Search Results - "Zewdie, Gebreab K"

Using machine learning to understand the temporal morphology of the PM2.5 annual cycle in East Asia by Wu, Daji, Lary, David J., Zewdie, Gebreab K., Liu, Xun

“…PM 2.5 air pollution is a significant issue for human health all over the world, especially in East Asia. A large number of ground-based measurement sites have…”
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Applying Deep Neural Networks and Ensemble Machine Learning Methods to Forecast Airborne Ambrosia Pollen by Zewdie, Gebreab K, Lary, David J, Levetin, Estelle, Garuma, Gemechu F

“…Allergies to airborne pollen are a significant issue affecting millions of Americans. Consequently, accurately predicting the daily concentration of airborne…”
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Estimating the daily pollen concentration in the atmosphere using machine learning and NEXRAD weather radar data by Zewdie, Gebreab K., Lary, David J., Liu, Xun, Wu, Daji, Levetin, Estelle

“…Millions of people have an allergic reaction to pollen. The impact of pollen allergies is on the rise due to increased pollen levels caused by global warming…”
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Applying machine learning to forecast daily Ambrosia pollen using environmental and NEXRAD parameters by Zewdie, Gebreab K., Liu, Xun, Wu, Daji, Lary, David J., Levetin, Estelle

“…Approximately 50 million Americans have allergic diseases. Airborne plant pollen is a significant trigger for several of these allergic diseases. Ambrosia…”
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High-resolution coherent backscatter interferometric radar images of equatorial spread F using Capon's method by Rodrigues, Fabiano S, de Paula, Eurico R, Zewdie, Gebreab K

“…We present results of Capon's method for estimation of in-beam images of ionospheric scattering structures observed by a small, low-power coherent backscatter…”
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Insights Into the Morphology of the East Asia PM2.5 Annual Cycle Provided by Machine Learning by Wu, Daji, Zewdie, Gebreab K, Liu, Xun, Kneen, Melanie Anne, Lary, David John

“…The abundance of airborne particulate matter with an aerodynamic equivalent diameter of 2.5 µm or less (PM2.5) is a significant environmental and health issue…”
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Using machine learning to estimate atmospheric Ambrosia pollen concentrations in Tulsa, OK by Liu, Xun, Wu, Daji, Zewdie, Gebreab K, Wijerante, Lakitha, Timms, Christopher I, Riley, Alexander, Levetin, Estelle, Lary, David J

“…This article describes an example of using machine learning to estimate the abundance of airborne Ambrosia pollen for Tulsa, OK. Twenty-seven years of…”
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Results of coherent backscatter radar imaging using Capon's method and measurements made by the Sao Luis radar interferometer by Zewdie, Gebreab K., Rodrigues, Fabiano S.

“…Interferometric radar imaging of F-region spread F irregularities is used to determine the distribution of scatterers within the radar field of view. In this…”
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Using machine learning to understand the temporal morphology of the PM 2.5 annual cycle in East Asia by Wu, Daji, Lary, David J, Zewdie, Gebreab K, Liu, Xun

“…PM air pollution is a significant issue for human health all over the world, especially in East Asia. A large number of ground-based measurement sites have…”
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Using a Comprehensive Characterization of the Physical Environment and Machine Learning to Forecast the Abundance of Airborne Pollen by Zewdie, Gebreab K

“…It is known that approximately 50 million Americans have allergic diseases. Airborne pollen is a significant trigger for several of these allergic diseases…”
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Insights Into the Morphology of the East Asia PM Annual Cycle Provided by Machine Learning by Daji Wu, Gebreab K Zewdie, Xun Liu, Melanie Anne Kneen, David John Lary

“…The abundance of airborne particulate matter with an aerodynamic equivalent diameter of 2.5 µm or less (PM 2.5 ) is a significant environmental and health…”
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Insights Into the Morphology of the East Asia PM 2.5 Annual Cycle Provided by Machine Learning by Wu, Daji, Zewdie, Gebreab K, Liu, Xun, Kneen, Melanie Anne, Lary, David John

“…The abundance of airborne particulate matter with an aerodynamic equivalent diameter of 2.5 µm or less (PM ) is a significant environmental and health issue…”
Get full text

Insights Into the Morphology of the East Asia PM 2.5 Annual Cycle Provided by Machine Learning by Wu, Daji, Zewdie, Gebreab K, Liu, Xun, Kneen, Melanie Anne, Lary, David John

“…The abundance of airborne particulate matter with an aerodynamic equivalent diameter of 2.5 µm or less (PM 2.5 ) is a significant environmental and health…”
Get full text

Using machine learning to estimate atmospheric pollen concentrations in Tulsa, OK by Xun Liu, Daji Wu, Gebreab K Zewdie, Lakitha Wijerante, Christopher I Timms, Alexander Riley, Estelle Levetin, David J Lary

“…This article describes an example of using machine learning to estimate the abundance of airborne Ambrosia pollen for Tulsa, OK. Twenty-seven years of…”
Get full text