Zobrazeno 1 - 10
of 226 952
pro vyhledávání: '"O'Connor, A."'
Autor:
Flanagan, Francis, O'Connor, Alison, Erfanian, Mozhdeh, Music, Omer, Brambley, Edward James, O'Kiely, Doireann
In this paper, we carefully develop a finite element (FE) model that gives accurate through-thickness predictions of stress and strain distributions during the steady-state cold rolling process. These through-thickness predictions unveil an oscillato
Externí odkaz:
http://arxiv.org/abs/2408.03242
Autor:
Erfanian, Mozhdeh, Brambley, Edward James, Flanagan, Francis, O'Kiely, Doireann, O'Connor, Alison
A new semi-analytic model of the metal rolling processes is presented and validated against finite element simulations. The model generalizes the classical Slab Method of cold rolling, and for the first time is able to predict the through-thickness s
Externí odkaz:
http://arxiv.org/abs/2408.01347
This paper proposes a framework for time series generation built to investigate anomaly detection in cloud microservices. In the field of cloud computing, ensuring the reliability of microservices is of paramount concern and yet a remarkably challeng
Externí odkaz:
http://arxiv.org/abs/2408.00006
Autor:
Owen, Cameron J., Marcella, Nicholas, O'Connor, Christopher R., Kim, Taek-Seung, Shimogawa, Ryuichi, Xie, Clare Yijia, Nuzzo, Ralph G., Frenkel, Anatoly I., Reece, Christian, Kozinsky, Boris
Supported metal nanoparticle (NP) catalysts are vital for the sustainable production of chemicals, but their design and implementation are limited by the ability to identify and characterize their structures and atomic sites that are correlated with
Externí odkaz:
http://arxiv.org/abs/2407.13643
Autor:
Owen, Cameron J., Russotto, Lorenzo, O'Connor, Christopher R., Marcella, Nicholas, Johansson, Anders, Musaelian, Albert, Kozinsky, Boris
Multi-component metal nanoparticles (NPs) are of paramount importance in the chemical industry, as most processes therein employ heterogeneous catalysts. While these multi-component systems have been shown to result in higher product yields, improved
Externí odkaz:
http://arxiv.org/abs/2407.13607
Autor:
Cabrera, Tomás, Palmese, Antonella, Hu, Lei, O'Connor, Brendan, Ford, K. E. Saavik, McKernan, Barry, Andreoni, Igor, Ahumada, Tomás, Amsellem, Ariel, Busmann, Malte, Clark, Peter, Coughlin, Michael W., Dadiani, Ekaterine, Diaz, Veronica, Graham, Matthew J., Gruen, Daniel, Kunnumkai, Keerthi, Postiglione, Jake, Sommer, Julian S., Valdes, Francisco
We carried out long-term monitoring of the LIGO/Virgo/KAGRA binary black hole (BBH) merger candidate S230922g in search of electromagnetic emission from the interaction of the merger remnant with an embedding active galactic nuclei (AGN) accretion di
Externí odkaz:
http://arxiv.org/abs/2407.10698
Autor:
Saliwanchik, Benjamin R. B., Herrmann, Sven, Kotov, Ivan, O'Connor, Paul, Potekhin, Maxim, Slosar, Anže, Bale, Stuart
The Lunar Surface Electromagnetics Experiment at Night (LuSEE-Night) is a project designed to investigate the feasibility of observing the Cosmic Dark Ages using an instrument on the lunar far-side. LuSEE-Night will measure the redshifted 21 cm trans
Externí odkaz:
http://arxiv.org/abs/2407.07173
Autor:
Albert, Paul, Valmadre, Jack, Arazo, Eric, Krishna, Tarun, O'Connor, Noel E., McGuinness, Kevin
Training a classifier on web-crawled data demands learning algorithms that are robust to annotation errors and irrelevant examples. This paper builds upon the recent empirical observation that applying unsupervised contrastive learning to noisy, web-
Externí odkaz:
http://arxiv.org/abs/2407.05528
Autor:
Dolata, Benjamin E., Cunha, Marco A Galvani, O'Connor, Thomas, Hopkins, Austin, Olmsted, Peter D.
Publikováno v:
ACS Macro Letters 13 (2024) 896-902
We investigate the universality of entanglement kinetics in polymer melts. We compare predictions of a recently developed constitutive equation for disentanglement to molecular dynamics simulations of both united-atom polyethylene and Kremer-Grest mo
Externí odkaz:
http://arxiv.org/abs/2407.04886
Autor:
de Queiroz, Mauricio Gomes, Jimenez, Paul, Cardoso, Raphael, Costa, Mateus Vidaletti, Abdalla, Mohab, O'Connor, Ian, Bosio, Alberto, Pavanello, Fabio
Photonic Neural Networks (PNNs) are gaining significant interest in the research community due to their potential for high parallelization, low latency, and energy efficiency. PNNs compute using light, which leads to several differences in implementa
Externí odkaz:
http://arxiv.org/abs/2406.18757