Papers and Articles

View a selection of the latest white papers, articles, and presentations from our technology experts, scientists, and subject matter experts. You must register to download a white paper.

Thinking Forward: An Internet of Things Primer for Emergency Managers

Authored by: Andrew Coffey, Ph.D, IEM Senior Analyst
Date: 10-2015

The Internet of Things (IoT) has progressively become a nexus of communication and information sharing, producing new opportunities for emergency management practitioners. However, in leveraging the IoT, practitioners must consider the implications of privacy protection versus national security. In this article, Dr. Andrew Coffey provides key examples of how the IoT could transform the practice of emergency management in the United States.

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Evaluating Intelligence and Information Sharing Networks: Examples from a Study of the National Network of Fusion Centers
Authored by: Andrew Coffey, Ph.D, IEM Senior Analyst
Date: 10-2015

This paper summarizes the findings of Dr. Andrew Coffey’s multi-year academic research examining several key factors contributing to observed results at the organizational (fusion center) level. The findings point to the critical importance of examining fusion centers for what they are—key nodes within a complex network whose primary strength is found in the relationships they build and maintain with key partners. The findings also open possible pathways for measuring the true value added by individual fusion centers and the national network moving forward.

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Disruptive by Design: IoT Ready to Redefine Local Intel
Authored by: Andrew Coffey, Ph.D, IEM Senior Analyst
Date: 10-2015

In this article, Dr. Andrew Coffey examines the impacts that the Internet of Things (IoT) could have on domestic intelligence in the United States, as well as the paradox it presents in terms of potential and vulnerability. He discusses the possibility of changing roles and expectations of local agencies, the need for collaboration and coordination between the private sector and the intelligence community, and the consequences of overdependence on IoT data.

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Fusion Centers as Buffers: Re-Examining the Role of State and Local Organizations in Securing the Homeland and Safeguarding Civil Liberties
Authored by: Andrew Coffey, Ph.D, IEM Senior Analyst
Date: 09-2015

In a review of Constructing the Suspicious: Data Production, Circulation, and Interpretation by DHS Fusion Centers, Dr. Coffey discusses the role of fusion centers and the importance of the Nationwide SAR Initiative. He explains the significance of liaison officers to the overall success of intelligence and information sharing networks, and proposes a re-examination of intelligence gathering and data analysis that seeks to balance trust, privacy, and security at the state and local levels.

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Every Disaster Has Public Health Consequences: Plan for Them
Authored by: Gary W. Scronce, Director of Preparedness Programs, IEM Director of Preparedness Programs
Date: 04-2015

Every disaster has public health consequences. Having that in the front of our minds as emergency managers can help us be more effective in our jobs and achieve better outcomes for the public.

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Comments on An Improvement to the Brent’s Method
Authored by: Steven A. Stage, Ph.D., IEM Atmospheric Physicist/Dispersion Modeler
Date: 02-2013

Say that for any given input value, x, we know how to compute an output value, y. There are many situations in which we know the output value, y, and would like to be able to determine the value of x that produced it. Sometimes this can easily be done using algebra or other math, but other times it is not possible to get an exact mathematical answer. Fortunately, several methods are available that enable computers to find good approximate answers. Dr. Stage’s paper, published in the International Journal of Experimental Algorithms (IJEA), examines several of these methods, including a method recently proposed in IJEA by Zhang, to see how quickly each method is able to find a good answer and provides guidance to help programmers select the method best suited to their specific needs.

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Maximizing Behavior Analysis with Massive Multi-Sensor Networks  
Authored by: Serge Olszanskyj, Ph.D., IEM Computational Scientist
Date: 06-2012

The demand for mission-critical, real-time information is exploding in the Intelligence Community. With sensors becoming increasingly sophisticated, inexpensive, and interconnected, the response to this demand is coming in the form of massive multi-sensor networks. While such systems tantalize us with the ever-increasing potential for analytical omniscience, the reality is that analysts and decision-makers are overwhelmed by the large data sets being generated. This paper, published in the April 2012 issue of IQT Quarterly, presents a path toward effectively transforming the exponential growth in data streams into an asset for analysts through automated suggestions of future outcomes and behavioral intent.

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Mass Prophylaxis Dispensing Concerns: Traffic and Public Access to PODs
Presented by: Dr. Sid Baccam, IEM Computational Epidemiologist
Date: 06-17-11

Policymakers have become increasingly concerned about the possibility of a terrorist attack using a biological agent on a civilian population.  In response to this threat, a federally funded effort has been developed to prepare major U.S. cities and metropolitan areas to respond quickly and effectively to a large-scale bioterrorism event.

Points of Dispensing, or PODs, are used by emergency responders to dispense post-exposure prophylaxis (PEP) to the public following a bioterrorism event. Any failure in PEP dispensing could have serious public health consequences, which is why IEM has focused study efforts on issues related to POD access.

The project described in the paper was partially funded by the U.S. Department of Health and Human Services (HHS) as part of a larger study on PEP dispensing logistics and medical consequences.

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The Mixing Layer Terrain Wind Adjustment Model (MILTWAM) for Airflow over Complex Terrain
Presented by: Steven A. Stage, Innovative Emergency Management, Inc., Baton Rouge, LA; and Z. Wu, N. Mainkar, J. Weltman, and M. Myirski

This paper presents the Mixing Layer Terrain Wind Adjustment Model (MILTWAM) for airflow over complex terrain. MILTWAM is a diagnostic, mass-consistent, wind-field model based on NUATMOS (Ross, 1988). It is specifically designed for use in the D2-Puff dispersion model developed by Innovative Emergency Management Inc. and it produces realistic estimates of winds, even when only a few wind observations are available. This model is also fast enough for use in an emergency response dispersion model that runs on a personal computer (PC). Key features of the MILTWAM model are:

  1. The height of the top of the mixing layer is explicitly included in the model and imposes a non-porous upper lid on the flow. This upper lid is a major influence in determining the flow over the terrain.
  2. A three-dimensional model with terrain-following coordinates is used when the top of the mixing layer is above the highest terrain; a vertically-averaged two-dimensional model is used when the mixing layer is below the highest terrain.
  3. The winds output by the model are designed to agree with the observed winds at the observation points.

Model results are shown for simple geometric terrain and for real terrain.
Quantitative Assessment of Emergency Preparedness and Response Using QEM-World™

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