Weeks 7-10:

Lectures:

Mathematical Modelling in Physiology and Medicine
Computational Genomics
Uncertainty Modelling
Learning in Autonomous Systems

This post is an overview of the weeks leading up to the Christmas break. It has very much been a case of requiring all hands on deck as far as brain cells can be considered crew of the ship that is me. To extend the metaphor, there was a certain amount of mutinous expression on the part of the aforementioned crew, but, on the whole, the appropriate work seemed to get done.

Week 7 saw the start of a new unit - Mathematical Modelling in Physiology and Medicine (MMPM) - which proved to be far more interesting than originally speculated. I will post a more detailed critique of my units later in the year, and I think this will be one of the most interesting to write as it may well be an essay of conversion. The unit is entirely coursework: two reports based on analysis of a physiological model as presented in a published paper. My model is based around the way cells use Calcium.

The detail for most of my reports this year is not what I would ideally like to present, but with the high volume of graphs and the low page limit, it is difficult to get across absolutely everything you want to.

We also had to hand in an interim report for our theses in this period. I can't remember what I wrote for this since I was more focused on the work than writing something that counted for nothing, but I have included it here since it might give some insight into what it is I am doing:

Interim Report for Thesis

And Finally...

Genomics, Uncertainty and Autonomous Systems all finished in week 10. I didn't enjoy the 2nd half of Genomics anywhere near as much as the 1st, and find that I am glad it's over, although there is still the final coursework to do over Christmas. Uncertainty was very satisfactory, but I have to admit to a feeling that when the exam revision period comes around I will suddenly realise that I didn't understand as much as I thought during the lectures. I have mixed feelings about Autonomous, I think I will reserve judgement until the results are in. The 2nd coursework was handed in this week , and now there is only the January exam remaining.

Weeks 4-6:

Lectures:

Computational Genomics
Uncertainty Modelling
Learning in Autonomous Systems

Well, it's been a hectic few weeks here, and there doesn't seem signs of a let-up anytime soon, so this will not be a particularly detailed post. Autonomous Systems was a complete washout, for a number of reasons, and although I now think I could theoretically go back and solve the problem I gave myself, I am so conditioned against the program that I cannot currently face revisiting it. So, that's a task for another day. On the other hand, my Computational Genomics project was somewhat more bearable.

The report is a little sketchy due to a pitiful page limit and an over-abundance of graphs, but I hope that something useful can be gleaned from it. Essentially, it aims to show that although the Peregrine Falcon and the Rock Pigeon have evolved such that one species preys on the other, they are actually quite closely related (closer than just both being birds, obviously).

Lastly, a pre-cursor of what is to come: after a pretty awful few weeks, Friday saw a development in my project which has me both excited and petrified as to the future work. I am in the process of formalising this new result, and will upload the document when it is complete. I may say at this point that I don't necessarily expect everyone else to get as thrilled as I was, but I hope to communicate an understanding of how that feeling came about.

Watch this space...

Week 3:

Lectures:

Computational Genomics
Uncertainty Modelling
Learning in Autonomous Systems

Not the best week - Operation Recuperation was not what you'd call a roaring success - however it cannot be said that I was totally unproductive: I made a start on my coursework for Autonomous Systems and have made progress in deciphering the background to my Thesis. During this week I will endeavour to post some of this insight and to explain a little about what I've done for the aforementioned coursework. As a taster, here is a basic outline of what the work is about:

Learning in Autonomous Systems - Assignment 1: CVRP

This project is based on finding solutions to an optimisation problem called the Capacitated Vehicle Routing Problem (CVRP). The basic concept is that of a supply depot needing to find routes for its delivery vehicles which will make sure all customers receive the correct (whole number) amount of ordered goods. The 'capacitated' bit means that the vehicles can only carry a fixed amount. The optimisation bit comes from the fact that the depot wants to minimise cost and therefore requires the 'optimal' (ie shortest total route) solution. I will be working on the project from a machine learning point of view, where the aim is for the program I write to perform multiple iterations of a given algorithm to hone in on a solution which is approaching optimal. It's a while since I've done programming of this type, and I may be a little rusty on implementing algorithms like this in code form, but I will report progress here, as and when it occurs.

Week 2:

Lectures:

Computational Genomics
Uncertainty Modelling
Learning in Autonomous Systems

Most of this week was focused on assimilating as much information about the background to my Thesis - I was aware of the psychology, but now I'm getting to the good stuff: the mathematical formulation. It's taken a bit longer than I was expecting, having some sort of stomach bug in the week which gave way to a stinking head cold on Friday.

The weekend was spent trying to recuperate, hence the late update, and although I still feel deadly, the plan this week is to model some of the theory in the background paper to properly visualise my starting point. Hopefully I'll have some useful plots and notes soon which will help to explain the principle behind my main project for the year.

This on top of the coursework I've been given for Autonomous Systems - watch this space for details on that...

Week 1:

Lectures:

Computational Genomics;
Uncertainty Modelling for Intelligent Systems;
Learning in Autonomous Systems.

This week consisted mainly of introductory lectures explaining the outline of the units. Not a lot to talk about, but it's looking good so far: interesting with the potential for some hair-raising complexity and all-night coursework blitzes.

On the Thesis front, I have been provided with some background reading material so I expect to be able to explain the foundations on which my work will be based in the next week or so.

A Taste of What's to Come

If you've stumbled across this page and are wondering why there's nothing here yet, there's a pretty simple explanation. I haven't written anything yet.

This site is designed to chronicle my final year at University (See Who Am I; What Is This?), and since term has not yet begun, I have nothing to chronicle. I simply wanted the infrastructure in place to simply begin slotting in posts at the appropriate time, without the hassle of starting from scratch. Bear with me, term starts at the beginning of October, and I may then have something to report.

Until then, here is a list of the units I will be studying this year:

Advanced Nonlinear Dynamics and Chaos

Computational Genomics and Bioinformatics Algorithms

Control Theory

Learning in Autonomous Systems

Mathematical Modelling and Physiology in Medicine

Pattern Analysis and Statistical Learning

Sustainable Systems

Uncertainty Modelling for Intelligent Systems.

Oh, and my Thesis (quite literally, my Masterpiece):

Can You Imagine a Chocolate Bicycle? A Prototype Theory of Category Combination.

Well, I hope that that whetted your appetite, but I suspect the urge to run for the hills is quite strong at the minute - it is with me. I would love to try and show you what this course means to me and how these topics can affect everyone's lives, so do think about checking back in a month or two, and take a look at my world.