UIUC CS Students Create Mobile Learning Apps for Android

Students in professor Klara Nahrstedt’s CS 425 Distributed Systems course had a unique opportunity this semester.  Test their course knowledge by creating distributed applications to help other undergraduate students use them in other classes.

Students in the CS 425 class spent their semester applying their skills in distributed systems to the task of learning to develop distributed applications on top of the Google Android development platform.  The Google phones purchase was sponsored by the Vodafone educational grant. The semester culminated in a head-to-head competition, sponsored by Qualcomm and Vodafone, to see who could create the best learning-focused application.
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Cazoodle Makes it Easy to Find Stuff on the Web; Unveils Its Shopping Search at DEMOfall 09

SAN DIEGO, Sept. 22 /PRNewswire/ – Shoppers no longer need to visit so many websites to find the electronics of their dreams. Cazoodle Shopping Search is the first and only organic shopping search service that simultaneously provides comprehensive as well as precise product information. The first launch is for consumer electronic products including laptop and desktop computer, digital camera and camcorder, printer, television, mp3 player, etc. Read more

Y Combinator Funded Start Up From Illinois: Mobile Mix of Yelp, Foursquare, and Digg

Three students from the University of Illinois have launched Y Combinator funded GraffitiGeo, a start up focused on user-generated reviews. The mobile application is like a mash up of review site Yelp, social network Foursquare, and social news site Digg. The Digg-like functionality is easiest to use: like a restaurant? Just vote it up. You can optionally leave comments about your experience, but co-founder Jared Tame says the experience is far simpler than Yelp’s traditional review process where users typically write several paragraphs. Read more

Illinois Researchers Work Results in Face Recognition Breakthrough

Illinois Professor Yi Ma and his students have developed a facial-recognition algorithm that can identify an individual even if the image is corrupted or occluded. The algorithm works with 90% to 95% accuracy when the nose, eyes or mouth is obscured, either by disguise or a corrupted image.   Kirk L. Kroeker reports for Communications of the ACM on the work.  Link here

NCSA teams up with U.S. Army to devise smart Web crawling system

By Erika Strebel

The surface Web is a vast ocean of millions of pages. People search the surface Web every day by putting keywords into search engines like Google or Yahoo! Search.  But when an Army trainer needs to quickly find information to put together a training session, a simple keyword search isn’t always the most efficient way to navigate the surface Web. Read more

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