[James Whomsley] likes flying, and likes flying fast. After reaching a speed of 114 miles an hour with an RC plane, he wanted to go further and break that record. To do so, he looked towards rocket power, and started a new build.

The design consists of a combination of 3D printed parts, laser-cut plywood bulkheads, and foamboard flight surfaces, with a few carbon fiber stiffeners thrown in here and there. For this early prototype, power is solely from hobby rocket motors, providing thrust for 1.6 seconds, meaning flight times are necessarily short. The craft is launched from an aluminium profile rail thanks to a 3D printed sliding guide pin.

Initial tests with two rocket motors were promising, leading to a second trial with a full six motors fitted. The thrust line was a little low, however, and a major pitch-up just after launch meant the plane only reached around 62 miles an hour. [James] still has a ways to go to beat his previous record, so intends to explore adding ducted fan propulsion to get the plane in the air before using the rockets as a speed booster in steady flight.

Of course, if you can’t lay your hands on rocket engines, you could always consider spinning up your own. (Or ditch the engine entirely.) Video after the break.

source https://hackaday.com/2020/09/27/rocket-plane-build-aims-for-high-speed-flight/

There’s nothing like a little diversion project to clear the cobwebs — something to carry one through the summer doldrums and charge you up for the rest of the hacking year. At least that’s what we think was up with [Sam Zeloof]’s printing Polaroid retro-conversion project.

Normally occupied with the business of learning how to make semiconductors in his garage, or more recently working on his undergraduate degree in electrical engineering, [Sam], like many of us, found himself with time to spare this summer. In search of a simple, fun project that wouldn’t glaze over the eyes of people when he showed it off, he settled on a printing party camera. The guts are pretty standard fare: a Raspberry Pi and Pi cam, coupled with a thermal receipt printer for instant hardcopy. The donor camera was a Polaroid Pronto from eBay, in good shape on the outside and mostly complete on the inside. A Dremel took care of the latter, freeing up space occupied by all the plastic bits that held the film cartridge and running gear of the film handling system.

The surgery made enough room to squeeze in the Pi Zero and a LiPo battery pack, along with a buck converter. Adding in the receipt printer and its drive board and mounting the Pi cam presented some challenges, but everything fit without breaking the original look and feel of the Polaroid. The camera now produces low-res hardcopy instantly using a dithering algorithm, and store high-resolution images on an SD card for later download. As a bonus, [Sam] included a simulated time and date stamp in the lower corner of the saved images, like those that used to show up on film.

[Sam]’s camera looks like a ton of fun. We’ve seen other Polaroid conversions, including a stunning SX-70 digital upgrade, but this one shines for its simplicity and instant hardcopy.

[via Tom’s Hardware]

source https://hackaday.com/2020/09/27/old-polaroid-gets-a-pi-and-a-printer/

Internet-connected sex toys are a great way to surprise your partner from work (even the home office) or for spicing up long-distance relationships. For some extra excitement, they also add that thrill of potentially having all your very sensitive private data exposed to the public — but hey, it’s not our place to kink-shame. However, their vulnerability issues are indeed common enough to make them regular guests in security conferences, so what better way to fight fire with fire than simply inviting the whole of Twitter in on your ride? Well, [Space Buck] built just the right device for that: the Double-Oh Battery, an open source LiPo-cell-powered ESP32 board in AA battery form factor as drop-in replacement to control a device’s supply voltage via WiFi.

In their simplest and cheapest form, vibrating toys are nothing more than a battery-powered motor with an on-off switch, and even the more sophisticated ones with different intensity levels and patterns are usually limited to the same ten or so varieties that may eventually leave something to be desired. To improve on that without actually taking the devices apart, [Space Buck] initially built the Slot-in Manipulator of Output Levels, a tiny board that squeezed directly onto the battery to have a pre-programmed pattern enabling and disabling the supply voltage — or have it turned into an alarm clock. But understandably, re-programming patterns can get annoying in the long run, so adding WiFi and a web server seemed the logical next step. Of course, more functionality requires more space, so to keep the AA battery form factor, the Double-Oh Battery’s PCB piggybacks now on a smaller 10440 LiPo cell.

But then, where’s the point of having a WiFi-enabled vibrator with a web server — that also happens to serve a guestbook — if you don’t open it up to the internet? So in some daring experiments, [Space Buck] showcased the project’s potential by hooking it up to his Twitter account and have the announcement tweet’s likes and retweets take over the control, adding a welcoming element of surprise, no doubt. Taking this further towards Instagram for example might be a nice vanity reward-system improvement as well, or otherwise make a great gift to send a message to all those attention-seeking people in your circle.

All fun aside, it’s an interesting project to remote control a device’s power supply, even though its application area might be rather limited due to the whole battery nature, but the usual Sonoff switches may seem a bit unfitting here. If this sparked your interest in lithium-based batteries, check out [Lewin Day]’s beginner guide and [Bob Baddeley]’s deeper dive into their chemistry.

source https://hackaday.com/2020/09/27/a-battery-to-add-a-tingling-sensation-to-your-tweets/

Internet-connected sex toys are a great way to surprise your partner from work (even the home office) or for spicing up long-distance relationships. For some extra excitement, they also add that thrill of potentially having all your very sensitive private data exposed to the public — but hey, it’s not our place to kink-shame. However, their vulnerability issues are indeed common enough to make them regular guests in security conferences, so what better way to fight fire with fire than simply inviting the whole of Twitter in on your ride? Well, [Space Buck] built just the right device for that: the Double-Oh Battery, an open source LiPo-cell-powered ESP32 board in AA battery form factor as drop-in replacement to control a device’s supply voltage via WiFi.

