The ultimate component in this workflow, Reference Evaluator, reports evaluation metrics based on two inputs: the reference input, which in this workflow comes directly from the CHEMDNER corpus reader and contains golden annotations, and the other branch in the workflow that attempts to reproduce the annotations in the input corpus.
Some matrix parameters were both included in the ultimate component, indicating that the variation in ultimate strain and postyield work could be largely explained by Raman-derived compositional parameters.
Each component therefore independently explains a different aspect of bone mechanics and can be separately used for bone modeling: the elastic component, characterized by elastic modulus and TMD, the yield, and the ultimate component.
Principal component analysis extracted three independent components explaining 86% of the total variance, representing elastic, yield, and ultimate components according to the included mechanical parameters.
Carbon and sulfur show an increasing trend towards upper part while other ultimate components like hydrogen, nitrogen and oxygen do not show any definite trend.
Significant effects of the statistical parameters on the failure behavior and ultimate component strength were observed, manifesting importance of accurate definitions of the statistical properties for predicting probabilistic failure behavior and damage tolerance of laminate composites.
Each mechanical variable is present with high loading in only one component, which allows naming them the elastic, yield, or ultimate component, indicating that they may independently explain different aspects of the bone mechanics.
Principal component analysis appeared to be able to separate the mechanical outcome in three different regions: elastic, yield, and ultimate component.
In this chapter, however, an attempt has been made to predict the ultimate strength of components using simplified inelastic analysis instead of empirical formulae, thus making it possible to account for more complex imperfections and boundary conditions.
formula's where: σ2 = estimated variance component, P = # patient, M = method, G = group, T = # therapist, R = region, S = side, and e designates the ultimate 'error' σ2 component in the model specified.
