistics and industrial site management applications, e.g., an automobile assembly plant. The key objective of the study is creating a map effectively. Simultaneous Localization and Mapping (SLAM) is established as a general map-generating method. The map is, however, created with ad hoc and manual. Thus, an exploration method in an unknown environment for autonomously generating a map has been studied for decades. The main method is frontier-based exploration. This method presents a problem for an efficient mapping method in a wide environment, and for accuracy of the map depending on the local area. In the backgrounds, an autonomous exploration algorithm using only infrared sensor and odometer information from a robot is proposed as a sensor-based exploration approach without using map information. The proposed method requires only a depth sensor and camera on a robot. Next, we propose a hybrid exploration to decrease unavailable areas in frontier-based exploration. To perform our proposed method, an environment map is created by a mobile robot, and the effectiveness of the hybrid exploration method is demonstrated.","PeriodicalId":6518,"journal":{"name":"2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)","volume":"1 1","pages":"994-999"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74943974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/COASE.2018.8560593
Yunduan Cui, Lingwei Zhu, Morihiro Fujisaki, H. Kanokogi, Takamitsu Matsubara
This research focuses on applying reinforcement learning towards chemical plant control problems in order to optimize production while maintaining plant stability without requiring knowledge of the plant models. Since a typical chemical plant has a large number of sensors and actuators, the control problem of such a plant can be formulated as a Markov decision process involving high-dimensional state and a huge number of actions that might be difficult to solve by previous methods due to computational complexity and sample insufficiency. To overcome these issues, we propose a new reinforcement learning method, Factorial Kernel Dynamic Policy Programming, that employs 1) a factorial policy model and 2) a factor-wise kernel-based smooth policy update by regularization with the Kullback-Leibler divergence between the current and updated policies. To validate its effectiveness, FKDPP is evaluated via the Vinyl Acetate Monomer plant (VAM) model, a popular benchmark chemical plant control problem. Compared with previous methods that cannot directly process a huge number of actions, our proposed method leverages the same number of training samples and achieves a better control strategy for VAM yield, quality, and plant stability.
{"title":"Factorial Kernel Dynamic Policy Programming for Vinyl Acetate Monomer Plant Model Control","authors":"Yunduan Cui, Lingwei Zhu, Morihiro Fujisaki, H. Kanokogi, Takamitsu Matsubara","doi":"10.1109/COASE.2018.8560593","DOIUrl":"https://doi.org/10.1109/COASE.2018.8560593","url":null,"abstract":"This research focuses on applying reinforcement learning towards chemical plant control problems in order to optimize production while maintaining plant stability without requiring knowledge of the plant models. Since a typical chemical plant has a large number of sensors and actuators, the control problem of such a plant can be formulated as a Markov decision process involving high-dimensional state and a huge number of actions that might be difficult to solve by previous methods due to computational complexity and sample insufficiency. To overcome these issues, we propose a new reinforcement learning method, Factorial Kernel Dynamic Policy Programming, that employs 1) a factorial policy model and 2) a factor-wise kernel-based smooth policy update by regularization with the Kullback-Leibler divergence between the current and updated policies. To validate its effectiveness, FKDPP is evaluated via the Vinyl Acetate Monomer plant (VAM) model, a popular benchmark chemical plant control problem. Compared with previous methods that cannot directly process a huge number of actions, our proposed method leverages the same number of training samples and achieves a better control strategy for VAM yield, quality, and plant stability.","PeriodicalId":6518,"journal":{"name":"2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)","volume":"59 1","pages":"304-309"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84227829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/COASE.2018.8560400
M. Zou, Bo Lu, B. Vogel‐Heuser
During the collaborative development of production systems, models are used to represent different views on the systems. These models are heterogeneous in forms but dependent in contents. Inconsistencies among them should be properly handled in an early time. An automated process is favored due to high efficiency and low error proneness when compared to the conventional manual fixing. In this study, an approach for knowledge-based automatically resolving inconsistencies (KARI) is proposed to resolve inconsistencies across development models. The approach can resolve several different inconsistencies simultaneously without causing new inconsistencies. At the same time, changes required to resolve inconsistencies can be minimized. The feasibility of this approach is proved by selected industrial cases in the simulation.
