Mixed-Mode Simulation-based Executable Architectures (MiMoSEA)

The MiMoSEA technology provides a methodology for generating and executing mixed-mode simulations for quantitative assessments of architectural frameworks.  It supports the entire analytic process from consistency checking of multiple system architectures to generating the requisite simulation and emulation models.

Today’s approaches to national defense are becoming more and more “capabilities”-centric.  This focus necessitates the ability to rapidly realize systems that are formed as collections of interoperating systems:  i.e., system-of-systems (SOS).  Each component system of an SOS is a complex hybrid of elements that include information, computation, mechanical, and human elements.  While information and computation elements of these systems-of-systems are the key functionality providers, the mechanical and human components ultimately deliver the punch.  As a consequence, the system architectures themselves should enable capabilities assessment:  these architectures should be directly usable for the quantitative assessment of interoperability or performance.

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Data Display Markup Language (DDML)

KBSI is developing an advanced component-based Data Display Markup Language (DDML), an XML-based neutral format also developed by KBSI, as the inter-lingua in translating the data display languages supported by different vendors.

Data display is a critical component for T&E environments in aircraft, space, and energy systems.  Because telemetry functions associated with these systems produce too much data for a single person to comprehend, data display–customizable display objects, including strip charts, bar charts, vertical meters, round gauges, cross plots, tabular displays, orientation displays, and bit maps–is critical in presenting this information in an understandable format.

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Biosurveillance-based Integrated Outbreak Warning And Recognition System (BIOWARS)

The BIOWARS technology is an adaptive system for discovering disease outbreaks and impending bio terrorism attacks.  BIOWARS uses syndromic surveillance to find symptomatic data patterns and applies Bayesian networks in collecting and archiving these patterns.

An important challenge faced by intelligence analysts and the intelligence community in our post 9/11 world is to gather, piece together, and correctly interpret vast amounts of intelligence data–data that may signal an impending attack or that may help limit the severity of an attack.  As a Defense Science Board study of transnational threats noted, the “making of connections between otherwise meaningless bits of information is at the core of (transnational) threat analysis.”

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Toolkit for Intelligent Combat Planning & Simulation (TINCOPS)

TINCOPS is a knowledge-based decision support system that manages and deploys knowledge for the U.S. military’s complex combat decision support applications and for analyzing and evaluating logistics plans.

The result of mission planning is a strategy for accomplishing the intended objectives that reflects decisions on the best methods and course of actions to follow.  The mission planning process is knowledge intensive and involves a number of factors that must be considered including uncertainties in the intelligence collected, enemy response, changes in logistics needs or routes, etc.  In addition, once the mission is active, changes in the battlespace can occur rapidly and commanders must receive accurate and current combat situational information in order to craft the most effective response and change to the original strategy.

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Pathfinder is a comprehensive suite of technologies for life-cycle cost justification, cost/benefit analysis, integrated performance prediction, quantified trade-off analysis, and management decision-making for individual project selection, monitoring, and control.

Pathfinder, a KBSI-led effort in partnership with Texas A&M University (TAMU), focused on the design and development of a comprehensive suite of technologies for life-cycle cost justification, cost/benefit analysis, integrated performance prediction, quantified trade-off analysis, and management decision-making for individual project selection, monitoring, and control.  The goals of Pathfinder addressed the need for life-cycle costing in depot environments, where the operational benefits of acquiring and maintaining weapons systems must be continually balanced.

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Environment, Epidemiology, & Etiology Surveillance & Analysis Toolkit (E3SAT)

The E3SAT tool suite allows researchers to collect, integrate, and data mine medical records, environmental exposures, and deployment locations.  This provides an encompassing data view of soldier health in the military healthcare system and enables studies of environmental, epidemiological, and etiological factors driving the system.

In the aftermath of Desert Shield and Desert Storm, researchers have struggled with explaining the array of serious health impairing symptoms that have become collectively known as Gulf War Syndrome.  Approximately 30 percent of the 700,000 U.S. servicemen and servicewomen in the first Persian Gulf War have registered in the Gulf War Illness database complaining of these symptoms.  A key stumbling block in researching Gulf War Syndrome is the absence of a means for integrating relevant data—soldier medical records, environmental health and surveillance data, deployment data—and discovering and analyzing to discover patterns and correlations between deployment exposures and soldier signs, symptoms, and potential causes.

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Adaptive Toolkit for Pattern Discovery (ATPD)

The ATPD technology is combining new machine learning techniques with advanced rule based methods for automated data utilization pattern discovery.  The technology allows users to monitor information use, discover use patterns, and develop ontology models of these relations and patterns.

This capability enables users to monitor information use across systems, discover usage patterns, analyze patterns for potential new (and useful) concepts and relations, and offer intelligent assistance to enterprise knowledge modelers about the integration of newly learned concepts into evolving reference knowledge models.

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Message Epidemiology Resource for Counter insURgencY (MERCURY)

MERCURY is computer modeling technology that helps U.S. and coalition forces improve their counter insurgency measures.  The technology provides computer modeling of counter insurgency message dissemination that considers the heterogeneity of population response and contact rate.

Predictive models have been used to help the U.S. and Coalition partners achieve force superiority in Iraq and Afghanistan.  While these statistical and physically quantifiable measures have been successful in delivering optimized kinetic and electronic results in conventional warfare theaters, insurgent-based conflicts were proving more difficult as environments in which to repeat this success, particularly in influence and information operations campaigns.

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Framework for Interoperability of Executable Architectures (FIEA)

FIEA is a language, tool framework, and methodology that enables the Air Force and DoD to share data among the many vendor specific tools and applications used in global joint service and multinational operations.

These tools, at best, provide a means for government agencies and their contractors to document their enterprise architectures:  they don’t facilitate the model-based analysis of architectures, a critical step in improving systems capability, acquisition, and investment returns.

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Framework for Adaptive Modeling & Ontology-Driven Simulation (FAMOS OSAI Method™)

The FAMOS OSAI Method™ technology is a system for developing and executing distributed military simulation applications.  The technology reduces the time and effort needed to develop and deploy distributed simulation applications and helps establish knowledge sharing and semantic integration among modeling and simulation applications.

In this initiative, KBSI collaborated with the Air Force to build a system for the development and execution of distributed military simulation applications.  The Framework for Adaptive Modeling and Ontology-driven Simulation (FAMOS OSAI Method™) reduces the time and effort required for developing and deploying distributed simulation applications and lays the groundwork for knowledge sharing, communication, and semantic integration among modeling and simulation applications.

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