In their simplest and cheapest form, vibrating toys are nothing more than a battery-powered motor with an on-off switch, and even the more sophisticated ones with different intensity levels and patterns are usually limited to the same ten or so varieties that may eventually leave something to be desired. To improve on that without actually taking the devices apart, [Space Buck] initially built the Slot-in Manipulator of Output Levels, a tiny board that squeezed directly onto the battery to have a pre-programmed pattern enabling and disabling the supply voltage — or have it turned into an alarm clock. But understandably, re-programming patterns can get annoying in the long run, so adding WiFi and a web server seemed the logical next step. Of course, more functionality requires more space, so to keep the AA battery form factor, the Double-Oh Battery’s PCB piggybacks now on a smaller 10440 LiPo cell.

But then, where’s the point of having a WiFi-enabled vibrator with a web server — that also happens to serve a guestbook — if you don’t open it up to the internet? So in some daring experiments, [Space Buck] showcased the project’s potential by hooking it up to his Twitter account and have the announcement tweet’s likes and retweets take over the control, adding a welcoming element of surprise, no doubt. Taking this further towards Instagram for example might be a nice vanity reward-system improvement as well, or otherwise make a great gift to send a message to all those attention-seeking people in your circle.

All fun aside, it’s an interesting project to remote control a device’s power supply, even though its application area might be rather limited due to the whole battery nature, but the usual Sonoff switches may seem a bit unfitting here. If this sparked your interest in lithium-based batteries, check out [Lewin Day]’s beginner guide and [Bob Baddeley]’s deeper dive into their chemistry.

source https://hackaday.com/2020/09/27/a-battery-to-add-a-tingling-sensation-to-your-tweets/

Internet-connected sex toys are a great way to surprise your partner from work (even the home office) or for spicing up long-distance relationships. For some extra excitement, they also add that thrill of potentially having all your very sensitive private data exposed to the public — but hey, it’s not our place to kink-shame. However, their vulnerability issues are indeed common enough to make them regular guests in security conferences, so what better way to fight fire with fire than simply inviting the whole of Twitter in on your ride? Well, [Space Buck] built just the right device for that: the Double-Oh Battery, an open source LiPo-cell-powered ESP32 board in AA battery form factor as drop-in replacement to control a device’s supply voltage via WiFi.

In their simplest and cheapest form, vibrating toys are nothing more than a battery-powered motor with an on-off switch, and even the more sophisticated ones with different intensity levels and patterns are usually limited to the same ten or so varieties that may eventually leave something to be desired. To improve on that without actually taking the devices apart, [Space Buck] initially built the Slot-in Manipulator of Output Levels, a tiny board that squeezed directly onto the battery to have a pre-programmed pattern enabling and disabling the supply voltage — or have it turned into an alarm clock. But understandably, re-programming patterns can get annoying in the long run, so adding WiFi and a web server seemed the logical next step. Of course, more functionality requires more space, so to keep the AA battery form factor, the Double-Oh Battery’s PCB piggybacks now on a smaller 10440 LiPo cell.

But then, where’s the point of having a WiFi-enabled vibrator with a web server — that also happens to serve a guestbook — if you don’t open it up to the internet? So in some daring experiments, [Space Buck] showcased the project’s potential by hooking it up to his Twitter account and have the announcement tweet’s likes and retweets take over the control, adding a welcoming element of surprise, no doubt. Taking this further towards Instagram for example might be a nice vanity reward-system improvement as well, or otherwise make a great gift to send a message to all those attention-seeking people in your circle.

All fun aside, it’s an interesting project to remote control a device’s power supply, even though its application area might be rather limited due to the whole battery nature, but the usual Sonoff switches may seem a bit unfitting here. If this sparked your interest in lithium-based batteries, check out [Lewin Day]’s beginner guide and [Bob Baddeley]’s deeper dive into their chemistry.

source https://hackaday.com/2020/09/27/a-battery-to-add-a-tingling-sensation-to-your-tweets/

Sometimes, projects are borne out of neccessity; a fix for a problem that needs to be solved. Other times, they’re done just for the love of creation and experimentation. [ultraembedded]’s FPGAmp media player falls under the latter, and served as a great learning experience along the way.

The aim of FPGAmp is to play back a variety of media files on the Arty A7 development board, basedd around the Xilinx Artix-7 FPGA. Capable of playing back MJPEG video at 800 x 600 resolution and 25 fps, it’s also able to play back MP3s as well for stereo audio. Demonstrating the device on Twitter, [ultraembedded] notes that the method of using an LED to do SPDIF optical audio output isn’t legit, but does work. A later update switches to using a dedicated audio output board with the Arty A7 platform, featuring an excellent song from The Cardigans.

Using a RISC V processor core and a hardware JPEG decoder, we imagine [ultraembedded] really sharpened their FPGA skills with this project. Particularly in the wake of the sale of ARM to NVIDIA, RISC V continues to gain relevance in the hardware community. We were lucky enough to feature a keynote at last year’s Supercon, with Megan Wachs speaking on the technology. Video after the break.

Thanks to the #LVGL user interface library, my @DigilentInc #ArtyA7 #FPGA based media player project is now looking half decent. Plays 800×600 25fps video, MP3's and JPEG stills. All RTL and firmware sources now available on Github: https://t.co/TTG7huzyZW pic.twitter.com/6UWy2UXOfW

— ultraembedded (@ultraembedded) September 20, 2020

source https://hackaday.com/2020/09/26/an-fpga-video-player-built-just-for-fun/

Unsatisfied with the standard fare of soldering practice kits that offer little to no purpose once they’re built, [Jim Heaney] decided to take matters into his own hands and design an easy-to-assemble kit for his class that, once put together, becomes the handiest of tools in any maker’s workbench: a functional voltmeter.

