What I Learned Today

I like to conduct experiments and measure things. My monthly electricity bill tells me how many kilowatts I’m consuming, but not at a very interesting or useful granularity. Which devices consume the most? Where could I make the most impact, in terms of turning things off or putting them on timers? What I really want is the equivalent of top, but reporting electricity consumption instead of CPU usage, for all currently active processes (devices).

Since no such thing exists, I instead went out and bought a Kill A Watt, which monitors all consumption of anything that is plugged (through it) into the wall. This is a nifty device; not only does it give you instantaneous consumption, but it will also record the total usage over time. The packaging contained a bit of over-selling, though:

Perfect for detecting voltage drops and brownout conditions before they damage delicate equipment.

Perfect, that is, if you’re sitting there ready to yank it out of the wall if the line quality drops below 120 V. It doesn’t have any automatic shutoff or power surge protection.

Once I got the Kill A Watt, I went around the house plugging everything I could find into it. Here are some of the highlights of what I learned:

• The largest instantaneous consumption comes from my microwave, at 1600 W.
• I confirmed that CFLs really do consume less energy than incandescent bulbs. :)
• My stereo uses about 40 W, whether playing the radio or playing a CD—and this amount increases with volume, as more power goes to the speakers. Same with the TV (a 19″ Samsung, 40 W, increases with volume).
• My laptop consumes 2 W when sleeping, 27 W awake with low load, 36 W charging (asleep), and 60 W charging (awake). My wireless router consumes 14 W.
• My front-loading high-efficiency washer uses 20 W when filling with water, 100 W when tumbling, and 460 W when spinning. The total consumption for one load is 0.14 kWh, which costs me all of 1.7 cents (not including the cost of the water).
• My gas dryer uses 750 W when first heating (and tumbling), then settles into 260 W once it’s hot. One load consumes 0.17 kWh, or 2.1 cents (not including the cost of the gas).
• Bottom line: I was surprised to realize that, based on this data, my biggest ongoing consumption might well be my dining room light fixture (2 75-W bulbs = 150 W), which has a dimmer switch and therefore isn’t amenable to regular CFLs. It might be worth the (more expensive) dimmer CFLs to address this, once the current bulbs burn out. However, my study was not comprehensive; I was unable to measure my fridge’s consumption, for example, nor do I have numbers for the oven, water heater, or air conditioner (which I know is a heavy consumer simply based on the seasonal change in my total bill). More study is merited!

Philip Torrone has posted instructions for how to convert your Kill A Watt into a Tweet-a-watt. That’s right, you can now tweet your consumption, for the edification of all. From the project description: “We feel there is a social imperative and joy in publishing one’s own daily KWH.” I’m content just sharing the preceding analysis, thanks!

Constrained art forms, like haiku or alliterative poetry or Weird Al parodies, have always intrigued me: I admire those who can create while laboring under (sometimes quite strict) limitations. Yesterday, I happened upon 100wordstories.com. Each day, they post a topic, and seven primary contributors write a story on that topic, using exactly 100 words, no more, no less. Visitors are encouraged to post their own stories.

The most recent topic was from June 19: “No one is listening.” Always up for a challenge, I posted this story:

A Furtive Caesura

My entrance is coming up in thirty seconds. I can hear the pirate’s brassy threats and Lisa’s pleading replies. I’m about to sweep in and save her from the villain. I brush at the curtain with my sword and check the timing. Twenty seconds left.

I duck away from the bright stage entrance and slip the note into her red canvas bookbag. I’m back at the curtain with three seconds to go. One deep breath, and I’m striding onto the stage, sword at the ready, howling for the pirate to let Lisa go. She’ll find out about the breakup later.

You can contribute your own story here.

(This post is also 100 words.)

Tune to the right radio frequency, and you can listen to Jupiter! Electrons passing through Jupiter’s magnetic field are accelerated and give off radio waves, a process called cyclotron radiation. The intensity varies with Jupiter’s longitude, and careful tracking of the radio waves has enabled a more precise estimate of Jupiter’s rotation period (previously estimated based on cloud features, which naturally are not stationary). NASA’s Radio Jove project encourages teachers, students, amateurs (and you) to listen in to Jupiter’s “broadcasts.” Here are examples of the two main radio burst types you might hear:

• L (long) burst from Jupiter
• S (short) burst from Jupiter

The frequency of the radio waves is proportional to the strength of the magnetic field. Jupiter’s frequency varies between 10 and 40 MHz, yielding “decametric” waves (where the wavelength is measured in tens of meters). Other planets would have different frequencies. In fact, there’s an ongoing effort to determine if we can detect known exoplanets via radio observations (with LOFAR or SKA)—and if so, then add this to the growing list of exoplanet detection techniques. As of today, we’re up to 353 exoplanets discovered… with more coming every day.

