Overview
In its 15th year, OSC's Summer Institute (SI) 2003 was a success for all involved: student participants, returning student helpers, OSC and Advanced Computing Center for the Arts & Design (ACCAD) staff! Everyone who participated can take credit for the great outcome of SI2003 and its rewards.
Students gained an increase in computer science knowledge, new friendships, an enhanced ability to work on a team, a unique opportunity to use state-of-the-art supercomputers, and exposure to campus life. Students left SI2003 with a greater confidence in their individual learning abilities and their ability to adapt while working and living in a new environment with new friends of similar interests.
Participants
Andi Fair Abhijeet Gummadavelli Kim Jackson Robert Jen Dallin Jensen David Kupiec |
Daniel Litt Jennifer Piepenburg Evgeniy Tkachenko Arthur Wang Marc Weil Jean Wheasler |
Projects
Students worked together in four teams on four diverse and challenging projects. Teams were comprised of a project leader (staff member who conceived and designed the project), students in the project group, a student leader (in charge of dividing project tasks), and a high school teacher. Teachers worked on the projects just like the students. Teams choose from the following projects: Mechanical Engineering, Parallel Processing, Neural Networks, and VRML/Motion Capture.
The Mechanical Engineering project consisted of modeling the stress response of cars and the impact upon their passengers (crash dummies) upon impact. The students built the cars with a finite element model with the Altair Hyperworks software package.
Click here for the animation.
The Parallel Processing project was designed mainly to teach the parallel processing language needed to split up a problem and assign different tasks to different processors. Their parallel code was run on supercomputers containing 128 and 256 separate processors. They simulated the genetic evolution of organisms using random gene mutations, mating, survival, and conflict. The parallel processing allowed simulation of 30,000 generations in just one hour.
Click here for the animation.
In its second year, the Neural Network project combined planning, computer programming, image processing, and Artificial Neural Network pattern recognition techniques. The group of three students and two teachers first were given tools they needed to complete their project: they learned the C programming language and the basic principles of Artificial Neural Networks, specifically, the mathematical equations and steps used in a pattern learning technique known as "Feed Forward Training" and those used in an error reducing algorithm known as "Back Error Propagation." The students built an application capable of pattern recognition that works in ways very similar to how neurons in the human brain interact in learning. The group wrote a program that recognized only the letters in one of the group member's name, 'T' 'o' 'n' 'y'. To verify later that the program worked, several other SI attendees provided samples of their 'T' 'o' 'n' and 'y' to be tested against the neural network trained only to recognize Tony's handwriting. To accomplish this task, the group broke into two teams; one team wrote the C code, the other took writing samples and processed the images. Once work from both teams was completed, they collaborated to train the network and test it with their samples. The project was successful since the neural network only slightly recognized others' handwriting as Tony's
Click here for animation 1.
Click here for animation 2.
The VRML / MOCAP project gave the group the opportunity to work in the high tech Motion Capture Laboratory at the Advanced Computing Center for the Arts and Design. The project team scripted a short story about a tour through a haunted house. The environment involved the exterior and interior of the house. The keyframes of the story were rigorously defined. In the MOCAP Lab one team member wore a special suit, which had 41 reflecting balls attached at critical points of the body. This one actor performed all the motions for all the characters. 14 specially designed cameras captured the action of the reflective balls. The position of the individual reflective balls was calculated and placed in virtual space. The team designed the haunted house using VRML. Other programming tools were used to put the marker positions in the house. The marker locations were then associated with a character, a skeleton, which jumped out during the tour.
Click here for the animation.
Click here to download a detailed schedule.
Photo Gallery
Click on the thumbnails for a larger image.