Archive for the ‘Science’ Category

Urban birds

Wednesday, 21 August, 2013

Friendly lorikeetI was walking home from the railway station after work today and I noticed an ibis and some parrots flying overhead. And I figured it might be interesting to list what birds I typically see in my daily life here in Sydney.

  • Pigeons. Yeah, they’re all over the place, alas.
  • Noisy miner. This is easily the second most common bird I see. And the most common one I hear – they’re not called “noisy” for nothing. They constantly chatter away as they flit around gardens and parks. The noise isn’t loud or offensive, just prolific.
  • Australian white ibis. Probably the next most common bird I encounter. I often see them flying relatively high and for longish distances across the city. If you look up at the sky much in Sydney, you’ll see these birds travelling from suburb to suburb. I often see them out the window of my office building too.
  • Rainbow lorikeet. Common around my home, since there are lots of gardens and some bushland in a nearby park. Sometimes they come and sit on my balcony (pictured). Some people feed them, but you need to be careful not to give them food that is bad for them.
  • Pied currawong. Usually just called currawongs, these are the only one of three currawong species commonly found in Sydney. These can be loud birds, with a very distinctive crow-like cry.
  • Berry Island Lapwing

  • Australian magpie. Unrelated to European magpies, these are larger crow-like birds. Their most notable thing is that they attack humans during nesting season (spring). A few people are hospitalised every year with wounds caused by magpie attacks; sometimes people lose eyes. The best way to prevent attacks is to look at them – they attack from behind. Wearing false eyes on the back of your head/hat also helps.
  • Masked lapwing (pictured). Pretty common near water and also in open grassy areas, looking for worms and grubs in the grass.
  • Silver gull. Everywhere near salt water. These are the squabbling pigeons of the shoreline. Also seen inland.
  • Sulphur-crested cockatoo. I see these in the parkland around my home.
  • House sparrow. Introduced from Europe and now common.

The above birds are common enough that I see them virtually every week. The following ones I see less often.
Laughing Kookaburra

  • Crested pigeon. These are much nicer birds than the more common feral pigeons. They have a comical topknot spike of feathers and make a squeaking/whistling sound as they fly. It’s caused by the air moving across their flapping wings.
  • Australian pelican. These are common near the ocean and sea lagoons, but I don’t travel out to the ocean every week, so I only see them occasionally.
  • Australian raven. Sometimes difficult to tell from a currawong from a distance. These are a bit less common.
  • Little pied cormorant. Fairly easy to spot on the harbour, rivers, and near the sea.
  • Laughing kookaburra (pictured from my living room window). I see one of these maybe a couple of times a month. Or hear them – they’re very loud.
  • Galah. These can be seen occasionally in large flocks, either flying across Sydney, or settled into grassy areas to graze on seeds. There’s a flock that I see occasionally in the park areas near my work.
  • White-faced heron. I never used to notice these, but since I’ve been keeping an eye out for birds, I see them moderately often, all over Sydney.
  • Pacific black duck. Seen near waterways and, well, everywhere ducks are seen.
  • Australian wood duck. Ditto, but a bit less common.
  • King parrot. I’ve seen these a few times in the park near my home.
  • Channel-billed cuckoo. These are more often heard than seen. They make loud raucous calls.

These birds I see a few times a month to a few times a year. There are other birds that I see occasionally or rarely within Sydney as well, such as: black swan, willy wagtail, purple swamphen, Australian brushturkey, superb lyrebird. Occasionally I’ll spot a raptor of some sort, a falcon or small eagle, flying far overhead. The coolest bird I’ve ever seen in the city is a powerful owl, perched on a power line as I was walking home from a restaurant one night.

I’m sure I’m missing some species, probably including some fairly common ones that I just don’t know the names of yet.

What I’m working on

Friday, 18 January, 2013

I work for Canon Information Systems Research Australia, a subsidiary R&D company of Canon. It’s usually very difficult for me to say much about what I’m working on beyond “stuff to do with optics and cameras”, because of the need to keep our current research within the corporation. Once the work is patented and published, it becomes more public and I can point and say, “I did that” – but that’s two years or more after I actually did the work.

But I just found some stuff on Canon’s own public website that will give you an idea of what I’m working on right now. This. I’m working on this. Not all of it, just some aspects. But yeah, my work right now feeds directly into this, and more specifically the last section, about health management and safety.

