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DETERMINING THE PRESENCE OF AN IGNITABLE LIQUID RESIDUE IN FIRE DEBRIS SAMPLES UTILIZING TARGET FACTOR ANALYSIS
Title
DETERMINING THE PRESENCE OF AN IGNITABLE LIQUID RESIDUE IN FIRE DEBRIS SAMPLES UTILIZING TARGET FACTOR ANALYSIS.
Creator
McHugh, Kelly, Sigman, Michael, University of Central Florida
Abstract / Description
Current fire debris analysis procedure involves using the chromatographic patterns of total ion chromatograms, extracted ion chromatograms, and target compound analysis to identify an ignitable liquid according to the American Society for Testing and Materials (ASTM) E 1618 standard method. Classifying the ignitable liquid is accomplished by a visual comparison of chromatographic data obtained from any extracted ignitable liquid residue in the debris to the chromatograms of ignitable liquids...
Show moreCurrent fire debris analysis procedure involves using the chromatographic patterns of total ion chromatograms, extracted ion chromatograms, and target compound analysis to identify an ignitable liquid according to the American Society for Testing and Materials (ASTM) E 1618 standard method. Classifying the ignitable liquid is accomplished by a visual comparison of chromatographic data obtained from any extracted ignitable liquid residue in the debris to the chromatograms of ignitable liquids in a database, i.e. by visual pattern recognition. Pattern recognition proves time consuming and introduces potential for human error. One particularly difficult aspect of fire debris analysis is recognizing an ignitable liquid residue when the intensity of its chromatographic pattern is extremely low or masked by pyrolysis products. In this research, a unique approach to fire debris analysis was applied by utilizing the samplesÂÂ' total ion spectrum (TIS) to identify an ignitable liquid, if present. The TIS, created by summing the intensity of each ion across all elution times in a gas chromatography-mass spectrometry (GC-MS) dataset retains sufficient information content for the identification of complex mixtures . Computer assisted spectral comparison was then performed on the samplesÂÂ' TIS by target factor analysis (TFA). This approach allowed rapid automated searching against a library of ignitable liquid summed ion spectra. Receiver operating characteristic (ROC) curves measured how well TFA identified ignitable liquids in the database that were of the same ASTM classification as the ignitable liquid in fire debris samples, as depicted in their corresponding area under the ROC curve. This study incorporated statistical analysis to aid in classification of an ignitable liquid, therefore alleviating interpretive error inherent in visual pattern recognition. This method could allow an analyst to declare an ignitable liquid present when utilization of visual pattern recognition alone is not sufficient.
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Date Issued
2010
Identifier
CFE0003042, ucf:48337
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0003042
Selective Multivariate Applications in Forensic Science
Title
Selective Multivariate Applications in Forensic Science.
Creator
Rinke, Caitlin, Sigman, Michael, Campiglia, Andres, Yestrebsky, Cherie, Kuebler, Stephen, Richardson, Martin, University of Central Florida
Abstract / Description
A 2009 report published by the National Research Council addressed the need for improvements in the field of forensic science. In the report emphasis was placed on the need for more rigorous scientific analysis within many forensic science disciplines and for established limitations and determination of error rates from statistical analysis. This research focused on multivariate statistical techniques for the analysis of spectral data obtained for multiple forensic applications which include...
Show moreA 2009 report published by the National Research Council addressed the need for improvements in the field of forensic science. In the report emphasis was placed on the need for more rigorous scientific analysis within many forensic science disciplines and for established limitations and determination of error rates from statistical analysis. This research focused on multivariate statistical techniques for the analysis of spectral data obtained for multiple forensic applications which include samples from: automobile float glasses and paints, bones, metal transfers, ignitable liquids and fire debris, and organic compounds including explosives. The statistical techniques were used for two types of data analysis: classification and discrimination. Statistical methods including linear discriminant analysis and a novel soft classification method were used to provide classification of forensic samples based on a compiled library. The novel soft classification method combined three statistical steps: Principal Component Analysis (PCA), Target Factor Analysis (TFA), and Bayesian Decision Theory (BDT) to provide classification based on posterior probabilities of class membership. The posterior probabilities provide a statistical probability of classification which can aid a forensic analyst in reaching a conclusion. The second analytical approach applied nonparametric methods to provide the means for discrimination between samples. Nonparametric methods are performed as hypothesis test and do not assume normal distribution of the analytical figures of merit. The nonparametric permutation test was applied to forensic applications to determine the similarity between two samples and provide discrimination rates. Both the classification method and discrimination method were applied to data acquired from multiple instrumental methods. The instrumental methods included: Laser Induced-Breakdown Spectroscopy (LIBS), Fourier Transform Infrared Spectroscopy (FTIR), Raman spectroscopy, and Gas Chromatography-Mass Spectrometry (GC-MS). Some of these instrumental methods are currently applied to forensic applications, such as GC-MS for the analysis of ignitable liquid and fire debris samples; while others provide new instrumental methods to areas within forensic science which currently lack instrumental analysis techniques, such as LIBS for the analysis of metal transfers. The combination of the instrumental techniques and multivariate statistical techniques is investigated in new approaches to forensic applications in this research to assist in improving the field of forensic science.
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Date Issued
2012
Identifier
CFE0004628, ucf:49942
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0004628
LASER INDUCED BREAKDOWN SPECTROSCOPY FOR DETECTION OF ORGANIC RESIDUES: IMPACT OF AMBIENT ATMOSPHERE AND LASER PARAMETERS
Title
LASER INDUCED BREAKDOWN SPECTROSCOPY FOR DETECTION OF ORGANIC RESIDUES: IMPACT OF AMBIENT ATMOSPHERE AND LASER PARAMETERS.
Creator
Brown, Christopher, Richardson, Martin, University of Central Florida
Abstract / Description
Laser Induced Breakdown Spectroscopy (LIBS) is showing great potential as an atomic analytical technique. With its ability to rapidly analyze all forms of matter, with little-to-no sample preparation, LIBS has many advantages over conventional atomic emission spectroscopy techniques. With the maturation of the technologies that make LIBS possible, there has been a growing movement to implement LIBS in portable analyzers for field applications. In particular, LIBS has long been considered the...
Show moreLaser Induced Breakdown Spectroscopy (LIBS) is showing great potential as an atomic analytical technique. With its ability to rapidly analyze all forms of matter, with little-to-no sample preparation, LIBS has many advantages over conventional atomic emission spectroscopy techniques. With the maturation of the technologies that make LIBS possible, there has been a growing movement to implement LIBS in portable analyzers for field applications. In particular, LIBS has long been considered the front-runner in the drive for stand-off detection of trace deposits of explosives. Thus there is a need for a better understanding of the relevant processes that are responsible for the LIBS signature and their relationships to the different system parameters that are helping to improve LIBS as a sensing technology. This study explores the use of LIBS as a method to detect random trace amounts of specific organic materials deposited on organic or non-metallic surfaces. This requirement forces the limitation of single-shot signal analysis. This study is both experimental and theoretical, with a sizeable component addressing data analysis using principal components analysis to reduce the dimensionality of the data, and quadratic discriminant analysis to classify the data. In addition, the alternative approach of 'target factor analysis' was employed to improve detection of organic residues on organic substrates. Finally, a new method of characterizing the laser-induced plasma of organics, which should lead to improved data collection and analysis, is introduced. The comparison between modeled and experimental measurements of plasma temperatures and electronic density is discussed in order to improve the present models of low-temperature laser induced plasmas.
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Date Issued
2011
Identifier
CFE0003708, ucf:48843
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0003708