Zobrazeno 1 - 10
of 6 187
pro vyhledávání: '"P. P. Deen"'
Autor:
Dung, On-Yu, Boden, Stephan, Vreman, Albertus W., Deen, Niels G., Schubert, Markus, Tang, Yali
X-ray radioscopy was used to measure the 2D projected dynamic void fraction in a zero/narrow gap alkaline water electrolyzer at a spatial resolution of 15 $\mu$m, for narrow gap sizes up to 300 $\mu$m and current densities up to 0.54 A/cm$^2$. As exp
Externí odkaz:
http://arxiv.org/abs/2411.08940
Autor:
Hui, Man-To, Wiegert, Paul A., Weryk, Robert, Micheli, Marco, Tholen, David J., Deen, Sam, Walker, Andrew J., Wainscoat, Richard
Saturn has long been the only giant planet in our solar system without any known Trojan members. In this paper, with serendipitous archival observations and refined orbit determination, we report that 2019 UO$_{14}$ is a Trojan of the gas giant. Howe
Externí odkaz:
http://arxiv.org/abs/2409.19725
Millimeter wave sensing provides people with the capability of sensing the surrounding crowds in a non-invasive and privacy-preserving manner, which holds huge application potential. However, detecting stationary crowds remains challenging due to sev
Externí odkaz:
http://arxiv.org/abs/2409.16209
Autor:
P. P. Deen
Publikováno v:
Frontiers in Physics, Vol 10 (2022)
In recent years the topic of frustrated magnetism has attracted significant scientific interest that shows little sign of abating. Within the field of frustrated magnetism, the compound Gd3Ga5O12 was, for many years, the archetypal frustrated magnet
Externí odkaz:
https://doaj.org/article/1689b6a259ea455b9aaad458779d974c
Autor:
Fygenson, Racquel, Jawad, Kazi, Li, Isabel, Ayoub, Francois, Deen, Robert G., Davidoff, Scott, Moritz, Dominik, Hess-Flores, Mauricio
Reconstruction of 3D scenes from 2D images is a technical challenge that impacts domains from Earth and planetary sciences and space exploration to augmented and virtual reality. Typically, reconstruction algorithms first identify common features acr
Externí odkaz:
http://arxiv.org/abs/2408.03503
Autor:
Chandler, Colin Orion, Trujillo, Chadwick A., Oldroyd, William J., Kueny, Jay K., Burris, William A., Hsieh, Henry H., DeSpain, Jarod A., Sedaghat, Nima, Sheppard, Scott S., Farrell, Kennedy A., Trilling, David E., Gustafsson, Annika, Magbanua, Mark Jesus Mendoza, Mazzucato, Michele T., Bosch, Milton K. D., Shaw-Diaz, Tiffany, Gonano, Virgilio, Lamperti, Al, Campos, José A. da Silva, Goodwin, Brian L., Terentev, Ivan A., Dukes, Charles J. A., Deen, Sam
We present the Citizen Science program Active Asteroids and describe discoveries stemming from our ongoing project. Our NASA Partner program is hosted on the Zooniverse online platform and launched on 2021 August 31, with the goal of engaging the com
Externí odkaz:
http://arxiv.org/abs/2403.09768
Autor:
Lass, Jakob, Lenander, Emma Y., Krighaar, Kristine M. L., Tošić, Tara N., Prabhakaran, Dharmalingam, Deen, Pascale P., Holm-Janas, Sofie, Lefmann, Kim
We extend previous inelastic neutron scattering results on the geometrically frustrated antiferromagnet hexagonal-YMnO$_3$, which has been suggested to belong to the class of classical spin liquids. We extend the energy transfer coverage of the diffu
Externí odkaz:
http://arxiv.org/abs/2403.07671
This short paper introduces a novel approach to global sensitivity analysis, grounded in the variance-covariance structure of random variables derived from random measures. The proposed methodology facilitates the application of information-theoretic
Externí odkaz:
http://arxiv.org/abs/2312.10541
Autor:
Kirkpatrick, J. Davy, Marocco, Federico, Gelino, Christopher R., Raghu, Yadukrishna, Faherty, Jacqueline K., Gagliuffi, Daniella C. Bardalez, Schurr, Steven D., Apps, Kevin, Schneider, Adam C., Meisner, Aaron M., Kuchner, Marc J., Caselden, Dan, Smart, R. L., Casewell, S. L., Raddi, Roberto, Kesseli, Aurora, Andersen, Nikolaj Stevnbak, Antonini, Edoardo, Beaulieu, Paul, Bickle, Thomas P., Bilsing, Martin, Chieng, Raymond, Colin, Guillaume, Deen, Sam, Dereveanco, Alexandru, Doll, Katharina, Luca, Hugo A. Durantini, Frazer, Anya, Gantier, Jean Marc, Gramaize, Léopold, Grant, Kristin, Hamlet, Leslie K., Higashimura, Hiro, Hyogo, Michiharu, Jałowiczor, Peter A., Jonkeren, Alexander, Kabatnik, Martin, Kiwy, Frank, Martin, David W., Michaels, Marianne N., Pendrill, William, Machado, Celso Pessanha, Pumphrey, Benjamin, Rothermich, Austin, Russwurm, Rebekah, Sainio, Arttu, Sanchez, John, Sapelkin-Tambling, Fyodor Theo, Schümann, Jörg, Selg-Mann, Karl, Singh, Harshdeep, Stenner, Andres, Sun, Guoyou, Tanner, Christopher, Thévenot, Melina, Ventura, Maurizio, Voloshin, Nikita V., Walla, Jim, Wedracki, Zbigniew, Adorno, Jose I., Aganze, Christian, Allers, Katelyn N., Brooks, Hunter, Burgasser, Adam J., Calamari, Emily, Connor, Thomas, Costa, Edgardo, Eisenhardt, Peter R., Gagné, Jonathan, Gerasimov, Roman, Gonzales, Eileen C., Hsu, Chih-Chun, Kiman, Rocio, Li, Guodong, Low, Ryan, Mamajek, Eric, Pantoja, Blake M., Popinchalk, Mark, Rees, Jon M., Stern, Daniel, Suárez, Genaro, Theissen, Christopher, Tsai, Chao-Wei, Vos, Johanna M., Zurek, David, Worlds, The Backyard, Collaboration, Planet 9
A complete accounting of nearby objects -- from the highest-mass white dwarf progenitors down to low-mass brown dwarfs -- is now possible, thanks to an almost complete set of trigonometric parallax determinations from Gaia, ground-based surveys, and
Externí odkaz:
http://arxiv.org/abs/2312.03639
Objective functions that optimize deep neural networks play a vital role in creating an enhanced feature representation of the input data. Although cross-entropy-based loss formulations have been extensively used in a variety of supervised deep-learn
Externí odkaz:
http://arxiv.org/abs/2312.10046