Experimental results on data analysis algorithms for extracting and interpreting edge feature data for duct tape and textile physical fit examinations.

A physical fit is an important observation that can result from the forensic analysis of trace evidence as it conveys a high degree of association between two items. However, physical fit examinations can be time-consuming, and potential bias from analysts may affect judgment. To overcome these shortcomings, a data analysis algorithm using mutual information and a decision tree has been developed to support practitioners in interpreting the evidence. We created these tools using data obtained from physical fit examinations of duct tape and textiles analyzed in previous studies, along with the reasoning behind the analysts' decisions. The relative feature importance is described by material type, enhancing the knowledge base in this field. Compared with the human analysis, the algorithms provided accuracies above 90%, with an improved rate of true positives for most duct tape subsets. Conversely, false positives were observed in high-quality scissor cut (HQ-HT-S) duct tape and textiles. As such, it is advised to use these algorithms in tandem with human analysis. Furthermore, the study evaluated the accuracy of physical fits when only partial sample lengths are available. The results of this investigation indicated that acceptable accuracies for correctly identifying true fits and non-fits occurred when at least 35% of a sample length was present. However, lower accuracies were observed for samples prone to stretching or distortion. Therefore, the models described here can provide a valuable supplementary tool but should not be the sole means of evaluating samples.

Assessing physical fit examinations of stabbed and torn textiles through a large dataset of casework-like items and interlaboratory studies.

Several organizations have outlined the need for standardized methods for conducting physical fit comparisons. This study answers this call by developing and evaluating a systematic and transparent approach for examining, documenting, and interpreting textile physical fits, using qualitative feature descriptors and a quantitative metric (Edge Similarity Score, ESS) for the physical fit examination of textile materials. Here, the results from 1027 textile physical fit comparisons are reported. This includes the evaluation of inter and intraanalyst variation when using this method for hand-torn and stabbed fabrics. ESS higher than 80% and ESS lower than 20%, respectively, support fit and nonfit conclusions. The results show that analyst accuracy ranges from 88% to 100% when using this criterion. The estimated false-positive rate for this dataset (2% false positives, 10 of 477 true nonfit pairs) demonstrates the importance of assessing the quality of a physical fit during an examination and reveals that potential errors are low, but possible in textile physical fit examinations. The risk of error must be accounted for in the interpretation and verification processes. Further analysis shows that factors such as the separation method, construction, and design of the samples do not substantially influence the ESS values. Additionally, the proposed method is independently evaluated by 15 practitioners in an interlaboratory exercise that demonstrates satisfactory reproducibility between participants. The standardized terminology and documentation criteria are the first steps toward validating approaches to streamline the peer review process, minimize bias and subjectivity, and convey the probative value of the evidence.

Using convolutional neural networks to support examiners in duct tape physical fit comparisons.

This paper describes the construction and use of a machine-learning model to provide objective support for a physical fit examination of duct tapes. We present the ForensicFit package that can preprocess and database raw tape images. Using the processed tape image, we trained a convolutional neural network to compare tape edges and predict membership scores (i.e., fit or non-fit category). A dataset of nearly 2000 tapes and 4000 images was evaluated, including various quality grades: low, medium, and high, as well as two separation methods, scissor-cut and hand-torn. The model predicts medium-quality and high-quality scissor-cut tape more accurately than hand-torn, whereas for low-quality tape predicts the hand-torn tapes more accurately. These results are consistent with previous studies performed on the same datasets by analyst examinations. A method of pixel importance was also implemented to show which pixels are used to make the decision. This method can confirm some fit features that correspond with analyst-identified features, like edge morphology and backing pattern. This pilot study demonstrates the feasibility of computational algorithms to build physical fit databases and automated comparisons using deep neural networks, which can be used as a model for other materials.

Technical Note: Intra-pane refractive index variability and adequate sample sizes in forensic glass analysis.

