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Time Blocks
Sunday - Tuesday
A
— 8:00am - 9:30am
B
— 11:00am - 12:30pm
C
— 1:30pm - 3:00pm
D
— 4:30pm - 6:00pm
TA01
The day of
the week
Time Block.
Matches the time
blocks shown in the Program
Schedule.
Room number.
Room locations are
also indicated in the listing for each
session.
How to Navigate the
Technical Sessions
There are four primary resources to help you
understand and navigate the Technical Sessions:
• This Technical Session listing, which provides the
most detailed information. The listing is presented
chronologically by day/time, showing each session
and the papers/abstracts/authors within each
session.
• The Author and Session indices provide
cross-reference assistance (pages 510-553).
Quickest Way to Find Your Own Session
Use the Author Index (page 510) — the session code
for your presentation will be shown along with the room
location. You can also refer to the full session listing for
the room location of your session.
The Session Codes
37
Sunday, 8:00am - 9:30am
SA01
01-Room 301, Marriott
Modeling and Combating Terrorism
Sponsor: Military Applications
Sponsored Session
Chair: Gary Kramlich, Orsa Team Leader, US Army INSCOM,
5837 New England Woods Dr, Burke, VA, 22015,
United States of America,
gary.r.kramlich.mil@mail.mil1 - Combating Terrorism: How to Degrade a Terrorist Network by
Strengthening a US Support Network
Chané Jackson, Instructor, United States Military Academy,
Department of Mathematics, West Point, NY, 10996,
United States of America,
chane.jackson@usma.eduNedialko Dimitrov, Anthony Johnson
To combat terrorism abroad, the US Forces seek to degrade a terrorist support
network and strengthen a US support network. We describe a general framework
for the problem of influence maximization in a social network. Solutions identify
key individuals to serve as a focus for US efforts to expand support. Our
framework both captures previous work in the area and yields many novel
problem formulations. We demonstrate the framework’s applicability through
insights gained on several examples.
2 - Countering Improvised Explosive Devices with Adaptive
Sensor Networks
Jorge Buenfil, PhD Student, Stevens Institute of Technology,
1 Castle Point Rd, Hoboken, NJ, 07030, United States of America,
jbuenfil@stevens.edu,Jose Emmanuel Ramirez-marquez
A combination of statistical analysis, artificial intelligence and human-machine
interface with an adaptive system is presented as a way to infer the presence of
IEDs in a dynamic environment. Specific algorithms, pattern recognition, and
statistical data processing are applied to this problem to accurately indicate the
presence of explosives with low probability of false alarms, high probability of
detection, and the ability to automatically improve the sensor network’s accuracy
over time.
SA02
02-Room 302, Marriott
Interdiction and Fortfication Models: Applications
Cluster: Homeland Security
Invited Session
Chair: Taofeek Biobaku, University of Houston, Houston, TX,
United States of America,
tobiobaku@uh.edu1 - A Network Interdiction Approach to the Rural Postman Problem
Gokhan Karakose, University of Missouri, Lafferre Hall,
Columbia, MO, United States of America,
gkz7c@mail.missouri.edu,Ronald McGarvey
We consider a network where some required arcs need to traversed by a manager
who wishes to minimize his total distance traveled. Opposing this manager an
interdictor seeks to disrupt arcs in order to impede the manager‘s travel. Given
that the manager can invest limited resources to protect a subset of arcs from
disruption, what investment strategy minimizes the maximum distance that the
manager might need to travel?
2 - Allocating Resources to Enhance Resilience, with Application to
Superstorm Sandy
Cameron MacKenzie, Assistant Professor, Iowa State University,
3004 Black Engineering, Ames, IA, 50011, United States of
America,
camacken@iastate.edu, Chris Zobel
We construct a framework to allocate resources to increase an organization’s
resilience to a system disruption. We first look at characterizing the optimal
resource allocations associated with several standard allocation functions. Next,
we apply the resource allocation model for resilience to uncertain disruptions.
The optimization model is applied to an example of increasing the resilience of an
electric power network to Superstorm Sandy.
T
E C H N I C A L
S
E S S I O N S
Wednesday
A
— 8:00am - 9:30am
B
— 11:00am - 12:30pm
C
— 12:45pm - 2:15pm
D
— 2:45pm - 4:15pm
E
— 4:30pm - 6:00pm
Room Locations /Tracks
All tracks and technical sessions will be held in the
Convention Center and Marriott. Room numbers are
shown on the Track Schedule and in the technical
session listing.