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The Courts

Submission + - Drug testing entire cities at once

Ellis D. Tripp writes: "Researchers have developed a technique for determining what illicit drugs people might be consuming in a given area, by testing a sample from the local sewage treatment plant. As little as a teaspoonful of untreated wastewater can reveal drug use patterns in a given community. From the article:

"one fairly affluent community scored low for illicit drugs except for cocaine. Cocaine and ecstasy tended to peak on weekends and drop on weekdays, she said, while methamphetamine and prescription drugs were steady throughout the week."

Obviously, any drugs found can't be tied to any specific user, but how much longer until the drug warriors want to deploy automatic sampling units farther upstream of the sewage treatment plant, sampling sewage output from selected neighborhoods, blocks, or even individual houses?

http://www.townhall.com/news/sci-tech/2007/08/21/s cientists_drug-test_whole_cities"
Handhelds

Submission + - AT&T crippling BlackBerry for iPhone? (blackberrycool.com)

0xdeadbeef writes: BlackBerryCool got a tip that not only was AT&T removing GPS functionality from their version of the BlackBerry 8820, they're doing it so it won't show up the iPhone. While carriers crippling phones to stop them from competing with pay-per-use services is nothing new, this might be the first time they've done it to make their other products seem less diminished.
Graphics

Submission + - Algorithm That Seemlesly Patches Holes in Images (cmu.edu)

Beetle B. writes: "From the site:

'What can you do with a million images? In this paper we present a new image completion algorithm powered by a huge database of photographs gathered from the Web. The algorithm patches up holes in images by finding similar image regions in the database that are not only seamless but also semantically valid. Our chief insight is that while the space of images is effectively infinite, the space of semantically differentiable scenes is actually not that large. For many image completion tasks we are able to find similar scenes which contain image fragments that will convincingly complete the image. Our algorithm is entirely data-driven, requiring no annotations or labelling by the user. Unlike existing image completion methods, our algorithm can generate a diverse set of image completions and we allow users to select among them. We demonstrate the superiority of our algorithm over existing image completion approaches.'

English translation: The algorithm replaces arbitrarily shaped blank areas in an image with portions of images from a huge catalog in a totally seamless manner."

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