A vital aspect for the forensic analysis of glass using refractive index (RI) is the determination of adequate sample size, or how many glass fragments are needed to sufficiently characterize the RI from a source of glass, such as a side window of an automobile. The number of fragments required is inversely related to the variance of the RI across the source of glass. Previous literature indicates decreased variability across tempered glass panes over time of manufacture; however, the most recent work is over two decades old and may not reflect potential increased homogeneity in more modern glass. A set of 218 tempered vehicle windows was constructed and 30 different edge RI measurements were gathered from ten bulk fragments of each window. Variability analysis was conducted using a linear mixed effects model. Within-source (between-fragments) and within-fragment variances were found to be similar (approximately 4.3e-5 and 4.7e-5) and relatively lower than previous studies have reported. Simulation studies were also conducted, estimating the error rates based on the comparison conclusions of the sample set. 21 RI measurements were taken from seven randomly selected glass fragments of one window to characterize the "known" source and either nine RI measurements (three fragments, each taken from separate tempered dice) or three RI measurements (one fragment) were used to characterize the "recovered" source. The conclusion of the comparisons where nine and 21 RI measurements were used yielded a lower false exclusion rate (approximately 1.97%) as compared to three and 21 RI measurements (6.73%), while the false inclusion rate remained mostly stable regardless of recovered glass sample size (approximately 4.05%).

Assessing significant factors that can influence physical fit examinations - Part I. Physical fits of torn and cut duct tapes.

This study expands upon a previously developed method that quantifies the similarity of the compared tape edges by systematically studying the effect of several separation methods and tape grades on the quality of a fit. Analysts examined more than 3300 pairs of hand-torn or scissor-cut duct tapes from three different tape grades while they were kept blind from the ground truth to minimize bias. The samples were examined following a three-step methodology: 1) qualitative assessment of the overall edge alignment and description of edge pattern, 2) macroscopic evaluation of the edges' features, 3) bin by bin subunit assessment of tape edges and estimation of the edge similarity score. A report template was designed to maintain records of the decision-making process. In the second and third steps, eight comparison features were defined and documented using auto-populated cell options. Generally, misidentification rates were low, with no false positives reported. Coinciding with previous research, low scores (under 20%) provided the most support for a non-fit conclusion, while high scores (80% or higher) supported a fit conclusion. A statistical analysis of the separation method and quality of tape revealed a potential interaction between these factors and showed that they significantly impact the edge scores for true fitting pairs, but not the true non-fits' scores. The developed comparison and documentation criteria can assist practitioners with a more straightforward, consistent, and transparent interpretation and reporting approach.

Consensus on validation of forensic voice comparison.

Since the 1960s, there have been calls for forensic voice comparison to be empirically validated under casework conditions. Since around 2000, there have been an increasing number of researchers and practitioners who conduct forensic-voice-comparison research and casework within the likelihood-ratio framework. In recent years, this community of researchers and practitioners has made substantial progress toward validation under casework conditions becoming a standard part of practice: Procedures for conducting validation have been developed, along with graphics and metrics for representing the results, and an increasing number of papers are being published that include empirical validation of forensic-voice-comparison systems under conditions reflecting casework conditions. An outstanding question, however, is: In the context of a case, given the results of an empirical validation of a forensic-voice-comparison system, how can one decide whether the system is good enough for its output to be used in court? This paper provides a statement of consensus developed in response to this question. Contributors included individuals who had knowledge and experience of validating forensic-voice-comparison systems in research and/or casework contexts, and individuals who had actually presented validation results to courts. They also included individuals who could bring a legal perspective on these matters, and individuals with knowledge and experience of validation in forensic science more broadly. We provide recommendations on what practitioners should do when conducting evaluations and validations, and what they should present to the court. Although our focus is explicitly on forensic voice comparison, we hope that this contribution will be of interest to an audience concerned with validation in forensic science more broadly. Although not written specifically for a legal audience, we hope that this contribution will still be of interest to lawyers.

Reply to Response to Vacuous standards - Subversion of the OSAC standards-development process.

This Letter to the Editor is a reply to Mohammed et al. (2021) https://doi.org/10.1016/j.fsisyn.2021.100145, which in turn is a response to Morrison et al. (2020) "Vacuous standards - subversion of the OSAC standards-development process" https://doi.org/10.1016/j.fsisyn.2020.06.005.

Vacuous standards - Subversion of the OSAC standards-development process.

In the context of development of standards for forensic science, particularly standards initially developed by the U.S. Organization of Scientific Area Committees for Forensic Science (OSAC), this perspective paper raises concern about the publication of vacuous standards. Vacuous standards generally state few requirements; the requirements they do state are often vague; compliance with their stated requirements can be achieved with little effort - the bar is set very low; and compliance with their stated requirements would not be sufficient to lead to scientifically valid results. This perspective paper proposes a number of requirements that we believe would be essential in order for a standard on validation of forensic-science methods to be fit for purpose.

Differential analysis of very small particles (VSP) from the contact surfaces and recessed areas of footwear.

