Here are step-by-step instructions about how to get the Swedish e-Legitimation to work in Linux. The instructions are specifically for Nordea bank customers.
You need the “pocket calculator” cardreader (I used Todos NCR1), a suitable USB cable and a card with an EMV chip. If you have Nordea-issued bankkort or VISA you’re OK.
Note: These instructions are Debian-specific but they should work with other distros too with appropriate, slight changes.
When the weather gets cold, the tough whip up a warm soup.
This one is slightly thai-influenced in its taste, and extremely quick and simple to do.
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To help keep the Andromeda strain swine flu away, you should take a swine flu shot.
Ingredients:
Enjoy!
Zenburn v2.13 is released!
Thanks to Zac Thompson and Christophe-Marie Duquesne, there is now:
Grab it from vim.sf.net or from the official Zenburn page.
Enjoy!
Zenburn v2.5 is released!
Changes: support for coloring Ignore-groups (thanks to John Gabriele). The Ignore-group coloring is toggleable, see the file for details.
Grab it from vim.sf.net or from the official Zenburn page.
In practice, the Vim help files will change from this (click pictures to show them bigger):
to this:
Gianfranco writes:
I send you an adaption of the zenburn colour scheme for SciTE v. 1.78. To install it on a Windows machine, just copy the *.properties files into the SciTE installation folder.
I needed DIMACS-format output from STP, so I hacked together a patch for it.
It works only against the SVN version of STP, but is trivial (although not automatic) to patch the latest non-SVN version also. To patch, cd to the STP folder, then use something like patch -R -p1 < stp_dimacs.patch
Then, use the "-o" switch to dump a DIMACS file to the current folder. Next, fire up your favorite SAT solver and profit...
Update: It seems the toDimacs call can create strange outputs. Be aware of bugs!
After admiring the Krypto-Kekkonen, I thought I’d roll my own.
Here’s a Python script called split_pic.py to split an image of your choosing into two shares as described by the Naor-Shamir “visual cryptography” scheme. See the script for details.
The script requires PIL (Python Image Library). The outputs are two files, “share1.png” and “share2.png”. Print share1.png on paper, and share2.png on transparency/foil/plastic and carefully align them on top of each other to see the hidden image.
Or, you can use an image editor such as Gimp. Note, the layer effect must be “multiply” for both layers.
Here are two examples you can play with:
First share of the hidden image
Second share of the hidden image
Nowadays a lot of music is in digital format. One of the most popular digital encoding methods is MPEG-1 Audio Layer III, aka. “MP3“. Typically an MP3 file takes around 1/10 the size of the uncompressed original (depending on quality), thereby saving storage space.
MP3 uses a form of lossy compression. This means that the original sound can not be perfectly recovered. What is recovered (sound you hear) is some kind of approximation of the original.
MP3 does this lossy compression by removing the sounds which a human ear cannot distinguish, using so-called “perceptual coding“. The sounds which are removed are specified by a psychoacoustic model, which is created using human input, for example listening tests.
In other words, this means that many people are all the time listening to music with “something missing”. But what is this something, what does this something sound like?
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