Pub Date : 2020-12-14DOI: 10.1109/WSC48552.2020.9383995
C. Kuhlman, S. Ravi, Gizem Korkmaz, F. Vega-Redondo
Protest is a collective action problem and can be modeled as a coordination game in which people take an action with the potential to achieve shared mutual benefits. In game-theoretic contexts, successful coordination requires that people know each others’ willingness to participate, and that this information is common knowledge among a sufficient number of people. We develop an agent-based model of collective action that was the first to combine social structure and individual incentives. Another novel aspect of the model is that a social network increases in density (i.e., new graph edges are formed) over time. The model studies the formation of common knowledge through local interactions and the characterizing social network structures. We use four real-world, data-mined social networks (Facebook, Wikipedia, email, and peer-to-peer networks) and one scale-free network, and conduct computational experiments to study contagion dynamics under different conditions.
{"title":"An Agent-Based Model of Common Knowledge and Collective Action Dynamics on Social Networks","authors":"C. Kuhlman, S. Ravi, Gizem Korkmaz, F. Vega-Redondo","doi":"10.1109/WSC48552.2020.9383995","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9383995","url":null,"abstract":"Protest is a collective action problem and can be modeled as a coordination game in which people take an action with the potential to achieve shared mutual benefits. In game-theoretic contexts, successful coordination requires that people know each others’ willingness to participate, and that this information is common knowledge among a sufficient number of people. We develop an agent-based model of collective action that was the first to combine social structure and individual incentives. Another novel aspect of the model is that a social network increases in density (i.e., new graph edges are formed) over time. The model studies the formation of common knowledge through local interactions and the characterizing social network structures. We use four real-world, data-mined social networks (Facebook, Wikipedia, email, and peer-to-peer networks) and one scale-free network, and conduct computational experiments to study contagion dynamics under different conditions.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"3 1","pages":"218-229"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75397615","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 : 2020-12-14DOI: 10.1109/WSC48552.2020.9383947
Yagmur S. Gök, M. Tomasella, Daniel Guimarans, Cemalettin Ozturk
The problem of developing robust daily schedules for the teams turning around aircraft at airports has recently been approached through an efficient combination of project scheduling and vehicle routing models, and solved jointly by constraint programming and mixed integer programming solvers, organized in a matheuristic approach based on large neighborhood search. Therein, robustness is achieved through optimally allocating time windows to tasks, as well as allocating slack times to the routes to be followed by each team throughout their working shift. We enhance that approach by integrating discrete event simulation within a simheuristic scheme, whereby results from simulation provide constructive feedback to improve the overall robustness of the plan. This is achieved as a trade-off between the interests of each separate turnaround service provider and that of the airport as a whole. Numerical experiments show the applicability of the developed approach as a decision support mechanism at any airport.
{"title":"A Simheuristic Approach for Robust Scheduling of Airport Turnaround Teams","authors":"Yagmur S. Gök, M. Tomasella, Daniel Guimarans, Cemalettin Ozturk","doi":"10.1109/WSC48552.2020.9383947","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9383947","url":null,"abstract":"The problem of developing robust daily schedules for the teams turning around aircraft at airports has recently been approached through an efficient combination of project scheduling and vehicle routing models, and solved jointly by constraint programming and mixed integer programming solvers, organized in a matheuristic approach based on large neighborhood search. Therein, robustness is achieved through optimally allocating time windows to tasks, as well as allocating slack times to the routes to be followed by each team throughout their working shift. We enhance that approach by integrating discrete event simulation within a simheuristic scheme, whereby results from simulation provide constructive feedback to improve the overall robustness of the plan. This is achieved as a trade-off between the interests of each separate turnaround service provider and that of the airport as a whole. Numerical experiments show the applicability of the developed approach as a decision support mechanism at any airport.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"6 1","pages":"1336-1347"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72873285","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 : 2020-12-14DOI: 10.1109/WSC48552.2020.9383941
Miguel Saiz, M. A. Lostumbo, A. Juan, David López-López
Among other variables, uncertainty and limitation of resources make real-life project portfolio management a complex activity. Simulation-optimization is considered an appropriate technique to face stochastic problems like this one. The main objective of this paper is to develop a hybrid model, which combines optimization with Monte Carlo simulation, to deal with stochastic project portfolio management. A series of computational experiments illustrate how these hybrid approach can include uncertainty into the model, and how this is an essential contribution for informed decision making. A relevant novelty is the inclusion of a sustainability dimension, which allows managers to select and prioritize projects not only based on their monetary profitability but also taking into account the associated environmental and/or social impact. This additional criterion can be necessary when evaluating projects in areas such as civil engineering, building and construction, or urban transformation.