At the heart of the kit is a standard Atmega 328P microcontroller. While he could’ve picked something smaller or cheaper, not only does the bulky part make for easier soldering, [Jim] reasons that it’s a chip that’s easy to repurpose should his students want to build something like a breadboard Arduino, for example. The voltmeter has a fixed measurement range from 0 to 100 VDC, the only switches on the board are for powering it on and a hold button, which freezes the value currently being shown in the three-digit, seven-segment display.

Along with selling his kit to other makers and educators, [Jim] also hopes that his project encourages others to design similar soldering kits which favor some sort of function rather than getting binned once there’s solder on all the pads, as well as part variety and documentation. If you’re on the other end of the soldering spectrum, then why not challenge your skills soldering on a time limit?

source https://hackaday.com/2020/09/26/soldering-practice-kit-remains-useful-after-completion/

A current probe isn’t a very common fixture on most workbenches because they are pretty expensive. [VoltLog] looks at a fairly inexpensive current probe from Micsig. He seemed impressed with the workmanship and it looks similar to more expensive offerings. There are two models with different bandwidth numbers (800 kHz and 2 MHz). It can measure current on a 10A and 100A scale.

According to [VoltLog] comparable probes from other vendors are more expensive and have lower bandwidth. He also liked that the device powers from USB since most newer scopes will have a USB port available.

If you aren’t familiar with a current probe, you might enjoy Digikey’s article on the topic or Keysight’s take on it. This probe can measure AC or DC current and while the specifications don’t promise super accuracy, [VoltLog] noted that his unit was better than the spec. He also noted that if you are wanting to measure small currents going to a microcontroller or similar device, these current probes are not really what you want to use.

We enjoyed the teardown of the device, too, about ten minutes into the video. The probe is surprisingly complex. It is possible that like some popular oscilloscopes, that changing the low bandwidth variant to the higher bandwidth model may be possible since the board appears to be used for both models.

We’ve looked at building very precise current probes. We’ve also looked at dirt cheap ones.

source https://hackaday.com/2020/09/26/cheap-current-probe-gets-good-review/

Typically in the RC community, radio control boats rely on small nitro engines or electric motors to get around. Fitted with traditional propellers, they’re capable of great speed and performance. Of course, there’s more than one way to skin a cat, as [Integza] shows with his latest build.

As far as the boat side of things is concerned, it’s a basic 3D printed single hull design. The innovation comes in the drivetrain, instead. The boat uses compressed air for propulsion, stored in a battery of four soda bottles, pressurized to 6 bar. The compressed air is used to drive a Tesla turbine of [Integza]’s design, which is 3D printed on a resin printer. Rather then driving a propeller, the Tesla turbine instead turns a Lily impeller, which pulls the boat through the water rather than pushing it along. The impeller uses a nature-inspired design, hence the name, and was also 3D printed, making producing its complex geometry a cinch. The guts of a toy radio control car are then used to control the boat.

Understandably, performance is less than stellar. The limited reserves of compressed air can’t propel the boat long, and the combination of the high RPM Tesla turbine and Lily impeller don’t provide a lot of thrust. However, the boat does move under its own power, demonstrating these oddball technologies while doing so.

[Integza] has been working with these technologies for a while; we featured an earlier Tesla turbine build back in 2018. Video after the break.

source https://hackaday.com/2020/09/26/tesla-turbine-boat-uses-lily-impeller/

Maybe you heard about the anger surrounding Twitter’s automatic cropping of images. When users submit pictures that are too tall or too wide for the layout, Twitter automatically crops them to roughly a square. Instead of just picking, say, the largest square that’s closest to the center of the image, they use some “algorithm”, likely a neural network, trained to find people’s faces and make sure they’re cropped in.

The problem is that when a too-tall or too-wide image includes two or more people, and they’ve got different colored skin, the crop picks the lighter face. That’s really offensive, and something’s clearly wrong, but what?

A neural network is really just a mathematical equation, with the input variables being in these cases convolutions over the pixels in the image, and training them essentially consists in picking the values for all the coefficients. You do this by applying inputs, seeing how wrong the outputs are, and updating the coefficients to make the answer a little more right. Do this a bazillion times, with a big enough model and dataset, and you can make a machine recognize different breeds of cat.

What went wrong at Twitter? Right now it’s speculation, but my money says it lies with either the training dataset or the coefficient-update step. The problem of including people of all races in the training dataset is so blatantly obvious that we hope that’s not the problem; although getting a representative dataset is hard, it’s known to be hard, and they should be on top of that.

Which means that the issue might be coefficient fitting, and this is where math and culture collide. Imagine that your algorithm just misclassified a cat as an “airplane” or as a “lion”. You need to modify the coefficients so that they move the answer away from this result a bit, and more toward “cat”. Do you move them equally from “airplane” and “lion” or is “airplane” somehow more wrong? To capture this notion of different wrongnesses, you use a loss function that can numerically encapsulate just exactly what it is you want the network to learn, and then you take bigger or smaller steps in the right direction depending on how bad the result was.

Let that sink in for a second. You need a mathematical equation that summarizes what you want the network to learn. (But not how you want it to learn it. That’s the revolutionary quality of applied neural networks.)

Now imagine, as happened to Google, your algorithm fits “gorilla” to the image of a black person. That’s wrong, but it’s categorically differently wrong from simply fitting “airplane” to the same person. How do you write the loss function that incorporates some penalty for racially offensive results? Ideally, you would want them to never happen, so you could imagine trying to identify all possible insults and assigning those outcomes an infinitely large loss. Which is essentially what Google did — their “workaround” was to stop classifying “gorilla” entirely because the loss incurred by misclassifying a person as a gorilla was so large.

