Zobrazeno 1 - 10
of 1 077
pro vyhledávání: '"Lin, TE"'
We investigated the beat-to-beat fluctuation of the photoplethysmography (PPG) waveform. The motivation is that morphology variability extracted from the arterial blood pressure (ABP) has been found to correlate with baseline condition and short-term
Externí odkaz:
http://arxiv.org/abs/2401.00173
In this paper, we present a hybrid neural-network and MAC (Marker-And-Cell) scheme for solving Stokes equations with singular forces on an embedded interface in regular domains. As known, the solution variables (the pressure and velocity) exhibit non
Externí odkaz:
http://arxiv.org/abs/2306.06333
Autor:
Lin, Te-Hsien1 (AUTHOR) shlin810@cgmh.org.tw, Chen, Wan-Ling1 (AUTHOR) windkidll@cgmh.org.tw, Hsu, Shao-Fan2 (AUTHOR) 60943043s@ntnu.edu.tw, Chen, I-Cheng2 (AUTHOR) ichen@ntnu.edu.tw, Lin, Chih-Hsin1 (AUTHOR) chlin416@cgmh.org.tw, Chang, Kuo-Hsuan1 (AUTHOR) gophy5128@cgmh.org.tw, Wu, Yih-Ru1 (AUTHOR) yihruwu@cgmh.org.tw, Chen, Yi-Ru3 (AUTHOR) yiruchem@ntnu.edu.tw, Yao, Ching-Fa3 (AUTHOR) cheyaocf@ntnu.edu.tw, Lin, Wenwei3 (AUTHOR) wenweilin@ntnu.edu.tw, Lee-Chen, Guey-Jen2 (AUTHOR) t43019@ntnu.edu.tw, Chen, Chiung-Mei1 (AUTHOR) t43019@ntnu.edu.tw
Publikováno v:
International Journal of Molecular Sciences. Oct2024, Vol. 25 Issue 19, p10707. 21p.
In this paper, we propose a cusp-capturing physics-informed neural network (PINN) to solve discontinuous-coefficient elliptic interface problems whose solution is continuous but has discontinuous first derivatives on the interface. To find such a sol
Externí odkaz:
http://arxiv.org/abs/2210.08424
Publikováno v:
Commun. Comput. Phys., Vol. 33, pp.1090-1105 (2023)
A new and efficient neural-network and finite-difference hybrid method is developed for solving Poisson equation in a regular domain with jump discontinuities on embedded irregular interfaces. Since the solution has low regularity across the interfac
Externí odkaz:
http://arxiv.org/abs/2210.05523
In this paper, we introduce a shallow (one-hidden-layer) physics-informed neural network for solving partial differential equations on static and evolving surfaces. For the static surface case, with the aid of level set function, the surface normal a
Externí odkaz:
http://arxiv.org/abs/2203.01581
Publikováno v:
In Experimental Cell Research 15 July 2024 440(2)
Publikováno v:
J. Comput. Phys., Vol.469 (2022) 111547
In this paper, a shallow Ritz-type neural network for solving elliptic equations with delta function singular sources on an interface is developed. There are three novel features in the present work; namely, (i) the delta function singularity is natu
Externí odkaz:
http://arxiv.org/abs/2107.12013
Autor:
Liang, Chia-Wei, Sung, Yu-Chi, Hwang, Sheng-Jye, Shih, Ming-Hsiang, Liao, Wen-Hsiang, Lin, Te-Hsun, Yang, Dong-Yan
Publikováno v:
In Journal of Manufacturing Processes 15 June 2024 119:649-665
Autor:
Tsai, Shao-Pu, Hong, Ming-Tai, Lin, Wei-Hsun, Lu, Ssu-Yun, Jiang, Yun-Rong, Lin, Te-Wei, Tung, Po-Yen
Publikováno v:
In Journal of Materials Research and Technology May-June 2024 30:7644-7654