AN AGENT-BASED MODELING FRAMEWORK TO STUDY THE BURDEN OF PERTUSSIS AND THE IMPACT OF PREVENTATIVE MEASURES

BIOMAT 2014 ◽  
2015 ◽  
Author(s):  
J.-E. POIRRIER ◽  
D. CURRAN ◽  
C. PHILEMOTTE
Author(s):  
Brian Thompson ◽  
James Morris-King

Mobile tactical networks facilitate communication, coordination, and information dissemination between soldiers in the field. Their increasing use provides important benefits, yet also makes them a prime enemy target. Furthermore, their dynamic, distributed, and ad-hoc nature makes them particularly vulnerable to cyber attack. Unfortunately, most existing research on cybersecurity in mobile ad-hoc networks either uses simplistic mobility models that are easier to analyze mathematically or focuses on modeling the dynamics of civilian networks. In this work, we present an agent-based modeling framework to study malware spread in mobile tactical networks. Our framework includes military-inspired models of hierarchical command structure, unit movement, communication over short-range radio, self-propagating malware, and cyber defense mechanisms. We implement several example scenarios representing military units engaged in tactical operations on a synthetic battlefield. Finally, we conduct a case study, using agent-based simulation to analyze the impact of hierarchy and cybersecurity policies on malware spread. Our results support the claim that agent-based modeling is particularly well-suited for representing the complex organizational and spatial structures inherent to military operations, and we urge others to incorporate the key elements of our framework into existing modeling tools when performing studies of cyber attacks on mobile tactical networks and corresponding cybersecurity measures.


Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3860
Author(s):  
Priyanka Shinde ◽  
Ioannis Boukas ◽  
David Radu ◽  
Miguel Manuel de Manuel de Villena ◽  
Mikael Amelin

In recent years, the vast penetration of renewable energy sources has introduced a large degree of uncertainty into the power system, thus leading to increased trading activity in the continuous intra-day electricity market. In this paper, we propose an agent-based modeling framework to analyze the behavior and the interactions between renewable energy sources, consumers and thermal power plants in the European Continuous Intra-day (CID) market. Additionally, we propose a novel adaptive trading strategy that can be used by the agents that participate in CID market. The agents learn how to adapt their behavior according to the arrival of new information and how to react to changing market conditions by updating their willingness to trade. A comparative analysis was performed to study the behavior of agents when they adopt the proposed strategy as opposed to other benchmark strategies. The effects of unexpected outages and information asymmetry on the market evolution and the market liquidity were also investigated.


MethodsX ◽  
2020 ◽  
Vol 7 ◽  
pp. 100953
Author(s):  
Aniruddha Belsare ◽  
Matthew Gompper ◽  
Barbara Keller ◽  
Jason Sumners ◽  
Lonnie Hansen ◽  
...  

2021 ◽  
Vol 12 (2) ◽  
pp. 73
Author(s):  
Dita Novizayanti ◽  
Eko Agus Prasetio ◽  
Manahan Siallagan ◽  
Sigit Puji Santosa

Currently, the adoption of electric vehicles (EV) draws much attention, as the environmental issue of reducing carbon emission is increasing worldwide. However, different countries face different challenges during this transition, particularly developing countries. This research aims to create a framework for the transition to EV in Indonesia through Agent-Based Modeling (ABM). The framework is used as the conceptual design for ABM to investigate the effect of agents’ decision-making processes at the microlevel into the number of adopted EV at the macrolevel. The cluster analysis is equipped to determine the agents’ characteristics based on the categories of the innovation adopters. There are 11 significant variables and four respondents’ clusters: innovators, early majority, late majority, and the uncategorized one. Moreover, Twitter data analytics are utilized to investigate the information engagement coefficient based on the agents’ location. The agents’ characteristics which emerged from this analysis framework will be used as the fundamental for investigating the effect of agents’ specific characteristics and their interaction through ABM for further research. It is expected that this framework will enable the discovery of which incentive scheme or critical technical features effectively increase the uptake of EV according to the agents’ specific characteristics.


PLoS ONE ◽  
2018 ◽  
Vol 13 (11) ◽  
pp. e0207072 ◽  
Author(s):  
Charlie Lin ◽  
Joshua Culver ◽  
Bronson Weston ◽  
Evan Underhill ◽  
Jonathan Gorky ◽  
...  

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