This is a fundamental problem with neural networks — they’re only as good as the data and the loss function. These days, the data has become less of a problem, but getting the loss right is a multi-level game, as these neural network trainwrecks demonstrate. And it’s not as easy as writing an equation that isn’t “racist”, whatever that would mean. The loss function is being asked to encapsulate human sensitivities, navigate around them and quantify them, and eventually weigh the slight risk of making a particularly offensive misclassification against not recognizing certain animals at all.

I’m not sure this problem is solvable, even with tremendously large datasets. (There are mathematical proofs that with infinitely large datasets the model will classify everything correctly, so you needn’t worry. But how close are we to infinity? Are asymptotic proofs relevant?)

Anyway, this problem is bigger than algorithms, or even their writers, being “racist”. It may be a fundamental problem of machine learning, and we’re definitely going to see further permutations of the Twitter fiasco in the future as machine classification is being increasingly asked to respect human dignity.

source https://hackaday.com/2020/09/26/twitter-its-not-the-algorithms-fault-its-much-worse/

Maybe you heard about the anger surrounding Twitter’s automatic cropping of images. When users submit pictures that are too tall or too wide for the layout, Twitter automatically crops them to roughly a square. Instead of just picking, say, the largest square that’s closest to the center of the image, they use some “algorithm”, likely a neural network, trained to find people’s faces and make sure they’re cropped in.

The problem is that when a too-tall or too-wide image includes two or more people, and they’ve got different colored skin, the crop picks the lighter face. That’s really offensive, and something’s clearly wrong, but what?

A neural network is really just a mathematical equation, with the input variables being in these cases convolutions over the pixels in the image, and training them essentially consists in picking the values for all the coefficients. You do this by applying inputs, seeing how wrong the outputs are, and updating the coefficients to make the answer a little more right. Do this a bazillion times, with a big enough model and dataset, and you can make a machine recognize different breeds of cat.

What went wrong at Twitter? Right now it’s speculation, but my money says it lies with either the training dataset or the coefficient-update step. The problem of including people of all races in the training dataset is so blatantly obvious that we hope that’s not the problem; although getting a representative dataset is hard, it’s known to be hard, and they should be on top of that.

Which means that the issue might be coefficient fitting, and this is where math and culture collide. Imagine that your algorithm just misclassified a cat as an “airplane” or as a “lion”. You need to modify the coefficients so that they move the answer away from this result a bit, and more toward “cat”. Do you move them equally from “airplane” and “lion” or is “airplane” somehow more wrong? To capture this notion of different wrongnesses, you use a loss function that can numerically encapsulate just exactly what it is you want the network to learn, and then you take bigger or smaller steps in the right direction depending on how bad the result was.

Let that sink in for a second. You need a mathematical equation that summarizes what you want the network to learn. (But not how you want it to learn it. That’s the revolutionary quality of applied neural networks.)

Now imagine, as happened to Google, your algorithm fits “gorilla” to the image of a black person. That’s wrong, but it’s categorically differently wrong from simply fitting “airplane” to the same person. How do you write the loss function that incorporates some penalty for racially offensive results? Ideally, you would want them to never happen, so you could imagine trying to identify all possible insults and assigning those outcomes an infinitely large loss. Which is essentially what Google did — their “workaround” was to stop classifying “gorilla” entirely because the loss incurred by misclassifying a person as a gorilla was so large.

This is a fundamental problem with neural networks — they’re only as good as the data and the loss function. These days, the data has become less of a problem, but getting the loss right is a multi-level game, as these neural network trainwrecks demonstrate. And it’s not as easy as writing an equation that isn’t “racist”, whatever that would mean. The loss function is being asked to encapsulate human sensitivities, navigate around them and quantify them, and eventually weigh the slight risk of making a particularly offensive misclassification against not recognizing certain animals at all.

I’m not sure this problem is solvable, even with tremendously large datasets. (There are mathematical proofs that with infinitely large datasets the model will classify everything correctly, so you needn’t worry. But how close are we to infinity? Are asymptotic proofs relevant?)

Anyway, this problem is bigger than algorithms, or even their writers, being “racist”. It may be a fundamental problem of machine learning, and we’re definitely going to see further permutations of the Twitter fiasco in the future as machine classification is being increasingly asked to respect human dignity.

source https://hackaday.com/2020/09/26/twitter-its-not-the-algorithms-fault-its-much-worse/

Maybe you heard about the anger surrounding Twitter’s automatic cropping of images. When users submit pictures that are too tall or too wide for the layout, Twitter automatically crops them to roughly a square. Instead of just picking, say, the largest square that’s closest to the center of the image, they use some “algorithm”, likely a neural network, trained to find people’s faces and make sure they’re cropped in.

The problem is that when a too-tall or too-wide image includes two or more people, and they’ve got different colored skin, the crop picks the lighter face. That’s really offensive, and something’s clearly wrong, but what?

A neural network is really just a mathematical equation, with the input variables being in these cases convolutions over the pixels in the image, and training them essentially consists in picking the values for all the coefficients. You do this by applying inputs, seeing how wrong the outputs are, and updating the coefficients to make the answer a little more right. Do this a bazillion times, with a big enough model and dataset, and you can make a machine recognize different breeds of cat.

What went wrong at Twitter? Right now it’s speculation, but my money says it lies with either the training dataset or the coefficient-update step. The problem of including people of all races in the training dataset is so blatantly obvious that we hope that’s not the problem; although getting a representative dataset is hard, it’s known to be hard, and they should be on top of that.

