I got my first migraine in high school. A blinding aura exploded in my vision, the entire left side of my body went numb, and I couldn't talk. I was afraid I was having a stroke. It took several years for me to put a name to the headaches. Since then, a migraine has knocked me out for a few hours every few months.
Something changed recently. I am currently recovering from my third migraine in a week and a half. Before this latest string of occurrences, it had been about a month. Before that, three months. I hope this is not the beginning of a trend.
Coincidentally, the most recent Scientific American published . I was particularly interested to learn that changes in blood flow are now viewed as an effect of a migraine rather than a cause:
It turns out that in many the pain is preceded not by a decrease in blood flow but by an increase—an increase of about 300 percent. During the headache itself, though, blood flow is not increased; in fact, circulation appears normal or even reduced.
...
The phases of hyperexcitability followed by inhibition that characterize cortical spreading depression can explain the changes in blood flow that have been documented to occur before migraine pain sets in. When neurons are active and firing, they require a great deal of energy and, thus, blood—just what investigators see during brain scans of patients experiencing aura. But afterward, during inhibition, the quiet neurons need less blood.
I watched Champaign and Urbana's Independence Day fireworks from on top of a tall parking garage. It could see several shows at once, but they lost a lot of their impact since I could not feel the explosions.
Afterward, I took some long-exposure pictures of the Carle Hospital campus and the progressing state of the 309 Green and 310 Burnham highrises.
And since I am posting night shots, I'll (re)post my favorite photo. It is a panorama of Purdue's Loeb Fountain, taken from the roof of .
My short paper entitled got accepted to . The paper describes some of the research I did at Agitar last summer.
Automatic white-box test generation is a challenging problem. Many existing tools rely on complex code analyses and heuristics. As a result, structural features of an input program may impact tool effectiveness in ways that tool users and designers may not expect or understand.
We develop a technique that uses structural program metrics to predict the test coverage achieved by three automatic test generation tools. We use coverage and structural metrics extracted from 11 software projects to train several decision tree classifiers. Our experiments show that these classifiers can predict high or low coverage with success rates of 82% to 94%.
I posted the and other supporting information at the paper's .
Unfortunately, Agitar despite having a mature product, many talented engineers, and a strong involvement in research. As I understand it, the company had difficulty getting developers to adopt their software, and the recent economic troubles were too much for it. Without Agitar to support a trip, it is unlikely that I will be able to go to Italy to present the paper in person. I am nevertheless very pleased with the work and am glad that it will get wider exposure.
