How Good Are The Head(amame) 3D Printed Headphones?

3D printing lets the average maker tackle building anything their heart desires, really, and many have taken to using the technology for audio projects. Printable speaker and headphone designs abound. The Head(amame) headphones from [Vector Finesse] are a design that combines 3D printed parts with hi-fi grade components to create a high-end listening experience. [Angus] of Maker’s Muse decided to try printing a set at home and has shared his thoughts on the hardware.

Printing the parts has to be done carefully, with things like the infill settings crucial to the eventual sound quality of the final product. Using a properly equipped slicer like CURA is key to getting the parts printed properly so the finer settings can be appropriately controlled. The recommendation is to print the pieces in PETG, which [Angus] notes can be difficult to work with, and several prints were required to get all the parts made correctly.

Assembly is straightforward enough with kits available with all the fasteners and electronic parts included. Subjectively, [Angus] found the sound quality to be impressive, with plenty of full bass and clearly defined highs. Overall, it’s a positive review in the areas of comfort and sound quality.

Detractors will note that the kit of parts costs over $100 USD alone, and that after hours of work and printing, the user is left with a set of headphones made out of obviously 3D-printed parts. It seems destined to be a product aimed at the 3D printing fanbase. If you want a set of headphones you can customise endlessly in form and color, these are ideal. If you prefer the fit and finish of a consumer-grade product, they may not be for you.

It’s a good look at a design sure to appeal to a wide set of makers out there. We’ve seen 3D printing put to good use in this realm before, too. Video after the break.

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Arduino Orchestra Plays The Planets Suite

We’ve seen a great many Arduino synthesizer projects over the years. We love to see a single Arduino bleeping out some monophonic notes. From there, many hackers catch the bug and the sky is truly the limit. [Kevin] is one such hacker who now has an Arduino orchestra capable of playing all seven movements of Gustav Holst’s Planets Suite.

The performers are not human beings with expensive instruments, but simple microcontrollers running code hewn by [Kevin’s] own fingertips. The full orchestra consists of 11 Arduino Nanos, 6 Arduino Unos, 1 Arduino Pro Mini, 1 Adafruit Feather 32u4, and finally, a Raspberry Pi.

Different synths handle different parts of the performance. There are General MIDI synths on harp and bass, an FM synth handling wind and horn sections, and a bunch of relays and servos serving as the percussive section. The whole orchestra comes together to do a remarkable, yet lo-fi, rendition of the whole orchestral work.

While it’s unlikely to win any classical music awards, it’s a charming recreation of a classical piece and it’s all the more interesting coming from so many disparate parts working together. It’s an entirely different experience than simply listening to a MIDI track playing on a set of headphones.

We’d love to see some kind of hacker convention run a contest for the best hardware orchestra. It could become a kind of demoscene contest all its own. In the meantime, scope one of [Kevin’s] earlier projects on the way to this one – 12 Arduinos singing Star Wars tracks all together. Video after the break.

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Adversarial Makeup: Your Contouring Skills Could Defeat Facial Recognition

Facial recognition is everywhere these days. Cloud servers churn through every picture uploaded to social media, phone cameras help put faces to names, and CCTV systems are being used to trace citizens in their day-to-day lives. You might want to dodge this without arousing suspicion, just for a little privacy now and then. As it turns out, common makeup techniques can help you do just that.

In research from a group at the Ben-Gurion University of the Negev, the team trialled whether careful makeup contouring techniques could fool a facial recognition system. There are no wild stripes or dazzle patterns here; these techniques are about natural looks and are used by makeup artists every day.

The trick is to use a surrogate facial recognition system and a picture of the person who intends to evade. Digital techniques are used to alter the person’s appearance until it fools the facial recognition system. This is then used as a guide for a makeup artist to recreate using typical contouring techniques.

The theory was tested with a two-camera system in a corridor. The individual was identified correctly in 47.57% of frames in which a face was detected when wearing no makeup. With random makeup, this dropped to 33.73%, however with the team’s intentionally-designed makeup scheme applied, the attacker was identified in just 1.22% of frames. (PDF)

The attack relies on having a good surrogate of the facial recognition system one wishes to fool. Else, it’s difficult to properly design appropriate natural-look makeup to fool the system. However, it goes to show the power of contouring to completely change one’s look, both in front of humans and the machines!

Facial recognition remains a controversial issue, but nothing is stopping its rollout across the world. Indeed, your facial profile may already be out there.

Making A Metal Hand Doorknob

Regular doorknobs are widely reviled for their bare simplicity, but by and large society has so many other problems that it never really comes up in day to day conversation. Fear not, however, for [Matthew] has created something altogether more special: a doorknob in the shape of his own outstretched hand.

