Theses and Dissertations
This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students.
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Abstract Latent fingerprints are a critical component of the evidence that is captured and analyzed from crime scenes and presented for convictions in court. Although fingerprint science has been used for many years in forensics, it is not without many criticisms and critiques from those that believe it is too subjective. Researchers from many disciplines have tried to refute this claim by completing experiments that would eventually lead to a fingerprint aging technique as well as providing statistical models and mathematical support. In this literature review, the research that has been widely published and talked about in this field was reviewed and analyzed to determine what aspects of the experiments are benefitting the study of degradation. By carefully combing through the methods and results of each study, it can be determined where future focuses should be and what disciplines need to be exploited for knowledge. Lastly, an important aspect of the experiments in recent years have depended on the collaboration with statistics so this evidence was examined to identify what models are realistic in determining error rates and likelihood ratios to support latent fingerprint evidence in court. After a thorough review, it is seen that although large strides have been taken to study the degradation of fingerprints, the day where fingerprints will be able to be definitively aged may be ways away. The current experiments have provided methods such as three-dimensional and visual parameters that could potentially find the solution, but also uncovered methods such as immunolabeling and chemical composition that face major challenges. From the statistically point of view, researchers are very close in developing equations that exploit the likelihood ratios of similarity and even calculate the various possible error rates. The evidence found in this review shows that science is one step closer to the age determination of fingerprints.
ContributorsPorter, Lindsey Jordan (Author) / De Alcaraz Fossoul, Josep (Thesis director) / Mancenido, Michelle (Committee member) / School of Criminology and Criminal Justice (Contributor) / School of Mathematical and Natural Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
As threats to Earth's biodiversity continue to evolve, an effective methodology to predict such threats is crucial to ensure the survival of living species. Organizations like the International Union for Conservation of Nature (IUCN) monitor the Earth's environmental networks to preserve the sanctity of terrestrial and marine life. The IUCN Red List of Threatened Species informs the conservation activities of governments as a world standard of species' risks of extinction. However, the IUCN's current methodology is, in some ways, inefficient given the immense volume of Earth's species and the laboriousness of its species' risk classification process. IUCN assessors can take years to classify a species' extinction risk, even as that species continues to decline. Therefore, to supplement the IUCN's classification process and thus bolster conservationist efforts for threatened species, a Random Forest model was constructed, trained on a group of fish species previously classified by the IUCN Red List. This Random Forest model both validates the IUCN Red List's classification method and offers a highly efficient, supplemental classification method for species' extinction risk. In addition, this Random Forest model is applicable to species with deficient data, which the IUCN Red List is otherwise unable to classify, thus engendering conservationist efforts for previously obscure species. Although this Random Forest model is built specifically for the trained fish species (Sparidae), the methodology can and should be extended to additional species.
ContributorsWoodyard, Megan (Author) / Broatch, Jennifer (Thesis director) / Polidoro, Beth (Committee member) / Mancenido, Michelle (Committee member) / School of Humanities, Arts, and Cultural Studies (Contributor) / School of Mathematical and Natural Sciences (Contributor) / College of Integrative Sciences and Arts (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Fingermarks have been used by law enforcement agencies to identify suspects in criminal activity. Although fingermarks remain persistent over time, the degradation pattern of latent fingermarks remains unknown. Previous studies examined the morphology of friction ridges on a two-dimensional scale, but recently 3D technology has been employed to examine how the height dimension degrades overtime. The Sa statistic was formulated to monitor the aging process of friction ridge heights from 6 donors. Fingermarks were deposited on two nonporous substrates (glass or plastic) and aged under dark or light exposure for 98 days. Pressure, time of contact, and treatment of finger prior to deposition were held constant while temperature and humidity were monitored throughout the study. Experimental variables included substrate and light exposure. Females exhibited slower degradation than males. For fingermarks deposited on glass, faster degradation was seen under light exposure. This finding was consistent for fingermarks deposited on plastic, but instrument contamination may have been possible. Slower degradation was seen on glass under both light exposures. This study indicates the Sa statistic is valuable for assessing fingermark degradation of friction ridges. However, due to a small sample size and variability in the rate of degradation between donors, genders, under different lighting and substrate conditions, the age of latent fingermarks cannot be determined at this time.
ContributorsGrasman, Simona Jun (Co-author) / Grasman, Simona (Co-author) / Kobojek, Kimberly (Thesis director) / Mancenido, Michelle (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / School of Mathematical and Natural Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05