Forensic anthropology has developed classification techniques for sex estimation of unknown skeletal remains, for example population-specific discriminant function analyses. These methods were designed for populations that lived mostly in the late nineteenth and twentieth centuries. Their level of reliability or misclassification is important for practical use in today's forensic practice; it is, however, unknown. We addressed the question of what the likelihood of errors would be if population specificity of discriminant functions of the tibia were disregarded. Moreover, five classification functions in a Czech sample were proposed (accuracies 82.1-87.5 %, sex bias ranged from -1.3 to -5.4 %). We measured ten variables traditionally used for sex assessment of the tibia on a sample of 30 male and 26 female models from recent Czech population. To estimate the classification accuracy and error (misclassification) rates ignoring population specificity, we selected published classification functions of tibia for the Portuguese, south European, and the North American populations. These functions were applied on the dimensions of the Czech population. Comparing the classification success of the reference and the tested Czech sample showed that females from Czech population were significantly overestimated and mostly misclassified as males. Overall accuracy of sex assessment significantly decreased (53.6-69.7 %), sex bias -29.4-100 %, which is most probably caused by secular trend and the generally high variability of body size. Results indicate that the discriminant functions, developed for skeletal series representing geographically and chronologically diverse populations, are not applicable in current forensic investigations. Finally, implications and recommendations for future research are discussed.
Dental development is frequently used to estimate age in many anthropological specializations. The aim of this study was to extract an accurate predictive age system for the Czech population and to discover any different predictive ability of various tooth types and their ontogenetic stability during infancy and adolescence. A cross-sectional panoramic X-ray study was based on developmental stages assessment of mandibular teeth (Moorrees et al. 1963) using 1393 individuals aged from 3 to 17 years. Data mining methods were used for dental age estimation. These are based on nonlinear relationships between the predicted age and data sets. Compared with other tested predictive models, the GAME method predicted age with the highest accuracy. Age-interval estimations between the 10th and 90th percentiles ranged from -1.06 to +1.01 years in girls and from -1.13 to +1.20 in boys. Accuracy was expressed by RMS error, which is the average deviation between estimated and chronological age. The predictive value of individual teeth changed during the investigated period from 3 to 17 years. When we evaluated the whole period, the second molars exhibited the best predictive ability. When evaluating partial age periods, we found that the accuracy of biological age prediction declines with increasing age (from 0.52 to 1.20 years in girls and from 0.62 to 1.22 years in boys) and that the predictive importance of tooth types changes, depending on variability and the number of developmental stages in the age interval. GAME is a promising tool for age-interval estimation studies as they can provide reliable predictive models.
Abstract. In this paper the problem of analysis of eye movements using sinusoidal head rotation test is presented. The goal of the method is to discard automatically the effect of the fast phase-saccades and consequently calculate the response of vestibular system in the form of phase shift and amplitude. The comparison of threshold detection and inductive models trained on saccades is carried out. After saccades detection we are left with discontinuous signal segments. This paper presents an approach to align them to form a smooth signal with the same frequencies that were originally present in the source signal. The approach is based on a direct estimation of the signal component parameters using the evolutionary strategy with covariance matrix adaptation. The performance of evolutionary approach is compared to least-square multimodal sinus fit. The experimental evaluation on real-world signals revealed that threshold saccades detection with combination of the evolutionary strategy is robust, scalable and reliable method.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.