The build was inspired by a similar doorknob at the WNDR museum in Chicago, and its one you can recreate yourself, too. It’s achieved through a multi-stage mold making process. [Matthew]’s first step was to make a flexible mold of his hand using Perfect Mold alginate material to do so.

Once solidified, [Matthew’s] hand was removed and the mold filled with wax. The wax duplicate of [Matthew]’s hand was then used to create an investment plaster mold for casting metal. Vents were added in the end of each fingertip in the mold to allow molten metal to effectively fill the entire cavity.

Once the investment mold was solid and dry, the wax was melted out and it was ready for casting. A propane furnace was used to melt the casting metal and fill the mold using a simple gravity casting method. [Matthew] ended up making two hands, one in aluminium and one in copper. Some cleanup with grinders and a wire wheel, and a replica of [Matthew]’s hand was in his hands!

The finished piece looks great attached to a door knob, and we’re sure it’s quite satisfying shaking hands with your hefty metal self every time you open the door. It bears noting that the same techniques can be used with 3D printing, too! If you pull off your own great home casting project, be sure to drop us a line. Video after the break.

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Rescuing A Wacom Digitizer From A Broken Lenovo Yoga Book

The Lenovo Yoga Book is a interesting thing, featuring a touch-surface keyboard that also doubles as a Wacom tablet. [TinLethax] sadly broke the glass of this keyboard when trying to replace a battery in their Yoga Book, but realised the Wacom digitizer was still intact. Thus began a project to salvage this part and repurpose it for the future.

The first step was to reverse engineer the hardware; as it turns out, the digitizer pad connects to a special Wacom W9013 chip which holds the company’s secret sauce (secret smoke?). As the GitHub page for [TinLethax]’s WacomRipoff driver explains, however, the chip communicates over I2C. Thus, it was a simple enough job to hook up a microcontroller, in this case an STM32 part, and then spit out USB HID data to a host.

It hasn’t all been smooth sailing, and it’s not 100% feature complete, but [TinLethax] was able to get the digitizer working as a USB HID input device. It appears the buttons and pressure sensitivity are functional, too.

If you’ve got a disused or defunct Yoga Book lying around, you might just consider the same mods yourself. We’ve seen some other great hacks in this space, too. Video after the break.

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Bluetooth Vulnerability: Arbitrary Code Execution On The ESP32, Among Others

Bluetooth has become widely popular since its introduction in 1999. However, it’s also had its fair share of security problems over the years. Just recently, a research group from the Singapore University of Technology and Design found a serious vulnerability in a large variety of Bluetooth devices. Having now been disclosed, it is known as the BrakTooth vulnerability.

Full details are not yet available; the research team is waiting until October to publicly release proof-of-concept code in order to give time for companies to patch their devices. The basic idea however, is in the name. “Brak” is the Norweigan word for “crash,” with “tooth” referring to Bluetooth itself. The attack involves repeatedly attempting to crash devices to force them into undesired operation.

The Espressif ESP32 is perhaps one of the worst affected. Found in all manner of IoT devices, the ESP32 can be fooled into executing arbitrary code via this vulnerability, which can do everything from clearing the devices RAM to flipping GPIO pins. In smart home applications or other security-critical situations, this could have dire consequences.

Other chipsets are affected to varying degrees, including parts from manufacturers like Texas Instruments and Cypress Semiconductor. Some parts are vulnerable to denial of service, while audio devices may be frozen up or shut down by the attack. The group claims over 1400 products could be affected by the bug.

Firmware patches are being rolled out, and researcher [Matheus E. Garbelini] has released code to build a sniffer device for the vulnerability on GitHub. If you’re involved with the design or manufacture of Bluetooth hardware, it might pay to start doing some homework on this one! Concerned vendors can apply for proof-of-concept test code here.

Even Faster Fourier Transforms On The Raspbery Pi Zero

Oftentimes in computing, we start doing a thing, and we’re glad we’re doing it. But then we realise, it would be much nicer if we could do it much faster. [Ricardo de Azambuja] was in just such a situation when working with the Raspberry Pi Zero, and realised that there were some techniques that could drastically speed up Fast Fourier Transforms (FFT) on the platform. Thus, he got to work.

The trick is using the Raspberry Pi Zero’s GPU to handle the FFTs instead of the CPU itself. This netted Ricardo a 7x speed upgrade for 1-dimensional FFTs, and a 2x speed upgrade for 2-dimensional operations.

The idea was cribbed from work we featured many years ago, which provided a similar speed up to the very first Raspberry Pi. Given the Pi Zero uses the same SoC as the original Raspberry Pi but at a higher clock rate, this makes perfect sense. However, in this case, [Ricardo] implemented the code in Python instead of C as suits his use case.

[Ricardo] uses the code with his Maple Syrup Pi Camera project, which pairs a Coral USB machine learning accelerator with a Pi Zero and a camera to achieve tasks such as automatic licence plate recognition or facemask detection. Fun!