Pub Date : 2013-12-08DOI: 10.1109/WSC.2013.6721693
Jamal Siadat, J. Ruwanpura
In the context of earth-moving (EM) projects, process-based simulation platforms have demonstrated their effectiveness in predicting project durations, costs, and resource requirements. However, these simulators are developed by simulation expert using advanced programming techniques. Therefore, understanding the details of these models or enhancing them to fit a particular purpose can be a daunting task. This paper presents Earth-Sim, an EM template developed using the SimFC simulation platform. Earth-Sim mimics the behaviors found in an earlier version of the SIMPHONY EMS template. SIMPHONY EMS was chosen because a) it is a well-recognized template which models all activities within the EM process; and b) it has been validated against data obtained from construction job-sites. This paper explains how Earth-Sim was developed solely using the common elements found in SimFC without any programming. Furthermore, the results obtained from Earth-Sim are compared against results from SIMPHONY EMS to illustrate the validity of the outputs.
{"title":"Effective simulation of earth moving projects","authors":"Jamal Siadat, J. Ruwanpura","doi":"10.1109/WSC.2013.6721693","DOIUrl":"https://doi.org/10.1109/WSC.2013.6721693","url":null,"abstract":"In the context of earth-moving (EM) projects, process-based simulation platforms have demonstrated their effectiveness in predicting project durations, costs, and resource requirements. However, these simulators are developed by simulation expert using advanced programming techniques. Therefore, understanding the details of these models or enhancing them to fit a particular purpose can be a daunting task. This paper presents Earth-Sim, an EM template developed using the SimFC simulation platform. Earth-Sim mimics the behaviors found in an earlier version of the SIMPHONY EMS template. SIMPHONY EMS was chosen because a) it is a well-recognized template which models all activities within the EM process; and b) it has been validated against data obtained from construction job-sites. This paper explains how Earth-Sim was developed solely using the common elements found in SimFC without any programming. Furthermore, the results obtained from Earth-Sim are compared against results from SIMPHONY EMS to illustrate the validity of the outputs.","PeriodicalId":223717,"journal":{"name":"2013 Winter Simulations Conference (WSC)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116894382","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}
Today's 300mm semiconductor facilities rely almost completely on Automated Material Handling Systems (AMHS) to transport wafers to equipment and storage areas in the wafer fabrication plant (fab). As the cost of equipment increases and the process technology becomes more and more sensitive to delivery times between steps, AMHS performance has become increasingly important to overall factory performance. Current AMHS design methods focus primarily on optimizing the balance between AMHS cost and AMHS performance. Understanding the influence of AMHS performance on fab operations has become an area of focus during the design process. This paper proposes a methodology to correlate AMHS performance measurements with simulated fab performance measures using a linked AMHS-fab model. This methodology facilitates model setup, scenario modification, model linkage, and calculations of performance impact. A sample evaluation study demonstrates the validation and analysis process, and derives conclusions applicable during the AMHS design process.
{"title":"Methodology to evaluate the impact of AMHS design characteristics on operational fab performance","authors":"G. Gaxiola, David Wizelman","doi":"10.5555/2675983.2675870","DOIUrl":"https://doi.org/10.5555/2675983.2675870","url":null,"abstract":"Today's 300mm semiconductor facilities rely almost completely on Automated Material Handling Systems (AMHS) to transport wafers to equipment and storage areas in the wafer fabrication plant (fab). As the cost of equipment increases and the process technology becomes more and more sensitive to delivery times between steps, AMHS performance has become increasingly important to overall factory performance. Current AMHS design methods focus primarily on optimizing the balance between AMHS cost and AMHS performance. Understanding the influence of AMHS performance on fab operations has become an area of focus during the design process. This paper proposes a methodology to correlate AMHS performance measurements with simulated fab performance measures using a linked AMHS-fab model. This methodology facilitates model setup, scenario modification, model linkage, and calculations of performance impact. A sample evaluation study demonstrates the validation and analysis process, and derives conclusions applicable during the AMHS design process.","PeriodicalId":223717,"journal":{"name":"2013 Winter Simulations Conference (WSC)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124194907","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 : 2013-12-08DOI: 10.1109/WSC.2013.6721701
S. Umeda
Due to environmental and ecological responsibility, enterprises are trying to reuse, remanufacture and recycle used products to reduce the negative impact on the environment. Reverse logistics is one of essential elements to implement such sustainable supply chain system. This paper proposes methodologies of simulation modeling and analysis of supply chain systems with reverse logistics flows. This paper discusses two types of reverse supply chain: PUSH-type reverse logistics and PULL-type reverse logistics. Generic models are introduced and analysis examples of individual features will be provided.
