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Researchers at UAH conduct research in the areas of machine learning, phenomena detection, knowledge discovery and distributed mining technologies. Particular emphasis is directed toward problems involving large heterogeneous spatial data sets, such as remotely sensed data.
FACULTY
 Dr. Ramazan Aygun
Dr. Sara J. Graves
Dr. Ranganath S. Heggere
Dr. Tim Newman
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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. |
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 F-MASS Mining Space Science Data (ITSC) |
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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.
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Discovery of knowledge from scientific and medical datasets can be aided by pattern recognition and computer vision techniques. Professor Newman and his students have developed new techniques for detecting cardiac irregularities, certain types of kidney troubles, and for determining anatomical parameters of the brain ventricular system from medical datasets. New methodologies for discovery of anamolies in scientific datasets have also been developed by Newman and his students through the coupling of visualization and mining.
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We are investigating mechanisms for automatic and semi-automatic detection of structures and phenomena in satellite data for missions related to the Earth and to the Sun. We are especially interested in utilizing shape-based model information to assist the detection process.
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