Graham White: My Notes

Much like moving bank account, it's not very often I move mobile network.  I tend to favour staying with the same provider unless they provide me with a good reason to leave.  My current network, TalkMobile, have just done so by completely shutting down their PAYG service and so are only able to offer me a contract (that I don't want) or a rubbish deal to move to Vodafone (they're a Vodafone MVNO).

I thought I'd write a similar post about my experience moving to the giffgaff network today to the one I wrote about Moving to TalkMobile back in 2012.  You'll see from that link that joining TalkMobile was extremely painful.  However, I'm happy to report I found the network very solid and reliable with what I can only presume is good coverage (there's always black spots, right?) on the Vodafone network.  Getting them to do anything was always painful as there's little option for self-service so it's more or less always a call to their support staff.  The staff are very polite and extremely helpful but the processes and presumably the systems they have to use seem somewhat antiquated today.

So in comparison to my previous blog post about moving to TalkMobile, moving to giffgaff went a bit like this:

Day 1 (yesterday)

1. Register a giffgaff SIM a friend gave me and create a new giffgaff account all in one simple guided wizard on the giffgaff web site
2. Request a PAC from TalkMobile
3. Go through the number transfer process via another simple wizard on the giffgaff web site

Day 2 (today)

1. Observe a short outage in mobile service as my number was transferred just after lunch
2. Happy customer

So now I'm looking forward to years of good service from giffgaff until they provide me with a good reason to leave some time in the future.

By the way, if you want to grab a giffgaff SIM then feel free to register via my referral link as we'll both get a free £5 credit if you do.

It's been a while, but true to our 4 year hardware refresh cycle, I've just received my latest laptop - a Lenovo P50.  I've been installing it with Fedora 25 since Friday and configuring and copying data over this weekend ready to swap laptops first thing this week.  I'm looking forward to trying out the new machine although I'm not quite sure why as the specs are barely different from the machine I was given 4 years ago.  It's certainly the best indication yet I've personally experienced of Moore's Law coming to a complete halt as well as many of the other specifications not improving a huge amount either.  The two most noticeable differences are likely to be the more powerful graphics chip and the inclusion of an SSD.  That said, there is twice as much RAM in this machine and I had upgraded my previous machine with an SSD as well so that particular upgrade isn't going to be noticeable for me at least.

My previous machine was a W530 and the one I had before that was a T61p (with a T41p before that) and so I'm well used to this particular line of Thinkpad laptops.

Here's the specifications of the machine I've got, as ever there are variants of the P50 so if you have one or are thinking of getting one the specifications could be a little different but will be broadly similar to this:

• Intel(R) Core(TM) i7-6820HQ CPU @ 2.70GHz (5433.79 bogomips in Linux)
• 32GB DDR4 2133MHz
• Samsung MZNLN512 (PM871) 512GB SSD
• 15.6" 1920 x 1080 IPS (non-touch)
• 6 Cell Battery
• Wireless A/C
• NVIDIA Quadro M1000M 4 GB
• Front Facing Web Cam, Mini Display Port, HDMI Out, Headphone, 4x USB3, Smart Card Reader, GBit Ethernet, Thunderbold, Fingerprint Reader

So looking at those and comparing in more detail to what I had before it seems my gut feeling was pretty good.  The CPU benchmarks are more-or-less exactly the same and certainly within tolerances of error as well as other performance increases that will effect the benchmarks such as the memory clock speed.  Here's the comparison between the W530 CPU and the P50 CPU:

The same can't be said of the GPU benchmarks though so it looks like GPUs are continuing to gain in power even when CPU speed increases have run out of steam:

Those of you that know me well will know I like Linux.  Don't get me wrong, there's a lot wrong with it and the community can be a pretty harsh place where more or less everyone has an opinion they think is the right one.  I don't get a lot of chance to contribute for various reasons but earlier this year I was (finally) accepted to be a package maintainer for the Fedora project.

