Abstract: The key role in phenomenological modelling of cyclic
plasticity is good understanding of stress-strain behaviour of given
material. There are many models describing behaviour of materials
using numerous parameters and constants. Combination of individual
parameters in those material models significantly determines whether
observed and predicted results are in compliance. Parameter
identification techniques such as random gradient, genetic algorithm
and sensitivity analysis are used for identification of parameters using
numerical modelling and simulation. In this paper genetic algorithm
and sensitivity analysis are used to study effect of 4 parameters of
modified AbdelKarim-Ohno cyclic plasticity model. Results
predicted by Finite Element (FE) simulation are compared with
experimental data from biaxial ratcheting test with semi-elliptical
loading path.
Abstract: In medical imaging, segmentation of different areas of
human body like bones, organs, tissues, etc. is an important issue.
Image segmentation allows isolating the object of interest for further
processing that can lead for example to 3D model reconstruction of
whole organs. Difficulty of this procedure varies from trivial for
bones to quite difficult for organs like liver. The liver is being
considered as one of the most difficult human body organ to segment.
It is mainly for its complexity, shape versatility and proximity of
other organs and tissues. Due to this facts usually substantial user
effort has to be applied to obtain satisfactory results of the image
segmentation. Process of image segmentation then deteriorates from
automatic or semi-automatic to fairly manual one. In this paper,
overview of selected available software applications that can handle
semi-automatic image segmentation with further 3D volume
reconstruction of human liver is presented. The applications are being
evaluated based on the segmentation results of several consecutive
DICOM images covering the abdominal area of the human body.