Casamento, S, Kwok, B, Roux, C, Dawson, M & Doble, P 2003, 'Optimization of the separation of organic explosives by capillary electrophoresis with artificial neural networks', JOURNAL OF FORENSIC SCIENCES, vol. 48, no. 5, pp. 1075-1083.
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The separation of 12 explosives by capillary electrophoresis was optimized with the aid of artificial neural networks (ANNs). The selectivity of the separation was manipulated by varying the concentration of sodium dodecyl sulfate (SDS) and the pH of the electrolyte, while maintaining the buffer concentration at 10 mM borate. The concentration of SDS and the electrolyte pH were used as input variables and the mobility of the explosives were used as output variables for the ANN. In total, eight experiments were performed based on a factorial design to train a variety of artificial neural network architectures. A further three experiments were required to train ANN architectures to adequately model the experimental space. A product resolution response surface was constructed based on the predicted mobilities of the best performing ANN. This response surface pointed to two optima; pH 9.0-9.1 and 60-65 mM SDS, and pH 8.4-8.6 and 50-60 mM SDS. Separation of all 12 explosives was achieved at the second optimum. The separation was further improved by changing the capillary to an extended cell detection window and reducing the diameter of the capillary from 75 μm to 50 μm. This provided a more efficient separation without compromising detection sensitivity.
Doble, P, Sandercock, M, Du Pasquier, E, Petocz, P, Roux, C & Dawson, M 2003, 'Classification. of premium and regular gasoline by gas chromatography/mass spectrometry, principal component analysis and artificial neural networks', FORENSIC SCIENCE INTERNATIONAL, vol. 132, no. 1, pp. 26-39.
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Detection and correct classification of gasoline is important for both arson and fuel spill investigation. Principal component analysis (PCA) was used to classify premium and regular gasolines from gas chromatographymass spectrometry (GCMS) spectral data obtained from gasoline sold in Canada over one calendar year. Depending upon the dataset used for training and tests, around 8093% of the samples were correctly classified as either premium or regular gasoline using the Mahalanobis distances calculated from the principal components scores. Only 4862% of the samples were correctly classified when the premium and regular gasoline samples were divided further into their winter/summer sub-groups. Artificial neural networks (ANNs) were trained to recognise premium and regular gasolines from the same GCMS data. The best-performing ANN correctly identified all samples as either a premium or regular grade. Approximately 97% of the premium and regular samples were correctly classified according to their winter or summer sub-group.
Exline, DL, Wallace, C, Roux, C, Lennard, C, Nelson, MP & Treado, PJ 2003, 'Forensic Applications of Chemical Imaging: Latent Fingerprint Detection Using Visible Absorption and Luminescence', Journal of Forensic Sciences, vol. 48, no. 5, pp. 1-7.
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Abstract Chemical imaging technology is a rapid examination technique that combines molecular spectroscopy and digital imaging, providing information on morphology, composition, structure, and concentration of a material. Among many other applications, chemical imaging offers an array of novel analytical testing methods, which limits sample preparation and provides high-quality imaging data essential in the detection of latent fingerprints. Luminescence chemical imaging and visible absorbance chemical imaging have been successfully applied to ninhydrin, DFO, cyanoacrylate, and luminescent dye-treated latent fingerprints, demonstrating the potential of this technology to aid forensic investigations. In addition, visible absorption chemical imaging has been applied successfully to visualize untreated latent fingerprints
Jones, N, Kelly, M, Stoilovic, M, Lennard, C & Roux, C 2003, 'The development of latent fingerprints on polymer banknotes', Journal of Forensic Identification, vol. 53, no. 1, pp. 50-77.
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Polymer banknotes, especially older banknotes and banknotes with aged prints, present challenges for latent print development. A sequence of techniques has been optimized for the development of aged prints on the surface of banknotes. The procedure involves optical examination, cyanoacrylate fuming, vacuum metal deposition treatment, and luminescence staining. It is essential to treat banknotes with cyanoacrylate fuming as soon as they are received so that the print degradation, which occurs quickly on the banknote surface, is minimized. Vacuum metal deposition treatment should also be applied as soon as possible after cyanoacrylate fuming. Treatments other than those outlined in this procedure should be avoided, because they will be detrimental to vacuum metal deposition development.
Jones, N, Lennard, C, Stoilovic, M & Roux, C 2003, 'An evaluation of multimetal deposition II', Journal of Forensic Identification, vol. 53, no. 4, pp. 444-488.
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Multimetal deposition (MMD) has not found routine application because of its complexity and inconsistent results. Recent research that sought to overcome these problems resulted in the development of a new formulation known as MMDII. MMDII utilizes smaller colloidal gold particles (14 nm as compared to 30 nm) and an alternative physical developer (silver acetate/hydroquinone rather than silver nitrate/iron(II)/iron(III)). Several MMD formulations were evaluated in this study, and MMDII proved to be the superior formulation, giving better overall print detail. On nonporous surfaces, MMDII may offer further print development than that achieved with cyanoacrylate fuming (CA) and luminescent staining, but vacuum metal deposition (VMD) always gave superior results to MMD. MMDII and VMD were compared to standard techniques on a number of semiporous surfaces, including expanded polystyrene, waxed paper, latex gloves, and nitrile gloves. MMDII proved to be the technique of choice on these surfaces. The ability of MMDII to react with print residue within and on the surface is believed to be important to its success.
Payne, G, Roux, C, Lennard, C, Comber, B & Exline, D 2003, 'Applications of chemical imaging to the detection of latent fingerprints', FORENSIC SCIENCE INTERNATIONAL, vol. 136, pp. 131-131.
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Thomas, J, Buzzini, P, Roux, C & Reedy, B 2003, 'A further look at Raman spectroscopy for the forensic examination of fibres', FORENSIC SCIENCE INTERNATIONAL, vol. 136, pp. 125-125.
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Thomas, J, Roux, C, Reedy, B & Robertson, J 2003, 'Raman spectroscopy of environmentally degraded fibre samples', FORENSIC SCIENCE INTERNATIONAL, vol. 136, pp. 118-119.
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Flynn, K, Roux, C, Maynard, P, Du Pasquier, E, Lennard, C & Stoilovic, M 1970, 'The evaluation of spray reagents for the detection of latent fingerprints at the crime scene', FORENSIC SCIENCE INTERNATIONAL, 3rd European-Academy-of-Forensic-Science Meeting, ELSEVIER SCI IRELAND LTD, ISTANBUL, TURKEY, pp. 132-133.
Stitt, J, Phillips, M, Brandi, J & Roux, C 1970, 'The examination of line crossings by environmental scanning electron microscopy and atomic force microscopy', FORENSIC SCIENCE INTERNATIONAL, 3rd European-Academy-of-Forensic-Science Meeting, ELSEVIER SCI IRELAND LTD, ISTANBUL, TURKEY, pp. 81-81.
Thomas, J, Buzzini, P & Roux, C 1970, 'Optimisation of laser wavelength for the Raman analysis of fibres', FORENSIC SCIENCE INTERNATIONAL, 3rd European-Academy-of-Forensic-Science Meeting, Elsevier Inc, ISI:000185538200256, pp. 117-118.
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