Which means that the issue might be coefficient fitting, and this is where math and culture collide. Imagine that your algorithm just misclassified a cat as an “airplane” or as a “lion”. You need to modify the coefficients so that they move the answer away from this result a bit, and more toward “cat”. Do you move them equally from “airplane” and “lion” or is “airplane” somehow more wrong? To capture this notion of different wrongnesses, you use a loss function that can numerically encapsulate just exactly what it is you want the network to learn, and then you take bigger or smaller steps in the right direction depending on how bad the result was.

Let that sink in for a second. You need a mathematical equation that summarizes what you want the network to learn. (But not how you want it to learn it. That’s the revolutionary quality of applied neural networks.)

Now imagine, as happened to Google, your algorithm fits “gorilla” to the image of a black person. That’s wrong, but it’s categorically differently wrong from simply fitting “airplane” to the same person. How do you write the loss function that incorporates some penalty for racially offensive results? Ideally, you would want them to never happen, so you could imagine trying to identify all possible insults and assigning those outcomes an infinitely large loss. Which is essentially what Google did — their “workaround” was to stop classifying “gorilla” entirely because the loss incurred by misclassifying a person as a gorilla was so large.

This is a fundamental problem with neural networks — they’re only as good as the data and the loss function. These days, the data has become less of a problem, but getting the loss right is a multi-level game, as these neural network trainwrecks demonstrate. And it’s not as easy as writing an equation that isn’t “racist”, whatever that would mean. The loss function is being asked to encapsulate human sensitivities, navigate around them and quantify them, and eventually weigh the slight risk of making a particularly offensive misclassification against not recognizing certain animals at all.

I’m not sure this problem is solvable, even with tremendously large datasets. (There are mathematical proofs that with infinitely large datasets the model will classify everything correctly, so you needn’t worry. But how close are we to infinity? Are asymptotic proofs relevant?)

Anyway, this problem is bigger than algorithms, or even their writers, being “racist”. It may be a fundamental problem of machine learning, and we’re definitely going to see further permutations of the Twitter fiasco in the future as machine classification is being increasingly asked to respect human dignity.

source https://hackaday.com/2020/09/26/twitter-its-not-the-algorithms-fault-its-much-worse/

On the face of it, making a clock that displays the time by moving a pointer along a linear scale shouldn’t be too hard. After all, steppers and linear drives should do the job in a jiffy. Throw an Arduino in and Bob’s your uncle, right?

Wrong. At least that’s not the way [Leo Fernekes] decided to build this unique ratcheting linear clock, a brilliant decision that made the project anything but run-of-the-mill. The idea has been kicking around in [Leo]’s head for years, and there it stayed until inspiration came in the unlikely form of [This Old Tony], one of our favorite YouTube machinists. [Old Tony] did a video on the simple genius of latching mechanisms, like the ones in retractable pens, and that served as an “A-ha!” moment for [Leo]. For a ratchet, he used a strip of bandsaw blade oriented so the teeth point upward. A complex bit of spring steel, bent to engage with the blade’s teeth, forms a pawl to keep the pointer moving upward until it reaches the top.

[Leo] decided early on that this would be an impulse clock, like the type used in schools and factories. He used a servo to jog a strip of tape upward once each minute; the tape is engaged by jaws that drag the pointer along with it, moving the pawl up the ratchet by one tooth and lifting the pointer one minute closer to the top. The pointer releases at the top and falls back to start the cycle over; to arrest its freefall, [Leo] had the genius idea of attaching magnets and using eddy currents induced in the aluminum frame for the job. Finished off with a 3D-printed Art Deco scale, the clock is a unique timepiece that’s anything but boring.

We really appreciate [Leo]’s unique and creative take on projects, and his range. Check out his everlasting continuity tester and his phage-like sentry gun for some neat build details.

source https://hackaday.com/2020/09/26/linear-clock-ratchets-up-the-action/

Fermentation is a natural process that has been exploited by humanity for millennia. Behind such favorites as cheese and beer, it takes just the right conditions to get the desired results. To aid in this process, and to explore the crafts of their ancestors, [Victoria] and [Petar] created an electronic fermentation quilt.

Anyone familiar with breadmaking will be familiar with throwing a cloth over dough when left to rest. This is all about temperature management, providing optimum conditions for the yeast to work their magic. This fermentation quilt takes things to the next level, integrating soft heater pads and temperature sensing hardware into the fabric itself. Rather than acting as a simple insulator, the quilt can actively supply heat where needed, switching off when reaching the set temperature. In this example, the quilt is set to maintain a temperature of 45 degrees for the optimum production of Bulgarian yogurt.

The fermentation quilt serves as an excellent example of what can be achieved when combining textiles with smart electronics. Tools like Adafruit’s Lilypad and conductive thread all come together to make this a functional and useful device, and shows that electronic textiles aren’t just limited to blinky wearables.

Fermentation is a popular topic among hackers, with [Trent Fehl]’s Supercon talk at the 2019 Supercon covering similar ground from a sourdough perspective. It goes to show that hardware skills can pay off in the kitchen, too!

source https://hackaday.com/2020/09/26/fermenting-yogurt-with-the-help-of-hardware/

Fermentation is a natural process that has been exploited by humanity for millennia. Behind such favorites as cheese and beer, it takes just the right conditions to get the desired results. To aid in this process, and to explore the crafts of their ancestors, [Victoria] and [Petar] created an electronic fermentation quilt.

Anyone familiar with breadmaking will be familiar with throwing a cloth over dough when left to rest. This is all about temperature management, providing optimum conditions for the yeast to work their magic. This fermentation quilt takes things to the next level, integrating soft heater pads and temperature sensing hardware into the fabric itself. Rather than acting as a simple insulator, the quilt can actively supply heat where needed, switching off when reaching the set temperature. In this example, the quilt is set to maintain a temperature of 45 degrees for the optimum production of Bulgarian yogurt.