{"title":"On the Use of Simulation-Optimization in Sustainability Aware Project Portfolio Management","authors":"Miguel Saiz, M. A. Lostumbo, A. Juan, David López-López","doi":"10.1109/WSC48552.2020.9383941","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9383941","url":null,"abstract":"Among other variables, uncertainty and limitation of resources make real-life project portfolio management a complex activity. Simulation-optimization is considered an appropriate technique to face stochastic problems like this one. The main objective of this paper is to develop a hybrid model, which combines optimization with Monte Carlo simulation, to deal with stochastic project portfolio management. A series of computational experiments illustrate how these hybrid approach can include uncertainty into the model, and how this is an essential contribution for informed decision making. A relevant novelty is the inclusion of a sustainability dimension, which allows managers to select and prioritize projects not only based on their monetary profitability but also taking into account the associated environmental and/or social impact. This additional criterion can be necessary when evaluating projects in areas such as civil engineering, building and construction, or urban transformation.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"41 1","pages":"2493-2504"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90779266","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 : 2020-12-14DOI: 10.1109/WSC48552.2020.9383919
Jake Martin, Pushpendra Singh, A. Cohn, Jakob Kiel-Locey, K. Shehadeh, S. Saini, Jacob E. Kurlander
Colonoscopy procedures are key to reducing colorectal cancer incidence and improving outcomes. For this reason, it is important that clinics be designed to maximize access to care and to use clinic time effectively. This paper presents a simulation tool that analyzes different scheduling policies to see how they impact overall clinic operations. By simultaneously simulating both scheduling and operations, the tool can account for more variability and better predict actual outcomes. This tool can be used to inform clinics on what scheduling policies work best for their clinic and help analyze what the trade-offs will be between different policies.
{"title":"Integrated Simulation Tool to Analyze Patient Access to and Flow During Colonoscopy Appointments","authors":"Jake Martin, Pushpendra Singh, A. Cohn, Jakob Kiel-Locey, K. Shehadeh, S. Saini, Jacob E. Kurlander","doi":"10.1109/WSC48552.2020.9383919","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9383919","url":null,"abstract":"Colonoscopy procedures are key to reducing colorectal cancer incidence and improving outcomes. For this reason, it is important that clinics be designed to maximize access to care and to use clinic time effectively. This paper presents a simulation tool that analyzes different scheduling policies to see how they impact overall clinic operations. By simultaneously simulating both scheduling and operations, the tool can account for more variability and better predict actual outcomes. This tool can be used to inform clinics on what scheduling policies work best for their clinic and help analyze what the trade-offs will be between different policies.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"9 11","pages":"934-943"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91425039","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 : 2020-12-14DOI: 10.1109/WSC48552.2020.9384028
Cristina Ruiz Martin, Guillermo G. Trabes, Gabriel A. Wainer
Discrete Event Systems Specification (DEVS) is a well-known formalism to develop models using the discrete event approach. One advantage of DEVS is a clear separation between the modeling and simulation activities. The user only needs to develop models and general algorithms execute the simulations. The PDEVS simulation protocol is a well-know and widely accepted algorithm to execute DEVS simulations. However, when events are scheduled with time advance equal to zero, this algorithm handles them sequentially. Events that occur at the same time are processed one after the other. This may result in unwanted simulation results. In this work, we propose a new algorithm that assures that the output bag of a model is transmitted only when all the outputs corresponding to a given simulation time have been collected.
{"title":"A New Simulation Algorithm for PDEVS Models with Time Advance Zero","authors":"Cristina Ruiz Martin, Guillermo G. Trabes, Gabriel A. Wainer","doi":"10.1109/WSC48552.2020.9384028","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9384028","url":null,"abstract":"Discrete Event Systems Specification (DEVS) is a well-known formalism to develop models using the discrete event approach. One advantage of DEVS is a clear separation between the modeling and simulation activities. The user only needs to develop models and general algorithms execute the simulations. The PDEVS simulation protocol is a well-know and widely accepted algorithm to execute DEVS simulations. However, when events are scheduled with time advance equal to zero, this algorithm handles them sequentially. Events that occur at the same time are processed one after the other. This may result in unwanted simulation results. In this work, we propose a new algorithm that assures that the output bag of a model is transmitted only when all the outputs corresponding to a given simulation time have been collected.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"36 1","pages":"2208-2220"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90772790","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 : 2020-12-14DOI: 10.1109/WSC48552.2020.9384066
B. Feng, Kai Liu
Variable annuities are long-term insurance products that offer a large variety of investment-linked benefits, which have gained much popularity in the last decade. Accurate valuation of large variable annuity portfolios is an essential task for insurers. However, these products often have complicated payoffs that depend on both of the policyholder’s mortality risk and the financial market risk. Consequently, their values are usually estimated by computationally intensive Monte Carlo simulation. Simulating large numbers of sample paths from complex dynamic asset models is often a computational bottleneck. In this study, we propose and analyze three Quasi-Monte Carlo path generation methods, Cholesky decomposition, Brownian Bridge, and Principal Component Analysis, for the valuation of large VA portfolios. Our numerical results indicate that all three PGMs produce more accurate estimates than the standard Monte Carlo simulation at both the contract and portfolio levels.
