385 karma · joined February 28, 2013
Earlier today, I found [1] which - amongst other things which you might be interested in - calls out a venture [2] to establish a network of 'citizen scientist' type flood sensors across the UK. Their scheme looks to be a network of radio-to-Internet gateways which support a number of independently-deployed sensor nodes.
[1] http://oomlout.co.uk/blogs/news/81763329-an-overview-of-ardu... [2] http://flood.network/
The published version has headings: Latitude, Latin name, Modern name and date of Roman foundation, Axis, Amplitude at solstice, Published research. Still no map, though.
http://www.intel.co.uk/content/www/uk/en/processors/architec...
> The sphere is dipped with
> its north pole pointing downward. The maximum error on the
> northern hemisphere is within 2mm. However, near its south pole
> the error is much larger (about 5mm). This is because after the
> water surface passes the sphere’s equator, the film gets stretched
> largely, and near the south pole the relative angle between the
> water surface and the object surface approaches to 180◦, leading
> to an ill-posed boundary condition for our simulation (recall
> Equation (1), when θ ≈ 180◦).
You can see the potential for a similar wraparound even on e.g. the mask dips. sudo apt-get update
sudo apt-get install build-essential linux-image-extra-virtual
sudo reboot
echo options nouveau modeset=0 | sudo tee -a /etc/modprobe.d/nouveau-kms.conf
cat > /etc/modprobe.d/blacklist-nouveau.conf
blacklist nouveau
blacklist lbm-nouveau
options nouveau modeset=0
alias nouveau off
alias lbm-nouveau off
<Ctrl+D>
sudo update-initramfs -u
sudo reboot
sudo apt-get install linux-headers-$(uname -r)
wget http://uk.download.nvidia.com/XFree86/Linux-x86_64/346.35/NVIDIA-Linux-x86_64-346.35.run
chmod +x NVIDIA-Linux-x86_64-346.35.run
sudo ./NVIDIA-Linux-x86_64-346.35.run
nvidia-smi -q | less
This is obviously not production-ready, and is heavily cribbed from online (I couldn't quickly re-find where) but is good enough if you just want to play.EDIT: I think this was the original: http://ubuntuhandbook.org/index.php/2015/01/install-nvidia-3...
> What is the `uniform' distribution we want, anyway? It is obviously not the uniform discrete distribution on the finite set of floating-point numbers in [0, 1] -- that would be silly. For our `uniform' distribution, we would like to imagine[*] drawing a real number in [0, 1] uniformly at random, and then choosing the nearest floating-point number to it.
Because of the logarithmic representation, there are as many floating point numbers between .25 and .5 as there are between .5 and 1. If you uniformly sample numbers with an exact, finite floating point representation then you don't get something that 'looks like' a uniform distribution of real numbers in [0, 1] -- which is more likely what was wanted.
Accelerators? http://ie.microsoft.com/activities/en-en/Default.aspx
Thanks very much!
The legend claims one-sigma (68% confidence assuming normality)