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• W2024484495 abstract "Spectral interference from overlaps of spectral lines is a well-documented problem optical emission spectrometry. Spectral interference is encountered even when spectrometers with medium to high resolution are used (e.g., with a focal length of 0.75 m 1 m). The adverse effects of spectral interference are more pronounced when portable spectrometers with low resolution are used (e.g., with focal lengths of about 12.5 cm). Portable spectrometers are suited for “taking part of the lab to the sample” types of applications. We used Artificial Neural Networks (ANNs) and Partial Least Squares (PLS) to address spectral interference correction. And our efforts using these methods are described." @default.
• W2024484495 created "2016-06-24" @default.
• W2024484495 creator A5009442578 @default.
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• W2024484495 date "2015-05-21" @default.
• W2024484495 modified "2023-09-23" @default.
• W2024484495 title "How do artificial neural networks (ANNs) compare to partial least squares (PLS) for spectral interference correction in optical emission spectrometry?" @default.
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• W2024484495 doi "https://doi.org/10.1117/12.2177516" @default.
• W2024484495 hasPublicationYear "2015" @default.
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