Since I like Linux I do tend to use it on the desktop both at home and at work.  I do more or less everything with Linux and Open Source software including photo editing with GIMP.  It bugged me that Fedora ship a library called lensfun which is a library of lens correction data but the only piece of software using it within Fedora was Digikam.  Preferring GIMP I decided to set about packaging and supporting gimp-lensfun for Fedora.

Becoming a Fedora Package Maintainer is a well documented process as there are joining instructions and package review guidelines for the packaging guidelines.  Whilst well documented, there's a heck of a lot of stuff you have to read through and comply with before you can submit your first package review request.  This is further complicated by not yet having any reputation within the Fedora community and so you have to build this up in other ways before your package will be recognised and one of the senior community members agrees to sponsor you as a package maintainer.

I eventually raised my first package review request for gimp-lensfun in April 2013.  Over a period of a few weeks people throw rocks at what you've done according to the various guidelines that you either didn't see or forgot about.  This is actually really good and helpful as it ensures quality and consistency between all the new packages being accepted into Fedora.

What I wasn't prepared for was the length of the wait.  I know this isn't an earth shattering change to Fedora but it took me over 2 years to get noticed enough for my package to be accepted and for me to be sponsored as a Fedora packager.  I think I'd probably still be waiting now but I bugged a few people on IRC to point out my review request had been sitting there for so long.

Finally! My first package was released into the wild for Fedora 21 and 22 and I've been given the chance to give just a little back to the community.

I recently had the need to Wi-Fi enable a Raspberry Pi and so bought a D-Link DWA-131 Wireless USB Adapter.  I knew from something I'd read that it was a bit of a gamble in terms of whether it would be supported by the Pi under Raspian.  It turns out there are currently 3 revs of this adapter with different chipsets in each.  The one I got was the latest E1 version identified with the USB Device ID 2001:3319 that requires the realtek 8192eu driver.

Here's how to get it working under the September 2015 Raspian Jessie running Kernel 4.1.7+ for which I found some similar instructions a helpful starter:

1.  Get up to date and ready for compilation

sudo apt-get update
sudo apt-get upgrade
sudo apt-get install build-essential git


2. Grab the Driver Source

git clone https://github.com/romcyncynatus/rtl8192eu.git

or from

http://support.dlink.com.au/download/download.aspx?product=DWA-131


3. Patch the driver source for Kernel 4.x

cd rtl8192eu
Apply the following patch to rtw_android.c

diff --git a/os_dep/linux/rtw_android.c b/os_dep/linux/rtw_android.c
index 40ddf07..f7c496e 100755
--- a/os_dep/linux/rtw_android.c
+++ b/os_dep/linux/rtw_android.c
@@ -342,7 +342,11 @@ int rtw_android_cmdstr_to_num(char *cmdstr)
 {
        int cmd_num;
        for(cmd_num=0 ; cmd_num<ANDROID_WIFI_CMD_MAX; cmd_num++)
+#if (LINUX_VERSION_CODE >= KERNEL_VERSION(4,0,0))
+               if(0 == strncasecmp(cmdstr , android_wifi_cmd_str[cmd_num], strlen(android_wifi_cmd_str[cmd_num])) )
+#else
                if(0 == strnicmp(cmdstr , android_wifi_cmd_str[cmd_num], strlen(android_wifi_cmd_str[cmd_num])) )
+#endif
                        break;

        return cmd_num;


4. Grab the rpi-source tool (to download the Pi kernel source)

wget https://raw.githubusercontent.com/notro/rpi-source/master/rpi-source 
chmod +x rpi-source
sudo mv rpi-source   /usr/bin/
sudo rpi-source -q --tag-update


5. Install the Pi kernel

sudo rpi-source --skip-gcc


6. Build and install the driver

make ARCH=arm
sudo make ARCH=arm install
sudo bash -c 'echo "options 8192eu rtw_power_mgnt=0 rtw_enusbss=0" > /etc/modprobe.d/8192eu.conf'
modprobe 8192eu

For a recent Hack Day at work I spent some time working with one of my colleagues, Adrian Lee, on a little side project to see if we could detect cancer cells in a biopsy image.  We've only spent a couple of days on this so far but already the results are looking very promising with each of us working on a distinctly different part of the overall idea.

