학술논문
A computational re-assessment of sexual dimorphism in the human cranium beyond traditional morphometrics: geometric morphometric methods and neural network analysis
Document Type
Dissertation/Thesis
Author
Source
TDX (Tesis Doctorals en Xarxa)
Subject
Language
English
Abstract
El objetivo principal de esta tesis de doctorado es avanzar en el estudio y la comprensión del dimorfismo sexual en los cráneos humanos modernos. Para lograr estos objetivos, primero exploramos cuáles son las características anatómicas adecuadas para establecer el dimorfismo sexual. En segundo lugar, introducimos un método novedoso para determinar el sexo de los cráneos humanos. Para cumplir con estos objetivos, aplicamos el enfoque de Morfometría Geométrica a una muestra de proveniencia geográficas variadas de cráneos. Nuestra investigación abarca tres estudios distintos, uno centrado en el neurocráneo, otro en el hueso frontal y el último en el cráneo completo, involucrando un total de 228 individuos, tanto mujeres como hombres. En busca del segundo objetivo, realizamos un Neural Network Analysis utilizando 10 mediciones lineales. Empleamos un conjunto de datos global para este análisis. Los resultados derivados de estos cuatro estudios demuestran la utilidad tanto de la Morfometría Geométrica como del Neural Network Analysis en el avance de nuestra comprensión del dimorfismo sexual en los cráneos humanos.
The primary objective of this Ph.D. dissertation is to advance the study and understanding of sexual dimorphism in modern human crania. To achieve these objectives, we first explore which anatomical features are suitable for establishing sexual dimorphism. Secondly, we introduce a novel method for determining the sex of human crania. To fulfill these objectives, we apply the Geometric Morphometrics approach to a diverse geographical sample of crania. Our research encompasses three distinct studies, one focusing on the neurocranium, another on the frontal bone, and the final one on the entire cranium, involving a total of 228 individuals, both female and male. In pursuit of the second objective, we conduct a Neural Network Analysis using 10 linear measurements. We employ a craniometric worldwide dataset for this analysis.
The primary objective of this Ph.D. dissertation is to advance the study and understanding of sexual dimorphism in modern human crania. To achieve these objectives, we first explore which anatomical features are suitable for establishing sexual dimorphism. Secondly, we introduce a novel method for determining the sex of human crania. To fulfill these objectives, we apply the Geometric Morphometrics approach to a diverse geographical sample of crania. Our research encompasses three distinct studies, one focusing on the neurocranium, another on the frontal bone, and the final one on the entire cranium, involving a total of 228 individuals, both female and male. In pursuit of the second objective, we conduct a Neural Network Analysis using 10 linear measurements. We employ a craniometric worldwide dataset for this analysis.