Friday, March 26, 2010
I had Jack take a picture of me tightening the Last Bolt. Really only the last bolt on the engine, and a false sunrise 'cause I ended up taking that plate off and reinstalling it at least five more times to try to get the clutch right.
Thursday, March 25, 2010
Classy jean jacket. Maaaybe I should get my hair cut.
Anyway... IT WORKS!
Here's a short list of what I've done to it:
Over the winter:
Rebuilt the carburetors
Took the engine off
Replaced every frozen bolt on the engine (ie every bolt) with stainless hex bolts
Replaced the piston rings
Replaced all the gaskets
Tapped out the right cylinder's exhaust stud hole
Unfroze and cleaned the oil filter
Over spring break (this week)
Put the cylinders on
Put the head on
Fixed a loose cam follower
Went to a honda dealer to get a masterlink for the cam chain cause the bastard I bought online was very obviously the wrong size
Riveted the cam chain (broke the motherfucking $80 chain tool in the process and ended up using a pair of vice grips)
Set the cam chain tension
Set the valve timing
Put the engine on the frame
Put a new clutch cable on
Went to a Honda dealer to have a new tube put in the back tire
Sealed the new gas tank (so it won't rust)
Put the carburetors on
Put new fuel hoses on
Polished the wheels and spokes
Installed the rear wheel and adjusted the brakes
Put new points on
Put a new condenser on
Installed new spark plugs
Fiddled around with the wiring for an hour 'cause I didn't realize I needed to set the points to a certain gap
Set the points
Cut the seat apart, made it two inches narrower and three inches shorter, and gorilla glued the cover back on.
Reinstalled the tachometer cable and wrapped it in red tape
Fixed the front brake cable
JB welded the exhaust stud into the cylinder.
and a lot of staring, fiddling, and cursing. The actual work that's gone into this bike probably would have taken a single afternoon, had I known what I was doing from the start.
Tuesday, March 23, 2010
Monday, March 15, 2010
I finally discovered the reason for the extremely ugly results that Mathematica seems prone to return for integrals: it makes no assumptions about the nature of your variables, and thus gives as general a result as possible (taking into account complex and negative possibilities, for instance). With the proper assumptions, it returns a very neat result:
As compared to the following, without the assumptions:
Note that the first form allows for assumptions, while the second (traditional) form doesn't seem to. I suspect that's incorrect, but I haven't figured out the syntax yet.
Thursday, March 11, 2010
Wednesday, March 10, 2010
"In machine learning, the kernel trick is a method for using a linear classifier algorithm to solve a non-linear problem by mapping the original non-linear observations into a higher-dimensional space, where the linear classifier is subsequently used; this makes a linear classification in the new space equivalent to non-linear classification in the original space.
Tuesday, March 9, 2010
I also found some Python packages (numpy and scipy) that may be useful in implementing some of the ideas I have on the subject.
So, I've got a curriculum laid out for myself, if other possibilities don't work out immediately.
We receive visual information in the form of a two dimensional matrix. Each eye's field of perception can be described with two orthogonal polar coordinates; angle and magnitude. With this information alone, all our visual concepts should be flat and two-dimensional. And yet we perceive depth. We take these streams of two dimensional information and add a third dimension; our visual concepts seem to include this dimension. We should therefore expect visual concepts to be represented as three dimensional arrays.
How is this done? Depth perception is deeply intertwined with being binocular; the combination of the information from each eye is what gives us the sense of depth (though mono-ocular people reportedly use other cues, and might provide an interesting contrast). I therefore hypothesize that there must be an area of the brain which observes activity caused by the inputs from each eye and integrates them into a third dimension, and that the transformation from two to three dimensions could be modeled mathematically.
How to test this hypothesis? The bi-hemispheric nature of the cortex suggests an experimental protocol. Since each eye communicates only with its own hemisphere of cortex, the integration of information from each eye must depend on communication between the hemispheres. The differences in simultaneous input received by each eye could perhaps be abstracted into the "depth" dimension. By what mechanism might this occur? Answering this question is the goal of this proposal.
Experimentation might begin by observing the how split-brain subjects perceive depth. If the assumptions above are true, then the severance of the corpus callosum should result in a deficit in depth-perception, perhaps similar to mono-ocular subjects. Experimental testing of this hypothesis should be relatively straightforward. [Added: its likely that this has already can be researched and that this portion could be accomplished by a literature review, for instance see this paper. Also this one, which does not support the hypothesis but perhaps lends some alternative, as well as providing copious references]
Next, comparative studies of split-brain and normal subjects could be undertaken with FMRI in order to identify what brain areas are active in depth-perception tasks. If significant differences are found, a histological study could be undertaken to identify the structures which act as inputs to the depth-perception related areas.
Identifying the way in which these structures interact would ideally result in a model of how higher-dimensional concepts are formed by abstracting from lower-order inputs. This approach could be used in studying abstractions of a fourth dimension as well: changes in input over time.
[Added: The cat paper I linked to above revealed something I didn't know: neurons from the the inside portion of the retinal feild of each eye cross to the other side of the cortex in the optic chiasm. That may shoot down my corpus callosum idea, but it opens another possibility.]
Thursday, March 4, 2010
The next version of Captain Forever has been released, and I beat it yesterday. Sadly, the screenshot I took only shows the score; I hit the shift key to do a screen grab and disengaged all my fancy kilo-modules.
Here's one from another session with the increasingly perplexed Captian Blix on my tail:
And for the win:
What a beautiful game. I wish I could examine the source code for it...
Farbs certainly defied my expectations in a most pleasing way. I had been expecting a more incremental-sort-of update, maybe with multiplayer, the addition of ships you could keep between sessions, maybe the possibility of a "home base." What he did was totally change the focus of the game. Before it was mostly about building a solid ship; piloting skills became secondary once you figured out how the game AI worked and how to exploit it.
This new game forces you to focus on piloting. Since you can only copy other ships, you have to learn to fly what would otherwise be suboptimal designs. It also goes much faster since you're not spending lots of time dragging modules around, and new enemies are thrown at you constantly.
In other news, I finally took a dive on the turn I like to take really fast on my bicycle. There was no chance of recovery; as soon as I realized something was wrong I was sprawled on the pavement. My left handlebar got stuck under the cross-beam; I imagine that I turned too sharply and the wheel caught and turned sideways. No real injury except for a couple raspberries and a twinge in my spine.
Monday, March 1, 2010
I've also just stumbled across "process algebra," which this article is claiming has the potential to do calculations that Turing machines are incapable of. I thought the whole idea of a Turing machine was that it could do any calculation whatsoever; but I suspect the trick lies in the temporal and memory constraints imposed by real world calculations. (A universal Turing machine can perform any computation, given infinite time and infinite memory).