Simulation‐based reasoning of residual tissue deformations in a two‐chamber test of a lymphedematous leg

2021 ◽  
Author(s):  
M. Kaczmarek ◽  
J. Nowak ◽  
W. L. Olszewski ◽  
M. Zaleska
Keyword(s):  
Simulation Based ◽  
Residual Tissue ◽  
Tissue Deformations

A FAST COMPUTATION METHOD FOR SOFT TISSUE DEFORMATIONS SIMULATION BASED ON SELF-SELECTION ALGORITHM FOR EMBEDDED OPERATING AREA

2017 ◽  
Vol 17 (07) ◽  
pp. 1740016
Author(s):  
MONAN WANG ◽  
ZHIYONG MAO ◽  
XIANJUN AN
Keyword(s):  
Soft Tissue ◽  
Soft Tissues ◽  
Nonlinear Problems ◽  
Rectus Femoris ◽  
Computation Method ◽  
Biomechanical Models ◽  
Simulation Based ◽  
Material Nonlinear ◽  
Tissue Deformations ◽  
Tissue Models

This study used biomechanical models of soft tissues based on combined exponential and polynomial models. Finite element methods were used to solve material nonlinear and geometrically nonlinear problems of soft tissue models. This involved assigning a screening coefficient in the model-accelerated computing process to filter the units involved in the calculation. The screening coefficient controlled both the accuracy of the results of simulation and the computing speed through setting up a subset of finite elements. The fast computer method based on the screening coefficient was applied to the rectus femoris simulation.

Inquiry Learning

2009 ◽  
Vol 23 (2) ◽  
pp. 117-127 ◽  
Author(s):  
Astrid Wichmann ◽  
Detlev Leutner
Keyword(s):  
Scientific Reasoning ◽  
Inquiry Learning ◽  
Instructional Support ◽  
Test Results ◽  
Knowledge Test ◽  
Simulation Based ◽  
Scientific Experiments ◽  
Specific Support ◽  
Science Classes

Seventy-nine students from three science classes conducted simulation-based scientific experiments. They received one of three kinds of instructional support in order to encourage scientific reasoning during inquiry learning: (1) basic inquiry support, (2) advanced inquiry support including explanation prompts, or (3) advanced inquiry support including explanation prompts and regulation prompts. Knowledge test as well as application test results show that students with regulation prompts significantly outperformed students with explanation prompts (knowledge: d = 0.65; application: d = 0.80) and students with basic inquiry support only (knowledge: d = 0.57; application: d = 0.83). The results are in line with a theoretical focus on inquiry learning according to which students need specific support with respect to the regulation of scientific reasoning when developing explanations during experimentation activities.

Employing Human Role-Players in Simulation-Based Training For Asymmetric and Unconventional Warfare

2004 ◽  
Author(s):  
L. L. Kusumoto ◽  
◽  
R. M. Gehorsam ◽  
B. D. Comer ◽  
J. R. Grosse
Keyword(s):  
Unconventional Warfare ◽  
Simulation Based ◽  
Role Players

Structured versus self-guided feedback in simulation-based training

2008 ◽  
Author(s):  
Steven Russell ◽  
David Dorsey ◽  
Michael Ford ◽  
Meredith Cracraft ◽  
Vivek Khare ◽  
...  
Keyword(s):  
Simulation Based
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