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The Architecture faculty realizes that computers are as attractive design studios because they're in other learning environments (for example lecture and seminar courses, travel studies, and in some cases at home). To be equally viable with traditional media in varied settings, the technology has to be fully portable. Therefore, the School of Architecture necessitates that students invest in a Windows-capable laptop laptop or computer and associated software as the following. Undergraduate students really should have the computers premade for required coursework at the beginning from the Fall Semester of the sophomore year. Graduate students really should have their computer available for required coursework at the beginning with their first semester.
"In the Summer of 2005," Sara continues, "we were staying in a hotel for four weeks for business. We had a small suite that had a bedroom and a little kitchen. We realized while we were there that we were extremely happy living in a smaller space. We liked knowing where Bella," their, at the time, three year old daughter, "was at all times without searching. We liked that cleaning up only took a few minutes instead of an entire afternoon. It just clicked."
A cover story in Internet Week magazine, featuring Wysopal and Zatko (a.k.a. Weld Pond and Mudge), finally blew their cover at work, but they weren't fired as they had feared. The New York Times Magazine also featured L0pht in a story, as did PBS and MTV. The hackers' boasts about being able to take down the Internet in 30 minutes — by exploiting flaws in a key Internet routing protocol called BGP — prompted mentions from Conan O'Brien and Rush Limbaugh, who called them "long-haired nerd computer hackers." These OIT algorithms have many similarities, and our investigations allowed us to construct a continuum on which they lie. During this categorization, we identified various new algorithms including stochastic layered alpha blending (SLAB), which combines stochastic transparency's consistent and (optionally) unbiased convergence with the smaller memory footprint of k-buffers. Our approach can be seen as a stratified sampling technique for stochastic transparency, generating quality better than 32× samples per pixel for roughly the cost and memory of 8× stochastic samples. As with stochastic transparency, we can exchange noise for added bias; our algorithm provides an explicit parameter to trade noise for bias. At one end, this parameter gives results identical to stochastic transparency. On the other end, the results are identical to k-buffering.
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