We held an open day in our department at work last month and I gave a lightening talk on the subject which you can see on YouTube:


There were a whole load of other talks given on the day that can be seen in the summary blog post over on the ETS (Emerging Technology Services) site.

A slight departure from my usual sort of posts but these are "my notes" so what the heck.

Last Christmas I treated myself (or strictly speaking was treated to) a new snooker cue.  I've always dabbled with snooker, not particularly good, but I can do enough to get by.  My old cue (18th birthday present) was getting a bit tired.  I decided to go with a really nice English make, Peradon, from Liverpool.  They are reasonably priced but the real treat is the quality of the craftsmanship and since I'm quite keen on making things from wood I really appreciate that side of the cue as much as anything else - it's clearly one that's far above the level to which I actually play the game.  I eventually settled on the Ascot ¾ cue.

With such a nice piece of wood I was surprised to see a complete lack of advice on how to care for and maintain it.  I wrote to Peradon for some help and what follows is their advice, and hence the reason for keeping it on my blog so I'll stand a chance of finding it again in the future...

The method is quite simple:

1. Rub down with a very fine steel wool (I use Liberon 0000) and wipe away any residue
2. Apply raw linseed oil (I use Liberon Raw Linseed Oil) with a lint free cloth and leave for 20-30 minutes
3. Buff the cue with a lint free cloth
4. Repeat if necessary (you can also heat or dilute the linseed oil for multiple coats)

It seems to work very well.  Peradon recommended I do this every couple of weeks which seems to be to be rather on the excessive side so I'll probably opt for "every now and then" and since this is the first time I've done it, it looks to be an annual event although I may do it more often now I've got all the gear.

I've written a few times in the past about various poor or laughable customer experiences I've had when dealing with technology and the companies making or retailing them.  Things usually work out well in the end of course as we're well protected as consumers here in the UK.  However, when my Nexus 4 went wrong late on Saturday night I thought I was in for another world of pain, I couldn't have been more wrong.

The short version of this post is that my phone died late on Saturday night.  On Sunday morning I raised a support call.  By Tuesday morning I had a brand new phone in my hand, delivered to my door, all under warranty.  I need not have worried it seems, Google appear to have customer support really very well sorted out.  I only wish the vast array of companies out there who are terrible to deal with would learn the lessons of having satisfied customers even when things go wrong.

The slightly longer version of the story is that my phone completely ran out of charge on Saturday and when I went to plug it in for an over night full charge before going to bed, I noticed the LED was solid red.  I've never seen this before but left it for a few hours and tried turning it on, nothing.  I left it on over night and it still wouldn't turn on the next morning.  I tried a few other things, like a separate wall outlet and another charger and cable but still all I got was a solid red light and no ability to boot the phone.

I phoned Google at 10am on a Sunday in the hope that they ran a call center on Sundays or that I would be connected to an international person who would be able to help.  I think that's probably what happened as it was an all-American experience from start to finish.  Benjamin answered the phone, asked me some questions and got me to do a couple of things with the phone, it was still dead.  He was first class, easy to understand and took ownership of the issue straight away, I can still email him directly about the problem now.

After Google support (Ben) realised the phone was dead, there was no quibble, no problem, no hoops to jump through.  He told me that he'd send the issue through to the warranty department, they would send me an email with how to order a new phone and when I receive it I should send back the old one in the same packaging (standard practice for the tech industry).  We parted company, and I'm thinking this is all a bit too easy and something will go wrong later.

