We’ve had great audience participation for our minisymposium at SIAM UQ 2012 so far!
There were 20-30 people in the audience throughout the entire mini-symposium.
Here’s a log of what’s going on!
5:30pm We had to cutoff questions for Barnabas’s talk! Please discuss here if you are interested.
5:35pm Qiqi Wang is now talking about unconventional information in simulations
5:37pm Qiqi on data and simulation: “This is the way we envision the future is going to be”
5:40pm Still Qiqi … “When you go to a chaotic dynamical system, [the adjoint method] breaks down.” “Let me tell you the solution we just worked out.”
5:42pm When you use time-averaging, you get a smaller magnitude of noise, but that makes the derivative of the noise larger (10^100)!. The difference between the finite time average and the infinite time average suffers from the butterfly effect, and this is a huge problem.
5:45pm Qiqi’s talk is too interesting, I need to pay attention now. The video will be online soon 🙂
5:55pm Qiqi is solving challenges on how to get information out of unsteady simulations.
6:00pm Chandrika Kamath is starting to talk about scientific data mining.
6:03pm Kamath – “80-90% of the time is spent in data processing” [in scientific data mining]
6:07pm Kamath – classifying Poincare orbits is a tough challenge due to multi-scale and fractal patterns in the data, not to mention noise
6:09pm Kamath – feature building for the Poincare orbits include using polar coordinates to exaggerate some features and using residuals in polynomial fits
6:13pm Kamath – using parallel plots help to identify useful regions in a object by feature matrix
6:15pm Kamath – using 5-6 features incredibly good performance
6:15pm Kamath – Rayleigh-Taylor instabilities, 30TB and 80TB of data. These are big problems!
6:17pm The problem – finding bubbles and spikes in tubulence data – isn’t even well defined. They used image analysis techniques.
6:22pm Darn, we lost the video (out of battery) for the end of Chandrika’s talk.