USB chargers are everywhere and it is the responsibility of every hacker to use this commonly available device to its peak potential. [Septillion] and [Hugatry] have come up with a hack to manipulate a USB charger into becoming a variable voltage source. Their project QC2Control works with chargers that employ Quick Charge 2.0 technology which includes wall warts as well as power banks.
Qualcomm’s Quick Charge is designed to deliver up to 24 watts over a micro USB connector so as to reduce the charging time of compatible devices. It requires both the charger as well as the end device to have compatible power management chips so that they may negotiate voltage limiting cycles.
In their project, [Septillion] and [Hugatry] use a 3.3 V Arduino Pro Mini to talk to the charger in question through a small circuit consisting of a few resistors and diodes. The QC2.0 device outputs voltages of 5 V, 9 V and 12 V when it sees predefined voltage levels transmitted over the D+ and D- lines, set by Arduino and voltage dividers. The code provides function calls to simplify the control of the power supply. The video below shows the hack in action.
Quick Charge has been around for a while and you can dig into the details of the inner workings as well as the design of a compatible power supply from reference designs for the TPS61088 (PDF). The patent (PDF) for the Quick Charge technology has a lot more detail for the curious.
Similar techniques have been used in the past and will prove useful for someone looking for a configurable power supply on the move. This is one for the MacGyver fans.
[inches] wanted the power of a Raspberry Pi 3 in a form factor closer to the Pi Zero for a Game Boy mod. This led him to design a custom PCB to interface with one of the less popular items in the Raspberry Pi line: the Compute Module 3. A hardware comparison between the three platforms is available here.
After correcting some minor issues, it booted correctly on the first try. The final result is slightly larger than a Raspberry Pi Zero, but significantly smaller than the Raspberry Pi 3, and fits perfectly inside the Game Boy for a clean build.
The Raspberry Pi Zero remains difficult to source in some parts of the world and can cost nearly as much as the more powerful CM3 (e.g. in Southeast Asia). If you’re comfortable making a breakout board and benefit from the added computing power, it’s a reasonable option when it needs to be small.
Worth noting is that the Raspberry Pi Foundation does sell an open-source development kit for the CM3 that has been used in some projects, but the retail cost is relatively high compared to a Raspberry Pi 3. Smaller but less feature-rich breakout boards like the one by [inches] make the CM3 more accessible.
The world is dealing with a serious refugee crisis, and with that comes a problem: finding people. The Refugee Reuniter, a project entered into this year’s Hackaday Prize, is a possible solution to this problem. It’s a device that allows people to reconnect with their family, whether it’s children lost in transit to destination countries, or mothers and fathers reuniting.
The basic problem the Refugee Reuniter is trying to solve is tracking people. This is a whole ball of wax that involves privacy and technological concerns. Ideas put forward so far include GPS trackers, implantable RFID tags, and other such draconian measures. The Refugee Reuniter puts another spin on this, while still assigning a unique, electronic ID to every name.
The basic hardware for the Refugee Reuniter is simply an RFID wristband or token, carried with the refugee at all times. This token is mapped to a name that can be looked up in a small terminal, tied to a specific location. If a refugee logs into one of these terminals, their location is logged and they can search for their relatives. It’s a simple technological solution to what is basically a gigantic dead-tree logbook, only backed up into an online database.
I normally stay away from talking about x86 single-board computers because I don’t have a lot to say about them. They’re too expensive, and run too hot, to be interesting. Enter the new UP Core funding now on Kickstarter.
The UP Core is just 56.5 mm × 66 mm (2.2 in × 2.6 in) and powered by a 64-bit Quad Core Intel Atom clocked at either 1.44 GHz or 1.92 GHz. It will ship with either 2 GB or 4 GB of RAM, and either 32 GB or 64 GB of eMMC. The board has a USB 3 port, HDMI, DSI/eDP, and two MIPI-CSI ports supporting either a 2 MP or 8 MP camera. It has both WiFi 802.11 b/g/n and Bluetooth LE built-in.
In other words it’s powerful enough to serve as a desktop PC running Linux, Android, or a full Windows 10 installation. The cheapest UP Core configuration—with 1 GB memory and 16 GB eMMC—is €69, or around $75. Continue reading “First Thoughts On The New UP Core”→
Model steam engines have intrigued hackers and makers for over 100 years. Many of us have seen old steam engine models up for sale at garage sales and various internet auction sites. The problem with these engines is the fact that many of them were sold as rough casting kits. This means the quality of the model is only as good as the original owner’s machining and fabrication skills.
First off is the paint. If you find nuts, bolts and random parts painted in different colors, the engine is probably bad. It sounds strange, but [Keith] has found this to be a rule over his years of working with these engines.
Another problem is rattles. [Keith] found one of these engines rattled terribly. The culprit was the crankshaft. Not only was it the wrong size, but it was built wrong. These engines use built up crankshafts, rather than shafts machined from a single piece of metal. This engine’s crankshaft was threaded into the crank webs rather than pinned. Whoever built it tried to re-engineer the design of the crankshaft, and failed miserably.
It’s not too often that you see handkerchiefs around anymore. Today, they’re largely viewed as unsanitary and well… just plain gross. You’ll be quite disappointed to learn that they have absolutely nothing to do with this article other than a couple of similarities they share when compared to your neocortex. If you were to pull the neocortex from your brain and stretch it out on a table, you most likely wouldn’t be able to see that not only is it roughly the size of a large handkerchief; it also shares the same thickness.
