The Experts below are selected from a list of 3948 Experts worldwide ranked by ideXlab platform
Mark Sandercock - One of the best experts on this subject based on the ideXlab platform.
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search prefilters for mid infrared absorbance spectra of clear coat automotive paint smears using stacked and linear classifiers
Journal of Chemometrics, 2014Co-Authors: Barry K Lavine, Ayuba Fasasi, Nikhil Mirjankar, Mark Sandercock, Steven D BrownAbstract:By using stacked partial least squares classifiers and genetic algorithms for feature selection and classification, it is demonstrated that search prefilters can be developed to extract Investigative Lead information from clear coat paint smears. The results obtained in this study also show that identifying specific wavelengths or wavelet coefficients in IR spectral data is superior to identifying informative wavelength windows when applying pattern recognition techniques to IR spectra from the paint data query (PDQ) database when differentiating paint samples by assembly plant. Search prefilters developed using specific wavelengths or wavelet coefficients outperformed search prefilters that utilized spectral regions. Clear coat paint spectra from the PDQ database may not be well suited for stacking as there are few spectral intervals that can reliably distinguish the different sample groups (i.e., assembly plants) in the data. The information contained in the IR spectra about assembly plant may not be highly compartmentalized in an interval, which also works against stacking. The similarity of the IR spectra within a plant group and the noise present in the IR spectra may also be obscuring information present in spectral intervals. Copyright © 2014 John Wiley & Sons, Ltd.
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wavelets and genetic algorithms applied to search prefilters for spectral library matching in forensics
Talanta, 2011Co-Authors: Barry K Lavine, Nikhil Mirjankar, Scott Ryland, Mark SandercockAbstract:Currently, the identification of the make, model and year of a motor vehicle involved in a hit and run collision from only a clear coat paint smear left at a crime scene is not possible. Search prefilters for searching infrared (IR) spectral libraries of the paint data query (PDQ) automotive database to differentiate between similar but nonidentical Fourier transform infrared (FTIR) paint spectra are proposed. Applying wavelets, FTIR spectra of clear coat paint smears can be denoised and deconvolved by decomposing each spectrum into wavelet coefficients which represent the sample's constituent frequencies. A genetic algorithm for pattern recognition analysis is used to identify wavelet coefficients for underdetermined data that are characteristic of the model and manufacturer of the automobile from which the spectra of the clear coats were obtained. Even in challenging trials where the samples evaluated were all the same manufacturer (Chrysler) with a limited production year range, the respective models and manufacturing plants were correctly identified. Search prefilters for spectral library matching are necessary to extract Investigative Lead information from a clear coat paint smear; unlike the undercoat and color coat paint layers, which can be identified using the text based portion of the PDQ database.
Barry K Lavine - One of the best experts on this subject based on the ideXlab platform.
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search prefilters for mid infrared absorbance spectra of clear coat automotive paint smears using stacked and linear classifiers
Journal of Chemometrics, 2014Co-Authors: Barry K Lavine, Ayuba Fasasi, Nikhil Mirjankar, Mark Sandercock, Steven D BrownAbstract:By using stacked partial least squares classifiers and genetic algorithms for feature selection and classification, it is demonstrated that search prefilters can be developed to extract Investigative Lead information from clear coat paint smears. The results obtained in this study also show that identifying specific wavelengths or wavelet coefficients in IR spectral data is superior to identifying informative wavelength windows when applying pattern recognition techniques to IR spectra from the paint data query (PDQ) database when differentiating paint samples by assembly plant. Search prefilters developed using specific wavelengths or wavelet coefficients outperformed search prefilters that utilized spectral regions. Clear coat paint spectra from the PDQ database may not be well suited for stacking as there are few spectral intervals that can reliably distinguish the different sample groups (i.e., assembly plants) in the data. The information contained in the IR spectra about assembly plant may not be highly compartmentalized in an interval, which also works against stacking. The similarity of the IR spectra within a plant group and the noise present in the IR spectra may also be obscuring information present in spectral intervals. Copyright © 2014 John Wiley & Sons, Ltd.
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wavelets and genetic algorithms applied to search prefilters for spectral library matching in forensics
Talanta, 2011Co-Authors: Barry K Lavine, Nikhil Mirjankar, Scott Ryland, Mark SandercockAbstract:Currently, the identification of the make, model and year of a motor vehicle involved in a hit and run collision from only a clear coat paint smear left at a crime scene is not possible. Search prefilters for searching infrared (IR) spectral libraries of the paint data query (PDQ) automotive database to differentiate between similar but nonidentical Fourier transform infrared (FTIR) paint spectra are proposed. Applying wavelets, FTIR spectra of clear coat paint smears can be denoised and deconvolved by decomposing each spectrum into wavelet coefficients which represent the sample's constituent frequencies. A genetic algorithm for pattern recognition analysis is used to identify wavelet coefficients for underdetermined data that are characteristic of the model and manufacturer of the automobile from which the spectra of the clear coats were obtained. Even in challenging trials where the samples evaluated were all the same manufacturer (Chrysler) with a limited production year range, the respective models and manufacturing plants were correctly identified. Search prefilters for spectral library matching are necessary to extract Investigative Lead information from a clear coat paint smear; unlike the undercoat and color coat paint layers, which can be identified using the text based portion of the PDQ database.