A couple of hours later, I get an email from Google warranty.  It has a link to click which allows you to order a new phone at no cost (the link is only live for 24 hours).  I set about ordering the phone, it was Sunday night by this time.

8:30am Tuesday morning and Parcel Force knock at the door and deliver my new phone.  Inside the package is a return envelope, exactly as described by Ben at Google and exactly what the warranty email said would happen.  I printed the RMA note attached to the email, packaged everything up and it's ready to go back to Google - we're still less than 5 days from the start of the issue at this point.

Quite simply, brilliant.  I thought I should say so (or more so).

So would I buy a new Google hardware product again?  You bet I would.  Software updates come regularly, I'm always at the latest Android level (unlike the Transformer Prime tablet we have in the house which is stuck on 4.1 because Asus dropped support after little more than a year), I don't suffer from the Apple single vendor lock-in issue, and now to top it all off it seems the warranty support is first class.

I've been a long time fan of Tweetdeck as a piece of software for social management, certainly long before it was bought by Twitter.  I've used it everywhere via the Air Desktop app, on the web, the Chrome app and on Android too.  That is, up until now.  In their infinite wisdom Twitter appear to have realised maintaining two clients across a wide range of platforms doesn't make sense (begs the question why the bought it in the first place but I wont have that argument here) any longer and most versions of Tweetdeck are being phased out leaving only the web version or the heavily-based-on-the-web-version Chrome app.  So for the fans, what's next?  Which Twitter client should I be using on my mobile device now?  I've been assessing a bunch of them for quite a while now and I know I'm not the only one facing this decision so here's what I've learned.

First of all to put into perspective my thoughts on each client, here's a list of things I want or that I'm concerned with in an Android client:

1. I should very easily be able to get to different content streams from my main Twitter stream, my mentions, searches, lists, to my direct messages.  A column interface (similar to Tweetdeck I guess) is ideal for this with a swipe gesture to navigate between them.
2. It should support multiple Twitter accounts and switch easily between each account.
3. It should be slick, fast, nice to use and be configurable in terms of its look and feel, notifications and ideally offer per column filters.
4. It should ideally support push notifications and Twitter streaming. When notifications are pressed in the notifications bar the client should open directly to the Tweet being notified.
5. It should not contain adverts.  It doesn't matter if I have to pay for the app or pay to get rid of the adverts, paying (within reason) is fine.
6. It would preferably be free (as in open source) but I appreciate many of them are not and indeed to get the best Android clients at the moment it's less likely to be so.

So onward, to the apps...

Twitter (official client)
I guess the main critique of a post such as this is to ask what's wrong with the official client.  Well for me I find it takes ages to get to the content I read regularly.  Twitter lists take 3 taps and a scroll-down to find (for each list) so the official client fails at point 1 in my requirements list.  It doesn't do particularly well at points 2 or 3 either.  However, it does have the beefed-up mentions column they're calling Interactions that also includes favourites and new followers which I really like so I'm likely to keep it installed just for this until some other clients catch up.

Scope
Requires a special Scope account in order to login.  Screenshots appear to indicate a lack of column support so I didn't even bother signing in and got rid of it straight away.

Slices
An interesting take on reading Twitter and may once have provided lots of useful extra functionality on top of the basic Twitter.  However, with the introduction of Twitter lists there seems less point to Slices ability to carve up your social content into chunks.  The UI I found to be really rather confusing and difficult to navigate.  I quickly got rid of it after some investigation into its features.

Carbon
One of the slickest and nicest looking Twitter clients I think there is, this one really excels at want list number 3 with its fancy animations and cool look.  However, in the end it's still a button based UI that takes far too many taps to get to each piece of content you want to read.  That makes it slow and confusing to navigate so it's a sad farewell when uninstalling this one as it does implement swipe between columns but you can't configure your own columns to swipe through.

