Zobrazeno 1 - 10
of 228 949
pro vyhledávání: '"Wells, A"'
Publikováno v:
Optical Materials 142, 114093 (2023)
Lanthanide-doped Y$_{2}$SiO$_{5}$ microcrystals were prepared using the solution combustion, solid state and sol-gel synthesis techniques. Of these, the sol-gel method yields the most reliable and high-quality X2 phase Y$_{2}$SiO$_{5}$ microcrystals.
Externí odkaz:
http://arxiv.org/abs/2409.16580
Publikováno v:
Optical Materials: X 24 , 100356 (2024)
K$_2$YF$_5$ crystals doped with lanthanide ions have a variety of possible optical applications. Owing to the low symmetry of the system, the crystal structure cannot be unambiguously determined by x-ray diffraction. However, electron-paramagnetic re
Externí odkaz:
http://arxiv.org/abs/2409.15630
Autor:
Mothkuri, Sagar, Reid, Michael F., Wells, Jon-Paul R., Lafitte-Houssat, Eloïse, Ferrier, Alban, Goldner, Philippe
Publikováno v:
Journal of Luminescence 275, 120705 (2024)
Laser site-selective spectroscopy and high-resolution absorption measurements have been used to determine 51 crystal-field energy levels for one of the Ho$^{3+}$ centres in Y$_{2}$SiO$_{5}$. This centre is denoted as Site 2 and has been tentatively a
Externí odkaz:
http://arxiv.org/abs/2409.15625
Autor:
Moull, M. D., Martin, J. B. L., Newman, T. G. M., Jeffery, A. L., Bartholomew, J. G., Wells, J. -P. R., Reid, M. F.
Erbium ions in crystals show considerable promise for the technologies that will form the backbone of future networked quantum information technology. Despite advances in leveraging erbium's fibre-compatible infrared transition for classical and quan
Externí odkaz:
http://arxiv.org/abs/2409.15622
Autor:
Candelori, Luca, Abanov, Alexander G., Berger, Jeffrey, Hogan, Cameron J., Kirakosyan, Vahagn, Musaelian, Kharen, Samson, Ryan, Smith, James E. T., Villani, Dario, Wells, Martin T., Xu, Mengjia
We propose a new data representation method based on Quantum Cognition Machine Learning and apply it to manifold learning, specifically to the estimation of intrinsic dimension of data sets. The idea is to learn a representation of each data point as
Externí odkaz:
http://arxiv.org/abs/2409.12805
Autor:
Fehrentz, Maximilian, Azampour, Mohammad Farid, Dorent, Reuben, Rasheed, Hassan, Galvin, Colin, Golby, Alexandra, Wells, William M., Frisken, Sarah, Navab, Nassir, Haouchine, Nazim
We present in this paper a novel approach for 3D/2D intraoperative registration during neurosurgery via cross-modal inverse neural rendering. Our approach separates implicit neural representation into two components, handling anatomical structure pre
Externí odkaz:
http://arxiv.org/abs/2409.11983
Autor:
Rasheed, Hassan, Dorent, Reuben, Fehrentz, Maximilian, Kapur, Tina, Wells III, William M., Golby, Alexandra, Frisken, Sarah, Schnabel, Julia A., Haouchine, Nazim
We propose in this paper a texture-invariant 2D keypoints descriptor specifically designed for matching preoperative Magnetic Resonance (MR) images with intraoperative Ultrasound (US) images. We introduce a matching-by-synthesis strategy, where intra
Externí odkaz:
http://arxiv.org/abs/2409.08169
Autor:
Ramdas, Tejas, Wells, Martin T.
In this study, we leverage powerful non-linear machine learning methods to identify the characteristics of trades that contain valuable information. First, we demonstrate the effectiveness of our optimized neural network predictor in accurately predi
Externí odkaz:
http://arxiv.org/abs/2409.05192
Autor:
Freeman, Brian S., Arriola, Kendall, Cottell, Dan, Lawlor, Emmett, Erdman, Matt, Sutherland, Trevor, Wells, Brian
This study evaluates the productivity improvements achieved using a generative artificial intelligence personal assistant tool (PAT) developed by Trane Technologies. The PAT, based on OpenAI's GPT 3.5 model, was deployed on Microsoft Azure to ensure
Externí odkaz:
http://arxiv.org/abs/2409.14511
Autor:
Tang, William, Feibush, Eliot, Dong, Ge, Borthwick, Noah, Lee, Apollo, Gomez, Juan-Felipe, Gibbs, Tom, Stone, John, Messmer, Peter, Wells, Jack, Wei, Xishuo, Lin, Zhihong
In addressing the Department of Energy's April, 2022 announcement of a Bold Decadal Vision for delivering a Fusion Pilot Plant by 2035, associated software tools need to be developed for the integration of real world engineering and supply chain data
Externí odkaz:
http://arxiv.org/abs/2409.03112