An Open-Source Implementation of the CMPS Algorithm for Assessing Similarity of Bullets

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2022
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Ju, Wangqian
Hofmann, Heike
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Copyright 2022 The R Foundation
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Statistics

The Department of Statistics seeks to teach students in the theory and methodology of statistics and statistical analysis, preparing its students for entry-level work in business, industry, commerce, government, or academia.

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The Department of Statistics was formed in 1948, emerging from the functions performed at the Statistics Laboratory. Originally included in the College of Sciences and Humanities, in 1971 it became co-directed with the College of Agriculture.

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1948-present

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Center for Statistics and Applications in Forensic Evidence
The Center for Statistics and Applications in Forensic Evidence (CSAFE) carries out research on the scientific foundations of forensic methods, develops novel statistical methods and transfers knowledge and technological innovations to the forensic science community. We collaborate with more than 80 researchers and across six universities to drive solutions to support our forensic community partners with accessible tools, open-source databases and educational opportunities.
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In this paper, we introduce the R package cmpsR, an open-source implementation of the Congruent Matching Profile Segments (CMPS) method developed at the National Institute of Standards and Technology (NIST) for objective comparison of striated tool marks. The functionality of the package is showcased by examples of bullet signatures that come with the package. Graphing tools are implemented in the package as well for users to assess and understand the CMPS results. Initial tests were performed on bullet signatures generated from two sets of 3D scans in the Hamby study under the framework suggested by the R package bulletxtrctr. New metrics based on CMPS scores are introduced and compared with existing metrics. A measure called sum of squares ratio is included, and how it can be used for evaluating different scans, metrics, or parameters is showcased with the Hamby study data sets. An open-source implementation of the CMPS algorithm makes the algorithm more accessible, generates reproducible results, and facilitates further studies of the algorithm such as method comparisons.
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This article is published as Ju & Hofmann, "The R Journal: An Open-Source Implementation of the CMPS Algorithm for Assessing Similarity of Bullets", The R Journal, 2022. doi:10.32614/RJ-2022-035. Posted with permission of CSAFE.

This article is under the Creative Commons Attribution 4.0 International license (CC BY 4.0, http://creativecommons.org/licenses/by/4.0/).
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