Pub Date : 2020-12-14DOI: 10.1109/WSC48552.2020.9383923
Javier Panadero, A. Juan, Alfons Freixes, M. Grifoll, C. Serrat, Mohammad Dehghanimohamamdabadi
Efficient coordination of unmanned aerial vehicles (UAVs) requires the solving of challenging operational problems. One of them is the integrated team task assignment and orienteering problem (TAOP). The TAOP can be seen as an extension of the well-known team orienteering problem (TOP). In the classical TOP, a homogeneous fleet of UAVs has to select and visit a subset of customers in order to maximize, subject to a maximum travel time per route, the total reward obtained from these visits. In the TAOP, a number of different tasks (customer services) have to be assigned to a fleet of heterogeneous UAVs, while the best routing plan must also be determined to cover these services. Since factors such as weather conditions might influence travel times, these are modeled as random variables. Reliability issues are also considered, since random times might prevent a route from being successfully completed before a UAV runs out of battery.
{"title":"An Agile Simheuristic for the Stochastic Team Task Assignment and Orienteering Problem: Applications to Unmanned Aerial Vehicles","authors":"Javier Panadero, A. Juan, Alfons Freixes, M. Grifoll, C. Serrat, Mohammad Dehghanimohamamdabadi","doi":"10.1109/WSC48552.2020.9383923","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9383923","url":null,"abstract":"Efficient coordination of unmanned aerial vehicles (UAVs) requires the solving of challenging operational problems. One of them is the integrated team task assignment and orienteering problem (TAOP). The TAOP can be seen as an extension of the well-known team orienteering problem (TOP). In the classical TOP, a homogeneous fleet of UAVs has to select and visit a subset of customers in order to maximize, subject to a maximum travel time per route, the total reward obtained from these visits. In the TAOP, a number of different tasks (customer services) have to be assigned to a fleet of heterogeneous UAVs, while the best routing plan must also be determined to cover these services. Since factors such as weather conditions might influence travel times, these are modeled as random variables. Reliability issues are also considered, since random times might prevent a route from being successfully completed before a UAV runs out of battery.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"10 1","pages":"1324-1335"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82595717","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/WSC48552.2020.9384113
Andrew J. Collins, Sheida Etemadidavan, Pilar Pazos Lago
Agent-based modeling (ABM) provides a means to investigate the emergent phenomenon generated from interacting autonomous agents. However, there are some concerns with this modeling approach. One concern is how to integrate strategic group formation, into ABM, without imposing macro-level aggregation rules. Another concern is whether the computerized agents’ behavior is reflective of actual human behavior. Collins and Frydenlund developed a hybrid modeling approach to address the first concern in 2018. The focus of our paper is on the second concern, in the context of the hybrid model. An experiment was conducted to help determine whether a person’s experiences affect their behavior and whether their behavior is similar to those generated by the hybrid model. The experimental results confirmed these two assertions. Our experiment used a standard cooperative game-theoretic game, called the glove game, as its base scenario.
{"title":"A Human Experiment Using a Hybrid Agent-Based Model","authors":"Andrew J. Collins, Sheida Etemadidavan, Pilar Pazos Lago","doi":"10.1109/WSC48552.2020.9384113","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9384113","url":null,"abstract":"Agent-based modeling (ABM) provides a means to investigate the emergent phenomenon generated from interacting autonomous agents. However, there are some concerns with this modeling approach. One concern is how to integrate strategic group formation, into ABM, without imposing macro-level aggregation rules. Another concern is whether the computerized agents’ behavior is reflective of actual human behavior. Collins and Frydenlund developed a hybrid modeling approach to address the first concern in 2018. The focus of our paper is on the second concern, in the context of the hybrid model. An experiment was conducted to help determine whether a person’s experiences affect their behavior and whether their behavior is similar to those generated by the hybrid model. The experimental results confirmed these two assertions. Our experiment used a standard cooperative game-theoretic game, called the glove game, as its base scenario.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"1 1","pages":"1016-1026"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83084580","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/WSC48552.2020.9383878
Philipp Gabriel Mazur, No-San Lee, D. Schoder
In the air cargo context, pallet loading faces substantial constraints and item heterogeneity. The stability constraint in the pallet loading problem is highly important due to its impact on the efficiency, security, and resulting costs of an air cargo company. In information systems that support pallet loading, physical simulations provide a realistic approximation of a pallet’s stability. However, current approaches neglect the opportunity to integrate physical simulations in underlying solvers. In this research, we propose and compare two approaches for integrating a physical simulation as a fixed component of the problem-solving heuristic and include irregular shapes. Our results achieve runtimes that meet air cargo requirements; therefore, assumptions about the cargo, e.g., shape assumptions, can be relaxed.