The fermentation quilt serves as an excellent example of what can be achieved when combining textiles with smart electronics. Tools like Adafruit’s Lilypad and conductive thread all come together to make this a functional and useful device, and shows that electronic textiles aren’t just limited to blinky wearables.

Fermentation is a popular topic among hackers, with [Trent Fehl]’s Supercon talk at the 2019 Supercon covering similar ground from a sourdough perspective. It goes to show that hardware skills can pay off in the kitchen, too!

source https://hackaday.com/2020/09/26/fermenting-yogurt-with-the-help-of-hardware/

Fermentation is a natural process that has been exploited by humanity for millennia. Behind such favorites as cheese and beer, it takes just the right conditions to get the desired results. To aid in this process, and to explore the crafts of their ancestors, [Victoria] and [Petar] created an electronic fermentation quilt.

Anyone familiar with breadmaking will be familiar with throwing a cloth over dough when left to rest. This is all about temperature management, providing optimum conditions for the yeast to work their magic. This fermentation quilt takes things to the next level, integrating soft heater pads and temperature sensing hardware into the fabric itself. Rather than acting as a simple insulator, the quilt can actively supply heat where needed, switching off when reaching the set temperature. In this example, the quilt is set to maintain a temperature of 45 degrees for the optimum production of Bulgarian yogurt.

The fermentation quilt serves as an excellent example of what can be achieved when combining textiles with smart electronics. Tools like Adafruit’s Lilypad and conductive thread all come together to make this a functional and useful device, and shows that electronic textiles aren’t just limited to blinky wearables.

Fermentation is a popular topic among hackers, with [Trent Fehl]’s Supercon talk at the 2019 Supercon covering similar ground from a sourdough perspective. It goes to show that hardware skills can pay off in the kitchen, too!

source https://hackaday.com/2020/09/26/fermenting-yogurt-with-the-help-of-hardware/

Are you still writing notes on paper and sticking them to the fridge like it’s the ’80s? Well, if you are, and you read this site, you’d probably like to upgrade to something a bit more 21st century. And, thanks to robot maker [James Bruton], you can leave your old, last century, message taking behind as he has a tutorial up showing you how to build an internet connected e-paper message display board. And, if you have a Raspberry Pi, an e-paper display and adapters just lying around doing nothing, then this project will cost you less than the buck that paper and a magnet will cost you.

Sarcasm aside, this is a pretty nice project. As mentioned, the base of this is a Raspberry Pi – [James] uses a Pi 4, but you could get away with an older, lower powered model as well. This powers the cheap(-ish) e-paper display he found online, which comes with the necessary adapters for the Pi, as well as a python library to write to the display. [James] uses a Google Sheet as the cloud storage for the message board, and there is some python code to access the cells in the Sheet and print them on the display if anything has changed. A cron job runs the script every 5 minutes to catch changes in the messages.

As with most of the projects that [James] does, he gives a good overview in the video and goes over the process of finding the hardware and writing and updating the script. He’s put the script and details as well as the CAD file for the frame he created for the project up on GitHub. [James] has been featured several times on the site before, check out some of his projects.

source https://hackaday.com/2020/09/25/internet-connected-e-paper-message-board/

Amateur radio operators and shortwave listeners have a common enemy: QRM, which is ham-speak for radio frequency interference caused by man-made sources. Indiscriminate, often broadband in nature, and annoying as hell, QRM spews forth from all kinds of sources, and can be difficult to locate and fix.

But [Emilio Ruiz], an operator from Mexico, got a little help from Mother Nature recently in his quest to lower his noise floor. Having suffered from a really annoying blast of RFI across wide swaths of the radio spectrum for months, a summer thunderstorm delivered a blessing in disguise: a power outage. Hooking his rig up to a battery — all good operators are ready to switch to battery power at a moment’s notice — he was greeted by blessed relief from all that noise. Whatever had caused the problem was obviously now offline.

Rather than waste the quiet time on searching down the culprit, [Emilio] worked the bands until the power returned, and with it the noise. He killed the main breaker in the house and found that the noise abated, leading him on a search of the premises with a portable shortwave receiver. The culprit? Unsurprisingly, it was a cheap laptop power supply. [Emilio] found that the switch-mode brick was spewing RFI over a 200-meter radius; a dissection revealed that the “ferrite beads” intended to suppress RFI emissions were in fact just molded plastic fakes, and that the cord they supposedly protected was completely unshielded.

We applaud [Emilio]’s sleuthing for the inspiration it gives to hunt down our own noise-floor raising sources. It kind of reminds us of a similar effort by [Josh (KI6NAZ)] a while back.

source https://hackaday.com/2020/09/25/tracking-down-radio-frequency-noise-source-with-help-from-mother-nature/

Very often, particularly on the Internet, we’re fooled into thinking bigger is always better. The fact remains that this isn’t always the case. When it comes to reflow ovens, for example if you’re working with short runs of small PCBs, or if you just don’t have a lot of space in the workshop, a smaller oven will be more desirable than a large one. It’s factors like these that drove [Sergi Martínez]’s latest build.

Built inside a metal project case, first attempts involved using an off-the-shelf heating element, with poor results. The element had a high thermal inertia, and was designed for use in water, so didn’t last in the reflow application. Learning from the experience of others, [Sergi] switched to using halogen lamps, netting much greater success. An Arduino Nano is responsible for running the show, using firmware developed by [0xPIT]. There’s also a screen for monitoring reflow profiles, and a cooling fan to help keep temperature in the ideal zone.

