Description of original award (Fiscal Year 2018, $726,344)
The overarching goal of this study is to enhance prosecution of strangulation crimes by strengthening the scientific validity of interpretation of forensic findings. This proposal uses machine learning and other sophisticated statistical modeling techniques to enhance court- based decision-making in the investigation and/or prosecution of crimes involving strangulation. Probabilistic modeling will be used to quantify the certainty/uncertainty that a constellation of injury patterns are suggestive of strangulation by making data-based comparisons of assaults against women with and without reported strangulation. Data will come from forensic exams of strangulation and non-strangulation cases from forensic nurse examiner programs in Virginia (N=1,050 since 2017) and Arizona (N=18,000 since 1998). This project will develop and disseminate guidelines for forensic examiners, particularly forensic nurse examiners, to use in understanding and applying the findings from this study in evidentiary proceedings. "Note: This project contains a research and/or development component, as defined in applicable law," and complies with Part 200 Uniform Requirements - 2 CFR 200.210(a)(14). ca/ncf.
- Computerized System for Aiding the Expert in Evaluating the Degree of Certainty in 2D Shoeprints
- Improvements to Laser Ablation-Inductively Coupled Plasma-Mass Spectrometry for Quantitative Forensic Analysis Using a Short Pulse (100 Femtosecond) Ultraviolet Laser
- One Pot Effluent Characterization and Standoff Detection Feasibility