Spring 1999 Computer Science Seminar,
Fridays at 12 o'clock,
Aeronautics 221
Speaker | Date | Topic |
William Shoaff | January 15 | Organizational Meeting |
Michael Thomason | January 22 | The Average Availability of Multiprocessor Checkpointing Systems |
John Ellis | January 29 | Pluto: A Satellite Simulator Tool Kit |
Gary Lutchansky and Ivica Kostanic | February 5 | Automatic Frequency Planning for Wireless Communications Systems using Simulated Annealing |
Mark Lucas | February 12 | Remote Sensing Image Processing |
Chris Graham and Joe Smith | February 19 | Pushing Java to the Extreme |
Steve Atkins | February 26 | Internationalization |
Alan Jorgenson | March 5 | Breaking Any Program |
Spring Break | March 12 | No Class |
Al Hevner | March 19 | The CATCH Project: Building a Data Warehouse to Support Comprehensive Assessment for Tracking Community Health for the State of Florida. |
Jeff Winterich | March 26 | TBA |
Michael Freeman | April 2 | NASA's Intelligent Systems Program |
Christopher Paluszek | April 9 | JINI |
Vince Kovarik | April 16 | TBA |
Kevin Fox | April 23 | Information Retrieval and Visualization |
Ivica Kostanic | April 30 | Automatic Frequency Planning for Wireless Communications Systems using Simulated Annealing |
The presentation will include an overview of remote sensing image processing with some conceptual graphics showing how some of the algorithms work. We use projective geometry algorithms that are similar in many ways to some ray tracing algorithms. The tools model the error in the collection process and automatically use feature correlation to adjust the error out of the sensor parameters. Each of the Sensor parameters (x,y,z, roll, pitch, yaw, focal length) have associated error models that limit the allowable adjustment. Finally, a brief overview of our current effort in porting to Linux and sponsoring an open source development effort at http://www.remotesensing.org.
Alan R. Hevner
Information Systems and Decision Sciences
College of Business Administration
University of South Florida
Tampa, FL 33620
A systematic methodology, Comprehensive Assessment for Tracking Community Health (CATCH), for analyzing the health status of communities has been under development at the University of South Florida since the early 1990s. CATCH draws 226 health status indicators from multiple data sources and uses an innovative comparative framework and weighted evaluation criteria to produce a rank-ordered list of community health problems. CATCH has been applied successfully in many Florida counties; focusing attention on high priority health issues and measuring the impact of health expenditures on community health status outcomes. Previously performed manually, we are automating the CATCH methodology with a full-scale data warehouse, user-friendly forms and reports, and extended analysis and data mining capabilities. The automated system, CATCH(IT), will reduce the time to prepare community health status reports from months to days. In this presentation, I present the current status of the project, along with the principal research and development issues and future directions of the project.
NASA's bold missions in space exploration and aeronautics require significant advances in many areas of science and technology. One of the most areas is information technology. The information technology revolution at NASA is two-fold: first, state of the art computer technology is enabling new missions at lower cost; and second, NASA is starting to understand itself as an information technology agency: "When people think of space, they think of rocket plumes and the Space Shuttle, but the future of space is information technology. We must develop a virtual presence, in space, on planets, in aircraft and spacecraft." * Daniel S. Goldin, NASA Administrator
The Intelligent Systems (IS) Initiative is designed to begin a national strategic research program that will fulfill or exceed the NASA Administrator's vision for next generation information technology capabilities. The Initiative will achieve this vision by developing state of the art and revolutionary IS technologies, by leveraging government and university research, and by feeding maturing technologies to ongoing NASA missions and activities, to industry activities, and to other government agencies.
Information retrieval systems search and retrieve unstructured data from a collection of documents in response to user queries. This talk will present an overview of a prototype Information Retrieval system, SENTINEL, under development at Harris Corporation's Information Systems Division. SENTINEL is a fusion of multiple information retrieval technologies, integrating n-grams, a vector space model, and a neural network training rule. One of the primary advantages of SENTINEL is its 3-dimensional visualization capability that provides users with an intuitive understanding, with relevance feedback/query refinement techniques that can be better utilized, resulting in higher retrieval accuracy (precision). This talk will also highlight results obtained by SENTINEL in Text REtrieval Conference (TREC) competition conducted by NIST, and suggest areas for future research.