Wolfram Computation Meets Knowledge

Date Archive: 2017 April

Leading Edge

Using the Sense HAT on a Raspberry Pi with Mathematica 11

Ever since the partnership between the Raspberry Pi Foundation and Wolfram Research began, people have been excited to discover---and are often surprised by---the power and ease of using the Wolfram Language on a Raspberry Pi. The Wolfram Language's utility is expanded even more with the addition of the Sense HAT, a module that gives the Raspberry Pi access to an LED array and a collection of environmental and movement sensors. This gives users the ability to read in data from the physical world and display or manipulate it in the Wolfram Language with simple, one-line functions. With the release of Mathematica 11, I've been working hard to refine functions that connect to the Sense HAT, allowing Mathematica to communicate directly with the device.
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Launching the Wolfram Data Repository: Data Publishing that Really Works

After a Decade, It's Finally Here!

I'm pleased to announce that as of today, the Wolfram Data Repository is officially launched! It's been a long road. I actually initiated the project a decade ago---but it's only now, with all sorts of innovations in the Wolfram Language and its symbolic ways of representing data, as well as with the arrival of the Wolfram Cloud, that all the pieces are finally in place to make a true computable data repository that works the way I think it should.

Walking the Dog: Neural Nets, Image Identification and Geolocation

It's National Pet Day on April 11, the day we celebrate furry, feathered or otherwise nonhuman companions. To commemorate the date, we thought we'd use some new features in the Wolfram Language to map a dog walk using pictures taken with a smartphone along the way. After that, we'll use some neural net functions to identify the content in the photos. One of the great things about Wolfram Language 11.1 is pre-trained neural nets, including Inception V3 trained on ImageNet Competition data and Inception V1 trained on Places365 data, among others, making it super easy for a novice programmer to implement them. These two pre-trained neural nets make it easy to: 1) identify objects in images; and 2) tell a user what sort of landscape an image represents.

How to Use Your Smartphone for Vibration Analysis, Part 2: The Wolfram Cloud

Vibration measurement is an important tool for fault detection in rotating machinery. In a previous post, "How to Use Your Smartphone for Vibration Analysis, Part 1: The Wolfram Language," I described how you can perform a vibration analysis with a smartphone and Mathematica. Here, I will show how this technique can be improved upon using the Wolfram Cloud. One advantage with this is that I don't need to bring my laptop.