## Archive for February, 2010

### mosquito-shooting laser

So this video of a mosquito-shooting laser in the article here has been making the Youtube rounds recently. This isn’t really new, is it? It was already demonstrated last year, as described in this article. I was curious about the technology that supposedly you can assemble from eBay-acquired parts, and it turns out to be kind of lame…

Demonstrating the technology recently, Dr. Kare, Mr. Myhrvold and other researchers stood below a small shelf mounted on the wall about 10 feet off the ground. On the shelf were five Maglite flashlights, a zoom lens from a 35mm camera, and the laser itself — a little black box with an assortment of small lenses and mirrors. On the floor below sat a Dell personal computer that is the laser’s brain.

To locate individual mosquitoes, light from the flashlights hits the tank across the room, creating tiny mosquito silhouettes on reflective material behind it. The zoom lens picks up the shadows and feeds the data to the computer, which controls the laser and fires it at the bug.

I’m sorry, but having a screen behind to form an image for detection is cheating and makes this much less exciting. How is this going to work in the field (cheaply) and be something more relevant than a net?

### yield curve based on yield curve

It occured to me the other day that based on certain models of the yield curve, it should make predictions about itself. It would be interesting to know how often it has been correct though.

As a start, we can convert the daily yield curve into implied short-term rates in the future. For instance, using the treasury yields as published here yesterday, we get these implied average rates over certain durations:

Suppose there is a straight road, infinitely long at both ends, located 1 unit from your starting location. Find the most efficient path to reach the road, and the worst-case total length of this path.

The trivial but wrong way is to go for 1 unit in some direction, then trace the circumference of a unit-radius circle. The road will surely be found this way, but the path length is $$1+2\pi$$, which can be improved upon.

### senate voting model graph

There was a talk today that referenced this paper by Banerjee, El Ghaoui, and d’Aspremont on obtaining sparse graphical models for parameterized distributions.

This undirected graphical model stating conditional independence relationships of senate voting behavior was shown.

If two nodes A and B are connected only through a set of nodes C, then A and B are independent, conditioned on C. Basically it says if you want to predict anything about B from A and C, then C is enough, because A won’t tell you anything more. As pretty as the graph looks, this is a rather odd visualization. Without seeing the (Ising) model parameters, especially where the edge weights are positive or negative, this graph is hard to interpret, and the conclusions in the paper are especially questionable to me. In particular, being in the middle of this graph does not necessarily imply “moderation” or “independence”, (unlike in let’s say this graph). We would expect moderates to exhibit weak dependency to either party’s large cliques. But if, for example, the edge weight between Allen and B. Nelson is a strongly negative one (which it very well may be, since the two parties are not otherwise connected via negatively weighted edges), then the graph seems to imply that how the two parties vote can largely be predicted from the votes of the likes of Allen or B. Nelson; in that sense, they are the indicators for their parties, disagreeing on exactly those party-disambiguating issues.

There is some additional funny stuff going on. According to the paper, a missing vote counts as a “no” because they only solved the problem for binary and Gaussian distributions. I also count only about 80 nodes in there, while there are 100 senators. The graph structure also seems a bit too sparse, but this may be intentional, in order to drop weak dependencies from the graph. One does wonder though, whether the results weren’t really that good without manual fudging.

Unrelatedly, this reminds me of another famous academic paper graph, the high school dating graph:

If you look carefully, there is some oddball stuff going on here, too.

### fail

Must have been a piece of work by MIT students… Windsor Street near Mass. Ave.

### employer of last resort

I’ve been reading about these “job guarantee” or “employer of last resort” theories, and they seem interesting. Basically the government provides employment at delta below the legal minimum wage for those who are unemployed, thereby absorbing excess labor into the public sector. The advantages are clear: it is certainly better than welfare and it doesn’t compete with the private sector.

Why is this? Let’s reason about it in a crude way.