> *Dissertation Defense Announcement
> To: The George Mason University Community*
>
> *Candidate: David L. Bolduc
> Program: PhD Biodefense
> *
> *Date: Tuesday April 26, 2011
> Time: 1:30 p.m.
> Place: George Mason University
> ** Research I Bldg., Room 161
> Fairfax campus <http://www.gmu.edu/resources/visitors/findex.html>
>
> Dissertation Chair: Dr. Robert L. Dudley
> Committee members: Dr. Charles L. Bailey, Dr. Joseph A. Marr*
> *Title: "Development of an Algorithm for Predicting /'Relative Risk'/
> of Terrorist-CBRN"
> *
> The dissertation is on reserve in the Johnson Center Library, Fairfax campus.
> The doctoral project will not be read at the meeting, but should be read in advance.
> /**/All members of the George Mason University community are invited to attend.
>
>
> *ABSTRACT:
> *In the past decade there has been a tremendous rise in the number of extremist groups with radical goals. To achieve their objectives, some of these groups
> are resorting to terrorist tactics. With the rapid expansion of scientific technology brought on through increasing globalization, the prospect of incorporating the
> use of chemical, biological, radiological and nuclear (CBRN) weapons into their tactics is becoming increasingly feasible and likely. As these radical groups
> become more energized, they may resort to using CBRN. In order to avert a disaster from a terrorist-CBRN (T-CBRN) event, it is important to study
> the likelihood of these groups employing CBRN. Analysts continue to search for sound methodologies in assessing the risk of such groups pursuing CBRN.
> Psychological and mathematical modeling attempts have been made in discerning terrorist's propensities for CBRN Asal (2010), Sullivan and Perry (2004),
> Post (2002), Tucker (2000) etc., but there still remains considerable gaps in these areas.
>
>
>
>
> Because of the deficiencies in analytical methodologies and
> controversial techniques used for modeling T-CBRN, we proposed the
> questions: can a more accurate predictive model of T-CBRN use be
> developed? And, when compared against past event data, would such a
> model reliably predict the amount of "/Relative Risk/" of a terrorist
> that would elect to use CBRN?
>
>
>
> This study entailed the development of an algorithm linked with
> statistical software (ProStat Version 5.5, Poly Software
> International) for predicting the Relative Risk of a terrorist seeking
> CBRN. This was achieved through four phases. Phase I involved
> searching open literature and proposing independent-variables
> associated with T-CBRN. Phase II entailed the construction of a
> "/Random-Nations Matrix/" representing the T-CBRN universe. This
> matrix was then used for correlating variables suspected of being
> associated with T-CBRN. Phase III involved the construction of a
> multivariate model from the variables which met our correlation
> criteria with T-CBRN. The final phase, Phase IV, entailed the
> construction of an algorithm derived from the model design, for
> predicting the amount of Relative Risk of a terrorist seeking,
> acquiring and or using CBRN, and the Relative Risk of T-CBRN occurring
> in a specific country. Probability was measured by the strength of
> the relationship indicated by the p-value.
>
>
>
> The study drew primarily from the following databases: the Memorial
> Institute for the Prevention of Terrorism (2007), the U.S. Department
> of State (2010), Globalsecurity.org (2010), the Global Terrorism
> Database (2010), the Central Intelligence Agency World Fact Book
> (2009-2010), the James Martin Center for Nonproliferation
> Studies/Monterey WMD Terrorism Database (2010), the Center for Defense
> Information (2009), the Freedom House Center for Systemic Peace (2009)
> and the McDonald's Corporation's list of worldwide McDonald's
> restaurants (2010).
>
>
>
> A Random Nations Matrix was developed for determining the two
> independent-variables that correlated with our dependent-variable
> "/Terrorist-CBRN/". This matrix was constructed from the random
> selection of 74 countries and/or locations from the CIA World Fact
> Book (2009-2010). Thirty-nine of the same variables were measured for
> each of the seventy-four selected countries or locations compiled in
> the matrix. The 39 variables selected for each country or location,
> were correlated with each other and the T-CBRN variable for
> determining correlative significance. A multivariate-model was
> developed with 67.3 percent predictive power for T-CBRN using the
> independent-variables: "/Political Violence Per Capita/" and "/Number
> of Terrorist-CBRN Technical Experts/". Average lag-times between
> terrorist's interest and use of CBRN were also calculated for the
> various classifications of terrorist-groups.
>
>
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