http://www.cnr.it/ontology/cnr/individuo/prodotto/ID22809
Instrumentation for the monitoring of toxic pollutants in water resources by means of neural network analysis of absorption and fluorescence spectra (Articolo in rivista)
- Type
- Label
- Instrumentation for the monitoring of toxic pollutants in water resources by means of neural network analysis of absorption and fluorescence spectra (Articolo in rivista) (literal)
- Anno
- 2007-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.1016/j.snb.2006.09.012 (literal)
- Alternative label
T. Kuzniz; D. Halot; A.G. Mignani; L. Ciaccheri; K. Kalli; M. Tur; A. Othonos; C. Christofides; D.A. Jackson (2007)
Instrumentation for the monitoring of toxic pollutants in water resources by means of neural network analysis of absorption and fluorescence spectra
in Sensors and actuators. B, Chemical (Print)
(literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- T. Kuzniz; D. Halot; A.G. Mignani; L. Ciaccheri; K. Kalli; M. Tur; A. Othonos; C. Christofides; D.A. Jackson (literal)
- Pagina inizio
- Pagina fine
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
- http://scholar.google.it/citations?view_op=view_citation&hl=it&user=gcrCP00AAAAJ&cstart=20&pagesize=100&sortby=pubdate&citation_for_view=gcrCP00AAAAJ:0EnyYjriUFMC (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
- Rivista
- Note
- Google S (literal)
- ISI Web of Science (WOS) (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- Kuzniz T.; Tur M.; - Tel Aviv University, Israel
Halot D.; Jackson D.A. - University of Kent, Physics Lab., UK
Mignani A.G.; Ciaccheri L.; - CNR IFAC, Italy
Kalli K.; Othonos A.; Christofides C.; - University of Cyprus, Department of Natural Sciences, Cyprus (literal)
- Titolo
- Instrumentation for the monitoring of toxic pollutants in water resources by means of neural network analysis of absorption and fluorescence spectra (literal)
- Abstract
- The concentration of several pollutants, usually present in industrialwastewaters, is predicted by the neural network data processing of absorption and fluorescence measurements in the visible spectral range. Proper network training provides quantitative analysis of many pollutants with sub-ppm resolution. Compact optical fibre instrumentation for absorption spectroscopy and an innovative flowcell for fluorescence measurements enable cost-effective, in situ, nonstop monitoring of waste waters. (literal)
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