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1.
Concurrent assessment of personal, indoor, and outdoor PM2.5 and PM1 levels and source contributions using novel low-cost sensing devices.
Indoor Air
; 31(3): 755-768, 2021 05.
Artículo
en Inglés
| MEDLINE | ID: mdl-33047373
2.
Application of Machine Learning for the in-Field Correction of a PM2.5 Low-Cost Sensor Network.
Sensors (Basel)
; 20(17)2020 Sep 03.
Artículo
en Inglés
| MEDLINE | ID: mdl-32899301
3.
Laboratory Evaluations of Correction Equations with Multiple Choices for Seed Low-Cost Particle Sensing Devices in Sensor Networks.
Sensors (Basel)
; 20(13)2020 Jun 30.
Artículo
en Inglés
| MEDLINE | ID: mdl-32629896
4.
Fusion of Environmental Sensing on PM2.5 and Deep Learning on Vehicle Detecting for Acquiring Roadside PM2.5 Concentration Increments.
Sensors (Basel)
; 20(17)2020 Aug 19.
Artículo
en Inglés
| MEDLINE | ID: mdl-32825023
5.
Research Priorities of Applying Low-Cost PM2.5 Sensors in Southeast Asian Countries.
Int J Environ Res Public Health
; 19(3)2022 01 28.
Artículo
en Inglés
| MEDLINE | ID: mdl-35162543
6.
A versatile low-cost sensing device for assessing PM2.5 spatiotemporal variation and quantifying source contribution.
Sci Total Environ
; 716: 137145, 2020 May 10.
Artículo
en Inglés
| MEDLINE | ID: mdl-32069696
7.
Correction: Panel study using novel sensing devices to assess associations of PM2.5 with heart rate variability and exposure sources.
J Expo Sci Environ Epidemiol
; 30(6): 1033, 2020 Nov.
Artículo
en Inglés
| MEDLINE | ID: mdl-32934345
8.
Panel study using novel sensing devices to assess associations of PM2.5 with heart rate variability and exposure sources.
J Expo Sci Environ Epidemiol
; 30(6): 937-948, 2020 11.
Artículo
en Inglés
| MEDLINE | ID: mdl-32753593
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