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Chung-Ho Wang

Researcher at Academia Sinica

Publications -  120
Citations -  3838

Chung-Ho Wang is an academic researcher from Academia Sinica. The author has contributed to research in topics: Groundwater & Monsoon. The author has an hindex of 33, co-authored 117 publications receiving 3471 citations. Previous affiliations of Chung-Ho Wang include National Defense University.

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Influence of the Yangtze River and grain size on the spatial variations of heavy metals and organic carbon in the East China Sea continental shelf sediments

TL;DR: In this paper, the authors investigated the influence of terrigenous sediments from the Yangtze River on the spatial variations of heavy metals and organic carbon on the East China Sea continental shelf.
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The calibration of D[Sr/Ca]versus sea surface temperature relationship for Porites corals

TL;DR: In this article, a calibration of D[Sr/Ca]-SST (D: distribution coefficient) relationships for Porites lobata and P. lutea was carried out.
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Optimization of multi-response processes using the VIKOR method.

TL;DR: In this paper, the VIKOR method was used to optimize multi-response processes in the context of chemical vapor deposition and copper chemical mechanical polishing, and the proposed method considered both the mean and the variation of quality losses associated with several multiple responses and ensured a small variation in quality losses among the responses, along with a small overall average loss.
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Deep sea and lake records of the Southeast Asian paleomonsoons for the last 25 thousand years

TL;DR: In this article, high resolution paleoceanographic proxy records from a deep-sea core in the northern South China Sea (SCS) and palynological record from a lake core in central Taiwan have been measured for the last 25 kyr.
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Optimization of multiple responses using principal component analysis and technique for order preference by similarity to ideal solution

TL;DR: In this article, the authors proposed a novel optimization procedure for multiple responses based on Taguchi's parameter design, where signal-to-noise (SN) ratio is initially used to assess the performance of each response, principal component analysis (PCA) is then conducted on the SN values to obtain a set of uncorrelated components, and the optimization direction for each component is determined based on the corresponding variation mode chart.