The Heat Of The Moments – Location Visualization In Python

December 5, 2019 by Sven Gregori 7 Comments

Have you ever taken a look at all the information that Google has collected about you over all these years? That is, of course, assuming you have a Google account, but that’s quite a given if you own an Android device and have privacy concerns overruled by convenience. And considering that GPS is a pretty standard smartphone feature nowadays, you shouldn’t be surprised that your entire location history is very likely part of the collected data as well. So unless you opted out from an everchanging settings labyrinth in the past, it’s too late now, that data exists — period. Well, we might as well use it for our own benefit then and visualize what we’ve got there.

Location data naturally screams for maps as visualization method, and [luka1199] thought what would be better than an interactive Geo Heatmap written in Python, showing all the hotspots of your life. Built around the Folium library, the script reads the JSON dump of your location history that you can request from Google’s Takeout service, and overlays the resulting heatmap on the OpenStreetMap world map, ready for you to explore in your browser. Being Python, that’s pretty much all there is, which makes [Luka]’s script also a good starting point to play around with Folium and map visualization yourself.

While simply just looking at the map and remembering the places your life has taken you to can be fun on its own, you might also realize some time optimization potential in alternative route plannings, or use it to turn your last road trip route into an art piece. Just, whatever you do, be careful that you don’t accidentally leak the location of some secret military facilities.

[via r/dataisbeautiful]

Updating To Windows 10 For Fun And Profit: Make Those OEM Keys Go Further

December 5, 2019 by Jonathan Bennett 215 Comments

Microsoft seems to have an every-other-version curse. We’re not sure how much of this is confirmation bias, but consider the track record of releases. Windows 95 was game-changing, Windows 98 famously crashed during live demo. Windows 2000 was amazing, Windows ME has been nicknamed the “Mistake Edition”. XP was the workhorse of the world for years and years, and Vista was… well, it was Vista. Windows 7 is the current reigning champion of desktop installs, and Windows 8 was the version that put a touchscreen interface on desktops. The “curse” is probably an example of finding patterns just because we’re looking for them, but the stats do show a large crowd clinging to Windows 7.

Windows 10 made a name for itself by automatically installing itself on Windows 7 and Windows 8 computers, much to the annoyance of many unexpecting “victims” of that free upgrade. Several years have gone by, Windows 10 has gotten better, and support for Windows 7 ends in January. If you’re tied to the Windows ecosystem, it’s time to upgrade to Windows 10. It’s too bad you missed out on the free upgrade to Windows 10, right?

About that… It’s probably an unintended side effect, but all valid Windows 7 and Windows 8 keys are also valid Windows 10 keys. Activation is potentially another issue, but we’ll get to that later.

Continue reading “Updating To Windows 10 For Fun And Profit: Make Those OEM Keys Go Further” →

Circuit Simulation In Python

November 30, 2019 by Bryan Cockfield 23 Comments

Using SPICE to simulate an electrical circuit is a common enough practice in engineering that “SPICEing a circuit” is a perfectly valid phrase in the lexicon. SPICE as a software tool has been around since the 70s, and its open source nature means there are more SPICE tools around now to count. It also means it is straightforward enough to use with other software as well, like integrating LTspice with Python for some interesting signal processing circuit simulation.

[Michael]’s latest project involves simulating filters in LTspice (a SPICE derivative) and then using Python/NumPy to both provide the input signal for the filter and process the output data from it. Basically, it allows you to “plug in” a graphical analog circuit of any design into a Python script and manipulate it easily, in any way needed. SPICE programs aren’t without their clumsiness, and being able to write your own tools for manipulating circuits is a powerful tool.

This project is definitely worth a look if you have any interest in signal processing (digital or analog) or even if you have never heard of SPICE before and want an easier way of simulating a circuit before prototyping one on a breadboard.

Training Bats In The Random Forest With The Confusion Matrix

November 21, 2019 by Pat Whetman 4 Comments

When exploring the realm of Machine Learning, it’s always nice to have some real and interesting data to work with. That’s where the bats come in – they’re fascinating animals that emit very particular ultrasonic calls that can be recorded and analysed with computer software to get a fairly good idea of what species they are. When analysed with an FFT spectogram, we can see the individual call shapes very clearly.

