December 23rd, 2013

A while ago, I wrote an emacs ‘reading mode’. It highlights a single sentence at a time, fading the rest of the text into a gentle grey, and a keypress moves onto the next sentence. It retains the familiarity and consistency of normal text layout, but provides additional cues about the extent of the current sentence.

Tonight, I played with the idea of including smarter parsing into this reading mode. The Stanford Parser parses english sentences. It tells you about the grammatical structure (noun phrases, verb phrases, etc) and dependencies between words. This is just about enough to do what I had in mind – a “superfluous word” highlighter. The whole world is absolutely packed full of so many documents with wholly unnecessary words. Ideally, I’d like to just delete the pointless words. But it’s rare for a word to be completely devoid of semantic meaning. So, my compromise is just to highlight those decorative words – adjectival and adverbial modifiers – which are commonly guilty.

Here’s some examples, not completely perfect, but useful nonetheless:

I REALLY want some SUPER TASTY chocolate.
The system has been VERY CAREFULLY designed, and will cope admirably with all 
  CONCEIVABLE combinations of circumstances.
I wanted to leave my SMALL pond and see HOW I'd fare in a BIG one, with some 
  of the BEST developers in the world.
You define HOW you want your data to be structured ONCE, THEN you can 
  use SPECIAL GENERATED source code to EASILY write and read your STRUCTURED data.


September 28th, 2013

“Wald applied his statistical skills in World War II to the problem of bomber losses to enemy fire. A study had been made of the damage to returning aircraft and it had been proposed that armor be added to those areas that showed the most damage. Wald’s unique insight was that the holes from flak and bullets on the bombers that did return represented the areas where they were able to take damage. The data showed that there were similar patches on each returning bomber where there was no damage from enemy fire, leading Wald to conclude that these patches were the weak spots that led to the loss of a plane if hit, and that must be reinforced.”



September 14th, 2013

I was mucking about in javascript, simulating geostationary satellites orbiting around the earth. Then I started thinking about simulating moon missions – ie. properly simulating the thrust of (say) the Saturn 5 rocket at various stages of the launch, how the fuel mass decreased and so resulted in increasing acceleration at fixed thrust. There’s plenty of data available about when they lit engines and started roll programmes for the Apollo missions.

Anyhow, this lead me to realise that I’m too earth-centric in my coordinate systems. I need to know where the moon was in 1969 when Apollo 11 took off. Actually, I’m wasn’t even sure which coordinate system you’d measure that in. WGS84, used by GPS sysems, ain’t so much use if you’re flying to the moon! The ICRF is what you need.

It also made me think about a location-a-pedia. Ie. something which tells you where objects were at a certain time. Where was the moon at the instant when Apollo 11 took off? Where was it when Apollo 11 landed? Perhaps for flying sims, you might have historical data about where different commercial flights were at different times. For space sims, you need to know where the objects of the solar system were. Newton’s laws will tell you how they move, but you need a starting point.

(Update: Omg, it’s 2013 and I just used a telnet interface to an online system).

Maybe in 20 years, all objects will be reporting their coordinates (in some galactic coordinate system) to a central database. That way, if you lose your keys, you’d have an easy way to find them. Even if you were on Mars.

July 17th, 2013

I’ve read a lot of engineering history books in my time, but rarely have they evoked Mills & Boon so strongly as this gem:

“He realized a machine to draw the wire from the reel, cut and shape it, pierce the holes in the leather, and place the staples in the sheet; but the forming of the second and final bend in the teeth was a problem that vexed his very soul as one of insurmountable difficulty. Hope was followed by despair, and the most glorious prize of all that would crown his machine with perfection, hovered around him like a phantom, enticing him on to further exertion, yet eluding his grasp. He did not lack, however, the support of encouraging friends, who believed in his ultimate success if he would only persevere believingly and courageously. To the cheerful assurances of his friends may be attributed much of his resolution and unremitting ardor in forcing his scheme to a successful finality.

While in this maze of doubt, his brain hot with feverish uncertainty, his thoughts dwelling vaguely on a theory of possibilities, his exhausted strength permitted the solution to come to him in a dream. Such is the testimony of some, and, whether it be true or not, it is not outside a common experience of many, to retire at night with a mind confused and mystified by unabated application to a single idea, and wake up in the morning with it fresh and clear with the mystery revealed and elucidated, as if it were the work of a vision. He arose at early dawn with a heart full of emotion, and a face beaming with joy, and eagerly sought his workshop to place on his machine the last piece of mechanism that was to transform it into a magnificent consummation”

(from the 1885 book, History of the American card-clothing industry)

Myron Tribus

February 17th, 2013

“If you try to improve the performance of a system of people, machines, and procedures by setting numerical goals for the improvement of individual parts of the system, the system will defeat your efforts and you will pay a price where you least expect it.”. – Myron Tribus

Myron Tribus was the source of the anecdote about why Shannon chose to name his measure of information after the thermodynamic concept of entropy. Furthermore, Shannon expressed to him “.. misgivings about using his definition of entropy for applications beyond communication channels”.

I don’t know if Shannon knew much about thermodynamics or not – he was an engineer and mathematician. I also don’t know whether Von Neumann (who certainly did know physics) suggested the name “entropy” based only on the superficial syntactic similarity between Shannon’s sum(pi log(pi)) and Boltzmann’s -Nk sum(pi log(pi)) .. or whether perhaps he grokked a deeper connection like what ET Jaynes later tried to pursue.