{"title":"Path Generation Methods for Valuation of Large Variable Annuities Portfolio using Quasi-Monte Carlo Simulation","authors":"B. Feng, Kai Liu","doi":"10.1109/WSC48552.2020.9384066","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9384066","url":null,"abstract":"Variable annuities are long-term insurance products that offer a large variety of investment-linked benefits, which have gained much popularity in the last decade. Accurate valuation of large variable annuity portfolios is an essential task for insurers. However, these products often have complicated payoffs that depend on both of the policyholder’s mortality risk and the financial market risk. Consequently, their values are usually estimated by computationally intensive Monte Carlo simulation. Simulating large numbers of sample paths from complex dynamic asset models is often a computational bottleneck. In this study, we propose and analyze three Quasi-Monte Carlo path generation methods, Cholesky decomposition, Brownian Bridge, and Principal Component Analysis, for the valuation of large VA portfolios. Our numerical results indicate that all three PGMs produce more accurate estimates than the standard Monte Carlo simulation at both the contract and portfolio levels.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"34 1","pages":"481-491"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78748910","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 : 2020-12-14DOI: 10.1109/WSC48552.2020.9384020
J. Surdu, Dirk Harrington, Jason Black, Tony Lynch, Wyatt Schmitz, Jordan Bracken
The Army has a significant training gap for Stinger gunners and teams. In particular, there is no solution that enables Stinger teams to get credit for successful engagements in large force-on-force exercises if the aircraft are not equipped with MILES detectors, which is apparently usually the case. This paper describes the development of a surrogate Stinger missile that facilitates both home station and deployed force-on-force training. The effort described in this paper resulted in a single device that addresses the training previously addressed by the three other devices, all of which are aging and often irreplaceable. This paper describes the design of the Low Altitude Air Defense Training System (LAADTS), the implementation of the prototype and results, and the future work.
{"title":"Low Altitude Air Defense Training System","authors":"J. Surdu, Dirk Harrington, Jason Black, Tony Lynch, Wyatt Schmitz, Jordan Bracken","doi":"10.1109/WSC48552.2020.9384020","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9384020","url":null,"abstract":"The Army has a significant training gap for Stinger gunners and teams. In particular, there is no solution that enables Stinger teams to get credit for successful engagements in large force-on-force exercises if the aircraft are not equipped with MILES detectors, which is apparently usually the case. This paper describes the development of a surrogate Stinger missile that facilitates both home station and deployed force-on-force training. The effort described in this paper resulted in a single device that addresses the training previously addressed by the three other devices, all of which are aging and often irreplaceable. This paper describes the design of the Low Altitude Air Defense Training System (LAADTS), the implementation of the prototype and results, and the future work.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"11 1","pages":"1974-1982"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90819332","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 : 2020-12-14DOI: 10.1109/WSC48552.2020.9383945
Natalie Gentner, A. Kyek, Yao Yang, Mattia Carletti, Gian Antonio Susto
One of the main challenges in developing Machine Learning-based solutions for Semiconductor Manufacturing is the high number of machines in the production and their differences, even when considering chambers of the same machine; this poses a challenge in the scalability of Machine Learning-based solutions in this context, since the development of chamber-specific models for all equipment in the fab is unsustainable. In this work, we present a domain adaptation approach for Virtual Metrology (VM), one of the most successful Machine Learning-based technology in this context. The approach provides a common VM model for two identical-in-design chambers whose data follow different distributions. The approach is based on Domain-Adversarial Neural Networks and it has the merit of exploiting raw trace data, avoiding the loss of information that typically affects VM modules based on features. The effectiveness of the approach is demonstrated on real-world Etching.