Tweet Lanes
This one does everything I want more or less out of the box with zero setup.  All I did for this app was sign in and a carousel swipe interface is loaded with all my tweets, mentions, lists, etc. and more can easily be added.  This app also appeals due to its free and open source mentality so is good for want list number 6.  However, it was left by the original developer (who no longer maintains it) somewhat feature incomplete with no notifications or sync although it does handle multiple accounts rather nicely.  Other developers have hacked in a few of these missing features here and there but there's still no driving force behind the project any more.  I wouldn't be expecting regular updates so the amount of life left in this app without someone taking up the reigns is probably quite short.  If it wasn't for the fact it's in a state of limbo I could seriously like this one but in the end lack of attention to detail such as pressing a notification in the notification bar and it merely starting the app rather than dropping you to the right place are just annoying.

Seesmic
A really popular client at one point, even if it's not now.  However, I really didn't get Seesmic at all.  It's a button based UI similar to the official Twitter client that takes lots of taps to get anywhere.  Lets count how I read a Twitter list: Profile Button -> Lists -> List Name, that's 3 which is too many in my book.  So it fails in the same way the official client fails at point 1 in my want list and doesn't do well at points 2 or 3 either.  It also has ads that I could pay to get rid of but why pay when it doesn't work very well for me anyway?

UberSocial
Not a bad column-based client that allows you to easily add the columns you want and arrange them in the order that suits.  It's easy to switch between accounts too.  The big problem with this client is that it's a battery-eater, I've no idea what it's doing but presumably polling quite a lot as when installed and in use on my phone it was one of the top reported apps in terms of battery usage where none of the other clients are anywhere to be seen.  If you want decent battery life then don't bother with this one.

TweetCaster
A not particularly easy on the eye button based app which, like other similar apps that limit the columns you're allowed and don't swipe between them, makes it rather awkward to traverse all the various parts of Twitter that a modern user might expect.  I really don't see the advantage of TweetCaster over the standard Twitter app.

The Winners Are
These three are all very good indeed and for me and my list, worth a shot.  I've not yet completely made my mind up which way I'll be going but it will definitely be one of these.

Janetter
With the default theme, this client can be a bit "oh my eyes" with its jet black text on bright white background.  Not much imagination in the colouring and shading of the interface except the bright lime green.  However, when switched to the dark theme it's much easier on the eye and you can start to look at the functionality a little more closely.  It manages multiple accounts very well, returning you to the same account you left when you start the app but making it easy to move between the two accounts - perfect for when you have a major account and other minor accounts you don't read that much.  The interface itself is the typical column/swipe style interface and the columns are easily configured, edited and arranged.  It also has another feature that is becoming more important in the management of busy columns, the idea of muting certain keywords, hashtags, user accounts or apps.  The free version has adverts built in but if this is the app I end up going for then it's a one-time £4.99 purchase to get rid of the ads and unlock a couple of other features.

HootSuite
Really easy to use from the off and has a nice separation of accounts that allow you to read content from any particular account with ease.  Accounts are separated so you can only scroll through the columns for a particular account that's active.  However, switching between accounts feels a little awkward to me as you have to remember how to navigate back to the main start page which isn't done using the most obvious (and normal for Android) method of clicking the button in the title bar.  Other than that, once you've got an account selected it's really quite nice to browse through all the different content and with no ads either, for free.  If you want more than a certain number of accounts (I'm not sure how many) or you want to unlock some particular features (that I've not found the need for) then you need to pay a fairly staggering $9.99 per month to use the pro version of the app.  That sum plus the features you get in the paid version clearly indicate HootSuite is aiming to make money from commercial users of Twitter where lots of different people might be maintaining lots of different accounts, a marketing department perhaps.  Because of that the free version is really good, as I've said, but I do wonder if one of the other two of my favourite apps will win out with a slicker user experience overall.

Plume

Enough time has passed since I undertook the Stanford University Natural Language Processing Course for me to forget just how much hard work it was for me to start all over again.  This year I decided to have a go at the coursera Machine Learning Course.