{"title":"Integration of Physical Simulations in Static Stability Assessments for Pallet Loading in Air Cargo","authors":"Philipp Gabriel Mazur, No-San Lee, D. Schoder","doi":"10.1109/WSC48552.2020.9383878","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9383878","url":null,"abstract":"In the air cargo context, pallet loading faces substantial constraints and item heterogeneity. The stability constraint in the pallet loading problem is highly important due to its impact on the efficiency, security, and resulting costs of an air cargo company. In information systems that support pallet loading, physical simulations provide a realistic approximation of a pallet’s stability. However, current approaches neglect the opportunity to integrate physical simulations in underlying solvers. In this research, we propose and compare two approaches for integrating a physical simulation as a fixed component of the problem-solving heuristic and include irregular shapes. Our results achieve runtimes that meet air cargo requirements; therefore, assumptions about the cargo, e.g., shape assumptions, can be relaxed.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"20 1","pages":"1312-1323"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90323558","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/WSC48552.2020.9383884
Timo P. Gros, Joschka Groß, V. Wolf
Computer simulations of manufacturing processes are in widespread use for optimizing production planning and order processing. If unforeseeable events are common, real-time decisions are necessary to maximize the performance of the manufacturing process. Pre-trained AI-based decision support offers promising opportunities for such time-critical production processes. Here, we explore the effectiveness of deep reinforcement learning for real-time decision making in a car manufacturing process. We combine a simulation model of a central production part, the line buffer, with deep reinforcement learning algorithms, in particular with deep Q-Learning and Monte Carlo tree search. We simulate two different versions of the buffer, a single-agent and a multi-agent one, to generate large amounts of data and train neural networks to represent near-optimal strategies. Our results show that deep reinforcement learning performs extremely well and the resulting strategies provide near-optimal decisions in real-time, while alternative approaches are either slow or give strategies of poor quality.
{"title":"Real-Time Decision Making for a Car Manufacturing Process Using Deep Reinforcement Learning","authors":"Timo P. Gros, Joschka Groß, V. Wolf","doi":"10.1109/WSC48552.2020.9383884","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9383884","url":null,"abstract":"Computer simulations of manufacturing processes are in widespread use for optimizing production planning and order processing. If unforeseeable events are common, real-time decisions are necessary to maximize the performance of the manufacturing process. Pre-trained AI-based decision support offers promising opportunities for such time-critical production processes. Here, we explore the effectiveness of deep reinforcement learning for real-time decision making in a car manufacturing process. We combine a simulation model of a central production part, the line buffer, with deep reinforcement learning algorithms, in particular with deep Q-Learning and Monte Carlo tree search. We simulate two different versions of the buffer, a single-agent and a multi-agent one, to generate large amounts of data and train neural networks to represent near-optimal strategies. Our results show that deep reinforcement learning performs extremely well and the resulting strategies provide near-optimal decisions in real-time, while alternative approaches are either slow or give strategies of poor quality.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"38 1","pages":"3032-3044"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83861706","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/WSC48552.2020.9384007
Elizabeth P. Reilly, S. Agarwala, Michael T. Kelbaugh, Agata Ciesielski, Hani-James M. Ebeid, Marisa Hughes
We built a system of systems model to better understand the relationship between the agricultural sector, other economic factors, and changes in the expected value of conflict. Our model integrates multiple factors, including food production, food trade, population, and civil conflict, and determines their interdependencies based on shared inputs or outputs. We find that severe food price shocks, precipitated by multiple breadbasket failures, can severely impact a country’s GDP and its ability to purchase and consume a sufficient amount of food, resulting in an increase in civil conflict and related casualties. A sharp population increase, as potentially caused by an immigration surge, was found to have a similar impact, though not as strong.
