It should probably come as no surprise to anyone that the images which we look at every day – whether printed or on a display – are simply illusions. That cat picture isn’t actually a cat, but rather a collection of dots that when looked at from far enough away tricks our brain into thinking that we are indeed looking at a two-dimensional cat and happily fills in the blanks. These dots can use the full CMYK color model for prints, RGB(A) for digital images or a limited color space including greyscale.
Perhaps more interesting is the use of dithering to further trick the mind into seeing things that aren’t truly there by adding noise. Simply put, dithering is the process of adding noise to reduce quantization error, which in images shows up as artefacts like color banding. Within the field of digital audio dithering is also used, for similar reasons. Part of the process of going from an analog signal to a digital one involves throwing away data that falls outside the sampling rate and quantization depth.
By adding dithering noise these quantization errors are smoothed out, with the final effect depending on the dithering algorithm used.
If you are a certain age, you probably remember the ads and publicity around Chisanbop — the supposed ancient art of Korean finger math. Was it Korean? Sort of. Was it faster than a calculator? Sort of. [Chris Staecker] offers a great look at Chisanbop, not just how to do it, but also how it became such a significant cultural phenomenon. Take a look at the video below. Long, but worth it.
Technically, the idea is fairly simple. Your right-hand thumb is worth 5, and each finger is worth 1. So to identify 8, you hold down your thumb and the first three digits. The left hand has the same arrangement, but everything is worth ten times the right hand, so the thumb is 50, and each digit is worth 10.
With a little work, it is easy to count and add using this method. Subtraction is just the reverse. As you might expect, multiplication is just repeated addition. But the real story here isn’t how to do Chisanbop. It is more the story of how a Korean immigrant’s system went viral decades before the advent of social media.
You can argue that this is a shortcut that hurts math understanding. Or, you could argue the reverse. However, the truth is that this was around the time the calculator became widely available. Math education would shift from focusing on getting the right answer to understanding the underlying concepts. In a world where adding ten 6-digit numbers is easy with a $5 device, being able to do it with your fingers isn’t necessarily a valuable skill.
Do you ever look at the news, and wonder about the process behind the news cycle? I did, and for the last couple of decades it’s been the subject of one of my projects. The Raspberry Pi on my shelf runs my word trend analysis tool for news content, and since my journey from curious geek to having my own large corpus analysis system has taken twenty years it’s worth a second look.
How Career Turmoil Led To A Two Decade Project
This is very much a minority spelling. Colin Smith, CC BY-SA 2.0.
In the middle of the 2000s I had come out of the dotcom crash mostly intact, and was working for a small web shop. When they went bust I was casting around as one does, and spent a while as a Google quality rater while I looked for a new permie job. These teams are employed by the search giant through temporary employment agencies, and in loose terms their job is to be the trained monkeys against whom the algorithm is tested. The algorithm chose X, and if the humans also chose X, the algorithm is probably getting it right. Being a quality rater is not in any way a high-profile job, but with the big shiny G on my CV I soon found myself in demand from web companies seeking some white-hat search engine marketing expertise. What I learned mirrored my lesson from a decade earlier in the CD-ROM business, that on the web as in any other electronic publishing medium, good content well presented has priority over any black-hat tricks.
But what makes good content? Forget an obsession with stuffing bogus keywords in the text, and instead talk about the right things, and do it authoritatively. What are the right things in this context? If you are covering a subject, you need to do so using the right language; that which the majority uses rather than language only you use. I can think of a bunch of examples which I probably shouldn’t talk about, but an example close to home for me comes in cider. In the UK, cider is a fermented alcoholic drink made from apples, and as a craft cidermaker of many years standing I have a good grasp of its vocabulary. The accepted spelling is “Cider”, but there’s an alternate spelling of “Cyder” used by some commercial producers of the drink. It doesn’t take long to realise that online, hardly anyone uses cyder with a Y, and thus pages concentrating on that word will do less well than those talking about cider.
We Brits rarely use the word “soccer” unless there’s a story about the Club World Cup in America.
I started to build software to analyse language around a given topic, with the aim of discerning the metaphorical cider from the cyder. It was a great surprise a few years later to discover that I had invented for myself the already-existing field of computational linguistics, something that would have saved me a lot of time had I known about it when I began. I was taking a corpus of text and computing the frequencies and collocates (words that appear alongside each other) of the words within it, and from that I could quickly see which wording mattered around a subject, and which didn’t. This led seamlessly to an interest in what the same process would look like for news data with a time axis added, so I created a version which harvested its corpus from RSS feeds. Thus began my decades-long project.
Normally you can’t read out the One Time Programming (OTP) memory in Microchip’s PIC MCUs that have code protection enabled, but an exploit has been found that gets around the copy protection in a range of PIC12, PIC14 and PIC16 MCUs.
