Lary, David J.
Browse by
David Lary is a Professor in the Physics Department. His research area is Applied Physics for Societal Benefit. He uses computational discovery to support decision-making in such varied areas as weather forecasting, climate data records, agriculture, tornado prediction, disaster response, famine relief, health systems, and online fraud.
Learn more about Dr. Lary on his home and Research Explorer pages.
Works in Treasures @ UT Dallas are made available exclusively for educational purposes such as research or instruction. Literary rights, including copyright for published works held by the creator(s) or their heirs, or other third parties may apply. All rights are reserved unless otherwise indicated by the copyright owner(s).
Recent Submissions
-
Estimating the Daily Pollen Concentration in the Atmosphere Using Machine Learning and NEXRAD Weather Radar Data
(Springer International Publishing, 2019-06-07)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 and the spread of highly invasive weeds. The production, release, ... -
Applying Deep Neural Networks and Ensemble Machine Learning Methods To Forecast Airborne Ambrosia Pollen
(MDPI AG, 2019-06-04)Allergies to airborne pollen are a significant issue affecting millions of Americans. Consequently, accurately predicting the daily concentration of airborne pollen is of significant public benefit in providing timely ... -
Phytophthora Megakarya and Phytophthora Palmivora, Closely Related Causal Agents of Cacao Black Pod Rot, Underwent Increases in Genome Sizes and Gene Numbers by Different Mechanisms
(2017-03-01)Phytophthora megakarya (Pmeg) and Phytophthora palmivora (Ppal) are closely related species causing cacao black pod rot. Although Ppal is a cosmopolitan pathogen, cacao is the only known host of economic importance for ... -
Holistics 3.0 for Health
(MDPI AG, 2014-07-24)Human health is part of an interdependent multifaceted system. More than ever, we have increasingly large amounts of data on the body, both spatial and non-spatial, its systems, disease and our social and physical environment. ... -
Using Remote Control Aerial Vehicles to Study Variability of Airborne Particulates
(Libertas Academica Ltd, 2015-08-04)Airborne particulates play a significant role in the atmospheric radiative balance and impact human health. To characterize this impact, global-scale observations and data products are needed. Satellite products allow for ... -
Survey on the Estimation of Mutual Information Methods as a Measure of Dependency Versus Correlation Analysis
(2015-02)In this survey, we present and compare different approaches to estimate Mutual Information (MI) from data to analyse general dependencies between variables of interest in a system. We demonstrate the performance difference ... -
Low Power Greenhouse Gas Sensors for Unmanned Aerial Vehicles
(2012-05-09)We demonstrate compact, low power, lightweight laser-based sensors for measuring trace gas species in the atmosphere designed specifically for electronic unmanned aerial vehicle (UAV) platforms. The sensors utilize ...
RSS 1.0