Ken Chiacchia's talk, "ESW in the Alleghenies," includes our most recent AMDR work, and much more. For example, he describes how to measure sweep width for a dog team. The key idea is treating the dog-handler team as the sensor.
Detection by a Dog-Handler Team (Chiacchia)
Ken also compared time to reach a coverage of 2 (or 86% POD) of a dog team and a human team, in some conditions:
Time-to-Coverage for a dog-handler team vs a two-human team. (Chiacchia)
Use the dogs where they give the biggest gain: here, full foliage, low-vis. There is no useful gain in the high-vis leafless condition.
Also make sure to see his work on the effect of convection on sweep width (for some conditions). Ken is doing the best work I know of on sweep width for dogs. I look forward to the paper.
Charles Twardy started the SARBayes project at Monash University in 2000. Work at Monash included SORAL, the Australian Lost Person Behavior Study, AGM-SAR, and Probability Mapper. At George Mason University, he added the MapScore project and related work. More generally, he works on evidence and inference with a special interest in causal models, Bayesian networks, and Bayesian search theory,
especially the analysis and prediction of lost person behavior.
From 2011-2015, Charles led the DAGGRE & SciCast combinatorial prediction market projects at George Mason University, and has recently joined NTVI Federal as a data scientist supporting the Defense Suicide Prevention Office.
Charles received a Dual Ph.D. in History & Philosophy of Science and Cognitive Science from Indiana University, followed by a postdoc in machine learning at Monash.
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