{"title":"Enhancing Scalability of Virtual Metrology: A Deep Learning-Based Approach for Domain Adaptation","authors":"Natalie Gentner, A. Kyek, Yao Yang, Mattia Carletti, Gian Antonio Susto","doi":"10.1109/WSC48552.2020.9383945","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9383945","url":null,"abstract":"One of the main challenges in developing Machine Learning-based solutions for Semiconductor Manufacturing is the high number of machines in the production and their differences, even when considering chambers of the same machine; this poses a challenge in the scalability of Machine Learning-based solutions in this context, since the development of chamber-specific models for all equipment in the fab is unsustainable. In this work, we present a domain adaptation approach for Virtual Metrology (VM), one of the most successful Machine Learning-based technology in this context. The approach provides a common VM model for two identical-in-design chambers whose data follow different distributions. The approach is based on Domain-Adversarial Neural Networks and it has the merit of exploiting raw trace data, avoiding the loss of information that typically affects VM modules based on features. The effectiveness of the approach is demonstrated on real-world Etching.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"32 1","pages":"1898-1909"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90872270","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 : 2020-12-14DOI: 10.1109/WSC48552.2020.9383908
Andreas Ruscheinski, Anja Wolpers, P. Henning, Tom Warnke, Fiete Haack, A. Uhrmacher
Particle-based simulation is a powerful approach for modeling systems and processes of entities interacting in continuous space. One way to validate a particle-based simulation is to check for the occurrence of spatio-temporal patterns formed by the particles, for example by statistical model checking. Whereas spatio-temporal logics for describing spatio-temporal patterns exist, they are defined on discrete rather than continuous space. We propose an approach to bridge this gap by automatically translating the output of continuous-space particle-based simulations into an input for discrete-space spatio-temporal logics. The translation is parameterized with information about relevant regions and their development in time. We demonstrate the utility of our approach with a case study in which we successfully apply statistical model-checking to a particle-based cell-biological model. A Java implementation of our approach is available under an open-source license.
{"title":"Pragmatic Logic-Based Spatio-Temporal Pattern Checking in Particle-Based Models","authors":"Andreas Ruscheinski, Anja Wolpers, P. Henning, Tom Warnke, Fiete Haack, A. Uhrmacher","doi":"10.1109/WSC48552.2020.9383908","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9383908","url":null,"abstract":"Particle-based simulation is a powerful approach for modeling systems and processes of entities interacting in continuous space. One way to validate a particle-based simulation is to check for the occurrence of spatio-temporal patterns formed by the particles, for example by statistical model checking. Whereas spatio-temporal logics for describing spatio-temporal patterns exist, they are defined on discrete rather than continuous space. We propose an approach to bridge this gap by automatically translating the output of continuous-space particle-based simulations into an input for discrete-space spatio-temporal logics. The translation is parameterized with information about relevant regions and their development in time. We demonstrate the utility of our approach with a case study in which we successfully apply statistical model-checking to a particle-based cell-biological model. A Java implementation of our approach is available under an open-source license.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"37 1","pages":"2245-2256"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85062820","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 : 2020-12-14DOI: 10.1109/WSC48552.2020.9383915
Gerd Wagner
This tutorial article, which is extracted from (Wagner 2019), shows how to use UML Class Diagrams and Discrete Event Process Modeling Notation (DPMN) Process Diagrams for making simulation models of business processes with resource-constrained activities based on the DES paradigm of Object Event Modeling and Simulation. In this approach, the state structure of a business system is captured by a UML Class Diagram, which defines the types of objects, events and activities underlying a DPMN Process Diagram, which captures the causal regularities of the system in the form of a set of event rules. DPMN Process Diagrams extend the Event Graphs proposed by Schruben (1983) by adding elements from the Business Process Modeling Notation (BPMN), viz. data objects and activities, and, as its main innovation over BPMN, resource-dependent activity start arrows.
{"title":"Business Process Modeling And Simulation With DPMN: Resource-Constrained Activities","authors":"Gerd Wagner","doi":"10.1109/WSC48552.2020.9383915","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9383915","url":null,"abstract":"This tutorial article, which is extracted from (Wagner 2019), shows how to use UML Class Diagrams and Discrete Event Process Modeling Notation (DPMN) Process Diagrams for making simulation models of business processes with resource-constrained activities based on the DES paradigm of Object Event Modeling and Simulation. In this approach, the state structure of a business system is captured by a UML Class Diagram, which defines the types of objects, events and activities underlying a DPMN Process Diagram, which captures the causal regularities of the system in the form of a set of event rules. DPMN Process Diagrams extend the Event Graphs proposed by Schruben (1983) by adding elements from the Business Process Modeling Notation (BPMN), viz. data objects and activities, and, as its main innovation over BPMN, resource-dependent activity start arrows.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"76 1","pages":"45-59"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85119396","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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