Wolfram Computation Meets Knowledge

Wolfram Community Highlights: Medicine, Drones, KenKen, and More!

With some impressive new features, new forums, and many new members, Wolfram Community has had a great year. As we approach the end of 2015, we wanted to share a few highlights from the last few months’ excellent posts on the Wolfram Community site.


Interested in drones? Check out these posts.

Connecting ROS to the Wolfram Language, Or Controlling a Parrot ArDrone 2.0 from Mathematica, by Loris Gliner, a student in aeronautical engineering.

Loris with drone

Loris Gliner used his time in the Wolfram mentorship program to work out how to connect the Wolfram Language to the Linux Robot Operating System. He includes code examples and a video showing the flight of a Parrot ArDrone 2.0 controlled via the Wolfram Language.

Analyzing Crop Yields by Drone, by Arnoud Buzing, Wolfram Research.

Using a Phantom 2 Vision+ drone from DJI, Arnoud Buzing got a bird’s-eye view of soy fields in order to apply the Wolfram Language’s photo-analyzing capabilities to estimate crop yields. As someone with a small farm, this post makes me want to get a drone and try this out.

In the comments, Diego Zviovich said he had played with a similar concept using Landsat data.

Environmental science

Ocean currents: from Fukushima and rubbish, to Malaysian airplane MH370
, by Marco Thiel, University of Aberdeen, Department of Physics/Mathematics.

Marco Thiel used the Wolfram Language and NASA’s ECCO2 data to simulate the flow of Fukushima’s radioactive particles drifting across the Pacific, carried by the currents. He also modeled the flow of garbage in the oceans that ends up trapped in gyres. The results are quite thought-provoking.

He challenges his readers to use these models to predict where parts of MH370 might be. If you try it, you could see how your version stacks up against this simulation published in The New York Times.


2D & 3D simulations of a glioma, by Laura Carrera Escalé.

Laura Carrera, a mathematics student who did an Erasmus internship at the mathematics department of the University of Aberdeen with Marco Thiel, follows up on Thiel’s post Simulating Brain Tumor Growth with Mathematica 10. She has created a simulation of a rapidly growing brain cancer that is both fascinating and creepy to watch.

Carrera remarks: “We can clearly see the difference between the two gliomas’ growth velocities displayed on the above videos over a period of just 200 days. Following steps on this topic might help to calculate the volume of the tumor and therefore to elaborate a time-volume graphic. Thus, the patient’s life expectancy on diagnosis could be predicted, given that death normally occurs when the volume of the glioma is higher than a sphere, radius 3 cm.”

What these two cancer simulation posts suggest to me is the possibility that in the near future, people diagnosed with tumors will be able to take the relatively cryptic radiologists’ reports and use the descriptions to create 3D simulations in order to better understand the course of their diseases. While the code behind these simulations is a bit out of the range of most patients, with the help of the Wolfram Language maybe soon the ability to create or access these models won’t be.


[GIF] Enneper surface + an introduction, by Clayton Shonkwiler, a mathematician at Colorado State University.

Animated visualization of an Enneper surface

Clayton Shonkwiler has used the Wolfram Language to create an animated visualization of an Enneper surface, a self-intersecting minimal surface generated by Enneper–Weierstrass parameterization. You can see more of his mathematical art on his website, shonkwiler.org/art.


Solving a KenKen puzzle using logic, by Sander Huisman, a postdoc in Lyon, France, researching Lagrangian turbulence.

Sander Huisman has come up with a way to solve KenKen puzzles with the Wolfram Language, a recurring discussion of interest. Frank Kampas’ post about KenKen was featured earlier this year. KenKen is a game similar to Sudoko, invented by Japanese math teacher Tetsuya Miyamoto; it is regularly featured in The New York Times and is widely syndicated.

Just this week, Bernat Espigulé Pons has followed up with a Secret Santa generator deployed in the Wolfram Cloud.

More games-related posts:

First forays into game design and agent reasoning about uncertainty, by Michael Hale.

Analysis of ‘Magic the Gathering’ card game, by David Gathercole.

Physics and engineering

Solving 2D Incompressible Flows using Finite Elements, by Ole Christian Astrup, Senior Principal Researcher at DNV GL.

Solving 2D Inconpressible Flows using Finite Elements image

New features in Version 10 of the Wolfram Language and Mathematica are spurring new investigations. Ole Christian Astrup describes the inspiration for his project: “I was inspired by the Wolfram blog by Mokhasi showing how to use Mathematica to solve a 2D stationary Navier–Stokes flow using a finite difference scheme to write this blog. I thought it should be possible to solve the 2D cavity box flow problem using Mathematica’s finite element capabilities. In the following, I show how the problem can be discretized and solved by the finite element method using an iterative scheme.”

More physics and engineering posts:

Basics of Supercapacitor Modeling, by Johan Rhodin, Wolfram Research.

GPS Mountainbike analysis, by Sander Huisman.

Making jokes

Finally, if you’re in the mood for a little light humor, you may appreciate this topic.

Joke Generator, by Jesse Friedman, current intern at Wolfram Research.

“Robert Heinlein famously said, ‘Never try to teach a pig to sing; it wastes your time and it annoys the pig.’ I had been thinking about how to teach computers expressive language, and one of the core skills of expressive language is making jokes. So making jokes was on my list of ‘How to teach the pig to sing.'”

I was delighted to see Jesse Friedman’s strategies for getting the Wolfram Language to tell jokes. Not all of these jokes are funny, but sometimes how they go wrong is as interesting as the jokes that work.

The post inspired me to see if I could take it further. I worked on methods to get nice groups of rhyming words out of which poems could later be made. Here I was testing out how to get the best rhymes by aggregating from both Wolfram|Alpha and the Wolfram Language data libraries. (For rhyming words, these are not identical.)

Rhyming words

When it works, this makes pleasing sets of three words. Like so:

Three word sets

(Not all words have rhymes available in these databases, so sometimes there are unpoetic error messages instead, which I have not yet suppressed.)

Thanks, Jesse, for the inspiration.

Visit Wolfram Community today to see what captures your attention, and join in on these and other interesting discussions. Better yet, make joining Community a New Year’s resolution. It’s a great place to share ideas, get feedback, and learn new things.


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