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pro vyhledávání: '"Eddy, William"'
Autor:
Stuchiner, Emily R., Jernigan, Wyatt A., Zhang, Ziliang, Eddy, William C., DeLucia, Evan H., Yang, Wendy H.
Publikováno v:
In Geoderma August 2024 448
For nearly a century, the initial reproduction number (R0) has been used as a one number summary to compare outbreaks of infectious disease, yet there is no `standard' estimator for R0. Difficulties in estimating R0 arise both from how a disease tran
Externí odkaz:
http://arxiv.org/abs/2003.10442
Autor:
Tai, Xiao Hui, Eddy, William F.
Firing a gun leaves marks on cartridge cases which purportedly uniquely identify the gun. Firearms examiners typically use a visual examination to evaluate if two cartridge cases were fired from the same gun, and this is a subjective process that has
Externí odkaz:
http://arxiv.org/abs/2003.00060
Akademický článek
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We study the distribution of brain source from the most advanced brain imaging technique, Magnetoencephalography (MEG), which measures the magnetic fields outside the human head produced by the electrical activity inside the brain. Common time-varyin
Externí odkaz:
http://arxiv.org/abs/1908.03926
Publikováno v:
East European Journal of Physics, Iss 3, Pp 104-114 (2022)
In this present study, we model Eckart-Hellmann Potential (EHP) to interact in a quark-antiquark system. The solutions of the Schrödinger equation are obtained with EHP using the Nikiforov-Uvarov method. The energy equation and normalized wave funct
Externí odkaz:
https://doaj.org/article/bf9a50b87d7f4782a5157bd8803670a4
Autor:
Richardson, Lee F., Eddy, William F.
This paper introduces a new tool for time-series analysis: the Sliding Window Discrete Fourier Transform (SWDFT). The SWDFT is especially useful for time-series with local- in-time periodic components. We define a 5-parameter model for noiseless loca
Externí odkaz:
http://arxiv.org/abs/1807.07797
Autor:
Richardson, Lee F., Eddy, William F.
Publikováno v:
ACM Transactions on Mathematical Software, Vol. 45, No. 1, Article 12. Publication date: February 2019
We present a new algorithm for the 2D Sliding Window Discrete Fourier Transform (SWDFT). Our algorithm avoids repeating calculations in overlapping windows by storing them in a tree data-structure based on the ideas of the Cooley- Tukey Fast Fourier
Externí odkaz:
http://arxiv.org/abs/1707.08213