In an article published in Quaternary Geochronology (Trauth, 2014), I introduced a new method for modeling complex stratigraphic sequences. I would like to explain at this point what the result of the modeling is, and what it is not.
So it all started. I was an invited speaker at the MATLAB Expo 2016 in Munich with a lecture on “Dust storms, blackouts and 50°C in the shade: with MATLAB in the cradle of humankind“. One of Keynote Lectures was held by Dr. Rainer Stetter of ITQ, “Industry 4.0 – Risks and Opportunities“, who talked, among other things, about the European Hi5 Hackethon 2016 with MATLAB and LEGO MINDSTORMS. I wondered how I could use the connection of MATLAB and LEGO MINDSTORMS, using the hardware support of The MathWorks in my shortcourses on geoscientific data analysis and future editions of the textbooks.
In MATLAB R2016b, the function to calculate a continuous 1D wavelet transform has been replaced by a new function, unfortunately with the same name. Here is a great example why I think that this blog is very useful: Here I can let you know how I would modify the script of Chapter 5.8 of MRES and ask for your comments on it, long before the 5th edition of MRES will be published.
For those of you who do not already know the two Springer books, here is a summary of the books, the available editions, the electronic supplement and errata files.
The website, which went online on Friday, obviously has a lot of Chinese readers for whom this information may be interesting: there is the 3rd edition of MRES in Chinese translation! Parick Chen (陈青), Rights and Permissions Manager at the Springer Beijing Representative Office, helped us to get this published. The Chinese publisher is National Defense Industry Press, Chinese ISBN: 978-7-118-10090-7. Thanks, Parick, for your great help with this!
Some people asked me where the photo on the cover of the 4th edition of the MRES book was taken. Here is the story about it.
I am currently working on a MATLAB/LEGO® MINDSTORMS® course for undergraduate and graduate students, aiming to improve their skills to build efficient teams to solve typical problems in earth sciences in acquiring, processing and analyzing typical multispectral (visible, infrared, thermal), geophysical (seismic, magnetic) and geometric (2D, 3D) data.