Bayesian methods for WiSAR
One of our SciCast forecasters posted an excellent analysis of how he estimated the (remaining) chance of success for Bluefin-21 finding MH370 by the end of the question.
Jkominek was wondering why the probability kept jumping up, and created a Bayes Net to argue that there was no good estimation reason for it. (There may be good market reasons -- cashing in to use your points elsewhere.)
The full blog post is here: http://blog.scicast.org/2014/06/11/scicast-bluefin-21-and-genie/
People are often incoherent: their probabilities don't add to 100%. We get an 18% gain in accuracy if we coherentize their estimates. But we get a 30% gain in accuracy if we also assign more weight to coherent estimates.
What implications does this have for making subjective probability maps?
The following figure is from a recent paper I co-authored*:
What implications does it have for making subjective "consensus" probability maps at the start of a search?
In which I discuss two-and-a-half approaches to crowdsourcing Search & Rescue, and invite you to try one -- namely, mine: http://bit.ly/1eBBMkq
In which I discuss two-and-a-half approaches to crowdsourcing Search & Rescue, and invite you to try one -- namely, mine. (SciCast)
NBC29 WVIR Charlottesville, VA News, Sports and Weather
Short interview showcasing GIS for search and rescue. The reporter only identifies the system as "ArcGIS" but I believe it is Don Ferguson's IGT4SAR.
One of the giants in Bayesian statistics passed away at his home earlier this week, coincidentally at the start of the O'Bayes 250 conference marking the 250th anniversary of the publication of Bayes' paper. Writeup in X'ian's 'Og.
In the summer of 2006, Rick Toman and Dan O'Connor (NewSAR) organized a sweep width experiment and summit called "Detection in the Berkshires" at Mount Greylock in Massachusetts. The data from that experiment has been used in previous blog posts, but hasn't been published independently.
In the summer of 2006, Rick Toman (Massachusetts State Police) and Dan O'Connor (NewSAR) organized a sweep width experiment and summit called "Detection in the Berkshires" at Mount Greylock in Massachusetts. In addition to the sweep-width experiment, Perkins & Roberts provided search tactics training for several teams, and the summit provided a chance for us to explore similarities and differences between formal search theory and formalized search tactics. It was an important the chance to meet many key people, compare notes, and discuss ideas. I wish I had been more diligent about following up. Many thanks to Rick & Dan for organizing the event, and to many others listed at the end. However, this post is mostly to provide a reference for the sweep width experiment.
Article by Don Ferguson on the WiSAR and GIS blog. Nice overview of search planning done in GIS.
Stay tuned for some MapScore updates.
The C4ISR Journal had a recent search theory article quoting me along with Larry Stone.
The C4ISR Journal had a recent search theory article quoting me along with Larry Stone. I'm quite honored, like the British company in Dirk Gently's Holistic Detective Agency:
...was the only British software company that could be mentioned in the same sentence as ... Microsoft.... The sentence would probably run along the lines of ‘...unlike ... Microsoft...’ but it was a start.
It's a good article, covering the undeniably exciting historical origins hunting U-boats, and looking at what may be a modern renaissance. I think the article stretches to connect search theory with Big Data, but the author does note that when the data is visual, and you have humans scanning it for objects, there is a connection. With planning, it could have been used to prioritize the Amazon Mechanical Turk search for Jim Gray. (The resolution of the actual images in that search was probably too low regardless, but the core idea was sound.)
My colleagues just published a paper in Euro Journal on Decision Processes, for their special issue on risk management.
Karvetski, C.W, Olson, K.C., Gantz, D.T., Cross, G.A., "Structuring and analyzing competing hypotheses with Bayesian networks for intelligence analysis".
My colleagues just published a paper in Euro Journal on Decision Processes, for their special issue on risk management.
Karvetski, C.W, Olson, K.C., Gantz, D.T., Cross, G.A., "Structuring and analyzing competing hypotheses with Bayesian networks for intelligence analysis". EURO Journal on Decision Processes, Special Issue on Risk Management: http://link.springer.com/article/10.1007/s40070-013-0001-x
Alas, it's behind a paywall and the printed edition isn't due until Autumn. Here's an excerpt from the abstract:
Continue reading "Structured Methods for Intelligence Analysis"
Thanks to Mike Goodrich for this RCMP Drone story. In short, the RCMP spotted a stranded driver by using a drone-mounted infrared camera.
We hope the FAA soon settles on good regulations for such drone use in the US.