Zobrazeno 1 - 10
of 134 283
pro vyhledávání: '"James, F A"'
Autor:
Peters, James F., Liyanage, Tharaka U.
This paper introduces an axiomatic approach in the theory of energy dissipation in Hilbert envelopes on waveforms emanating from various vibrating systems. A Hilbert envelope is a curve tangent to peak points on a motion waveform. The basic approach
Externí odkaz:
http://arxiv.org/abs/2409.19016
Autor:
Ubach, Santiago, Steiner, James F., Jiang, Jiachen, Garcia, Javier, Connors, Riley M. T., Mastroserio, Guglielmo, Feng, Ye, Tomsick, John A.
We present our analysis of MAXI J1813-095 during its hard state ``stalled'' outburst in 2018. This self-consistent analysis has been carried out using \NICER, \Swift, \Chandra, and {\NuSTAR} throughout seven observations of MAXI J1813-095. We find a
Externí odkaz:
http://arxiv.org/abs/2409.13481
Autor:
Zhong, Junru, Yao, Yongcheng, Xiao, Fan, Ong, Tim-Yun Michael, Ho, Ki-Wai Kevin, Li, Siyue, Huang, Chaoxing, Chan, Queenie, Griffith, James F., Chen, Weitian
Objective: To establish an automated pipeline for post-processing of quantitative spin-lattice relaxation time constant in the rotating frame ($T_{1\rho}$) imaging of knee articular cartilage. Design: The proposed post-processing pipeline commences w
Externí odkaz:
http://arxiv.org/abs/2409.12600
In this paper we introduce a multi-agent deep-learning method which trades in the Futures markets based on the US S&P 500 index. The method (referred to as Model A) is an innovation founded on existing well-established machine-learning models which s
Externí odkaz:
http://arxiv.org/abs/2408.11740
Autor:
Xiong, Yuzan, Christy, Andrew, Yan, Zixin, Pishehvar, Amin, Mahdi, Muntasir, Wu, Junming, Cahoon, James F., Yang, Binbin, Hamilton, Michael C., Zhang, Xufeng, Zhang, Wei
Publikováno v:
Phys. Rev. Applied (2024)
Hybrid magnonic systems have emerged as a promising direction for information propagation with preserved coherence. Due to high tunability of magnons, their interactions with microwave photons can be engineered to probe novel phenomena based on stron
Externí odkaz:
http://arxiv.org/abs/2408.07197
Autor:
Nathan, Edward, Ingram, Adam, Steiner, James F., König, Ole, Dauser, Thomas, Lucchini, Matteo, Mastroserio, Guglielmo, van der Klis, Michiel, García, Javier A., Connors, Riley, Kara, Erin, Wang, Jingyi
The black hole X-ray binary H1743-322 lies in a region of the Galaxy with high extinction, and therefore it has not been possible to make a dynamical mass measurement. In this paper we make use of a recent model which uses the X-ray reflection spectr
Externí odkaz:
http://arxiv.org/abs/2408.05268
Autor:
Miller, Mark Roman, Nair, Vivek, Han, Eugy, DeVeaux, Cyan, Rack, Christian, Wang, Rui, Huang, Brandon, Latoschik, Marc Erich, O'Brien, James F., Bailenson, Jeremy N.
Social virtual reality is an emerging medium of communication. In this medium, a user's avatar (virtual representation) is controlled by the tracked motion of the user's headset and hand controllers. This tracked motion is a rich data stream that can
Externí odkaz:
http://arxiv.org/abs/2407.18380
Autor:
Nair, Vivek, Miller, Mark Roman, Wang, Rui, Huang, Brandon, Rack, Christian, Latoschik, Marc Erich, O'Brien, James F.
The use of virtual and augmented reality devices is increasing, but these sensor-rich devices pose risks to privacy. The ability to track a user's motion and infer the identity or characteristics of the user poses a privacy risk that has received sig
Externí odkaz:
http://arxiv.org/abs/2407.18378
Autor:
Wilson-Whitford, Samuel R., Kramer, David, Gao, Jinghui, Roffin, Maria Chiara, Gilchrist, James F.
Particle sedimentation through porous media is limited by the inability of passive material to overcome surface interactions and a tortuous network of pores. This limits transport, delivery, and effectiveness of chemicals used as reactants, nutrients
Externí odkaz:
http://arxiv.org/abs/2407.18116
Parkinson's Disease (PD) diagnosis remains challenging. This study applies Convolutional Kolmogorov-Arnold Networks (ConvKANs), integrating learnable spline-based activation functions into convolutional layers, for PD classification using structural
Externí odkaz:
http://arxiv.org/abs/2407.17380