Grantee Research Project Results
Publications Details for Grant Number SU839965
Machine Learning Calibrated Low-Cost Sensing (MLCS)
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Reference Type | Citation | Progress Report Year | Document Sources |
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Journal Article | Wijeratne LO, Kiv DR, Aker AR, Talebi S, Lary DJ. Using machine learning for the calibration of airborne particulate sensors. Sensors 2020;20(1):99. |
SU839965 (2020) |
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Journal Article | Zhang Y, Wijeratne LO, Talebi S, Lary DJ. Machine Learning for Light Sensor Calibration. Sensors 2021;21(18):6259. |
SU839965 (Final) |
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Presentation | Lary DJ. Dense Urban Environment Dosimetry for Actionable Information and Recording Exposure (DUE DARE). Presented at the University of Texas at Dallas, Richardson, United States, 2019. |
SU839965 (2020) |
not available |
Presentation | Lary DJ. Fun of Physics:Physics in Service of Society. Presented at UT Dallas, Fun of Physics Seminar Series, 2020. |
SU839965 (2020) |
not available |
The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.