For a while I had been contemplating replacing my 2008 Macbook (4,1) as it was stuck on OSX 10.6. But I couldn’t find any new affordable laptop that took my fancy (too expensive, too big, too small, just not right). I remembered reading about running Linux on MacBooks a while ago and thought, why don’t I try Linux?
I downloaded the 17.1 Linux Mint iso (cinnamon flavour) and followed the instructions to make a bootable USB stick.
I took out the internal hard disk and replaced it with an old one I had kicking about. After that, I plugged in the USB stick rebooted the MacBook holding down the ALT key and the machine booted into Linux after choosing the correct device (in the second attempt). I followed instructions that I largely ignored as they were not applicable. To get the WIFI working this line
apt-get install firmware-b43-installer
sufficed. And another irritation is that the touchpad doesn’t quite work but the interwebs have solutions for that as well. Though the relevant config file appears to live in
You can experiment with the settings using synclient.
I also added
And it’s a good idea to switch off hardware acceleration in Chrome as the screen goes black when watching youtube videos otherwise.
After a weekend of testing, I splashed out on a 1Tb SSD and put that in the MacBook and now have a fairly zippy 4Gb MacBook running a modern OS. Even Google’s tensorflow installed without a hitch.
Between 6 December and 22 November 2015 there were 2068 failed attempts to login into my machine exposed on the interwebs. I excluded the the ones due to me being unable to type my super-safe password correctly. This equates to about 6 attempts per hour on a machine that is not widely advertised. Presumably, this is mainly due to random attacks that you can also investigate with network telescope, in fact my machine is a network telescope of sorts. So looking at the frequency of usernames used in failed attempts (or attempted break ins if you like) root is the most popular choice and the top 20 are:
Plotting the rank of a user name against its frequency logarithmically we get the all too familiar picture of a heavy tailed distribution or power law:
However, here the x-axis barely covers 2 decades, so one should be a bit careful to declare that we see a power law with a gradient of about -1.5. Another way to visualise the data is to look at the usernames used in chronological order (excluding repeats) as nodes in a network. Even this very small sample produces a surprisingly complicated graph.
This is a graph produced by the twopi program of graphviz which looked like the prettiest one. The most connected nodes are root and admin. Is this useful? One interesting way approach this question would be to compare this graph and the analysis above with a data set that contains only valid and successful logins. If the data looks suitably diffrent one could use this approach to get alerted to unwanted behaviour. Unfortunately, I do not have access to such a data set.
I was also intrigued to see the user name pi to feature quite high in the charts, ten years ago this would have been less popular.
The last few weeks have been very wet and not very pleasant for cycling to work. But as reward there have been some spectacular sunrises.
And in central Reading the “Winter Wonderland” has been assembled in Forbury Gardens.
This morning Jupiter, Mars, Venus and the moon all lined up nicely. Mercury was around as well, but it was too low on the horizon and I think I was also a bit late for it. The sky was already too bright to see it.
At the end of September there was a special lunar eclipse with a particularly red moon. It was visible in Berkshire during the very small hours of the morning. Fortunately, I did manage to wake up in time and was rewarded with a spectacular view.
Last month I managed to ride to the Bungsberg again, the first time for a long time. It is Schleswig-Holstein‘s highest point with phenomenal 168m above sea level. On the way there I followed the B202 from Kiel which wasn’t too bad. But the cyclepaths along are quite bad in places due to roots from trees popping the tarmac. Also, cyclepaths designers are also under mistaken impression that cyclist enjoy bonus tight corners and extra hills. Near the Bungsberg the cyclepaths were even worse with big cracks and large potholes. I also made the mistake to follow a signpost indicating a cycle route to my destination which for the last kilometre turned into a steep and narrow footpath. But the weather was nice, sunny but not too warm,
and I had good view from the top. Unfortunately, I had not brought a lock along and therefore could not climb up the telecommunications tower. The ride home was more pleasant, though still riddled with bumpy mandatory cyclepaths through villages that have a 30km/h speed limit. I took a rural route to Preetz just to the North of Malente and Plön.
Still, a nice trip that was just above the 100km mark that I can recommend for a bike ride on a sunny day.
Yesterday’s visit to Bad Schwartau finally gave me the opportunity to visit the location of the original settlement of Lübeck which was later abandoned.
You can still see why the location must have been a good for a small settlement, a small hill overlooking the confluence of two rivers. However, there was little room for flood proof extension.
I also had a go at trying to take a picture of the forest in Bad Schwartau as panorama, good effort, but room for improvement.