COSIMA data analysis using multivariate techniques

COSIMA data analysis using multivariate techniques

We describe how to use multivariate analysis of complex TOF-SIMS (time-of-flight secondary ion mass spectrometry) spectra by introducing the method of random projections. The technique allows us to do full clustering and classification of the measured mass spectra. In this paper we use the tool for...

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Main Authors: J. Silén, H. Cottin, M. Hilchenbach, J. Kissel, H. Lehto, S. Siljeström, K. Varmuza
Format: Article
Language:English
Published: Copernicus Publications 2015-02-01
Series:Geoscientific Instrumentation, Methods and Data Systems
Online Access:http://www.geosci-instrum-method-data-syst.net/4/45/2015/gi-4-45-2015.pdf
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spelling doaj-113d5671439d4165b30fd6733c5352c92020-11-24T23:30:03ZengCopernicus PublicationsGeoscientific Instrumentation, Methods and Data Systems2193-08562193-08642015-02-0141455610.5194/gi-4-45-2015COSIMA data analysis using multivariate techniquesJ. Silén0H. Cottin1M. Hilchenbach2J. Kissel3H. Lehto4S. Siljeström5K. Varmuza6Finnish Meteorological Institute, Erik Palmenin aukio 1, PB 503, 00101 Helsinki, FinlandLaboratoire Interuniversitaire des Systèmes Atmosphériques (LISA), UMR7583 – CNRS, Université Paris Est – Créteil (UPEC), Université Paris Diderot (UPD), 61 Avenue du Général de Gaulle, 94010 Créteil, FranceMax Planck Institute for Solar System Research Justus-von-Liebig-Weg 3, 37077 Göttingen, GermanyMax Planck Institute for Solar System Research Justus-von-Liebig-Weg 3, 37077 Göttingen, GermanyTuorla Observatory Dept of Physics and Astronomy University of Turku, 21500 Piikkiö, FinlandDepartment of Chemistry, Materials and Surfaces, SP Technical Research Institute of Sweden, Borås, SwedenVienna University of Technology, Department of Statistics and Probability Theory, Wiedner Hauptstrasse 7/107, 1040 Vienna, AustriaWe describe how to use multivariate analysis of complex TOF-SIMS (time-of-flight secondary ion mass spectrometry) spectra by introducing the method of random projections. The technique allows us to do full clustering and classification of the measured mass spectra. In this paper we use the tool for classification purposes. The presentation describes calibration experiments of 19 minerals on Ag and Au substrates using positive mode ion spectra. The discrimination between individual minerals gives a cross-validation Cohen κ for classification of typically about 80%. We intend to use the method as a fast tool to deduce a qualitative similarity of measurements.http://www.geosci-instrum-method-data-syst.net/4/45/2015/gi-4-45-2015.pdf
collection DOAJ
language English
format Article
sources DOAJ
author J. Silén
H. Cottin
M. Hilchenbach
J. Kissel
H. Lehto
S. Siljeström
K. Varmuza
spellingShingle J. Silén
H. Cottin
M. Hilchenbach
J. Kissel
H. Lehto
S. Siljeström
K. Varmuza
COSIMA data analysis using multivariate techniques
Geoscientific Instrumentation, Methods and Data Systems
author_facet J. Silén
H. Cottin
M. Hilchenbach
J. Kissel
H. Lehto
S. Siljeström
K. Varmuza
author_sort J. Silén
title COSIMA data analysis using multivariate techniques
title_short COSIMA data analysis using multivariate techniques
title_full COSIMA data analysis using multivariate techniques
title_fullStr COSIMA data analysis using multivariate techniques
title_full_unstemmed COSIMA data analysis using multivariate techniques
title_sort cosima data analysis using multivariate techniques
publisher Copernicus Publications
series Geoscientific Instrumentation, Methods and Data Systems
issn 2193-0856
2193-0864
publishDate 2015-02-01
description We describe how to use multivariate analysis of complex TOF-SIMS (time-of-flight secondary ion mass spectrometry) spectra by introducing the method of random projections. The technique allows us to do full clustering and classification of the measured mass spectra. In this paper we use the tool for classification purposes. The presentation describes calibration experiments of 19 minerals on Ag and Au substrates using positive mode ion spectra. The discrimination between individual minerals gives a cross-validation Cohen κ for classification of typically about 80%. We intend to use the method as a fast tool to deduce a qualitative similarity of measurements.
url http://www.geosci-instrum-method-data-syst.net/4/45/2015/gi-4-45-2015.pdf
work_keys_str_mv AT jsilen cosimadataanalysisusingmultivariatetechniques
AT hcottin cosimadataanalysisusingmultivariatetechniques
AT mhilchenbach cosimadataanalysisusingmultivariatetechniques
AT jkissel cosimadataanalysisusingmultivariatetechniques
AT hlehto cosimadataanalysisusingmultivariatetechniques
AT ssiljestrom cosimadataanalysisusingmultivariatetechniques
AT kvarmuza cosimadataanalysisusingmultivariatetechniques
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