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Proceedings Paper

Bayesian performance metrics and small system integration in recent homeland security and defense applications
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Paper Abstract

In this paper, Bayesian inference is applied to performance metrics definition of the important class of recent Homeland Security and defense systems called binary sensors, including both (internal) system performance and (external) CONOPS. The medical analogy is used to define the PPV (Positive Predictive Value), the basic Bayesian metrics parameter of the binary sensors. Also, Small System Integration (SSI) is discussed in the context of recent Homeland Security and defense applications, emphasizing a highly multi-technological approach, within the broad range of clusters ("nexus") of electronics, optics, X-ray physics, γ-ray physics, and other disciplines.

Paper Details

Date Published: 5 May 2010
PDF: 10 pages
Proc. SPIE 7666, Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense IX, 76660U (5 May 2010); doi: 10.1117/12.850539
Show Author Affiliations
Tomasz Jannson, Physical Optics Corp. (United States)
Andrew Kostrzewski, Physical Optics Corp. (United States)
Edward Patton, Physical Optics Corp. (United States)
Ranjit Pradhan, Physical Optics Corp. (United States)
Min-Yi Shih, Physical Optics Corp. (United States)
Kevin Walter, Physical Optics Corp. (United States)
Gajendra Savant, Physical Optics Corp. (United States)
Rick Shie, Physical Optics Corp. (United States)
Thomas Forrester, Physical Optics Corp. (United States)


Published in SPIE Proceedings Vol. 7666:
Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense IX
Edward M. Carapezza, Editor(s)

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