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Raman Spectroscopic Examination of B...
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Mistek, Ewelina M.
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Raman Spectroscopic Examination of Bloodstains for Forensic Purposes: Background and Race Determination.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Raman Spectroscopic Examination of Bloodstains for Forensic Purposes: Background and Race Determination./
作者:
Mistek, Ewelina M.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2019,
面頁冊數:
98 p.
附註:
Source: Masters Abstracts International, Volume: 80-11.
Contained By:
Masters Abstracts International80-11.
標題:
Chemistry. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13879487
ISBN:
9781392154663
Raman Spectroscopic Examination of Bloodstains for Forensic Purposes: Background and Race Determination.
Mistek, Ewelina M.
Raman Spectroscopic Examination of Bloodstains for Forensic Purposes: Background and Race Determination.
- Ann Arbor : ProQuest Dissertations & Theses, 2019 - 98 p.
Source: Masters Abstracts International, Volume: 80-11.
Thesis (M.S.)--State University of New York at Albany, 2019.
This item must not be sold to any third party vendors.
Chapter 1 of this thesis critically overviews recent developments in forensic trace evidence analysis since 2016. It covers improvements to existing techniques as well as new methods for the analysis of fibers, hair, paint, glass, gunshot residue (GSR), and explosives.Chapter 2 of this thesis shows the results of an experimental work on race differentiation by Raman spectroscopy of a bloodstain for forensic purposes. Bearing in mind forensic purposes, a nondestructive and rapid method was developed for race differentiation of peripheral blood donors. Blood is an extremely valuable form of evidence in forensic investigations so proper analysis is critical. Because potentially miniscule amounts of blood traces can be found at a crime scene, having a method that is nondestructive, and provides a substantial amount of information about the sample, is ideal. In this study Raman spectroscopy was applied with advanced statistical analysis to discriminate between Caucasian (CA) and African American (AA) donors based on dried peripheral blood traces. Spectra were collected from 20 donors varying in gender and age. Support vector machines discriminant analysis (SVMDA) was used for differentiation of the two races. An outer loop subject-wise cross-validation (CV) method evaluated the performance of the SVM classifier for each individual donor from the training data set. The performance of SVMDA, evaluated by the area under the curve (AUC) metric, showed 83% probability of correct classification for both races, and a specificity and sensitivity of 80%. This preliminary study shows promise for distinguishing between different races of human blood. The method has great potential for real crime scene investigation, providing rapid and reliable results, with no sample preparation, destruction, or consumption.
ISBN: 9781392154663Subjects--Topical Terms:
516420
Chemistry.
Subjects--Index Terms:
Bloodstains
Raman Spectroscopic Examination of Bloodstains for Forensic Purposes: Background and Race Determination.
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Chapter 1 of this thesis critically overviews recent developments in forensic trace evidence analysis since 2016. It covers improvements to existing techniques as well as new methods for the analysis of fibers, hair, paint, glass, gunshot residue (GSR), and explosives.Chapter 2 of this thesis shows the results of an experimental work on race differentiation by Raman spectroscopy of a bloodstain for forensic purposes. Bearing in mind forensic purposes, a nondestructive and rapid method was developed for race differentiation of peripheral blood donors. Blood is an extremely valuable form of evidence in forensic investigations so proper analysis is critical. Because potentially miniscule amounts of blood traces can be found at a crime scene, having a method that is nondestructive, and provides a substantial amount of information about the sample, is ideal. In this study Raman spectroscopy was applied with advanced statistical analysis to discriminate between Caucasian (CA) and African American (AA) donors based on dried peripheral blood traces. Spectra were collected from 20 donors varying in gender and age. Support vector machines discriminant analysis (SVMDA) was used for differentiation of the two races. An outer loop subject-wise cross-validation (CV) method evaluated the performance of the SVM classifier for each individual donor from the training data set. The performance of SVMDA, evaluated by the area under the curve (AUC) metric, showed 83% probability of correct classification for both races, and a specificity and sensitivity of 80%. This preliminary study shows promise for distinguishing between different races of human blood. The method has great potential for real crime scene investigation, providing rapid and reliable results, with no sample preparation, destruction, or consumption.
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http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13879487
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