Pub Date : 2020-12-14DOI: 10.1109/WSC48552.2020.9384099
Bastian C. Schumacher, H. Kohl
In this paper, ways are shown how students can be familiarized with executing simulation studies for the design and improvement of new and existing material flow systems using flexible discrete-event simulation (DES) tools. The prototypical app "Production Simulation Application" is described. It combines learning-conducive components that are used to familiarize users with objects, the graphical model buildup, and the use of programming language. Game elements such as levels, badges, and points are shaped to motivate learners to interact frequently. They enable immediate feedback. A test shows that the app has been used repeatedly at short intervals beyond the course. A procedure for experience-based learning for conducting simulation studies is developed, in which a so-called learning factory enables learners to complete a simulation study. It is shown that the developments can contribute to the dissemination of DES and to increasing the planning quality in times of rising complexity of production systems.
{"title":"Learning Environment for Introduction in Discrete-Event Simulation for Design and Improvement of New and Existing Material Flow Systems","authors":"Bastian C. Schumacher, H. Kohl","doi":"10.1109/WSC48552.2020.9384099","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9384099","url":null,"abstract":"In this paper, ways are shown how students can be familiarized with executing simulation studies for the design and improvement of new and existing material flow systems using flexible discrete-event simulation (DES) tools. The prototypical app \"Production Simulation Application\" is described. It combines learning-conducive components that are used to familiarize users with objects, the graphical model buildup, and the use of programming language. Game elements such as levels, badges, and points are shaped to motivate learners to interact frequently. They enable immediate feedback. A test shows that the app has been used repeatedly at short intervals beyond the course. A procedure for experience-based learning for conducting simulation studies is developed, in which a so-called learning factory enables learners to complete a simulation study. It is shown that the developments can contribute to the dissemination of DES and to increasing the planning quality in times of rising complexity of production systems.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"263 6-10","pages":"3224-3235"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91509037","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/WSC48552.2020.9383998
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}
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/WSC48552.2020.9384007
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/WSC48552.2020.9384044
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/WSC48552.2020.9384093
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/WSC48552.2020.9384062
Anne Schwientek, Ann-Kathrin Lange, C. Jahn
Given the growth in ship size and increasing demands, it is essential for seaport container terminals to make well-founded tactical and operational decisions. Here, horizontal transport is an important element of container terminals, connecting seaside handling with container storage. An efficient design of horizontal transport, especially the assignment of vehicles to orders, strongly influences the terminal performance. Most existing scientific studies vary only individual parameters or dispatching strategies neglecting different terminal targets. This study approaches this research gap. In a discrete-event simulation model, the influence of various terminal parameters on dispatching strategies is examined, taking into account the terminal targets. The two most influencing terminal parameters, terminal size and yard block assignment to containers, are analyzed in detail. The results show that the best choice of yard block assignment and dispatching method for a given terminal size depends on the combination of both parameters and the aspired targets.
{"title":"Effects of Terminal Size, Yard Block Assignment, and Dispatching Methods on Container Terminal Performance","authors":"Anne Schwientek, Ann-Kathrin Lange, C. Jahn","doi":"10.1109/WSC48552.2020.9384062","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9384062","url":null,"abstract":"Given the growth in ship size and increasing demands, it is essential for seaport container terminals to make well-founded tactical and operational decisions. Here, horizontal transport is an important element of container terminals, connecting seaside handling with container storage. An efficient design of horizontal transport, especially the assignment of vehicles to orders, strongly influences the terminal performance. Most existing scientific studies vary only individual parameters or dispatching strategies neglecting different terminal targets. This study approaches this research gap. In a discrete-event simulation model, the influence of various terminal parameters on dispatching strategies is examined, taking into account the terminal targets. The two most influencing terminal parameters, terminal size and yard block assignment to containers, are analyzed in detail. The results show that the best choice of yard block assignment and dispatching method for a given terminal size depends on the combination of both parameters and the aspired targets.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"177 1","pages":"1408-1419"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79880053","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/WSC48552.2020.9383948
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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：