{"title":"Simulation analysis of supply chain systems with reverse logistics","authors":"S. Umeda","doi":"10.1109/WSC.2013.6721701","DOIUrl":"https://doi.org/10.1109/WSC.2013.6721701","url":null,"abstract":"Due to environmental and ecological responsibility, enterprises are trying to reuse, remanufacture and recycle used products to reduce the negative impact on the environment. Reverse logistics is one of essential elements to implement such sustainable supply chain system. This paper proposes methodologies of simulation modeling and analysis of supply chain systems with reverse logistics flows. This paper discusses two types of reverse supply chain: PUSH-type reverse logistics and PULL-type reverse logistics. Generic models are introduced and analysis examples of individual features will be provided.","PeriodicalId":223717,"journal":{"name":"2013 Winter Simulations Conference (WSC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125118517","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 : 2013-12-08DOI: 10.1109/WSC.2013.6721605
P. Einzinger, N. Popper, F. Breitenecker, N. Pfeffer, Reinhard Jung, G. Endel
In health care the reimbursement of medical providers is an important topic and can influence the overall outcome. We present the agent-based GAP-DRG model, which allows a comparison of reimbursement schemes in outpatient care. It models patients and medical providers as agents. In the simulation patients develop medical problems (i.e., diseases) and a need for medical services. This leads to utilization of medical providers. The reimbursement system receives information on the patients' visits via its generic interface, which facilitates an easy replacement. We describe the assumptions of the model in detail and show how it makes extensive use of available Austrian routine care data for its parameterization. The model design is optimized for utilizing as much of these data as possible. However, many assumptions have to be simplifications. Further work and detailed comparisons with health care data will provide insight on which assumptions are valid descriptions of the real process.
{"title":"The GAP-DRG model: Simulation of outpatient care for comparison of different reimbursement schemes","authors":"P. Einzinger, N. Popper, F. Breitenecker, N. Pfeffer, Reinhard Jung, G. Endel","doi":"10.1109/WSC.2013.6721605","DOIUrl":"https://doi.org/10.1109/WSC.2013.6721605","url":null,"abstract":"In health care the reimbursement of medical providers is an important topic and can influence the overall outcome. We present the agent-based GAP-DRG model, which allows a comparison of reimbursement schemes in outpatient care. It models patients and medical providers as agents. In the simulation patients develop medical problems (i.e., diseases) and a need for medical services. This leads to utilization of medical providers. The reimbursement system receives information on the patients' visits via its generic interface, which facilitates an easy replacement. We describe the assumptions of the model in detail and show how it makes extensive use of available Austrian routine care data for its parameterization. The model design is optimized for utilizing as much of these data as possible. However, many assumptions have to be simplifications. Further work and detailed comparisons with health care data will provide insight on which assumptions are valid descriptions of the real process.","PeriodicalId":223717,"journal":{"name":"2013 Winter Simulations Conference (WSC)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125382461","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 : 2013-12-08DOI: 10.1109/WSC.2013.6721519
Gerd Wagner
We discuss two forms of user-interactive simulation: in exploratory simulation users may explore a system by means of interventions, and in participatory simulation they may participate in a multi-agent simulation scenario by controlling (or `playing') one of the agents. Exploratory simulation can be used by researchers for validating a simulation model and it can be used by students and trainees for learning the dynamics of a system by interacting with a simulation model of it. Participatory simulation allows dealing with simulation problems where one (or more) of the involved human roles cannot be modeled sufficiently faithfully and therefore have to be played by human actors that participate in simulation runs. We elaborate the concepts of exploratory and participatory simulation on a general, implementation-independent level. We also show how they can be implemented with the AOR Simulation (AORS 2012) platform based on the human-computer interaction paradigm of agent control.
