Student feedback

So, first course taught at Plymouth seems to have gone down well with the students. Maximum scores across the board, no negative comments, and some really nice positive comments.

• FANTASTIC LECTURES!
• It was actually Andy wills who taught us, he was BRILLIANT! Really inspiring and enthusiastic about his topic which was engaging and inspiring
• Probably my favourite lecturer of my whole uni experience. 

Top 30

To my amazement, I'm currently in the world Top 30 categorisation researchers (from a list of over 4000 authors). Nice way to end the week :-)

Incidentally, the metric is number of ISI indexed articles on the topic categorization and in the research area psychology, experimental. 31-may-2013.

Parallel computing in R

R is a free, general purpose programming language that is particularly popular for data processing and analysis (www.r-project.org). I've been using it today for Monte Carlo simulations and, having tried to optimize my code (x3 speed increase) and moved the script from my laptop to my workstation (x2 speed increase), each simulation was still going to take a few hours, and I had a lot of them to do.

That's when I decided I was going to learn how to use the snowfall package for R. This allows one to spread computations across multiple computers or, more relevant in my case, across the 8 threads of the processor in my machine. It's fairly easy to use; it took about an hour to modify my code - and I'm sure it'd take much less time now I know how. Snowfall gave close to a further x8 speed increase for the Monte Carlo simulations.

You can find a good introduction to snowfall  here

www.imbi.uni-freiburg.de/parallel/

I didn't bother with the SSH stuff mentioned in this guide and it worked just fine for me. Basically, just install the snowfall package:

library( snowfall )

, set up a cluster using sfInit,

sfInit( parallel=TRUE, cpus=8, type="SOCK" )

, use sfLapply to do anything you would do with lapply, but across all threads,

store <- sfLapply(1:10000, awoneit, numcat = ncat, nitems = nitms, np = nppts))

and finally simply the list back to a numeric vector to make calculation of means etc easy:

store <- simplify2array(store)
store <- as.numeric(store)

 Close the cluster using:

sfStop()
 

Rustling University - Interview Training

Dear Professor Turtle,

Thank you for the opportunity to participate in our online interview training. I can think of no other opportunity where I could have learned that the statement "everyone should be treated equally" was false. Apparently, by treating everyone equally, I would not provide audio format materials to a blind person. I had previously believed that equally and identically were not synonymous; now I know better.

Fortunately, I see that, as Dean of FANAS, you are making strenuous efforts to stamp out equality wherever it occurs, and I just wanted to say ... keep up the good work!

Your humble servant

Dr. David Pressed
Faculty of Non-aligned Subjects
Rustling University

Chocolate consumption and Nobel prize winning

I assume this article was written as a joke. It certainly made me laugh. Full article here

Goodbye David Routh

I went to David Routh's funeral yesterday. His death was quite sudden - I saw him over the summer and he seemed (and I think was) fine at that time. David was a much-loved figure at both the Bristol and Exeter psychology departments and he'll be sorely missed. I never knew much about his published work - I knew him as a research seminar contributor par excellence - but his most cited work was Routh (1971), which argued that transfer from short-term acoustic store to a more persistent memory store was passive rather than active.

Workload Models