By Leroy Andrew Huizenga (PhD Thesis)
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Extra info for The Akedah in Matthew (Dissertation Duke University)
Soc. Netw. (2009) 30. : Mapping the Global Muslim Population. Pew Research Center, Oct 2009 32 A. Gutfraind 31. : The International Terrorist Threat to the UK. MI5 website (Nov 2006). html 32. : Notes on CEPII’s distances measures. htm (May 2006), Centre d’Etudes Prospective et d’Informations Internationales 33. : International Terrorism: Attributes of Terrorist Events (ITERATE). http://www. xml (2009) 34. OECD: Immigrants and expatriates: Total population by nationality and country of birth. online (2006), Organisation for Economic Co-Operation and Development 35.
Raising this yield is equivalent to raising risks throughout the network. The results are in Fig. 6. The effect of A is non-linear with a threshold at around A D 35 beyond which attacks decline. Unfortunately, the threshold lies quite high, indeed nearer to the yield from attacking the US ( 54) than countries such as France ( 6:8), implying that it would be necessary to create a very large deterrence effect to reduce the number of plots. If this level of deterrence is somehow achieved, the reduction in attacks will not occur at once in all countries because cells in some countries have lower translocation costs than cells in other countries.
Mathematical Methods in Counterterrorism, pp. 205–214. J. Bourassa Abstract Attention is the critical resource for intelligence analysts, so tools that provide focus are useful. One way to determine focus is by computing significance. In the context of a known model, new data can be placed on a spectrum defined by: normal, anomalous, interesting, novel, or random; and significance is greatest towards the middle of this spectrum. However, significance also depends on the mental state of the analyst (and the organization).
The Akedah in Matthew (Dissertation Duke University) by Leroy Andrew Huizenga (PhD Thesis)