{"title":"Modeling the Relationship Between Food and Civil Conflict","authors":"Elizabeth P. Reilly, S. Agarwala, Michael T. Kelbaugh, Agata Ciesielski, Hani-James M. Ebeid, Marisa Hughes","doi":"10.1109/WSC48552.2020.9384007","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9384007","url":null,"abstract":"We built a system of systems model to better understand the relationship between the agricultural sector, other economic factors, and changes in the expected value of conflict. Our model integrates multiple factors, including food production, food trade, population, and civil conflict, and determines their interdependencies based on shared inputs or outputs. We find that severe food price shocks, precipitated by multiple breadbasket failures, can severely impact a country’s GDP and its ability to purchase and consume a sufficient amount of food, resulting in an increase in civil conflict and related casualties. A sharp population increase, as potentially caused by an immigration surge, was found to have a similar impact, though not as strong.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"35 1","pages":"715-726"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86330172","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/WSC48552.2020.9383948
Román Cárdenas, Kevin Henares, Patricia Arroba, Gabriel A. Wainer, J. L. Risco-Martín
The Discrete EVent System Specification (DEVS) formalism provides a unified method to define any discrete-event system accurately. As the complexity of the system under study increases, the necessity of simulation engines with higher performance rises. In this research, we present a chained DEVS simulator, a DEVS-compliant, function-oriented simulation algorithm that exploits shared memory patterns to improve the performance of sequential and parallel simulations. We also illustrate the positive impact of this novel approach executing a set of DEVStone synthetic benchmarks and comparing a state-of-the-art simulation engine with an updated version that implements the chained algorithm. Results show that the chained simulator introduces up to 40% less synchronization overhead than the traditional simulation approach.
{"title":"A dEVS Simulation Algorithm Based on Shared Memory for Enhancing Performance","authors":"Román Cárdenas, Kevin Henares, Patricia Arroba, Gabriel A. Wainer, J. L. Risco-Martín","doi":"10.1109/WSC48552.2020.9383948","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9383948","url":null,"abstract":"The Discrete EVent System Specification (DEVS) formalism provides a unified method to define any discrete-event system accurately. As the complexity of the system under study increases, the necessity of simulation engines with higher performance rises. In this research, we present a chained DEVS simulator, a DEVS-compliant, function-oriented simulation algorithm that exploits shared memory patterns to improve the performance of sequential and parallel simulations. We also illustrate the positive impact of this novel approach executing a set of DEVStone synthetic benchmarks and comparing a state-of-the-art simulation engine with an updated version that implements the chained algorithm. Results show that the chained simulator introduces up to 40% less synchronization overhead than the traditional simulation approach.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"23 1","pages":"2184-2195"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83939469","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/WSC48552.2020.9383993
A. M. Law
One of the most important but neglected aspects of a simulation study is the proper design and analysis of simulation experiments. In this tutorial we give a state-of-the-art presentation of what the practitioner really needs to know to be successful. We will discuss how to choose the simulation run length, the warmup-period duration (if any), and the required number of model replications (each using different random numbers). The talk concludes with a discussion of three critical pitfalls in simulation output-data analysis.
{"title":"Statistical Analysis of Simulation Output Data: The Practical State of the Art","authors":"A. M. Law","doi":"10.1109/WSC48552.2020.9383993","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9383993","url":null,"abstract":"One of the most important but neglected aspects of a simulation study is the proper design and analysis of simulation experiments. In this tutorial we give a state-of-the-art presentation of what the practitioner really needs to know to be successful. We will discuss how to choose the simulation run length, the warmup-period duration (if any), and the required number of model replications (each using different random numbers). The talk concludes with a discussion of three critical pitfalls in simulation output-data analysis.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"1 1","pages":"1117-1127"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88072007","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/WSC48552.2020.9384093
J. L. Lay, V. Augusto, Xiaolan Xie, Edgar Alfonso-Lizarazo, B. Bongué, T. Celarier, R. Gonthier, Malek Masmoudi
Bed occupancy ratio reflects the state of the hospital at a given time. It is important for management to keep track of this figure to proactively avoid overcrowding and maintain a high level of quality of care. The objective of this work consists in proposing a decision-aid tool for hospital managers allowing to decide on the bed requirements for a given hospital or network of hospitals on a short-medium term horizon. To that extent we propose a new data-driven discrete-event simulation model based on data from a French university hospital to predict bed and staff requirements. We propose a case study to illustrate the tool’s ability to monitor bed occupancy in the recovery unit given the admission rate of ED patients during the pandemic of Sars-Cov-2. These results give an interesting insight on the situation, providing decision makers with a powerful tool to establish an enlightened response to this situation.
