Chemical detection using the receptor density algorithm

James A. Hilder; Nick D.L. Owens; Mark J. Neal; Peter J. Hickey; Stuart N. Cairns; David P.A. Kilgour; Jon Timmis; Andy M. Tyrrell

doi:10.1109/TSMCC.2012.2218236

Chemical detection using the receptor density algorithm

James A. Hilder^*, Nick D.L. Owens, Mark J. Neal, Peter J. Hickey, Stuart N. Cairns, David P.A. Kilgour, Jon Timmis, Andy M. Tyrrell

^*Corresponding author for this work

Department of Computer Science

Research output: Contribution to journal › Article › peer-review

17 Citations (Scopus)

Abstract

This paper describes the application of the receptor density algorithm, an artificial immune system, as used to detect chemicals from data provided by various spectrometers. The system creates chemical signatures which are matched to a library of known chemicals, allowing the positive identification of hazardous substances. The performance of the system is tested against a publicly available mass-spectrometry dataset, against which it has previously been demonstrated as an effective anomaly detection algorithm. An autonomous chemical-detection device is then discussed, in which the algorithm is running on hardware embedded in a Pioneer robot carrying a portable chemical agent monitor.

Original language	English
Article number	6392458
Pages (from-to)	1730-1741
Number of pages	12
Journal	IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews)
Volume	42
Issue number	6
DOIs	https://doi.org/10.1109/TSMCC.2012.2218236
Publication status	Published - Nov 2012

Keywords

hazardous materials
SPECTRA
NEURAL-NETWORKS
ION MOBILITY SPECTROMETRY
chemical sensors
Biological techniques
spectroscopy

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title = "Chemical detection using the receptor density algorithm",

abstract = "This paper describes the application of the receptor density algorithm, an artificial immune system, as used to detect chemicals from data provided by various spectrometers. The system creates chemical signatures which are matched to a library of known chemicals, allowing the positive identification of hazardous substances. The performance of the system is tested against a publicly available mass-spectrometry dataset, against which it has previously been demonstrated as an effective anomaly detection algorithm. An autonomous chemical-detection device is then discussed, in which the algorithm is running on hardware embedded in a Pioneer robot carrying a portable chemical agent monitor.",

keywords = "hazardous materials, SPECTRA, NEURAL-NETWORKS, ION MOBILITY SPECTROMETRY, chemical sensors, Biological techniques, spectroscopy",

author = "Hilder, {James A.} and Owens, {Nick D.L.} and Neal, {Mark J.} and Hickey, {Peter J.} and Cairns, {Stuart N.} and Kilgour, {David P.A.} and Jon Timmis and Tyrrell, {Andy M.}",

note = "Funding Information: Manuscript received November 17, 2011; revised May 4, 2012; accepted August 29, 2012. Date of current version December 17, 2012. This work was supported by the Defence Science and Technology Laboratory under Contract 1000032154. This paper was recommended by Associate Editor Y. Jin.",

year = "2012",

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doi = "10.1109/TSMCC.2012.2218236",

language = "English",

volume = "42",

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AU - Hilder, James A.

AU - Owens, Nick D.L.

AU - Neal, Mark J.

AU - Hickey, Peter J.

AU - Cairns, Stuart N.

AU - Kilgour, David P.A.

AU - Timmis, Jon

AU - Tyrrell, Andy M.

N1 - Funding Information: Manuscript received November 17, 2011; revised May 4, 2012; accepted August 29, 2012. Date of current version December 17, 2012. This work was supported by the Defence Science and Technology Laboratory under Contract 1000032154. This paper was recommended by Associate Editor Y. Jin.

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AB - This paper describes the application of the receptor density algorithm, an artificial immune system, as used to detect chemicals from data provided by various spectrometers. The system creates chemical signatures which are matched to a library of known chemicals, allowing the positive identification of hazardous substances. The performance of the system is tested against a publicly available mass-spectrometry dataset, against which it has previously been demonstrated as an effective anomaly detection algorithm. An autonomous chemical-detection device is then discussed, in which the algorithm is running on hardware embedded in a Pioneer robot carrying a portable chemical agent monitor.

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KW - SPECTRA

KW - NEURAL-NETWORKS

KW - ION MOBILITY SPECTROMETRY

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KW - Biological techniques

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JO - IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews)

JF - IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews)

IS - 6

M1 - 6392458

ER -

Chemical detection using the receptor density algorithm

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Keywords

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