Author Archives: Charles R. Twardy

Charles R. Twardy

September 13, 2014

Thanks very much to summer intern Jonathan Lee (@jonathanlee1) for many MapScore fixes.  Jonathan is a keen Python programmer with extra geek points for running Linux on his Macbook Air and having an ASCII-art avatar.  He learned his way around Django in no time and brought us a slew of features and code refactoring including: Continue reading

Bluefin-21 Analysis

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.

Forecast trend for Bluefin-21 success, on SciCast.

Forecast trend for Bluefin-21 success, on SciCast.

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.)

Bayes net model created by jkominek to explore the Bluefin question.

Bayes net model created by jkominek to explore the Bluefin question.

 

The full blog post is here: http://blog.scicast.org/2014/06/11/scicast-bluefin-21-and-genie/

 

Incoherence & Mattson

The following figure is from a recent paper I co-authored*:

Figure from Karvetski et al. 2014 showing we get more accuracy by ignoring incoherent estimates than by simple unweighted averages.

Figure from Karvetski et al. 2014 showing we get more accuracy by ignoring incoherent estimates than by simple unweighted averages.  (The unfortunately abbreviated 'BS' means 'Brier Score'. Lower is better, with 0 being perfect.)

What implications does it have for making subjective "consensus" probability maps at the start of a search?

Continue reading

RIP Dennis Lindley

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.

Berkshires 2006 Sweep Width Experiment

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.

Continue reading

MapScore Updates

The MapScore site has been updated! The most exciting new feature is Batch Upload.

  • Batch Upload!  In one fell swoop, upload and re-score all your models and cases (or as many as necessary).  No more clicking around or messing with “active” vs “inactive” cases.  (Unless you want to...)
MapScore batch upload screen. New Nov. 2013.

MapScore batch upload screen. New Nov. 2013.

Continue reading

Search Theory in C4ISR Journal

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.)

Continue reading