{"title":"Exploratory and participatory simulation","authors":"Gerd Wagner","doi":"10.1109/WSC.2013.6721519","DOIUrl":"https://doi.org/10.1109/WSC.2013.6721519","url":null,"abstract":"We discuss two forms of user-interactive simulation: in exploratory simulation users may explore a system by means of interventions, and in participatory simulation they may participate in a multi-agent simulation scenario by controlling (or `playing') one of the agents. Exploratory simulation can be used by researchers for validating a simulation model and it can be used by students and trainees for learning the dynamics of a system by interacting with a simulation model of it. Participatory simulation allows dealing with simulation problems where one (or more) of the involved human roles cannot be modeled sufficiently faithfully and therefore have to be played by human actors that participate in simulation runs. We elaborate the concepts of exploratory and participatory simulation on a general, implementation-independent level. We also show how they can be implemented with the AOR Simulation (AORS 2012) platform based on the human-computer interaction paradigm of agent control.","PeriodicalId":223717,"journal":{"name":"2013 Winter Simulations Conference (WSC)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114584788","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 : 2013-12-08DOI: 10.1109/WSC.2013.6721470
Soumyadip Ghosh, R. Pasupathy
The traditional estimator ξp, n for the p-quantile ξp of a random variable X, given n observations from the distribution of X, is obtained by inverting the empirical cumulative distribution function (cdf) constructed from the obtained observations. The estimator ξp, n requires O(n) storage, and it is well known that the mean squared error of ξp, n (with respect to p) decays as O(n-1). In this article, we present an alternative to ξp, n that seems to require dramatically less storage with negligible loss in convergence rate. The proposed estimator, ξp, n, relies on an alternative cdf that is constructed by accumulating the observed random variâtes into variable-sized bins that progressively become finer around the quantile. The size of the bins are strategically adjusted to ensure that the increased bias due to binning does not adversely affect the resulting convergence rate. We present an "online" version of the estimator ξp, n, along with a discussion of results on its consistency, convergence rates, and storage requirements. We also discuss analogous ideas for density estimation. We limit ourselves to heuristic arguments in support of the theoretical assertions we make, reserving more detailed proofs to a forthcoming paper.
