Searched for: subject%3A%22Airborne%22
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Peng, Z. (author), Pineda Rojas, A.L. (author), Kropff, E. (author), Bahnfleth, W. (author), Buonanno, G. (author), Dancer, S.J. (author), Kurnitski, J. (author), Li, Y. (author), Boerstra, A.C. (author), Jimenez, J.L. (author)
Some infectious diseases, including COVID-19, can undergo airborne transmission. This may happen at close proximity, but as time indoors increases, infections can occur in shared room air despite distancing. We propose two indicators of infection risk for this situation, that is, relative risk parameter (Hr) and risk parameter (H). They combine...
journal article 2022
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Li, X. (author), Huang, J. (author), Klees, R. (author), Forsberg, R. (author), Willberg, M. (author), Slobbe, D.C. (author), Hwang, C. (author), Pail, R. (author)
In this study, we compare six commonly used methods for the downward continuation of airborne gravity data. We consider exact and noisy simulated data on grids and along flight trajectories and real data from the GRAV-D airborne campaign. We use simulated and real surface gravity data for validation. The methods comprise spherical harmonic...
journal article 2022
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Nurunnabi, A. (author), Teferle, F. N. (author), Li, J. (author), Lindenbergh, R.C. (author), Parvaz, S. (author)
Semantic segmentation of point clouds is indispensable for 3D scene understanding. Point clouds have credibility for capturing geometry of objects including shape, size, and orientation. Deep learning (DL) has been recognized as the most successful approach for image semantic segmentation. Applied to point clouds, performance of the many DL...
journal article 2021