This exploit is called PIC Burnout, and was developed by [Prehistoricman], with the cautious note that although this process is non-invasive, it does damage the memory contents. This means that you likely will only get one shot at dumping the OTP data before the memory is ‘burned out’.
The copy protection normally returns scrambled OTP data, with an example of PIC Burnout provided for the PIC16LC63A. After entering programming mode by setting the ICSP CLK pin high, excessively high programming voltage and duration is used repeatedly while checking that an area that normally reads as zero now reads back proper data. After this the OTP should be read out repeatedly to ensure that the scrambling has been circumvented.
The trick appears to be that while there’s over-voltage and similar protections on much of the Flash, this approach can still be used to affect the entire flash bit column. Suffice it to say that this method isn’t very kind to the Flash memory cells and can take hours to get a good dump. Even after this you need to know the exact scrambling method used, which is fortunately often documented by Microchip datasheets.
Some people slander retrocomputing as an old man’s game, just because most of those involved are more ancient than the hardware they’re playing with. But there are veritable children involved too — take the [ComputerSmith], who isrecreating Conway’s game of life on a Macintosh Plusthat could very well be as old as his parents. If there’s any nostalgia here, it’s at least a generation removed — thus proving for the haters that there’s more than a misplaced desire to relive one’s youth in exploring these ancient machines.
So what does a young person get out of programming on a 1980s Mac? Well, aside from internet clout, and possible YouTube monetization, there’s the sheer intellectual challenge of the thing. You cant go sniffing around StackExchange or LLMs for code to copy-paste when writing C for a 1986 machine, not if you’re going to be fully authentic. ANSI C only dates to 1987, after all, and figuring out the quirks and foibles of the specific C implementation is both half the fun, and not easily outsourced. Object Pascal would also have been an option (and quite likely more straightforward — at least the language was clearly-defined), but [ComputerSmith] seems to think the exercise will improve his chops with C, and he’s likely to be right.
Apparently [ComputerSmith] brought this project to VCS Southwest, so anyone who was there doesn’t have to wait for Part 2 of the video to show up to see how this turns out, or to snag a copy of the code (which was apparently available on diskette). If you were there, let us know if you spotted the youngest Macintosh Plus programmer, and if you scored a disk from him.
Yes, you read that right– not benchy, but beanie, as in the hat. A toque, for those of us under the Maple Leaf. It’s not 3D printed, either, except perhaps by the loosest definition of the word: it is knit, by [Kevr102]’smotorized turbo knitter.
The turbo-knitter started life as an Addi Express King knitting machine. These circular knitting machines are typically crank-operated, functioning with a cam that turns around to raise and lower special hooked needles that grab and knit the yarn. This particular example was not in good working order when [Kevr102] got a hold of it. Rather than a simple repair, they opted to improve on it.
A 12 volt motor with a printed gear and mount served for motorizing the machine. The original stitch counter proved a problem, so was replaced with an Arduino Nano and a hall effect sensor driving a 7-digit display. In theory, the Arduino could be interfaced with the motor controller and set to run the motor for a specific number of stitches, but in practice there’s no point as the machine needs babysat to maintain tension and avoid dropping stitches and the like. Especially, we imagine, when it runs fast enough to crank out a hat in under six minutes. Watch it go in the oddly cropped demo video embedded below.
Five minutes would still be a very respectable time for benchy, but it’s not going to get you on the SpeedBoatRace leaderboards against something like the minuteman we covered earlier.
If you prefer to take your time, thisknitting machine clock might be more your fancy. We don’t see as many fiber arts hacks as perhaps we should here, so if you’re tangled up in anything interesting in that scene, please drop us a line.
Many people who get analog electronics still struggle a bit to design oscillators. Even common simulators often need a trick to simulate some oscillating circuits. The Barkhausen criteria state that for stable oscillation, the loop gain must be one, and the phase shift around the feedback loop must be a multiple of 360 degrees. [All Electronics Channel] provides a thorough exploration of oscillators and, specifically, negative resistance, which is punctuated by practical measurements using a VNA. Check it out in the video below.
The video does have a little math and even mentions differential equations, but don’t worry. He points out that the universe solves the equation for you.
In an LC circuit, you can consider the losses in the circuit as a resistor. That makes sense. No component is perfect. But if you could provide a negative resistance, it would cancel out the parasitic resistance. With no loss, the inductor and capacitor will go back and forth, electrically, much like a pendulum.
So, how do you get a negative resistance? You’ll need an active device. He presents some example oscillator architectures and explains how they generate negative resistances.
Crystals are a great thing to look at with a VNA. That used to be a high-dollar piece of test gear, but not anymore.