Prior work has shown that the contact surfaces of footwear rapidly lose very small particles (VSP) when walking on dry soil. Other research, with more general sampling from shoe soles, has shown that particles can persist much longer. Given rapid losses from contact surfaces, we hypothesize that non-contact, recessed areas of footwear retain particles from prior exposures. Here we conduct differential analysis of VSP recovered separately from contact and recessed surfaces, following a controlled series of environmental exposures. Work boots and tennis shoes were exposed by walking distances of 250 m, sequentially, in three environmental sites. VSP were harvested separately from contact and recessed surfaces using a moist swabbing procedure. VSP were analyzed by microscopy and the proportions attributable to each site were determined using a newly developed statistical model. The principal findings are (1) contact surfaces of footwear are dominated by VSP attributable to the most recent site of exposure, (2) recessed surfaces of footwear retain VSP from prior exposures, (3) sole type appears to be a source of major differences in the amount of VSP from prior exposures remaining in recessed areas, and (4) when VSP attributable to prior exposures are found, there is no clear trend for dominance between earlier exposures. The significance of these findings is considerable. In cases where the last site visited is of interest, VSP from contact surfaces of footwear will give a nearly pure sample of that site. In cases where prior sites visited are of interest, the VSP from the contact surfaces can be used as a background signal, providing a means for differential analysis of VSP mixtures found in the recessed areas of the sole. The strong influence of shoe sole type on the retention of VSP from prior exposures indicates that efforts to explore the rates of VSP loss from recessed areas will need to take characteristics of the sole type into account. The absence of a clear trend for dominance between earlier exposures suggests that once traces are lodged within the recessed areas of footwear soles they can be retained for long periods of time. These findings support prior research on the retention of particles on footwear that shows periods of long retention following rapid initial losses of trace materials. The differential analysis of VSP is a significant contribution to the methods available for the deconvolution of particle mixtures into fractions that are characteristic of their contributing sources.

Rates of loss and replacement of very small particles (VSP) on the contact surfaces of footwear during successive exposures.

It has previously been shown that a walk of 250 m (approximately 175 steps/shoe) in a new environment is sufficient to remove and replace particles present on the contact surfaces of footwear. However, it is unknown how quickly this replacement occurs. This paper describes experiments measuring how quickly (in terms of steps) this loss and replacement of VSP occurs. Three environmental exposure sites were chosen to have different, characteristic particle types (soil minerals). Footwear of two types (work boots and tennis shoes) were tested, accumulating particles by walking 250 m in one site, followed by walking a designated number of steps (per shoe) in a second site. Very small particles (VSP) were harvested from contact surfaces of the footwear (those surfaces in direct contact with the ground when walking) using a moist swabbing procedure. The resulting numbers and types of VSP were determined using forensic microscopy and the proportions of VSP attributable to the first and second site were determined by particle combination analysis using a latent Dirichlet allocation model. The principal findings from this study are (1) that the contact surfaces of footwear are dominated by VSP attributable to the most recent site of exposure, (2) that walking in a new location rapidly removes and replaces VSP from the contact surfaces of footwear, (3) major replacement occurs in 5 to 10 steps and nearly complete replacement occurs by 25 steps, (4) the character of the loading site may influence the initial rate of loss and replacement of VSP (during the first five steps), and (5) overall, the loss and replacement of VSP on footwear in these experiments can be reasonably described by the relationship 1/(Steps + 2.68). The significance of these findings is considerable. In cases where the last site visited is of interest, VSP from contact surfaces of footwear will give a nearly pure sample of that site. In cases where prior sites visited are of interest, the VSP from the contact surfaces can be used as a background signal, providing a necessary beginning for efforts to resolve mixtures of VSP arising from different exposures. The usefulness of VSP on footwear evidence depends on developing this ability so that a reliable, relevant evidentiary "signal" can be separated from background noise (or signals from other exposures).

Discrimination and classification among common items of evidence using particle combination profiles.

