Dotterboard smt counter

Tame The Tape: Open-Source Dotterboard For Bulk SMT Parts

One of the great things about building electronics today is how affordable SMT components have become — sometimes just fractions of a cent each. That low price often means ordering far more than you need so you’ll have spares on hand the next time a project calls for them. Keeping track of exactly how many of each part you actually have, though, is rarely easy. To solve that problem, [John] built the Dotterboard, an open-source SMT tape counter.

While working on some of his other projects, [John] found himself managing thousands of tiny SMT parts and decided it was time to automate the counting. The Dotterboard takes inspiration from the BeanCounter — a compact, portable SMT tape counter — but expands the design to handle larger components beyond the 8 mm tapes the BeanCounter targets.

The Dotterboard is mostly 3D-printed and uses just a few common hardware parts such as springs and ball bearings. An OLED displays the current count, which comes from an encoder tracking movement and multiplying by the number of components per hole. At the heart sits an RP2040 Zero that needs nothing more than a single USB-C cable for power, unlike the bulky industrial SMT counters that demand AC outlets and desk space.

Be sure to check out all the details of the build on [John]’s website, and grab the files from his GitHub if you want to make your own. Let us know what are some projects you’ve done to save you the headache of doing the same task by hand for hours on end.

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Spy Tech: Conflicts Bring A New Number Station

If you know much about radios and espionage, you’ve probably encountered number stations. These are mysterious stations that read out groups of numbers or otherwise encoded messages to… well… someone. Most of the time, we don’t know who is receiving the messages. You’d be excused for thinking that this is an old technology. After all, satellite phones, the Internet, and a plethora of options now exist to allow the home base to send spies secret instructions. However, the current-day global conflict has seen at least one new number station appear, apparently associated with the United States and, presumably, targeting some recipients in Iran, according to priyom.org.

As you might expect, these stations don’t identify themselves, but the Enigma Control List names this one as V32. It broadcasts two two-hour blocks a day at 0200 UTC and a repeat at 1800 UTC. Each message starts with the Farsi word for “attention” followed by what is assumed to be some header information as two 5-digit groups. Then there is a set of 181 five-digit groups. Each message is padded out to take 20 minutes, and there are six messages in each transmission.

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An overlay is shown on a topographical map. High points are highlighted in blue. The letters "A" and "B" are shown in red text at two points.

Using A Scientific Satellite For Passive Radar

The basic principle of radar systems is simple enough: send a radio signal out, and measure the time it takes for a reflection to return. Given the abundant sources of RF signals – television signals, radio stations, cellular carriers, even Wi-Fi – that surround most of us, it’s not even necessary to transmit your own signal. This is the premise of passive radar, which uses passive RF illumination to form an image. The RF signal doesn’t even need to come from a terrestrial source, as [Jean Michel Friedt] demonstrated with a passive radar illuminated by the NISAR radar-imaging satellite (pre-print paper).

NISAR is a synthetic-aperture radar satellite jointly built by NASA and ISRO, and it completes a pass over the world every twelve days. It uses an L-band chirp radar signal, which can be picked up with GNSS antennas. One antenna points up towards the satellite, and has a ground plane blocking the signal from directly reaching the second antenna, which picks up reflections from the landscape under observation. Since the satellite would illuminate the scene for less than a minute, [Jean-Michel] had to predict the moment of peak intensity, and achieved an accuracy of about three seconds.

The signals themselves were recorded with an SDR and a Raspberry Pi. High-end, high-resolution SDRs such as the Ettus B210 gave the best results, but an inexpensive homebuilt MAX2771-based SDR also produced recognizable images. This setup won’t be providing any particularly detailed images, but it did accurately show the contours of the local geography – quite a good result for such a simple setup.

If you’re more interested in tracking aircraft than surveying landscapes, check out this ADS-B-synchronized passive radar system. Although passive radar doesn’t require a transmitter license, that doesn’t mean it’s free from legal issues, as the KrakenSDR team can testify.

The Hazards Of Charging USB-C Equipped Cells In-Situ

Can you charge those Li-ion based cells with USB-C charging ports without taking them out of the device? While this would seem to be answered with an unequivocal ‘yes’, recently [Colin] found out that this could easily have destroyed the device they were to be installed in.

After being tasked with finding a better way to keep the electronics of some exercise bikes powered than simply swapping the C cells all the time, [Colin] was led to consider using these Li-ion cells in such a manner. Fortunately, rather than just sticking the whole thing together and calling it a day, he decided to take some measurements to satisfy some burning safety questions.