Nikhil Mirjankar - One of the best experts on this subject based on the ideXlab platform.
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search prefilters for mid infrared absorbance spectra of clear coat automotive paint smears using stacked and linear classifiers
Journal of Chemometrics, 2014Co-Authors: Barry K Lavine, Ayuba Fasasi, Nikhil Mirjankar, Mark Sandercock, Steven D BrownAbstract:By using stacked partial least squares classifiers and genetic algorithms for feature selection and classification, it is demonstrated that search prefilters can be developed to extract Investigative Lead information from clear coat paint smears. The results obtained in this study also show that identifying specific wavelengths or wavelet coefficients in IR spectral data is superior to identifying informative wavelength windows when applying pattern recognition techniques to IR spectra from the paint data query (PDQ) database when differentiating paint samples by assembly plant. Search prefilters developed using specific wavelengths or wavelet coefficients outperformed search prefilters that utilized spectral regions. Clear coat paint spectra from the PDQ database may not be well suited for stacking as there are few spectral intervals that can reliably distinguish the different sample groups (i.e., assembly plants) in the data. The information contained in the IR spectra about assembly plant may not be highly compartmentalized in an interval, which also works against stacking. The similarity of the IR spectra within a plant group and the noise present in the IR spectra may also be obscuring information present in spectral intervals. Copyright © 2014 John Wiley & Sons, Ltd.
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wavelets and genetic algorithms applied to search prefilters for spectral library matching in forensics
Talanta, 2011Co-Authors: Barry K Lavine, Nikhil Mirjankar, Scott Ryland, Mark SandercockAbstract:Currently, the identification of the make, model and year of a motor vehicle involved in a hit and run collision from only a clear coat paint smear left at a crime scene is not possible. Search prefilters for searching infrared (IR) spectral libraries of the paint data query (PDQ) automotive database to differentiate between similar but nonidentical Fourier transform infrared (FTIR) paint spectra are proposed. Applying wavelets, FTIR spectra of clear coat paint smears can be denoised and deconvolved by decomposing each spectrum into wavelet coefficients which represent the sample's constituent frequencies. A genetic algorithm for pattern recognition analysis is used to identify wavelet coefficients for underdetermined data that are characteristic of the model and manufacturer of the automobile from which the spectra of the clear coats were obtained. Even in challenging trials where the samples evaluated were all the same manufacturer (Chrysler) with a limited production year range, the respective models and manufacturing plants were correctly identified. Search prefilters for spectral library matching are necessary to extract Investigative Lead information from a clear coat paint smear; unlike the undercoat and color coat paint layers, which can be identified using the text based portion of the PDQ database.
Scott Ryland - One of the best experts on this subject based on the ideXlab platform.
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wavelets and genetic algorithms applied to search prefilters for spectral library matching in forensics
Talanta, 2011Co-Authors: Barry K Lavine, Nikhil Mirjankar, Scott Ryland, Mark SandercockAbstract:Currently, the identification of the make, model and year of a motor vehicle involved in a hit and run collision from only a clear coat paint smear left at a crime scene is not possible. Search prefilters for searching infrared (IR) spectral libraries of the paint data query (PDQ) automotive database to differentiate between similar but nonidentical Fourier transform infrared (FTIR) paint spectra are proposed. Applying wavelets, FTIR spectra of clear coat paint smears can be denoised and deconvolved by decomposing each spectrum into wavelet coefficients which represent the sample's constituent frequencies. A genetic algorithm for pattern recognition analysis is used to identify wavelet coefficients for underdetermined data that are characteristic of the model and manufacturer of the automobile from which the spectra of the clear coats were obtained. Even in challenging trials where the samples evaluated were all the same manufacturer (Chrysler) with a limited production year range, the respective models and manufacturing plants were correctly identified. Search prefilters for spectral library matching are necessary to extract Investigative Lead information from a clear coat paint smear; unlike the undercoat and color coat paint layers, which can be identified using the text based portion of the PDQ database.
Heather Miller Coyle - One of the best experts on this subject based on the ideXlab platform.
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JScholar Publishers Cold Case Homicide with Paternity as an Investigative Lead (People of State
2015Co-Authors: Kayla Baylor, Heather Miller CoyleAbstract:jury convicted a forty three year old Flor-ida man of murder for the death of a Bronx man in Febru-ary 1994, fifteen years after the incident [1]. Louis Moscatelli was found murdered at his home on 2553 Tendroeck Avenue where he was stabbed thirty nine times and had his throat slit during a fight and struggle. The victim has been heard shout-ing “no, Bob, don’t hit me ” for approximately twenty minutes before the neighbourhood became silent again. The first scene of the crime was in the bathroom where the victim was found. In the dining room area, there was blood from an ashtray and three bloodlike stains from the floor were collected for further analysis. A trail of blood led out the door, droplets of blood were found on the concrete walk outside and at the second scene at 2559 Tendroek Avenue where bloodstains were locat-ed on the shower curtain and bath mat. The main question i
