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  1. Bahraminejad B, Basri S, Isa M, Hambli Z
    Sensors (Basel), 2010;10(6):5359-77.
    PMID: 22219666 DOI: 10.3390/s100605359
    In this study, the ability of the Capillary-attached conductive gas sensor (CGS) in real-time gas identification was investigated. The structure of the prototype fabricated CGS is presented. Portions were selected from the beginning of the CGS transient response including the first 11 samples to the first 100 samples. Different feature extraction and classification methods were applied on the selected portions. Validation of methods was evaluated to study the ability of an early portion of the CGS transient response in target gas (TG) identification. Experimental results proved that applying extracted features from an early part of the CGS transient response along with a classifier can distinguish short-chain alcohols from each other perfectly. Decreasing time of exposition in the interaction between target gas and sensing element improved the reliability of the sensor. Classification rate was also improved and time of identification was decreased. Moreover, the results indicated the optimum interval of the early transient response of the CGS for selecting portions to achieve the best classification rates.
  2. Karami A, Christianus A, Bahraminejad B, Gagné F, Courtenay SC
    Ecotoxicol Environ Saf, 2012 Mar;77:28-34.
    PMID: 22101109 DOI: 10.1016/j.ecoenv.2011.10.026
    This study examined the potential of artificial neural network (ANN) modeling to infer timing, route and dose of contaminant exposure from biomarkers in a freshwater fish. Hepatic glutathione S-transferase (GST) activity and biliary concentrations of BaP, 1-OH BaP, 3-OH BaP and 7,8D BaP were quantified in juvenile Clarias gariepinus injected intramuscularly or intraperitoneally with 10-50 mg/kg benzo[a]pyrene (BaP) 1-3 d earlier. A feedforward multilayer perceptron (MLP) ANN resulted in more accurate prediction of timing, route and exposure dose than a linear neural network or a radial basis function (RBF) ANN. MLP sensitivity analyses revealed contribution of all five biomarkers to predicting route of exposure but no contribution of hepatic GST activity or one of the two hydroxylated BaP metabolites to predicting time of exposure and dose of exposure. We conclude that information content of biomarkers collected from fish can be extended by judicious use of ANNs.
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