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Models to Address Diplomatic, Information, Military, Economic (DIME) Factors for the Propagation/Evolution of Ideas Through Defined Populations

Award Information
Agency: Department of Defense
Branch: Army
Contract: W15P7T-07-C-K401
Agency Tracking Number: A062-094-2534
Amount: $119,353.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: A06-094
Solicitation Number: 2006.2
Solicitation Year: 2006
Award Year: 2006
Award Start Date (Proposal Award Date): 2006-12-22
Award End Date (Contract End Date): 2007-10-22
Small Business Information
11660 Alpharetta Highway, Suite 720
Roswell, GA 30076
United States
DUNS: 808996508
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Norman Geddes
 CEO and Distinguished Scientist
 (770) 518-4228
Business Contact
 Sharon Scott
Title: VP Business Services
Phone: (770) 518-4228
Research Institution

We propose to evaluate and recommend a set of candidate models of the flow and evolution of population beliefs and intentions as the starting point for developing a deployable DIME Effects Model (DEM) for tactical commanders. DIME (Diplomatic, Information, Military and Economic) seeks to avoid counter-productive and conflicting activities during tactical operations by considering these factors in a coordinated manner during mission planning and execution. A DIME Effects Model will enable better integration of DIME into Effects Based Operations. To develop a DIME Effects Model, we bring depth and breadth of modeling experience and knowledge of Army doctrine and operations. Our team will identify the candidate models from the existing work on dynamic models of populations and select models with the potential for predictive modeling of DIME effects on populations, including effects on the population beliefs and PMESII itself. This effort will also create a framework for comparing disparate population models and an inventory of validation methods that for the models. In Phase 1 Option, we will implement a segment of one candidate model and demonstrate the model execution using one of the validation methods we identified.

* Information listed above is at the time of submission. *

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