{"title":"Resolving Inconsistencies Optimally in the Model-Based Development of Production Systems","authors":"M. Zou, Bo Lu, B. Vogel‐Heuser","doi":"10.1109/COASE.2018.8560400","DOIUrl":"https://doi.org/10.1109/COASE.2018.8560400","url":null,"abstract":"During the collaborative development of production systems, models are used to represent different views on the systems. These models are heterogeneous in forms but dependent in contents. Inconsistencies among them should be properly handled in an early time. An automated process is favored due to high efficiency and low error proneness when compared to the conventional manual fixing. In this study, an approach for knowledge-based automatically resolving inconsistencies (KARI) is proposed to resolve inconsistencies across development models. The approach can resolve several different inconsistencies simultaneously without causing new inconsistencies. At the same time, changes required to resolve inconsistencies can be minimized. The feasibility of this approach is proved by selected industrial cases in the simulation.","PeriodicalId":6518,"journal":{"name":"2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)","volume":"26 1","pages":"1064-1070"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85931634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/COASE.2018.8560409
Hyun-Jung Kim, Jun-Ho Lee
This paper examines a uniform parallel machine scheduling problem in which jobs can be split arbitrary into multiple sections and such job sections can be processed on a set of dedicated machines simultaneously. Once a job type is changed, a setup performed by an operator is required. The setup time is sequence-independent, and the number of setup operators is limited. Machines conduct the same operation but have different speeds. The objective is to minimize the maximum completion time. This problem is motivated from real-life applications that manufacture automotive pistons in Korea. We propose efficient heuristic algorithms for this problem and show experimentally that the performance of the algorithms is good enough to be used in practice.
{"title":"Uniform Parallel Machine Scheduling with Dedicated Machines, Job Splitting and Setup Resources","authors":"Hyun-Jung Kim, Jun-Ho Lee","doi":"10.1109/COASE.2018.8560409","DOIUrl":"https://doi.org/10.1109/COASE.2018.8560409","url":null,"abstract":"This paper examines a uniform parallel machine scheduling problem in which jobs can be split arbitrary into multiple sections and such job sections can be processed on a set of dedicated machines simultaneously. Once a job type is changed, a setup performed by an operator is required. The setup time is sequence-independent, and the number of setup operators is limited. Machines conduct the same operation but have different speeds. The objective is to minimize the maximum completion time. This problem is motivated from real-life applications that manufacture automotive pistons in Korea. We propose efficient heuristic algorithms for this problem and show experimentally that the performance of the algorithms is good enough to be used in practice.","PeriodicalId":6518,"journal":{"name":"2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)","volume":"54 1","pages":"661-663"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78299565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/COASE.2018.8560537
A. Lüder, J. Pauly, M. Wimmer
The engineering of control systems is an essential part within the engineering of production systems cumulating various predecessor engineering activities. Therefore a high data quality of the predecessor activities has to be ensured especially avoiding inconsistencies between provided sets of engineering data. Within this paper, a methodology is sketched applicable to model engineering discipline crossing consistency rules to enable an automatic evaluation for consistency management. It is based on the use of AutomationML as production system modelling language but can be generalized to further modelling means.
{"title":"Modelling consistency rules within production system engeering","authors":"A. Lüder, J. Pauly, M. Wimmer","doi":"10.1109/COASE.2018.8560537","DOIUrl":"https://doi.org/10.1109/COASE.2018.8560537","url":null,"abstract":"The engineering of control systems is an essential part within the engineering of production systems cumulating various predecessor engineering activities. Therefore a high data quality of the predecessor activities has to be ensured especially avoiding inconsistencies between provided sets of engineering data. Within this paper, a methodology is sketched applicable to model engineering discipline crossing consistency rules to enable an automatic evaluation for consistency management. It is based on the use of AutomationML as production system modelling language but can be generalized to further modelling means.","PeriodicalId":6518,"journal":{"name":"2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)","volume":"23 1","pages":"664-667"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78537737","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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