{"title":"Impact of COVID-19 Epidemics on Bed Requirements in a Healthcare Center Using Data-Driven Discrete-Event Simulation","authors":"J. L. Lay, V. Augusto, Xiaolan Xie, Edgar Alfonso-Lizarazo, B. Bongué, T. Celarier, R. Gonthier, Malek Masmoudi","doi":"10.1109/WSC48552.2020.9384093","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9384093","url":null,"abstract":"Bed occupancy ratio reflects the state of the hospital at a given time. It is important for management to keep track of this figure to proactively avoid overcrowding and maintain a high level of quality of care. The objective of this work consists in proposing a decision-aid tool for hospital managers allowing to decide on the bed requirements for a given hospital or network of hospitals on a short-medium term horizon. To that extent we propose a new data-driven discrete-event simulation model based on data from a French university hospital to predict bed and staff requirements. We propose a case study to illustrate the tool’s ability to monitor bed occupancy in the recovery unit given the admission rate of ED patients during the pandemic of Sars-Cov-2. These results give an interesting insight on the situation, providing decision makers with a powerful tool to establish an enlightened response to this situation.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"38 1","pages":"771-781"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79834432","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/WSC48552.2020.9384044
C. Bayliss, Marti Serra, Mariem Gandouz, A. Juan, Armando Nieto
The management of assets and liabilities is of critical importance for insurance companies and banks. Complex decisions need to be made regarding how to assign assets to liabilities in such a way that the overall benefit is maximised over a time horizon. In addition, the risk of not being able to cover the liabilities at any given time must be kept under a certain threshold level. This optimisation challenge is known in the literature as the asset and liability management (ALM) problem. In this work, we propose a biased-randomized (BR) algorithm to solve a deterministic version of the ALM problem. Firstly, we outline a greedy heuristic. Secondly, we transform it into a BR algorithm by employing skewed probability distributions. The BR algorithm is then extended into a simheuristic by incorporating Monte-Carlo simulation to deal with the stochastic version of the problem.
{"title":"A Simheuristic Algorithm for Reliable Asset and Liability Management Under Uncertainty Scenarios","authors":"C. Bayliss, Marti Serra, Mariem Gandouz, A. Juan, Armando Nieto","doi":"10.1109/WSC48552.2020.9384044","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9384044","url":null,"abstract":"The management of assets and liabilities is of critical importance for insurance companies and banks. Complex decisions need to be made regarding how to assign assets to liabilities in such a way that the overall benefit is maximised over a time horizon. In addition, the risk of not being able to cover the liabilities at any given time must be kept under a certain threshold level. This optimisation challenge is known in the literature as the asset and liability management (ALM) problem. In this work, we propose a biased-randomized (BR) algorithm to solve a deterministic version of the ALM problem. Firstly, we outline a greedy heuristic. Secondly, we transform it into a BR algorithm by employing skewed probability distributions. The BR algorithm is then extended into a simheuristic by incorporating Monte-Carlo simulation to deal with the stochastic version of the problem.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"123 1","pages":"2093-2104"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85673879","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/WSC48552.2020.9383998
Justin Jose, Divye Singh, Amit Patel, Harshal G. Hayatnagarkar
For planetary explorations, the space agencies have usually sent single robotic rovers to complete missions. An alternative approach is to send multiple rovers, which can insure against failure of one or more rovers. Planning for a multi-rover mission has its own challenges, and simulations can aid in identifying and addressing such challenges. In this paper, we present an ontology-based approach to simulate a multi-rover planetary exploration mission, with a focus on resilience, adaptation, heterogeneity, and reconfigurability. We present an ontology that describes multiple rovers along with an inventory of their parts shipped with a lander. Our approach shows that having the ontology-based simulations help in complex scenarios such as to loan parts from inventory, and salvaging a damaged rover for good parts.
{"title":"Simulating Re-configurable Multi-Rovers for Planetary Exploration Using Behavior-Based Ontology","authors":"Justin Jose, Divye Singh, Amit Patel, Harshal G. Hayatnagarkar","doi":"10.1109/WSC48552.2020.9383998","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9383998","url":null,"abstract":"For planetary explorations, the space agencies have usually sent single robotic rovers to complete missions. An alternative approach is to send multiple rovers, which can insure against failure of one or more rovers. Planning for a multi-rover mission has its own challenges, and simulations can aid in identifying and addressing such challenges. In this paper, we present an ontology-based approach to simulate a multi-rover planetary exploration mission, with a focus on resilience, adaptation, heterogeneity, and reconfigurability. We present an ontology that describes multiple rovers along with an inventory of their parts shipped with a lander. Our approach shows that having the ontology-based simulations help in complex scenarios such as to loan parts from inventory, and salvaging a damaged rover for good parts.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"33 1","pages":"254-265"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87921623","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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