The December without a summer

Monday, 12 December, 2011

Sydney weather, December 2011It’s supposed to be summer here, but you wouldn’t know it. Here’s a graph of Sydney’s weather for December so far, including official observations and the current 7-day forecast.

Parrots!

Wednesday, 5 October, 2011

Rainbow LorikeetBirdie Num NumWalking home from the train station this afternoon, I saw a colourful parrot fly right through my eyeline and up into a nearby tree. I figured it was just a rainbow lorikeet (left), which are plentiful around our home. We have several species of parrots that are common around here. The lorikeets are all over the place, but we also get sulphur-crested cockatoos and galahs fairly often.

So anyway, this lorikeet flew right past… Only it wasn’t a lorikeet! I had to look twice at it when it was perched in the tree, and I realised it was too big and the colour… It was a king parrot (right)! This is only the second time I’ve seen a king parrot within earshot of home, in almost 15 years living here. What’s more, as I was standing gawping and admiring the bird, another one flew past. Cool.

Origami notes

Friday, 26 August, 2011

We had a brilliant lunchtime seminar by a guest speaker at work today. She talked about origami.

I wasn’t sure what to expect – if it’d just be demos of paper folding, or cool models that people had made, or what. There were both of these things, but there was much more. The speaker is doing a Ph.D. in statistics, so has a strong mathematical background. She started by showing some examples of origami with a slide presentation. But then… she went to the whiteboard…

She presented origami as a composition of two functions: a first one-to-one (and thus bijective) mapping from a flat sheet of paper to a 3-dimensional folded version of that sheet of paper – specifically a folded version which produces a number of points that can be used as the basis of extremities of a model (for example, animal limbs, fingers, horns, etc); and a second function mapping that 3-dimensional structure to a tree diagram with nodes at end points and junctions. The second mapping doesn’t preserve point correspondences or distances, but (and she proved this as a theorem) points on the tree diagram corresponding to points on the sheet of paper are separated by a distance less than or equal to their separation on the paper.

The upshot of this is that you can sketch a three-dimensional stick figure of anything you like, with correctly proportioned stick lengths; then map that on to a flat sheet of paper such that you produce a tree with nodes and branches in analogous positions such that the distances between them are equal to or greater than the corresponding distances in the stick figure; then from there you can apply a deterministic algorithm to figure out the arrangement of mountain and valley folds to produce the points at the nodes. There are programs that can do this and solve the fold pattern for any desired stick figure in a few minutes.

The result is a map of exactly how to fold the sheet of paper to produce a 3-D model that resembles your stick figure, with the correct number, arrangement, and lengths of all the extremities. From there it’s a simple matter of subtly modifying the shapes of the points with additional folds to produce an accurate model of your desired shape. She showed an example of a buck deer with four legs, a tail, a head with a nose, and two antlers, each with 4 distinct points. The resulting tree has 14 leaf nodes, and produces a complex fold map, but it’s perfectly doable, and the resulting origami model looked amazing.

I was utterly blown away. I always figured origami artists created new models by trial and error and months of hard work. But apparently you can do it with a stick figure sketch and a simple piece of mathematical computer code, in a few minutes. I should stress this only produces the basic “stick figure” form, and the subtle shaping of a 14-pointed piece of folded paper into a realistic deer shape still takes artistic talent, but still, I was amazed that the hard structural part of the work was so tractable and solvable by a beautiful application of mathematics. It shows how mathematics can be applied to surprising fields and come up with usable models and solvable answers for problems that seem unapproachable any other way. Very nice stuff.

Getting a handle on parameter space

Wednesday, 20 July, 2011

I’m exploring a bunch of different possibilities at work, looking for an optimal set of parameters for an image processing problem. For this algorithm I’m looking at, there are three independent tunable parameters, so for each combination of parameters I’m generating a sample output. This gives me a data cube, with each of the three axes roughly 20 elements in length to explore the space adequately.

Now, at each point in this data cube, the output is an image. With about 10 megapixels.

And each pixel of the image contains not a single value (e.g. a greyscale image), not three values (a full colour image), but six different data values (an actual greyscale “image”, plus a 2D alignment vector at each point, plus 3 separate measures of confidence values in those).