It’s a tidy build that would be particularly useful for quickly running batches of small PCBs without the long wait times required to heat a larger oven. Energy efficiency should be better, too. Of course, if you’re a fan of the classic toaster oven builds, we’ve got those too. Video after the break.

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Finally there is some reflow going on! It's nice to see how the solder paste melts. #smd #reflowpcb #reflow #ac #arduino #pcb #opensource #openhardware #diy #electronics #diyelectronics #nanoreflowcontroller

A post shared by ComputingTheBishop (@computingthebishop) on May 26, 2020 at 2:39pm PDT

source https://hackaday.com/2020/09/25/building-a-compact-reflow-oven-with-halogen-lamps/

Good news, Fusion 360 fans — Autodesk just announced that they won’t be removing support for STEP file exports for personal use licensees of the popular CAD/CAM platform after all.

As we noted last week, Autodesk had announced major changes to the free-to-use license for Fusion 360. Most of the changes, like the elimination of simulations, rolling back of some CAM features, and removal of generative design tools didn’t amount to major workflow disruptions for many hobbyists who have embraced the platform. But the loss of certain export formats, most notably STEP files, was a bone of contention and the topic of heated discussion in the makerverse. Autodesk summed up the situation succinctly in their announcement, stating that the reversal was due to “unintended consequences for the hobbyist community.”

While this is great news, bear in mind that the other changes to the personal use license are still scheduled to go into effect on October 1, while the planned change to limit the number of active projects will go into effect in January 2021. So while Fusion 360 personal use licensees will still have STEP files, the loss of other export file formats like IGES and SAT are still planned.

source https://hackaday.com/2020/09/25/autodesk-blinks-keeps-step-file-export-in-free-version-of-fusion-360/

Alumni from Innovation Design Engineering at Imperial College London and the Royal College of Art want to raise awareness of a road pollution source we rarely consider: tire wear. If you think about it, it is obvious. Our tires wear out, and that has to go somewhere, but what surprises us is how fast it happens. Single-use plastic is the most significant source of oceanic pollution, but tire microplastics are next on the naughty list. The team calls themselves The Tyre Collective, and they’re working on a device to collect tire particles at the source.

Tires become positively charged as you drive, like a Van De Graaff generator, so the team postulates that the most efficient way to collect the waste is to mount electrostatically charged plates where the plastics discharge. Road dust should pass through instead of gumming up the system since it is not charged. In an odd twist, hybrid vehicles are more dangerous regarding this type of pollution than their 100% petrol counterparts since they have to support a battery and electric motor.

When the tire dust is collected, it isn’t dumped out, because it can be reused as a pigment or even refined back into new tires. They’re collecting 60% of thrown particles in a lab setting, and they’re improving. What goes around comes around.

source https://hackaday.com/2020/09/25/road-pollution-doesnt-just-come-from-exhaust/

Alumni from Innovation Design Engineering at Imperial College London and the Royal College of Art want to raise awareness of a road pollution source we rarely consider: tire wear. If you think about it, it is obvious. Our tires wear out, and that has to go somewhere, but what surprises us is how fast it happens. Single-use plastic is the most significant source of oceanic pollution, but tire microplastics are next on the naughty list. The team calls themselves The Tyre Collective, and they’re working on a device to collect tire particles at the source.

Tires become positively charged as you drive, like a Van De Graaff generator, so the team postulates that the most efficient way to collect the waste is to mount electrostatically charged plates where the plastics discharge. Road dust should pass through instead of gumming up the system since it is not charged. In an odd twist, hybrid vehicles are more dangerous regarding this type of pollution than their 100% petrol counterparts since they have to support a battery and electric motor.

When the tire dust is collected, it isn’t dumped out, because it can be reused as a pigment or even refined back into new tires. They’re collecting 60% of thrown particles in a lab setting, and they’re improving. What goes around comes around.

source https://hackaday.com/2020/09/25/road-pollution-doesnt-just-come-from-exhaust/

Alumni from Innovation Design Engineering at Imperial College London and the Royal College of Art want to raise awareness of a road pollution source we rarely consider: tire wear. If you think about it, it is obvious. Our tires wear out, and that has to go somewhere, but what surprises us is how fast it happens. Single-use plastic is the most significant source of oceanic pollution, but tire microplastics are next on the naughty list. The team calls themselves The Tyre Collective, and they’re working on a device to collect tire particles at the source.

Tires become positively charged as you drive, like a Van De Graaff generator, so the team postulates that the most efficient way to collect the waste is to mount electrostatically charged plates where the plastics discharge. Road dust should pass through instead of gumming up the system since it is not charged. In an odd twist, hybrid vehicles are more dangerous regarding this type of pollution than their 100% petrol counterparts since they have to support a battery and electric motor.

When the tire dust is collected, it isn’t dumped out, because it can be reused as a pigment or even refined back into new tires. They’re collecting 60% of thrown particles in a lab setting, and they’re improving. What goes around comes around.

source https://hackaday.com/2020/09/25/road-pollution-doesnt-just-come-from-exhaust/

News comes overnight that the Windows XP source code has been leaked. The Verge says they have “verified the material as legitimate” and that the leak also includes Windows Server 2003 and some DOS and CE code as well. The thing is, it has now been more than six years since Microsoft dropped support for XP, does it really matter if the source code is made public?

The Poison Pill

As Erin Pinheiro pointed out in her excellent article on the Nintendo IP leak earlier this year (perhaps the best Joe Kim artwork of the year on that one, by the way), legitimate developers can’t really make use of leaked code since it opens them up to potential litigation. Microsoft has a formidable legal machine that would surely go after misuse of the code from a leak like this. Erin mentions in her article that just looking at the code is the danger zone for competitors.