This project used established analytical tools and statistical methods to determine the evidential value of very small particle (VSP) profiles found on handguns, cell phones, drug packaging, and ski masks. Sampling protocols were designed, tested and used to sample VSP from evidence items from a single county-level crime laboratory: 30 handguns, 31 cell phones, 36 drug packaging specimens and 32 ski masks. Specimens were prepared for analysis employing established protocols for semi-automated scanning electron microscopy with elemental characterization by energy dispersive x-ray analysis (SEM/EDS). Statistical methods of particle combination analysis were applied to (1) remove particle "noise" from the datasets, (2) define a set of highly discriminating target particle types, (3) measure the strength of correspondence between profiles, and (4) measure the potential of VSP as an evidence type under defined experimental conditions. Most (84%) of the VSP specimens recovered from common evidence items showed sufficient variety and complexity in their VSP profiles to allow meaningful classification among closed sets of approximately 30 specimens. Correct associations were achieved for 93.5% of test specimens (drug packaging: 97.2%; cell phones: 92.6%; handguns: 92.9%; ski masks 88.2%). Test specimens with VSP numbers greater than 125 showed predominantly correct classifications. These findings establish (1) that VSP are present on the surfaces common items of physical evidence, (2) that the VSP can be efficiently recovered, prepared and analyzed by computer-assisted SEM/EDS analysis, (3) that the variety of particles is sufficient for the definition of classifiers based on reference sources, and (4) that the classifiers perform very well for these particle sets, showing that VSP recovery, analytical methods and computational methods are working effectively. The use of adhering VSP to establish quantitative associations among items of physical evidence is a new approach, exploiting a form of trace evidence that is typically ignored. It is highly significant for its potential to expand the number of cases to which trace evidence can meaningfully contribute and for its ability to include a quantitative statistical approach to data interpretation.

An argument against presenting interval quantifications as a surrogate for the value of evidence.

In the various forensic science disciplines, recent analytical developments paired with modern statistical computational tools have led to the proliferation of adhoc techniques for quantifying the probative value of forensic evidence. Many legal and scientific scholars agree that the value of evidence should be reported as a likelihood ratio or a Bayes Factor. Quantifying the probative value of forensic evidence is subjected to many sources of variability and uncertainty. There is currently a debate on how to characterize the reliability of the value of evidence. Some authors have proposed associating a confidence/credible interval with the value of evidence assigned to a collection of forensic evidence. In this paper, we will discuss the reasons for our opinion that interval quantifications for the value of evidence should not be used directly in the Bayesian decision-making process to determine the support of the evidence for one of the two competing hypotheses.

Determination of AFIS "sufficiency" in friction ridge examination.

Fingerprints have been used with considerable success over the past century in multiple civil government, law enforcement and criminal investigation applications. Since the 1970s, computer assisted systems (AFIS - Automated Fingerprint Identification System) have been increasingly used to automatically compare fingerprints and propose associations between multiple friction ridge impressions of known or unknown sources. AFIS were initially entirely subordinated to human examiners. Improvements in the matching algorithms and workload considerations have pushed agencies to implement completely automated processes, known as "Lights-out" modes, where AFIS's render unsupervised conclusions on the donors of the queries. Such fully automated process is common for tenprint-to-tenprint comparisons; however it is currently not being widely adopted for other types of comparisons, such as latent print-to-tenprint comparisons. In this paper, we explore a statistical model that can be used to facilitate the latent print examination workflow by predicting whether any latent print should be searched in AFIS. In particular, we are interested in preventing poor quality latent prints to be searched in vain, and thus unnecessarily consume resources. Ultimately, we show that our model could be used to efficiently manage workflow and workload by categorizing latent prints as a function of the quality and quantity of information that can be observed on them, which enables examiners to select the most appropriate examination and quality assurance processes for each print.

Exploitation of very small particles to enhance the probative value of carpet fibers.

Environmentally acquired very small particles (VSP), present on the surfaces of carpet fibers, have shown potential for the association of fibers with their carpet source. To unlock this potential, research is required addressing a number of areas, including the application of methods under realistic casework conditions and the utilization of computational methods for the refinement and testing of the approach. In this work field collections of carpet fibers were conducted by crime scene practitioners under realistic casework conditions. VSP were isolated using previously developed methods, and analyses were conducted using SEM/EDS analytical protocols in an operational crime laboratory setting. Computational methods were designed, allowing sets of hundreds to thousands of VSP to be characterized. Classifiers were designed to associate and discriminate among specimens. These classifiers were applied to the VSP data for specimens collected by crime scene practitioners, as well as to a previously collected research dataset. Quantitative measures of correspondence and probative value were designed based on the classification measures and successfully applied to both sets of VSP data. Particle sets larger than 500 showed strong promise for quantitative associations with their sources. The use of larger numbers of target particle types (TPTs) showed strong promise to improve the performance of classification and association. Overall, the usefulness of VSP to provide objective, quantitative associations has been established. Because VSP are acquired post-manufacture, these methods can address fundamental limitations to probative value that arise when class characteristics, determined by manufacture, are shared among mass produced commodities. These findings are of broad significance for the future of trace evidence analysis. The results of this research are likely extendable, with minor modifications, to other trace evidence types (such as glass, tape and human hair), and are expected to contribute significantly for those types of trace evidence that have long been considered of low evidential value (such as undyed cotton and animal hairs). Furthermore, entirely new approaches to trace evidence are enabled by exploiting VSP profiles, such as comparing different types of trace evidence with one another and comparing VSP defined by crime scene or suspect environments to those on virtually any item of physical evidence.