{"title":"Low-storage online estimators for quantiles and densities","authors":"Soumyadip Ghosh, R. Pasupathy","doi":"10.1109/WSC.2013.6721470","DOIUrl":"https://doi.org/10.1109/WSC.2013.6721470","url":null,"abstract":"The traditional estimator ξ<sub>p, n</sub> for the p-quantile ξ<sub>p</sub> of a random variable X, given n observations from the distribution of X, is obtained by inverting the empirical cumulative distribution function (cdf) constructed from the obtained observations. The estimator ξ<sub>p, n</sub> requires O(n) storage, and it is well known that the mean squared error of ξ<sub>p, n</sub> (with respect to <sub>p</sub>) decays as O(n<sup>-1</sup>). In this article, we present an alternative to ξ<sub>p, n</sub> that seems to require dramatically less storage with negligible loss in convergence rate. The proposed estimator, ξ<sub>p, n</sub>, relies on an alternative cdf that is constructed by accumulating the observed random variâtes into variable-sized bins that progressively become finer around the quantile. The size of the bins are strategically adjusted to ensure that the increased bias due to binning does not adversely affect the resulting convergence rate. We present an \"online\" version of the estimator ξ<sub>p, n</sub>, along with a discussion of results on its consistency, convergence rates, and storage requirements. We also discuss analogous ideas for density estimation. We limit ourselves to heuristic arguments in support of the theoretical assertions we make, reserving more detailed proofs to a forthcoming paper.","PeriodicalId":223717,"journal":{"name":"2013 Winter Simulations Conference (WSC)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129510151","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 : 2013-12-08DOI: 10.1109/WSC.2013.6721505
Vincent Béchard, Normand Cote
Modeling industrial systems involving discrete and continuous processes is a challenge for practitioners. A simulation approach to handle these situations is based on flow rate discretization (instead of mass discretization): the discrete simulation unfolds as a series of steady-state flows calculation updated when a state variable changes or a random event occurs. Underlying mass balancing problem can be solved with the linear programming simplex algorithm. This paper presents a novel technique based on maximizing flow through a network where nodes are black-box model units. This network-based method is less sensitive to problem size; the computation effort required to solve the mass balance is proportional to O(m+n) instead of O(mn) with linear programming. The approach was implemented in FlexsimTM software and used to simulate an iron ore port terminal. Processes included in the model were: mine-to-port trains handling, port terminal equipment (processing rate, capacity, operating logic, failures) and ship loading.
{"title":"Simulation of mixed discrete and continuous systems: An iron ore terminal example","authors":"Vincent Béchard, Normand Cote","doi":"10.1109/WSC.2013.6721505","DOIUrl":"https://doi.org/10.1109/WSC.2013.6721505","url":null,"abstract":"Modeling industrial systems involving discrete and continuous processes is a challenge for practitioners. A simulation approach to handle these situations is based on flow rate discretization (instead of mass discretization): the discrete simulation unfolds as a series of steady-state flows calculation updated when a state variable changes or a random event occurs. Underlying mass balancing problem can be solved with the linear programming simplex algorithm. This paper presents a novel technique based on maximizing flow through a network where nodes are black-box model units. This network-based method is less sensitive to problem size; the computation effort required to solve the mass balance is proportional to O(m+n) instead of O(mn) with linear programming. The approach was implemented in FlexsimTM software and used to simulate an iron ore port terminal. Processes included in the model were: mine-to-port trains handling, port terminal equipment (processing rate, capacity, operating logic, failures) and ship loading.","PeriodicalId":223717,"journal":{"name":"2013 Winter Simulations Conference (WSC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129737147","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 : 2013-12-08DOI: 10.1109/WSC.2013.6721426
Anatoli Djanatliev, R. German
Prospective Health Technology Assessment allows early decision making for innovative health care technologies. The main idea is to combine available domain knowledge with advanced simulation techniques in order to predict the effects of medical products and to find bottlenecks and weaknesses within the health system. In our recent publications a hybrid simulation approach with System Dynamics and Agent-Based Modeling has been presented. Hospital workflows have been modeled by state charts within agent behavioral models and have to be instantiated each time an agent is entering a hospital. This paper presents a mechanism to generate agents dynamically from SD models and extends the previously presented hybrid approach by process-oriented Discrete Event Simulation for hospital modeling. It connects processes to health care institutions and not to persons traversing them. Two extended example case studies show potentials for medical decision making using the three simulation paradigms in a common environment.