Even if other software companies did look at the source code and implement their own improvements without crossing the legal line, how much is there still to gain? Surely companies with this kind of motivation would have reverse engineered the secret sauce of the long dead OS by now, right?

Spy vs. Spy

The next thing that comes to mind are the security implications. At the time of writing, statcount pegs Windows XP at a 0.82% market share which is still going to be a very large number of machines. Perhaps a better question to consider is what types of machines are still running it? I didn’t find any hard data to answer this question, however there are dedicated machines like MRIs that don’t have easy upgrade paths and still use the OS and there is an embedded version of XP that runs on point-of-sale, automated teller machines, set-top boxes, and other long-life hardware that are notorious for not being upgraded by their owners.

From both the whitehat and blackhat side, source code is a boon for chasing down vulnerabilities. Is there more to be gained by cracking the systems or submitting bug fixes? The OS is end of life, however Microsoft has shown that a big enough security threat still warrants a patch like they did with a remote desktop protocol vuln patch in May of 2019. I wonder if any of this code is still used in Windows 10, as that would make it a juicy tool for security researchers.

As for dangerous information in the leak, there have been some private keys found, like the NetMeeting root certificate. But its hard to say how much of a risk keys like this are due to the age of the software. You should stop using NetMeeting for high-security video conferencing if you haven’t already… it was end of life thirteen years ago so there’s nothing surprising there.

You Just Might Learn Something

I think the biggest news with a leak of code like this is the ability to learn from it. Why do people look at the source code of open source projects? Sure, you might be fixing a bug or adding a feature, but a lot times it’s to see how other coders are doing things. It’s the apprenticeship program of the digital age and having source code of long-dead projects both preserves how things were done for later research, and lets the curious superstars of tomorrow hone their skills at the shoulder of the masters.

Like a Museum Vouching for the Legitimacy of Artifacts

Why don’t company’s get out in front of this and publish end-of-life code as open source? This would vouch for the validity of the code. As it stands, how do you verify leaked code acquired from the more dimly lit corners of the Internet? Publishing the official source code for end of life projects preserves the history, something the Internet age has never given much thought to, but we should. We’ve heard the company promoting the message that Microsoft loves open source, here’s another great chance to show that by releasing the source code since it’s already out there from this leak. It would be a great step to do so now, and an even better one to take before leaks happen with future end of life products.

This is a pie-in-the-sky idea that we often trot out when we encounter stories of IoT companies that go out of business and brick their hardware on their way out. In those cases, the source code would allow users to roll their own back-end services that no longer exist, but Microsoft would be likely to frown on a “LibreWinXP” project based on their own code. It’s likely that the company still has a few long-term contracts to provide support for entities using XP hardware.

So What Do You Think?

This is Ask Hackaday so we want to know your take on this. When old source code leaks, is it a bad thing? Are there any compelling reasons for keeping the source code from projects that have seen their last sunset a secret? And now that the XP code is out there somewhere, what do you think may come for it? Weigh in below!

source https://hackaday.com/2020/09/25/ask-hackaday-is-windows-xp-source-code-leak-a-bad-thing/

Hackaday editors Elliot Williams take Mike Szczys peruse the world of hacks. There was so much news this week that we lead off the show with a rundown to catch you up. Yet there is still no shortage of hardware hacks, with prosthetic legs for your rubber ducky, a RC cart that channels the spirit of Formula 1, and a project that brings 80’s video conferencing hardware to Zoom. There’s phosphine gas on Venus and unlimited hacking projects inside your guitar. The week wouldn’t be complete without the joy of riffing on the most useless machine concept.

Take a look at the links below if you want to follow along, and as always, tell us what you think about this episode in the comments!

Direct download (~60 MB)

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Episode 086 Show Notes:

New This Week:

• SpaceX Sending Tom Cruise To The Space Station In 2021
• Closely Examining How A PG&E Transmission Line Claimed 85 Lives In The 2018 Camp Fire
• Autodesk Announces Major Changes To Fusion 360 Personal Use License Terms
• Community Testing Suggests Bias In Twitter’s Cropping Algorithm
• Remoticon Tickets And Workshops Just Dropped

Interesting Hacks of the Week:

• Plastic Prosthetics For Rubber Duckies
• 1/3 Scale Hybrid RC Car With A Scratch-Built 125cc V10 Engine
• Teleconferencing Like It’s 1988: Connecting Vintage Hardware To Zoom
• Wooden Disc Player Translates Binary Back Into Text
• Mirror Turns Webcam Into Document Camera
  • Mirror, Mirror, On Your Cam, Show Us What You’ve Drawn By Hand
  • Building A Crystal Clear Whiteboard
  • Document camera with pencil and a CD
• Finally, A Differently Useless Machine
  • Pull-string Most Useless Machine
  • Most Useless Machine: Building Elevator Edition

Quick Hacks:

• Elliot’s Picks:
  • Watch A Fast Sand Plotter Plow Patterns At Speed
  • Cyberplotter Uses Multiple Tools To Great Success
  • A Walking Robot With A Single Servo
• Mike’s Picks:
  • A Big Computer Needs A Big Keyboard
  • Custom Strain Gauges Help Keep Paraglider Aloft
  • Controlling A Broken Super Nintendo With MIDI

Can’t-Miss Articles:

• Axe Hacks: New Sounds For Your Electric Guitar Beginning From What Makes Them Tick
• Exploring The Clouds Of Venus; It’s Not Fantasy, But It Will Take Specialized Spacecraft
  • Phosphine gas in the cloud decks of Venus

source https://hackaday.com/2020/09/25/hackaday-podcast-086-news-overflow-formula-1-3-racer-standing-up-for-rubber-duckies-and-useless-machine-takes-a-turn/