And this is for one of my potential competing algorithms, of which I have six different ones to try. And every time we stop to think about it a bit, we come up with new algorithms, or other possible parameter tweaks that might improve the older ones.

Leviathan

Tuesday, 14 June, 2011

There’s something wonderful about cracking open a new book for the first time, after finishing the previous one. A sense of expectation, the feeling of new knowledge about to be uncovered.

I’ve just finished The Age of Wonder, by Richard Holmes, a survey of British science in the Romantic era, beginning around 1769 and ending around 1835, told in biographical snippets of the pre-eminent natural philosophers of the day. Wonderful book; I didn’t want it to end. I’m now seeking a book in a similar style that will carry me onwards from 1835. This book was shortlisted for the BBC Samuel Johnson Prize for Non-Fiction in 2009.

But I’ve just started Leviathan by Philip Hoare, a book about whales, which won the BBC Samuel Johnson Prize for Non-Fiction in 2009. So yeah, I’m expecting great things. I’m sure it won’t disappoint.

The thrill of opening to the first page and reading the first few words was spine-tingling enough to prompt this blog post. And that’s really all I have to say.

I forgot to mention…

Wednesday, 1 June, 2011

Tartan patternMy first professional academic publication in 16 years:

Measurement of the lens optical transfer function using a tartan pattern.

We’ve actually paid a fee to have this paper published as open access, so anyone can view the full paper, but it still seems to be behind a pay wall. Don’t pay for it – it should hopefully be released soon.

Science and Imagination

Thursday, 19 May, 2011

The perception of truth is almost as simple a feeling as the perception of beauty; and the genius of Newton, of Shakespeare, of Michael Angelo, and of Handel, are not very remote in character from each other. Imagination, as well as the reason, is necessary to perfection in the philosophic mind. A rapidity of combination, a power of perceiving analogies, and of comparing them by facts, is the creative source of discovery. Discrimination and delicacy of sensation, so important in physical research, are other words for taste; and love of nature is the same passion, as the love of the magnificent, the sublime, and the beautiful.

– Humphry Davy, chemist and poet, 1807.

Science for the win

Thursday, 24 February, 2011

I’m just watching Who Wants to be a Millionaire, and one of the later questions was:

How much larger is the Earth’s diameter than the Moon’s? A: 2.5; B: 3.7; C: 5.8; D: 9.2

I blanked briefly. Despite being a science question, and specifically an astronomy question, I had no idea what the correct answer was.

But then I started thinking: can I possibly figure it out? What facts do I know about the Earth and the Moon that I can use? My thoughts turned to eclipses – if I could remember the size of the Sun and the radius of the Moon’s orbit, I could calculate the size of the Moon from similar triangles, and I know the size of the Earth…

But alas I don’t know the size of the Sun offhand. What else do I know about the Moon? It has weaker gravity than Earth… in fact if I remember rightly it has about 1/7 the gravity of Earth. And gravity is proportional to the mass, and inversely proportional to the square of the radius (thank you Isaac Newton). I have no idea what the masses of the Earth and Moon are, but I know they must both have similar densities, being primarily made of rock, so the masses would be proportional to the volumes, and the mass of a sphere is proportional to the cube of the diameter. This means the relative strength of gravity on the surfaces of the Earth and Moon must be roughly in the same proportion as their radii to the power of 3/2.

So if I take 7, and square it to get 49, then take the cube root of 49… let’s see, 4 cubed is 64, so the cube root of 49 must be a bit less than 4… scan the options… the answer must be 3.7. B!

I went through all of this in my head in the 30 seconds that the contestant had to answer the question, and reached my answer before the contestant locked in what was nothing more than a random guess. (She guessed C: 5.8.)

The answer? 3.7. Science wins!

EDIT: Oops! So embarrassing! The moon has a gravity 1/6 that of Earth, not 1/7. And the correct thing to do is divide the radius cubed by the radius squared, leaving the surface gravity varying proportionally to the radius, not the radius to the power of 3/2, assuming the densities are the same. But it also turns out the Earth and Moon have significantly different densities (5.5 compared to 3.3), and multiplying 6 by the ratio 3.3/5.5 gives 3.6, close enough to the answer of 3.7.

In other words, I stuffed up on 3 different facts, and produced the correct answer only by a happy cancellation of errors. Still, I did it in under 30 seconds and got the right answer, so I’m still claiming the money! (Somewhat sheepishly.)