Krishnan Ganesh, Hofmann Heike
Department of Statistics, Iowa State University and CSAFE (Center for Statistics and Applications in Forensic Evidence), Iowa State University, 195 Durham, 613 Morril Road, Ames, IA, 50010, United States.
J Forensic Sci. 2019 May;64(3):728-740. doi: 10.1111/1556-4029.13950. Epub 2018 Nov 16.
The same-source problem remains a major challenge in forensic toolmark and firearm examination. Here, we investigate the applicability of the Chumbley method (J Forensic Sci, 2018, 63, 849; J Forensic Sci, 2010, 55, 953) (10,12), developed for screwdriver markings, for same-source identification of striations on bullet LEAs. The Hamby datasets 44 and 252 measured by NIST and CSAFE (high-resolution scans) are used here. We provide methods to identify parameters that minimize error rates for matching of LEAs, and a remedial algorithm to alleviate the problem of failed tests, while increasing the power of the test and reducing error rates. For 85,491 land-to-land comparisons (84,235 known nonmatches and 1256 known matches), the adapted test does not provide a result in 176 situations (originally more than 500). The Type I and Type II error rates are 7.2% (6105 out of 84,235) and 21.4% (271 out of 1256), respectively. This puts the proposed method on similar footing as other single-feature matching approaches in the literature.
同源问题仍然是法医工具痕迹和枪支检验中的一个重大挑战。在此,我们研究了为螺丝刀痕迹开发的Chumbley方法(《法医科学杂志》,2018年,63卷,849页;《法医科学杂志》,2010年,55卷,953页)(10,12)在子弹LEA上条纹同源识别中的适用性。这里使用了由美国国家标准与技术研究院(NIST)和CSAFE测量的Hamby数据集44和252(高分辨率扫描)。我们提供了识别参数的方法,这些参数可将LEA匹配的错误率降至最低,并提供一种补救算法来缓解测试失败的问题,同时提高测试的效力并降低错误率。对于85491次膛线对膛线的比较(84235次已知不匹配和1256次已知匹配),改进后的测试在176种情况下未得出结果(原超过500种)。I型和II型错误率分别为7.2%(84235次中有6105次)和21.4%(1256次中有271次)。这使得所提出的方法与文献中其他单特征匹配方法处于类似水平。