Name
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. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/TSMCC.2012.2218236 | IEEE Transactions on Systems, Man, and Cybernetics, Part C |
Keywords | Field | DocType |
artificial immune systems,chemical sensors,data analysis,hazardous materials,mass spectroscopic chemical analysis,mass spectroscopy,mobile robots,spectroscopy computing,AIS,CAM,Pioneer robot,RDA,anomaly detection algorithm,artificial immune system,autonomous chemical-detection device,chemical signatures,mass-spectrometry dataset,portable chemical agent monitor,receptor density algorithm,spectrometers,Biological techniques,chemical sensors,hazardous materials,spectroscopy | Anomaly detection,Artificial immune system,Computer science,Algorithm,Robot,Artificial neural network,Mobile robot | Journal |
Volume | Issue | ISSN |
42 | 6 | 1094-6977 |
Citations | PageRank | References |
7 | 0.49 | 3 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| James A. Hilder | 1 | 59 | 6.98 |
| Nick D. L. Owens | 2 | 116 | 9.18 |
| Mark James Neal | 3 | 24 | 4.77 |
| Peter J. Hickey | 4 | 11 | 1.05 |
| Stuart N. Cairns | 5 | 11 | 1.05 |
| David P. A. Kilgour | 6 | 11 | 1.05 |
| Jonathan Timmis | 7 | 339 | 33.03 |
| Andrew M. Tyrrell | 8 | 326 | 49.07 |