Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Zhipeng Lou"'
Publikováno v:
Biometrika.
SummaryIn this paper, we develop a systematic theory for high-dimensional analysis of variance in multivariate linear regression, where the dimension and the number of coefficients can both grow with the sample size. We propose a new U-type statistic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4c1e154883b0e40880c0103463e1a349
https://doi.org/10.1093/biomet/asad001
https://doi.org/10.1093/biomet/asad001
Publikováno v:
Volume 2: Multiphase Flow (MFTC); Computational Fluid Dynamics (CFDTC); Micro and Nano Fluid Dynamics (MNFDTC).
Metachronal motion is a unique swimming strategy widely adopted by many small animals on the scale of microns up to several centimeters (e.g., ctenophores, copepods, krill, and shrimp). During propulsion, each evenly spaced appendage performs a propu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f29e3c16fde20d691600c679d0a0c2a3
https://doi.org/10.1115/fedsm2022-86967
https://doi.org/10.1115/fedsm2022-86967
Publikováno v:
74th Annual Meeting of the APS Division of Fluid Dynamics - Gallery of Fluid Motion.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cfb9bace8ddf871589a6174a5c9bd83f
https://doi.org/10.1103/aps.dfd.2021.gfm.v0044
https://doi.org/10.1103/aps.dfd.2021.gfm.v0044
Publikováno v:
Volume 1: Aerospace Engineering Division Joint Track; Computational Fluid Dynamics.
Dolphins are known for their outstanding swimming performance. However, the difference in flow physics at different speeds remains elusive. In this work, the underlying mechanisms of dolphin swimming at three speeds, 2 m/s, 5 m/s, and 8 m/s, are expl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7ddc9ad7f2375d71fe8733b0a993e4ba
https://doi.org/10.1115/fedsm2021-65792
https://doi.org/10.1115/fedsm2021-65792
Publikováno v:
Combustion and Flame. 204:414-429
The flamelet method has been used extensively as an affordable turbulence-combustion interaction model that obviates the need to solve the evolution equations for the species mass fractions during a large-eddy or Reynolds-averaged Navier–Stokes cal
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c2e7ecebc99bdb08866af186f0f9ae87
https://doi.org/10.1016/j.combustflame.2019.03.030
https://doi.org/10.1016/j.combustflame.2019.03.030
Publikováno v:
Volume 2: Fluid Mechanics; Multiphase Flows.
In this paper, a numerical approach combined with experiments is employed to characterize the airflow through the vocal cord. Rabbits are used to perform in vivo magnetic resonance imaging (MRI) experiments and the MRI scan data are directly imposed
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bb1818566699fbbc9a89c3646d8352d5
https://doi.org/10.1115/fedsm2020-20369
https://doi.org/10.1115/fedsm2020-20369
Autor:
Foluso Ladeinde, Zhipeng Lou
Publikováno v:
Journal of Propulsion and Power. 34:750-761
This paper has the objective of addressing a few basic issues pertaining to the use of the laminar flamelet method to model turbulence-combustion interactions in supersonic combustion. Specifically...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7747c8aa6651280ef38fae6cda53f504
https://doi.org/10.2514/1.b36779
https://doi.org/10.2514/1.b36779
Autor:
Zhipeng Lou1 ZHIPENGPROB@GMAIL.COM, Wanrong Zhu2 WANRONGZHU@UCHICAGO.EDU, Wei Biao Wu2 WBWU@GALTON.UCHICAGO.EDU
Publikováno v:
Journal of Machine Learning Research. 2022, Vol. 23, p1-22. 22p.
Publikováno v:
Handbook of Big Data Analytics ISBN: 9783319182834
We present a systematic theory for tests for means of high-dimensional data. Our testing procedure is based on an invariance principle which provides distributional approximations of functionals of non-Gaussian vectors by those of Gaussian ones. Diff
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1cdf9e8271a5c74cc3ec5a33dd3eabc9
https://doi.org/10.1007/978-3-319-18284-1_8
https://doi.org/10.1007/978-3-319-18284-1_8