As it turns out, at least the cells that he tested – with a twin USB-C connector on a single USB-A – have all the negative terminals and USB-C grounds connected. Since the cells are installed in a typical series configuration in the device, this would have made for an interesting outcome. Although you can of course use separate USB-C leads and chargers per cell, it’s still somewhat disconcerting to run it without any kind of electrical isolation.

In this regard the suggestion by some commentators to use NiMHs and trickle-charge these in-situ similar to those garden PV lights might be one of the least crazy solutions.

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Writing An Open-World Engine For The Nintendo 64

Anyone who has ever played Nintendo 64 games is probably familiar with the ways that large worlds in these games got split up, with many loading zones. Another noticeable aspect is that of the limited drawing distance, which is why even a large open area such as in Ocarina of Time‘s Hyrule Field has many features that limit how far you can actually see, such as hills and a big farming homestead in the center. Yet as [James Lambert] demonstrates in a recent video, it’s actually possible to create an open world on the N64, including large drawing distances.

As explained in the video, the drawing distance is something that the developer controls, and thus may want to restrict to hit certain performance goals. In effect he developer sets where the far clipping plane is set, beyond which items are no longer rendered. Of course, there are issues with just ramping up the distance to the far clipping plane, as the N64 only has a 15-bit Z-buffer, after which you get ‘Z fighting’, where render order becomes an issue as it’s no longer clear what is in front of what.

One fix is to push the near clipping plane further away from the player, but this comes with its own share of issues. Ergo [James] fixed it by doing two render passes: first all the far-away objects with Z-buffer disabled, and then all the nearby objects. These far-away objects can be rendered back-to-front with low level-of-detail (LoD), so this is relatively fast and also saves a lot of RAM, as the N64 is scraping by in this department at the best of times.

In the video the full details of this rendering approach, as well as a new fog rendering method, are explained, with the code and such available on GitHub for those who wish to tinker with it themselves. [James] and friends intend to develop a full game using this engine as well, so that’s definitely something to look forward to.

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Training A Transformer With 1970s-era Technology

Although generative language models have found little widespread, profitable adoption outside of putting artists out of work and giving tech companies an easy scapegoat for cutting staff, their their underlying technology remains a fascinating area of study. Stepping back to the more innocent time of the late 2010s, before the cultural backlash, we could examine these models in their early stages. Or, we could see how even older technology processes these types of machine learning algorithms in order to understand more about their fundamentals. [Damien Boureille] has put a 60s-era IBM as well as a PDP-11 to work training a transformer algorithm in order to take a closer look at it.

For such old hardware, the task [Damien Boureille] is training his transformer to do is to reverse a list of digits. This is a trivial problem for something like a Python program but much more difficult for a transformer. The model relies solely on self-attention and a residual connection. To fit within the 32KB memory limit of the PDP-11, it employs fixed-point arithmetic and lookup tables to replace computationally expensive functions. Training is optimized with hand-tuned learning rates and stochastic gradient descent, achieving 100% accuracy in 350 steps. In the real world, this means that he was able to get the training time down from hours or days to around five minutes.

Not only does a project like this help understand these tools, but it also goes a long way towards demonstrating that not every task needs a gigawatt datacenter to be useful. In fact, we’ve seen plenty of large language models and other generative AI running on computers no more powerful than an ESP32 or, if you need slightly more computing power, on consumer-grade PCs with or without GPUs.

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Hackaday Links: March 29, 2026

Whether it’s a new couch or a rare piece of hardware picked up on eBay, we all know what it feels like to eagerly await a delivery truck. But the CERN researchers involved in a delivery earlier this week weren’t transporting anyone’s Amazon Prime packages, they were hauling antimatter.

Moving antimatter, specifically antiprotons, via trucks might seem a bit ridiculous. But ultimately CERN wants to transfer samples between various European laboratories, and that means they need a practical and reliable way of getting the temperamental stuff from point A to B. To demonstrate this capability, the researchers loaded a truck with 92 antiprotons and drove it around for 30 minutes. Of course, you can’t just put antiprotons in a cardboard box, the experiment utilized a cryogenically cooled magnetic containment unit that they hope will eventually be able to keep antimatter from rudely annihilating itself on trips lasting as long as 8 hours.

Speaking of deliveries, anyone building a new computer should be careful when ordering components. Shady companies are looking to capitalize on the currently sky high prices of solid-state drives by counterfeiting popular models, and according to the Japanese site AKIBA PC Hotline, there are some examples in the wild that would fool  all but the most advanced users. They examine a bootleg drive that’s a nearly identical replica of the Samsung 990 PRO —  the unit and its packaging are basically a mirror image of the real deal, the stated capacity appears valid, and it even exhibits similar performance when put through a basic benchmark test.

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