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<![CDATA[Ph.D. Proposal Oral Exam - Joseph Ellis]]>
Title: Detection and Characterization of Ionospheric Sporadic E: A Machine Learning Approach
Committee:
Dr. Cohen, Advisor
Dr. Steffes, Chair
Dr. Davenport
Dr. Emmons
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The objective of the proposed research is to improve the detection and characterization capabilities for sporadic E, a phenomenon which manifests as regions of enhanced ionization occurring 90-130 km above the Earth's surface. To better model sporadic E, this proposed work will focus on the application of advanced signal processing and machine learning (ML) techniques. The major areas that will be pursued are the development of models that infer sporadic E characteristics from radio occultation measurements, and nowcast models using only globally available sources such as solar and geomagnetic indices, weather, and meteor data.
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https://gatech.zoom.us/j/97220032338
- 434371
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1788
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102851
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