Mining Environment
Research Projects
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Information Technology and Systems Center The University of Alabama in Huntsville
Huntsville, AL 35899 (256) 824-6868

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Research Projects

The DMSC currently directs research involving data mining and advanced data analysis techniques in several projects covering a spectrum of science domains and new information technology directions.

EVE Embedded On-board Mining and Data Processing
The modular character of ADaM enables its application to special environments such as embedded On-Board processing systems, satellite, airborne, and ground-based sensor platforms, as well as PDAs. Through the EnVironmEnt for Onboard Processing (EVE) program data mining is used for classification and feature extraction that contribute to Earth science research applications, including natural hazard detection and prediction, fusion of multi-sensor measurements, intelligent sensor control, and the generation of customized data products for direct distribution to users.

F-MASS Mining Space Science Data
ITSC is employing ADaM to build a data mining framework for the space science community. The interdisciplinary research team is investigating several Sun-Earth Connection Science research problems, such as the identification of polar cap boundary and determination of polar cap size, the recognition of some types of auroral activity, and the identification of magnetospheric substorms, as guiding scenarios for the development of this research.

GMAO Mining Atmospheric Model Data
UAH’s data mining tool, ADaM (Algorithm Development and Mining system), is being applied to numerical model output data generated at NASA's Goddard Global Modeling and Assimilation Office (GMAO). These independent experiments focus on the automated detection and mining of atmospheric phenomena within the model data.

MEAD Grid-based Mining
The mission of MEAD is to develop/adapt the cyberinfrastructure that will enable
simulation, data mining, and visualization of hurricanes and storms on the TeraGrid both retrospectively and concurrently. ADaM is critical data mining technology to a modeling environment for atmospheric discovery.

LEAD – Real-time Mining of Weather Phenomena
Scientific advances and societal benefits associated with the accurate prediction of mesoscale weather are enormous. The University of Alabama in Huntsville's Information Technology and Systems Center (ITSC) has teamed with seven other universities to accommodate the real time, on-demand, and dynamically-adaptive nature of mesoscale problems; the complexities associated with its vastly disparate, high volume and bandwidth data; and the tremendous computational demands of its models and data assimilation systems. This joint IT research will enable an integrated, scalable framework -- known as Linked Environments for Atmospheric Discovery (LEAD) -- for use in accessing, preparing, assimilating, predicting, managing, mining/analyzing, and displaying a broad array of meteorological and related information, independent of format and physical location.

ITSC researchers and UAH Computer Science Department faculty and students work closely in ongoing ITSC research projects.