Unlike the 12 week NLP course last year which estimated 10 hours a week and turned out to be more like 15-20 hours a week, this course was much more realistic in estimation at 10 weeks of 8 hours.  I think I more or less hit the mark on that point spending about 1 day every week for the past 10 weeks studying machine learning - so around half the time required for the NLP course.

The course was written and presented by Andrew Ng who seems to be rather prolific and somewhat of an academic star in his fields of machine learning and artificial intelligence.  He is one of the co-founders of the coursera site which along with their main rival, Udacity, have brought about the popular rise of Massive Open Online Learning.

The Machine Learning Course followed the same format as the NLP course from last year which I can only assume is the standard coursera format, at least for technical courses anyway.  Each week there were 1 or two main topic areas to study which were presented in a series of videos featuring Andrew talking through a set of slides on which he's able to hand write notes for demonstration purposes, just as if you're sitting in a real lecture hall at university.  To check your understanding of the content of the videos there are questions which must be answered on each topic against which you're graded.  The second main component each week is a programming exercise which for the Machine Learning Course must be completed in Octave - so yet another programming language to add to your list.  Achieving a mark of 80% or above across all the questions and programming exercises results in a course pass.  I appear to have done that with relative ease for this course.

The 18 topics covered were:

• Introduction
• Linear Regression with One Variable
• Linear Algebra Review
• Linear Regression with Multiple Variables
• Octave Tutorial
• Logistic Regression
• Regularisation
• Neural Networks Representation
• Neural Networks Learning
• Advice for Applying Machine Learning
• Machine Learning System Design
• Support Vector Machines
• Clustering
• Dimensionality Reduction
• Anomaly Detection
• Recommender Systems
• Large Scale Machine Learning
• Application Example Photo OCR

The course served as a good revision of some maths I haven't used in quite some time, lots of Linear Algebra for which you need a pretty good understanding and lots of calculus which you didn't really need to understand if all you care about is implementing the algorithms rather than working out how they're derived or proven.  Being quite maths based, the course used matrices and vectorisation very heavily rather than using the loop structures that most of us would use as a go-to framework for writing complex algorithms.  Again, this was some good revision as I've not programmed in this fashion for quite some time.  You're definitely reminded of just how efficient you can make complex tasks on modern processors if you stand back from your algorithm for a bit and work out how best to utilise the hardware (via the appropriately optimised libraries) you have.

The major thought behind the course seems to be to teach as many different algorithms as possible.  There really is a great range.  Starting of simply with linear algorithms and progressing right up to the current state-of-the-art Neural Networks and the ever fashionable map-reduce stuff.

I didn't find the course terribly difficult, I'm no expert in any of the topics but have studied enough maths not to struggle with that side of things and don't struggle with programming either.  I didn't need to use the forums or any of the other social elements offered during the course so I don't really have a feel for how others found the course.  I can certainly imagine someone finding it a real struggle if they don't have a particularly deep background in either maths or programming.

There was, as far as I can think right now, one (or maybe two depending on how you count) omission from the course.  Most of the programming exercises were heavily frameworked for you in advance, you just have to fill in the gaps.  This is great for learning the various different algorithms presented during the course but does leave a couple of areas at the end of the course you're not so confident with (aside from not really having a wide grasp of the Octave programming language).  The omission of which I speak is that of storing and bootstrapping the models you've trained with the algorithm.  All the exercises concentrated on training a model, storing it in memory, using it and as the program terminates then so your model disappears.  It would have been great to have another module on the best ways to persist models between program runs, and how to continue training (bootstrap) a model that you have already persisted.  I'll feed that thought back to Andrew when the opportunity arises over the next couple of weeks.

The problem going forward wont so much be applying what has been offered here but working out what to apply it to.  The range of problems that can be tackled with these techniques is mind-blowing, just look at the rise of analytics we're seeing in all areas of business and technology.

Overall then, a really nice introduction into the world of machine learning.  Recommended!