TOF-SIMS Image Data Fusion by Multivariate Analysis and TOF-SIMS Spectrum Analysis by Sparse Modeling and Machine Learning
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- Ishikura Wataru
- Faculty of Science and Technology, Seikei University
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- Takahashi Kazuma
- Faculty of Science and Technology, Seikei University
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- Yamagishi Takayuki
- Faculty of Science and Technology, Seikei University
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- Aoki Dan
- Graduate School of Bioagricultural Sciences, Nagoya University
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- Fukushima Kazuhiko
- Graduate School of Bioagricultural Sciences, Nagoya University
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- Shiga Motoki
- Faculty of Engineering, Gifu University JST PRESTO Center for Advanced Intelligence Project, RIKEN
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- Aoyagi Satoka
- Faculty of Science and Technology, Seikei University
Bibliographic Information
- Other Title
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- 多変量解析を利用したTOF-SIMSイメージデータ フュージョンとスパースモデリングおよび機械学習によるTOF-SIMSスペクトル解析
- タヘンリョウ カイセキ オ リヨウ シタ TOF-SIMS イメージデータフュージョン ト スパースモデリング オヨビ キカイ ガクシュウ ニ ヨル TOF-SIMS スペクトル カイセキ
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Abstract
Time-of-Flight secondary ion mass spectrometry (TOF-SIMS) and scanning electron microscope (SEM) images were fused and then evaluated by means of principal component analysis. As a result, TOF-SIMS spatial resolution could be improved by adding SEM image information to TOF-SIMS data without drastic change of TOF-SIMS spectrum information. Sparse modeling and machine learning were applied to TOF-SIMS data to interpret complex TOF-SIMS spectra. Least Absolute Shrinkage and Selection Operator (LASSO) provided a simplified TOF-SIMS spectrum with less noise. Machine learning using Random Forest and k-Nearest Neigbour appropriately predicted unknown test samples by learning TOF-SIMS data similar the test samples.
Journal
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- Journal of Surface Analysis
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Journal of Surface Analysis 25 (2), 103-114, 2018
The Surface Analysis Society of Japan
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Details 詳細情報について
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- CRID
- 1390846609810345344
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- NII Article ID
- 130007806258
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- NII Book ID
- AA11448771
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- ISSN
- 13478400
- 13411756
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- NDL BIB ID
- 029408722
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- Text Lang
- ja
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
- KAKEN
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- Abstract License Flag
- Disallowed