Nyctalus noctula (noctule bat)

Myotis nattereri (natterera’s bat)

Plecotus auritus (brown long eared)

Pipistrellus pipistrellus (common pipistrelle)

Creating an open source classifier for bats is also potentially useful for the world outside of Machine Learning as it could not only enable us to more easily monitor bats themselves, but also the knock on effects of modern farming methods on the natural environment. Bats feed on moths and other night flying insects which themselves have been decimated in numbers. Even in the depths of the countryside here in the UK these insects are a fraction of the population that they used to be 30 years ago, but nobody seems to have monitored this decline.

So getting back to our spectograms, it would be perfectly reasonable to throw these images at a convolutional neural network (CNN) and use an image feature-recognition strategy. But I wanted to explore the depths of the mysterious Random Forest. Continue reading “Training Bats In The Random Forest With The Confusion Matrix” →

Symbiflow Open Source FPGA Toolchain

November 1, 2019 by Gerrit Coetzee 12 Comments

Anyone who’s ever had the pleasure of programming FPGAs knows that it’s a land of proprietary tools that almost require marriage level commitment to a specific platform to be effective. Symbiflow hopes to solve this by becoming the GCC of FPGAs.

Rather than a tool built around a specific chip or architecture, Symbiflow will provide a more universal interface. Users can program in Verilog; architecture definitions define how the code will be compiled for the right chip. They are currently targeting the popular Xilinx 7-series, the very affordable iCE40 series from lattice, and the ECP5 FPGAs also from Lattice.

If you’re headed to Hackaday Supercon this year, [Timothy Ansell] will be giving a talk on how Symbiflow is making this process much more approachable and much less proprietary. Overall we’re very excited about a common interface, especially as the price of FPGAs keep dropping into micro controller territory while also increasing in capability.

(Speaking of Supercon, and maybe this is a spoiler, the badge would not have been possible without Symbiflow, Project Trellis, Yosys, and NextPNR.)

Unix Tell All Book From Kernighan Hits The Shelves

October 29, 2019 by Al Williams 56 Comments

When you think of the Unix and C revolution that grew out of Bell Labs, there are a few famous names. Dennis Ritchie, Ken Thompson, and Brian Kernighan come to mind. After all, the K in both K&R C and in AWK stand for Kernighan. While Kernighan is no stranger to book authorship — he’s written several classics including “the white book” for C and Unix — he has a new book out that is part historical record and part memoir about the birth of Unix.

Usually, when a famous person writes a retrospective like this, it is full of salacious details, but we don’t expect much of that here. The book talks about Bell Labs and Multics, of course. There’s serious coverage of the first, sixth, and seventh editions with biographies of people integral to those releases.

Continue reading “Unix Tell All Book From Kernighan Hits The Shelves” →

An Algorithm For De-Biasing AI Systems

October 21, 2019 by Sharon Lin 52 Comments

A fundamental truth about AI systems is that training the system with biased data creates biased results. This can be especially dangerous when the systems are being used to predict crime or select sentences for criminals, since they can hinge on unrelated traits such as race or gender to make determinations.

A group of researchers from the Massachusetts Institute of Technology (MIT) CSAIL is working on a solution to “de-bias” data by resampling it to be more balanced. The paper published by PhD students [Alexander Amini] and [Ava Soleimany] describes an algorithm that can learn a specific task – such as facial recognition – as well as the structure of the training data, which allows it to identify and minimize any hidden biases.

Testing showed that the algorithm minimized “categorical bias” by over 60% compared against other widely cited facial detection models, all while maintaining the same precision of detection. This figure was maintained when the team evaluated a facial-image dataset from the Algorithmic Justice League, a spin-off group from the MIT Media Lab.

The team says that their algorithm would be particularly relevant for large datasets that can’t easily be vetted by a human, and can potentially rectify algorithms used in security, law enforcement, and other domains beyond facial detection.