Conference proceeding
Compound-Cognizant Feature Compression of Gas Chromatographic Data to Facilitate Environmental Forensics
2015 Data Compression Conference, Vol.2015-, pp.443-443
04/2015
DOI: 10.1109/DCC.2015.73
Abstract
We present complementary compound-cognizant data engineering techniques for feature compression and data indexing across two-dimensional gas chromatographic (GC×GC) datasets with petroleum forensics as the primary application. We propose single-linkage clustering of dominant compounds (targets) along with local interpretation across biomarker peak profiles. Our methods enable high-volume data compression, along with robust querying and forensic distinction between similar sources. We validate our techniques against a diverse dataset of thirty-four crude oil injections collected from nineteen distinct sources across the planet, with emphasis on Macon do well, the source of Deepwater Horizon disaster (Gulf of Mexico, April 2010).
Details
- Title: Subtitle
- Compound-Cognizant Feature Compression of Gas Chromatographic Data to Facilitate Environmental Forensics
- Creators
- Hamidreza Ghasemi Damavandi - University of IowaAnanya Sen Gupta - University of IowaChristopher Reddy - Woods Hole Oceanographic InstitutionRobert Nelson - Woods Hole Oceanographic Institution
- Resource Type
- Conference proceeding
- Publication Details
- 2015 Data Compression Conference, Vol.2015-, pp.443-443
- Publisher
- IEEE
- DOI
- 10.1109/DCC.2015.73
- ISSN
- 1068-0314
- eISSN
- 2375-0359
- Language
- English
- Date published
- 04/2015
- Academic Unit
- Electrical and Computer Engineering
- Record Identifier
- 9984197229602771
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