The neocortex, or cortex for short, is Latin for “new rind”, or “new bark”, and represents the most recent evolutionary change to the mammalian brain. It envelopes the “old brain” and has several ridges and valleys (called sulci and gyri) that formed from evolution’s mostly successful attempt to stuff as much cortex as possible into our skulls. It has taken on the duties of processing sensory inputs and storing memories, and rightfully so. Draw a one millimeter square on your handkerchief cortex, and it would contain around 100,000 neurons. It has been estimated that the typical human cortex contains some 30 billion total neurons. If we make the conservative guess that each neuron has 1,000 synapses, that would put the total synaptic connections in your cortex at 30 trillion — a number so large that it is literally beyond our ability to comprehend. And apparently enough to store all the memories of a lifetime.
In the theater of your mind, imagine a stretched-out handkerchief lying in front of you. It is… you. It contains everything about you. Every memory that you have is in there. Your best friend’s voice, the smell of your favorite food, the song you heard on the radio this morning, that feeling you get when your kids tell you they love you is all in there. Your cortex, that little insignificant looking handkerchief in front of you, is reading this article at this very moment.
What an amazing machine; a machine that is made possible with a special type of cell – a cell we call a neuron. In this article, we’re going to explore how a neuron works from an electrical vantage point. That is, how electrical signals move from neuron to neuron and create who we are.
Despite the amazing feats a human brain performs, the neuron is comparatively simple when observed by itself. Neurons are living cells, however, and have many of the same complexities as other cells – such as a nucleus, mitochondria, ribosomes, and so on. Each one of these cellular parts could be the subject of an entire book. Its simplicity arises from the basic job it does – which is outputting a voltage when the sum of its inputs reaches a certain threshold, which is roughly 55 mV.
Using the image above, let’s examine the three major components of a neuron.
Soma
The soma is the cell body and contains the nucleus and other components of a typical cell. There are different types of neurons whose differing characteristics come from the soma. Its size can range from 4 to over 100 micrometers.
Dendrites
Dendrites protrude from the soma and act as the inputs of the neuron. A typical neuron will have thousands of dendrites, with each connecting to an axon of another neuron. The connection is called a synapse but is not a physical one. There is a gap between the ends of the dendrite and axon called a synaptic cleft. Information is relayed through the gap via neural transmitters, which are chemicals such as dopamine and serotonin.
Axon
Each neuron has only a single axon that extends from the soma, and acts similar to an electrical wire. Each axon will terminate with terminal fibers, forming synapses with as many as 1,000 other neurons. Axons vary in length and can reach a few meters long. The longest axons in the human body run from the bottom of the foot to the spinal cord.
The basic electrical operation of a neuron is to output a voltage spike from its axon when the sum of its input voltages (via its dendrites) crosses a specific threshold. And since axons are connected to dendrites of other neurons, you end up with this vastly complicated neural network.
Since we’re all a bunch of electronic types here, you might be thinking of these ‘voltage spikes’ as a difference of potential. But that’s not how it works. Not in the brain anyway. Let’s take a closer look at how electricity flows from neuron to neuron.
Action Potentials – The Communication Protocol of the Brain
The axon is covered in a myelin sheet which acts as an insulator. There are small breaks in the sheet along the length of the axon which are named after its discoverer, called Nodes of Ranvier. It’s important to note that these nodes are ion channels. In the spaces just outside and inside of the axon membrane exists a concentration of potassium and sodium ions. The ion channels will open and close, creating a local difference in the concentration of sodium and potassium ions.
We all should know that an ion is an atom with a charge. In a resting state, the sodium/potassium ion concentration creates a negative 70 mV difference of potential between the outside and inside of the axon membrane, with there being a higher concentration of sodium ions outside and a higher concentration of potassium ions inside. The soma will create an action potential when -55 mV is reached. When this happens, a sodium ion channel will open. This lets positive sodium ions from outside the axon membrane to leak inside, changing the sodium/potassium ion concentration inside the axon, which in turn changes the difference of potential from -55 mV to around +40 mV. This process in known as depolarization.
One by one, sodium ion channels open along the entire length of the axon. Each one opens only for a short time, and immediately afterward, potassium ion channels open, allowing positive potassium ions to move from inside the axon membrane to the outside. This changes the concentration of sodium/potassium ions and brings the difference of potential back to its resting place of -70 mV in a process known as repolarization. Fro start to finish, the process takes about five milliseconds to complete. The process causes a 110 mV voltage spike to ride down the length of the entire axon, and is called an action potential. This voltage spike will end up in the soma of another neuron. If that particular neuron gets enough of these spikes, it too will create an action potential. This is the basic process of how electrical patterns propagate throughout the cortex.
The mammalian brain, specifically the cortex, is an incredible machine and capable of far more than even our most powerful computers. Understanding how it works will give us a better insight into building intelligent machines. And now that you know the basic electrical properties of a neuron, you’re in a better position to understand artificial neural networks.
Depending on whom you talk to, music can be an integral part of getting work done. At the Hackheim hackerspace in Trondheim, Norway, [Nikolai Ovesen] thought that the previous system of playing music over Bluetooth took away from the collaborative, interactive spirit of the space. Solution: a weekend build of a Raspberry Pi-powered jukebox.
The jukebox is simply laser-cut from plywood and bolted together. Inside, the touchscreen is mounted using double-sided tape, with the Raspberry Pi 3 and buck converter mounted on its rear with motherboard spacers. An IBM ThinkPad power cable was re-purposed and modified so it supplies the amp, as well as the Pi and touchscreen through the buck converter.
Once everything was connected, tested, and fired up, a bit of clever software working around had to be done in order to get Golang working, along with setting up the touchscreen and amp. Hackers interact with the jukebox using the Mopidy music server and its Mopify(Spotify) plugin — but they can also request songs through a bot in the Hackheim Slack channel.