If you had to pick reference points to define a new temperature scale, what would you use? If you were Daniel Gabriel Fahrenheit, a glassblower and chemist, you picked: the equilibrium temperature of a specific brine, the temperature at which water freezes, and the temperature of the human armpit. Apparently, he used his wife as his calibration reference. The brine is interesting: a frigorific mixture of ice, water, and ammonium chloride. Frigorific indicates that the mixture goes to an equilibrium temperature no matter what the initial temperatures of the components were. Water + ice is a frigorific mixture that goes to 32 F (or 0 C).

Next, what numbers do you assign to these reference points? Fahrenheit assigned 0 F to the brine, 32 F to the ice, and 96 F to human body temperature. The seemingly arbitrary numbers arose because Fahrenheit modeled his system after the Romer scale, which assigned 0 degrees to brine and 60 degrees to boiling water, which put the freezing point of water at an awkward 7.5 degrees. Fahrenheit multiplied everything by 4, got 96 degrees for the human body, and then fudged his definition of a degree (which just means a “step”) a bit so that the freezing point of water would be exactly 64 degrees less than body temperature (so, 32 F). Why? So that his thermometers could be easily marked between those two points — 64 is a power of 2 and that means it’s easy to get equal divisions by repeatedly marking the midpoint between existing marks.

Fahrenheit published his scale in 1724. Later, the scale was revised so that there would be exactly 180 degrees between the freezing and boiling points of water (180 being a number that is divisible by a conveniently large number of numbers). This pushed the human body temperature up, on the Fahrenheit scale, to 98.6 F.

That’s all very interesting, but you have to wonder: once you’ve invented a new scale, how do you persuade others to use it? I’m wondering what kind of marketing Fahrenheit employed, other than his presentation at the Royal Society of London. Clearly, it was quite effective… until Anders Celsius came along 20 years later.

I recently discovered Google Squared, an interesting combination of web search and automated information extraction. Actually, it reminds me strongly of the strictly formatted report we had to write in 6th grade English class on frogs. You had to draw a square chart and then label the rows with different kinds of information about frogs, like how they reproduce, what kind of food they eat, and where they live. You then labeled the columns with different information sources, like “Encyclopedia Britannica”, and then you filled in each square with what source X reported about property Y. You then used this chart to write the report itself. This was supposed to teach you how to do research, in the “look up information” sense of the word.

With Google Squared, though, the system figures out what the rows should be (different examples of the category you searched on) and what the columns should be (different properties of each of the examples). It’s fascinating, although you immediately run up against the limitations of current state-of-the-art IE (Information Extraction) technology.

Exhibit A: mars spacecraft

This produces a nice collection of Mars spacecraft, with columns for “mass”, “launch vehicle”, and “launch date.” The first thing I wanted to do was sort by launch date. Unfortunately, the columns aren’t sortable. You can however add your own columns, so I tried “cost”. This looked mostly reasonable, except that “Phoenix” was cited as $350M, “Mars Phoenix Lander” was $420M, Mariner was $2.6 (dollars?), and the Spirit rover was $10,000 (if only!). However, a really neat feature is that each factoid reports its source if you hover over it, and you can click to see other candidate values as well as a confidence rating. All of the values under “cost” were rated low-confidence, even the ones that looked accurate to me.

Exhibit B: science fiction authors

This yielded a combination of books and authors, with the auto-chosen columns being “publisher”, “language”, and “Australia” (?!). Specifying “science fiction author” yields the same list of items, but with different columns: “publisher”, “ISBN”, and “language”.

Exhibit C: ballroom dance

This yielded an excellent list of ballroom dances. Unfortunately, the columns (“typical instrument”, “mainstream popular” (?), and “stylistic origins”) were almost entirely unpopulated with data. I tried to add “tempo”, but this yielded a result for tango only (33 mpm). That one could definitely use work!

In summary, I’d say it’s a very cool idea (and fun to play with), but still definitely at the beta level. Doing a good job of information extraction from unrestricted text (the Web) is a really hard task. Keep at it, Google!