I learned halfway through January how easy it was to capsize the catamaran when I failed to shift my weight fast enough during a tacking maneuver in a 30 knot wind. So I’ve gotten back into 3d printing in a big way in anticipation of needing to print water-tight enclosures for the electronics in my sailboat anemometer project. After dusting off my Creality Ender 3 printer I was reminded of the challenges of open-air ABS printing, specifically, preventing uneven cooling that leads to warped ABS prints.
Last year I posted my New Years’s resolutions and discussed my hopes and ambitions for 2020. Needless to say, things didn’t exactly go as planned. I had three resolutions. The first was to do 3 sets of push ups every day. As the pandemic unfolded that evolved into “do 50 push-ups prior to each serving of alcohol that I consumed. Generally that meant 50-100 pushups a day, translating into roughly 20,000 pushups over the course of the year.
I realized that over the last few months I’ve been publishing some pretty technically dense material. So I figured I’d take a break to cover a much more light-hearted topic, politics! Back in 2016 I wrote about the Hillary-Trump election. It makes for quaint reading given the perspective of 2020. What’s funny is that in 2016 a lot of my conservative friends believed that Obama wasn’t going to give up the White House if Hillary lost.
This is the second part in the Information Theory in IoT series and will discuss converting natural data into independent and identically distributed (IID) values as well as Huffman encoding. The photograph is of of David A. Huffman, developer of Huffman Encoding. Before we get into Huffman encoding though we need to discuss making the data IID. In this article we’ll address the compression of a single metric, calories per minute.
This is the first part in a two part series and will focus on the broad concepts of information theory. Part two will discuss converting natural data into independent identically distributed values as well as Huffman encoding. Pictured is Claude Shannon, the founder of Information Theory. I’ve recently been reading Information Theory: A Tutorial Introduction by James Stone, partly out of curiosity, partly out of the hope that what I learn may be in some way applicable to my current work.
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