Zobrazeno 1 - 10
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pro vyhledávání: '"John, P N"'
Autor:
Veillette, Mark S., Kurdzo, James M., Stepanian, Phillip M., Cho, John Y. N., Samsi, Siddharth, McDonald, Joseph
Weather radar is the primary tool used by forecasters to detect and warn for tornadoes in near-real time. In order to assist forecasters in warning the public, several algorithms have been developed to automatically detect tornadic signatures in weat
Externí odkaz:
http://arxiv.org/abs/2401.16437
Military chaff is a metallic, fibrous radar countermeasure that is released by aircraft and rockets for diversion and masking of targets. It is often released across the United States for training purposes, and, due to its resonant cut lengths, is of
Externí odkaz:
http://arxiv.org/abs/2211.16417
Autor:
Veillette, Mark S., Kurdzo, James M., Stepanian, Phillip M., McDonald, Joseph, Samsi, Siddharth, Cho, John Y. N.
Radial velocity estimates provided by Doppler weather radar are critical measurements used by operational forecasters for the detection and monitoring of life-impacting storms. The sampling methods used to produce these measurements are inherently su
Externí odkaz:
http://arxiv.org/abs/2211.13181
The vortex dynamics resulting from the interaction of synthetic jets with turbulent boundary layers was investigated experimentally using stereoscopic particle image velocimetry (SPIV). Three aspect ratio 18 rectangular orifice geometries were tested
Externí odkaz:
http://arxiv.org/abs/2205.07370
Autor:
Hu, Yang, Imes, Connor, Zhao, Xuanang, Kundu, Souvik, Beerel, Peter A., Crago, Stephen P., Walters, John Paul N.
Deep neural networks with large model sizes achieve state-of-the-art results for tasks in computer vision (CV) and natural language processing (NLP). However, these large-scale models are too compute- or memory-intensive for resource-constrained edge
Externí odkaz:
http://arxiv.org/abs/2110.14895
Inferring parameter distributions of complex industrial systems from noisy time series data requires methods to deal with the uncertainty of the underlying data and the used simulation model. Bayesian inference is well suited for these uncertain inve
Externí odkaz:
http://arxiv.org/abs/2106.09597
Autor:
Imran, Ali, Posokhova, Iryna, Qureshi, Haneya N., Masood, Usama, Riaz, Muhammad Sajid, Ali, Kamran, John, Charles N., Hussain, MD Iftikhar, Nabeel, Muhammad
Publikováno v:
Informatics in Medicine Unlocked, vol. 20, p. 100378, 2020
Background: The inability to test at scale has become humanity's Achille's heel in the ongoing war against the COVID-19 pandemic. A scalable screening tool would be a game changer. Building on the prior work on cough-based diagnosis of respiratory di
Externí odkaz:
http://arxiv.org/abs/2004.01275
Autor:
Bales, Charles, Nabeel, Muhammad, John, Charles N., Masood, Usama, Qureshi, Haneya N., Farooq, Hasan, Posokhova, Iryna, Imran, Ali
Emerging wireless technologies, such as 5G and beyond, are bringing new use cases to the forefront, one of the most prominent being machine learning empowered health care. One of the notable modern medical concerns that impose an immense worldwide he
Externí odkaz:
http://arxiv.org/abs/2004.01495
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Akademický článek
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