{"title":"Prospective healthcare decision-making by combined system dynamics, discrete-event and agent-based simulation","authors":"Anatoli Djanatliev, R. German","doi":"10.1109/WSC.2013.6721426","DOIUrl":"https://doi.org/10.1109/WSC.2013.6721426","url":null,"abstract":"Prospective Health Technology Assessment allows early decision making for innovative health care technologies. The main idea is to combine available domain knowledge with advanced simulation techniques in order to predict the effects of medical products and to find bottlenecks and weaknesses within the health system. In our recent publications a hybrid simulation approach with System Dynamics and Agent-Based Modeling has been presented. Hospital workflows have been modeled by state charts within agent behavioral models and have to be instantiated each time an agent is entering a hospital. This paper presents a mechanism to generate agents dynamically from SD models and extends the previously presented hybrid approach by process-oriented Discrete Event Simulation for hospital modeling. It connects processes to health care institutions and not to persons traversing them. Two extended example case studies show potentials for medical decision making using the three simulation paradigms in a common environment.","PeriodicalId":223717,"journal":{"name":"2013 Winter Simulations Conference (WSC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128472296","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 : 2013-12-08DOI: 10.1109/WSC.2013.6721453
Yuan Jun, S. Ng
Computer models are widely used to simulate complex and costly real processes and systems. In the calibration process of the computer model, the calibration parameters are adjusted to fit the model closely to the real observed data. As these calibration parameters are unknown and are estimated based on observed data, it is important to estimate it accurately and account for the estimation uncertainty in the subsequent use of the model. In this paper, we study in detail an empirical Bayes approach for stochastic computer model calibration that accounts for various uncertainties including the calibration parameter uncertainty, and propose an entropy based criterion to improve on the estimation of the calibration parameter. This criterion is also compared with the EIMSPE criterion.
{"title":"An entropy based sequential calibration approach for stochastic computer models","authors":"Yuan Jun, S. Ng","doi":"10.1109/WSC.2013.6721453","DOIUrl":"https://doi.org/10.1109/WSC.2013.6721453","url":null,"abstract":"Computer models are widely used to simulate complex and costly real processes and systems. In the calibration process of the computer model, the calibration parameters are adjusted to fit the model closely to the real observed data. As these calibration parameters are unknown and are estimated based on observed data, it is important to estimate it accurately and account for the estimation uncertainty in the subsequent use of the model. In this paper, we study in detail an empirical Bayes approach for stochastic computer model calibration that accounts for various uncertainties including the calibration parameter uncertainty, and propose an entropy based criterion to improve on the estimation of the calibration parameter. This criterion is also compared with the EIMSPE criterion.","PeriodicalId":223717,"journal":{"name":"2013 Winter Simulations Conference (WSC)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126562231","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 : 2013-12-08DOI: 10.1109/WSC.2013.6721502
Guilherme Steinmann, Paulo José de Freitas Filho
The call center industry has expanded greatly over recent years and it is constantly striving to increase business efficiency and customer service effectiveness. Incoming call volume forecasting algorithms are used in inbound call centers to predict the demand for services and, as a result, to plan resource allocation. However, a number of phenomena can have an impact on incoming call volumes, meaning that classical forecasting algorithms will produce less than satisfactory results. When evaluating the performance of a forecasting algorithm, acquiring the data needed for research is not always straightforward. This article shows how simulation can be of use to generate data that can be used to evaluate incoming call forecasting algorithms.
{"title":"Using simulation to evaluate call forecasting algorithms for inbound call center","authors":"Guilherme Steinmann, Paulo José de Freitas Filho","doi":"10.1109/WSC.2013.6721502","DOIUrl":"https://doi.org/10.1109/WSC.2013.6721502","url":null,"abstract":"The call center industry has expanded greatly over recent years and it is constantly striving to increase business efficiency and customer service effectiveness. Incoming call volume forecasting algorithms are used in inbound call centers to predict the demand for services and, as a result, to plan resource allocation. However, a number of phenomena can have an impact on incoming call volumes, meaning that classical forecasting algorithms will produce less than satisfactory results. When evaluating the performance of a forecasting algorithm, acquiring the data needed for research is not always straightforward. This article shows how simulation can be of use to generate data that can be used to evaluate incoming call forecasting algorithms.","PeriodicalId":223717,"journal":{"name":"2013 Winter Simulations Conference (WSC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126107127","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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