In the early 1990s, I was lucky enough to get some time on a 60 MeV linear accelerator as part of an undergraduate lab course. Having had this experience, I can feel for the scientists at CERN who have had to make do with their current 13 TeV accelerator, which only manages energies some 200,000 times larger. So, I read with great interest when they announced the publication of the initial design concept for the Future Circular Collider (FCC), which promises collisions nearly an order of magnitude more energetic. The plan, which has been in the works since 2014, includes three proposals for accelerators which would succeed CERN’s current big iron, the LHC.
Want to know what’s on the horizon in high-energy physics?
Think of bicycles, and your first mental image could be something pretty fancy. Depending on which side of the sport you favor, you could end up thinking of a road bike or an MTB, maybe DH, CX, BMX, TT, tandem or recumbent.
But for people in most parts of the World such as Asia, Africa and South America, the bicycle conjures up a very different image – that of the humble roadster. And this simple, hardy machine has spawned innumerable hacks to extend its usefulness and functionality by enterprising people with limited means. For them, it is not as much a means of transport, as a means for livelihood and survival. Continue reading “Hacking The Humble Roadster Bicycle”→
Videogames have always existed in a weird place between high art and cutting-edge technology. Their consumer-facing nature has always forced them to be both eye-catching and affordable, while remaining tasteful enough to sit on retail shelves (both physical and digital). Running in real-time is a necessity, so it’s not as if game creators are able to pre-render the incredibly complex visuals found in feature films. These pieces of software constantly ride the line between exploiting the hardware of the future while supporting the past where their true user base resides. Each pixel formed and every polygon assembled comes at the cost of a finite supply of floating point operations today’s pieces of silicon can deliver. Compromises must be made.
Often one of the first areas in games that fall victim to compromise are environmental model textures. Maintaining a viable framerate is paramount to a game’s playability, and elements of the background can end up getting pushed to “the background”. The resulting look of these environments is somewhat more blurry than what they would have otherwise been if artists were given more time, or more computing resources, to optimize their creations. But what if you could update that ten-year-old game to take advantage of today’s processing capabilities and screen resolutions?
The wheels of government move slowly, far slower than the pace at which modern technology is evolving. So it’s not uncommon for laws and regulations to significantly lag behind the technology they’re aimed at reigning in. This can lead to something of a “Wild West” situation, which could either be seen as a good or bad thing depending on what side of the fence you’re on.
In the United States, it’s fair to say that we’ve officially moved past the “Wild West” stage when it comes to drone regulations. Which is not to say that remotely controlled (RC) aircraft were unregulated previously, but that the rules which governed them simply couldn’t keep up with the rapid evolution of the technology we’ve seen over the last few years. The previous FAA regulations for remotely operated aircraft were written in an era where RC flights were lower and slower, and long before remote video technology moved the operator out of the line of sight of their craft.
To address the spike in not only the capability of RC aircraft but their popularity, the Federal Aviation Administration was finally given the authority to oversee what are officially known as Unmanned Aerial Systems (UAS) with the repeal of Section 336 in the FAA Reauthorization Act of 2018. Section 336, known as the “Special Rule for Model Aircraft” was previously put in place to ensure the FAA’s authority was limited to “real” aircraft, and that small hobby RC aircraft would not be subject to the same scrutiny as their full-size counterparts. With Section 336 gone, one could interpret the new FAA directives as holding manned and unmanned aircraft and their operators to the same standards; an unreasonable position that many in the hobby strongly rejected.
At the time, the FAA argued that the repealing Section 336 would allow them to create new UAS regulations from a position of strength. In other words, start with harsh limits and regulations, and begin to whittle them down until a balance is found that everyone is happy with. U.S. Secretary of Transportation Elaine L. Chao has revealed the first of these refined rules are being worked on, and while they aren’t yet official, it seems like the FAA is keeping to their word of trying to find a reasonable middle ground for hobby fliers.
Chromecast devices have become popular in homes around the world in the last few years. They make it easy to cast audio or video from a smartphone or laptop, to a set of speakers or a display connected to the same network. [Akos] wanted to control the volume on these devices with a single, simple piece of equipment, rather than always reaching for a smartphone. Thus was built the CastVolumeKnob.
The project began by using Wireshark to capture data sent by the pychromecast library. Once [Akos] understood the messaging format, this was implemented in MicroPython on an ESP8266. A rotary encoder is used as a volume knob, and a Neopixel ring is used for visual feedback as to the device being controlled and the current volume level.
Further work was done to improve usability, with an ATtiny85 microcontroller being used to monitor the encoder for button presses before waking up the ESP8266, greatly reducing power consumption. The device is also rechargeable, thanks to an 18650 lithium polymer battery, and charger and boost converter boards. It’s all wrapped up in a sleek 3D printed case, with a translucent bezel for the LEDs and a swanky machined aluminium knob as the cherry on top.
It’s a homemade device that nonetheless would be stylish and unobtrusive in the living room environment. We imagine it proves very useful when important phone calls come in and it’s necessary to cut the stereo down to a more appropriate volume.
In an earlier installment of Linux Fu, I mentioned how you can use inotifywait to efficiently watch for file system changes. The comments had a lot of alternative ways to do the same job, which is great. But there was one very easy-to-use tool that didn’t show up, so I wanted to talk about it. That tool is entr. It isn’t as versatile, but it is easy to use and covers a lot of common use cases where you want some action to occur when a file changes.
I’ve always been fascinated by AI and machine learning. Google TensorFlow offers tutorials and has been on my ‘to-learn’ list since it was first released, although I always seem to neglect it in favor of the shiniest new embedded platform.
Last July, I took note when Intel released the Neural Compute Stick. It looked like an oversized USB stick, and acted as an accelerator for local AI applications, especially machine vision. I thought it was a pretty neat idea: it allowed me to test out AI applications on embedded systems at a power cost of about 1W. It requires pre-trained models, but there are enough of them available now to do some interesting things.
You can add a few of them in a hub for parallel tasks. Image credit Intel Corporation.
I wasn’t convinced I would get great performance out of it, and forgot about it until last November when they released an improved version. Unambiguously named the ‘Neural Compute Stick 2’ (NCS2), it was reasonably priced and promised a 6-8x performance increase over the last model, so I decided to give it a try to see how well it worked.
I took a few days off work around Christmas to set up Intel’s OpenVino Toolkit on my laptop. The installation script provided by Intel wasn’t particularly user-friendly, but it worked well enough and included several example applications I could use to test performance. I found that face detection was possible with my webcam in near real-time (something like 19 FPS), and pose detection at about 3 FPS. So in accordance with the holiday spirit, it knows when I am sleeping, and knows when I’m awake.
That was promising, but the NCS2 was marketed as allowing AI processing on edge computing devices. I set about installing it on the Raspberry Pi 3 Model B+ and compiling the application samples to see if it worked better than previous methods. This turned out to be more difficult than I expected, and the main goal of this article is to share the process I followed and save some of you a little frustration.
