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Institution

National Cheng Kung University

EducationTainan City, Taiwan
About: National Cheng Kung University is a education organization based out in Tainan City, Taiwan. It is known for research contribution in the topics: Population & Thin film. The organization has 49723 authors who have published 69799 publications receiving 1437420 citations. The organization is also known as: NCKU.


Papers
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Journal ArticleDOI
TL;DR: Although China had higher morbidity and mortality than other sites, the number of new daily cases in China has been lower than outside of China since 26 February 2020, and the incidence and mortality were correlated with the DCI.

309 citations

Journal ArticleDOI
TL;DR: Low temperature sputtered NiOx thin film is introduced, which substitutes the PEDOT-PSS and solution-processed NiOx as an effective electron blocking layer for mesoscopic NiO/CH3NH3PbI3 perovskite solar cells, and has the advantage for cost-effective perovSkite-based photovoltaics.
Abstract: We introduce the use of low temperature sputtered NiOx thin film, which substitutes the PEDOT–PSS and solution-processed NiOx as an effective electron blocking layer for mesoscopic NiO/CH3NH3PbI3 perovskite solar cells. The influences of film thickness and oxygen doping on the photovoltaic performances are scrutinized. The cell efficiency has been improved from 9.51 to 10.7% for devices using NiOx fabricated under pure argon atmosphere. With adequate doping under 10% oxygen flow ratio, we achieved power conversion efficiency of 11.6%. The procedure is large area scalable and has the advantage for cost-effective perovskite-based photovoltaics.

309 citations

Journal ArticleDOI
TL;DR: In this paper, a review of the transport and performance modeling of proton exchange membrane (PEM) fuel cells is presented, where the authors show how these modeling studies offer valid findings and recommendations that can be applied in enhancing transport processes for improving the cell performance.

307 citations

Proceedings ArticleDOI
17 Jul 2019
TL;DR: This work analyzes the nature of spurious statistical cues in the dataset and demonstrates that a range of models all exploit them, informing the construction of an adversarial dataset on which all models achieve random accuracy.
Abstract: We are surprised to find that BERT’s peak performance of 77% on the Argument Reasoning Comprehension Task reaches just three points below the average untrained human baseline. However, we show that this result is entirely accounted for by exploitation of spurious statistical cues in the dataset. We analyze the nature of these cues and demonstrate that a range of models all exploit them. This analysis informs the construction of an adversarial dataset on which all models achieve random accuracy. Our adversarial dataset provides a more robust assessment of argument comprehension and should be adopted as the standard in future work.

307 citations

Journal ArticleDOI
TL;DR: In this article, a 3D transient inverse heat conduction problem is solved using the conjugate gradient method (CGM) and the general purpose commercial code CFX4.2.

306 citations


Authors

Showing all 49872 results

NameH-indexPapersCitations
Yi Chen2174342293080
Yang Yang1642704144071
R. E. Hughes1541312110970
Mercouri G. Kanatzidis1521854113022
Thomas J. Smith1401775113919
Hui Li1352982105903
Gerald M. Reaven13379980351
Chi-Huey Wong129122066349
Joseph P. Vacanti11944150739
Kai Nan An10995351638
Ding-Shinn Chen10477446068
James D. Neaton10133164719
David C. Christiani100105255399
Jo Shu Chang9963937487
Yu Shyr9854239527
Network Information
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202373
2022315
20213,425
20203,154
20192,895
20182,764