Quantifying the weight of fingerprint evidence through the spatial relationship, directions and types of minutiae observed on fingermarks.

This paper presents a statistical model for the quantification of the weight of fingerprint evidence. Contrarily to previous models (generative and score-based models), our model proposes to estimate the probability distributions of spatial relationships, directions and types of minutiae observed on fingerprints for any given fingermark. Our model is relying on an AFIS algorithm provided by 3M Cogent and on a dataset of more than 4,000,000 fingerprints to represent a sample from a relevant population of potential sources. The performance of our model was tested using several hundreds of minutiae configurations observed on a set of 565 fingermarks. In particular, the effects of various sub-populations of fingers (i.e., finger number, finger general pattern) on the expected evidential value of our test configurations were investigated. The performance of our model indicates that the spatial relationship between minutiae carries more evidential weight than their type or direction. Our results also indicate that the AFIS component of our model directly enables us to assign weight to fingerprint evidence without the need for the additional layer of complex statistical modeling involved by the estimation of the probability distributions of fingerprint features. In fact, it seems that the AFIS component is more sensitive to the sub-population effects than the other components of the model. Overall, the data generated during this research project contributes to support the idea that fingerprint evidence is a valuable forensic tool for the identification of individuals.

Detection of insertion/deletion polymorphisms from challenged samples using the Investigator DIPplex® kit.

This research focuses on detection of bi-allelic insertion/deletion polymorphisms (InDels) from challenged samples using the Investigator DIPplex® Kit from Qiagen. The study included analyzing body fluids from humans, as well as pristine and degraded samples. For the purpose of assessing species specificity, samples from various animals were included. At first, an analytical threshold (AT) for the detection of alleles was established based on an assessment of the noise in the system. Then, InDel profiles were obtained from samples exposed to detrimental environmental conditions, washed bloodstains, lipsticks, ChapStick®, ancient Croatian bone samples, and every day products such as toothbrushes and dental floss. Concordant profiles were obtained from different body fluids of the same donor. InDel profiles were also generated successfully when body fluids were deposited on substrates and directly amplified without pre-treatment with buffer or washing reagents. InDels can provide additional information when only partial STR profiles are generated from challenged samples.

A comment on experimental results of fingerprint comparison validity and reliability: A review and critical analysis.

We respond to the article "Experimental results of fingerprint comparison validity and reliability: A review and critical analysis" by Ralph and Lyn Haber which offers (a) a one-sided criticism of the state of affairs in latent print examination, (b) lack of original data supporting that their suggested approach, and (c) a host of incorrect statements, inaccuracies, or obscure interpretations of the existing data.

Quantitative assessment of evidential weight for a fingerprint comparison. Part II: a generalisation to take account of the general pattern.

The authors have proposed a quantitative method for assessing weight of evidence in the case where a fingermark from a crime scene is compared with a set of control prints from the ten fingers of a suspect. The approach is based on the notion of calculating a Likelihood Ratio (LR) that addresses a pair of propositions relating to the individual who left the crime mark. The current method considers only information extracted from minutiae, such as location, direction and type. It does not consider other information usually taken into account by fingerprint examiners, such as the general pattern of the ridge flow on the mark and the control prints. In this paper, we propose an improvement to our model that allows a fingerprint examiner to take advantage of pattern information when assessing the evidential weight to be assigned to a fingerprint comparison. We present an extension of the formal analysis proposed earlier and we illustrate our approach with an example.

Operational benefits and challenges of the use of fingerprint statistical models: a field study.

Research projects aimed at proposing fingerprint statistical models based on the likelihood ratio framework have shown that low quality finger impressions left on crime scenes may have significant evidential value. These impressions are currently either not recovered, considered to be of no value when first analyzed by fingerprint examiners, or lead to inconclusive results when compared to control prints. There are growing concerns within the fingerprint community that recovering and examining these low quality impressions will result in a significant increase of the workload of fingerprint units and ultimately of the number of backlogged cases. This study was designed to measure the number of impressions currently not recovered or not considered for examination, and to assess the usefulness of these impressions in terms of the number of additional detections that would result from their examination.