Blurring is a commonly used visual effect when digitally editing photos and videos. One of the most common blurs used in these fields is the Gaussian blur. You may have used this tool thousands of times without ever giving it greater thought. After all, it does a nice job and does indeed make things blurrier.
Liquid handling workstations are commonly used in drug development, and look like small CNC machines with droppers on the ends which can dispense liquid into any container in a grid array. They are also extraordinarily expensive, as is most specialty medical research equipment. This liquid handling workstation doesn’t create novel drugs, though, it creates art, and performs similar functions to its professional counterparts at a much lower cost in exchange for a lot of calibration and math.
The art is created by pumping a small amount of CMYK-colored liquids into a 24×16 grid, with each space in the grid able to hold a small amount of the colored liquid. The result looks similar to a Lite-Brite using liquids instead of small pieces of plastic. The creator [Zach Frew] created the robot essentially from scratch using an array of 3D printers, waterjets, and CNC machines. He was able to use less expensive parts, compared to medical-grade equipment, by using servo-controlled valves and peristaltic pumps, but makes up for their inaccuracies with some detailed math and calibration.
The results of the project are striking, especially when considering that a lot of hurdles needed to be cleared to get this kind of quality, including some physical limitations on the way that the liquids behave in the first place. It’s worth checking out not just for the art but for the amount of detail involved as well. And, for those still looking to scratch the 90s nostalgia itch, there are plenty of other projects using the Lite Brite as inspiration.
There are many ways to update an embedded system in the field. Images can fly through the air one a time, travel by sneaker or hitch a ride on other passing data. OK, maybe that’s a stretch, but there are certainly a plethora of ways to get those sweet update bytes into a target system. How are those bytes assembled, and what are the tools that do the assembly? This is the problem I needed to solve.
Recall, my system wasn’t a particularly novel one (see the block diagram below). Just a few computers asking each other for an update over some serial busses. I had chosen to bundle the payload firmware images into the binary for the intermediate microcontroller which was to carry out the update process. The additional constraint was that the blending of the three firmware images (one carrier and two payload) needed to happen long after compile time, on a different system with a separate toolchain. There were ultimately two options that fit the bill.
Performing over-the-air updates of devices in the field can be a tricky business. Reliability and recovery is of course key, but even getting the right bits to the right storage sectors can be a challenge. Recently I’ve been working on a project which called for the design of a new pathway to update some small microcontrollers which were decidedly inconvenient.
There are many pieces to a project like this; a bootloader to perform the actual updating, a robust communication protocol, recovery pathways, a file transfer mechanism, and more. What made these micros particularly inconvenient was that they weren’t network-connected themselves, but required a hop through another intermediate controller, which itself was also not connected to the network. Predictably, the otherwise simple “file transfer” step quickly ballooned out into a complex onion of tasks to complete before the rest of the project could continue. As they say, it’s micros all the way down.
Schlieren imaging is a technique for viewing the density of transparent fluids using a camera and some clever optical setups. Density of a fluid like air might change based on the composition of the air itself with various gasses, or it may vary as a result of a sound or pressure wave. It might sound like you would need a complicated and/or expensive setup in order to view such things, but with a few common things you can have your own Schlieren setup as [elad] demonstrates.
His setup relies on a cell phone, attached to a selfie stick, with a spherical mirror at the other end. The selfie stick makes adjusting the distance from the camera to the mirror easy, as a specific distance from the camera is required as a function of focal length. For cell phone cameras, it’s best to find this distance through experimentation using a small LED as the point source. Once it’s calibrated and working, a circular field of view is displayed on the phone which allows the viewer to see any change in density in front of the mirror.
The only downside of this build that [elad] notes is that the selfie stick isn’t stiff enough to prevent the image from shaking around a little bit, but all things considered this is an excellent project that shows a neat and useful trick in the photography/instrumentation world that could be useful for a lot of other projects. We’ve only seen Schlieren imaging once before and it used a slightly different method of viewing the changing densities.
If you have your ear even slightly to the ground of the software community, you’ll have heard of Docker. Having recently enjoyed a tremendous rise in popularity, it continues to attract users at a rapid pace, including many global firms whose infrastructure depends on it. Part of Docker’s rise to fame can be attributed to its users becoming instant fans with evangelical tendencies.
But what’s behind the popularity, and how does it work? Let’s go through a conceptual introduction and then explore Docker with a bit of hands-on playing around.
There was a time when a pair of rabbit ears accompanied every new TV. Those days are gone, but [Thomas Cholakov (N1SPY)] managed to find one of the old TV dipoles in his garage, complete with 300-ohm twinlead and spade connectors. He put it to work listening to a NOAA weather satellite on 137 MHz by configuring it in a horizontal V-dipole arrangement. The antenna legs are spread about 120° apart and adjusted to about 20.5 inches (52 cm) length each. The length makes the antenna resonant at the right frequency, the vee shape makes the radiation pattern nearly circular, and the horizontal polarization excludes signals from the nearby FM broadcast band and directs the pattern skyward. [Thomas] doesn’t mention how he matched the antenna’s impedance to the SDR, but there appears to be some sort of balun in the video below. The satellite signal is decoded and displayed in real time with surprisingly good results.
Itching to listen to satellites but don’t have any rabbit ears? No problem — just go find a cooking pot and get to it.