scholarly journals Gauss–Galerkin quadrature rules for quadratic and cubic spline spaces and their application to isogeometric analysis

2017 ◽  
Vol 82 ◽  
pp. 57-67 ◽  
Author(s):  
Michael Bartoň ◽  
Victor Manuel Calo
Keyword(s):  
Isogeometric Analysis ◽  
Cubic Spline ◽  
Quadrature Rules

scholarly journals Optimal and reduced quadrature rules for tensor product and hierarchically refined splines in isogeometric analysis

2017 ◽  
Vol 316 ◽  
pp. 966-1004 ◽  
Author(s):  
René R. Hiemstra ◽  
Francesco Calabrò ◽  
Dominik Schillinger ◽  
Thomas J.R. Hughes
Keyword(s):  
Tensor Product ◽  
Isogeometric Analysis ◽  
Quadrature Rules

A simple algorithm for obtaining nearly optimal quadrature rules for NURBS-based isogeometric analysis

2012 ◽  
Vol 249-252 ◽  
pp. 15-27 ◽  
Author(s):  
F. Auricchio ◽  
F. Calabrò ◽  
T.J.R. Hughes ◽  
A. Reali ◽  
G. Sangalli
Keyword(s):  
Isogeometric Analysis ◽  
Simple Algorithm ◽  
Quadrature Rules ◽  
Optimal Quadrature

scholarly journals Efficient quadrature rules for subdivision surfaces in isogeometric analysis

2018 ◽  
Vol 340 ◽  
pp. 1-23 ◽  
Author(s):  
Pieter J. Barendrecht ◽  
Michael Bartoň ◽  
Jiří Kosinka
Keyword(s):  
Isogeometric Analysis ◽  
Quadrature Rules ◽  
Subdivision Surfaces

scholarly journals Dispersion-minimizing quadrature rules for C1 quadratic isogeometric analysis

2018 ◽  
Vol 328 ◽  
pp. 554-564 ◽  
Author(s):  
Quanling Deng ◽  
Michael Bartoň ◽  
Vladimir Puzyrev ◽  
Victor Calo
Keyword(s):  
Isogeometric Analysis ◽  
Quadrature Rules

scholarly journals Reduced Bézier element quadrature rules for quadratic and cubic splines in isogeometric analysis

2014 ◽  
Vol 277 ◽  
pp. 1-45 ◽  
Author(s):  
Dominik Schillinger ◽  
Shaikh J. Hossain ◽  
Thomas J.R. Hughes
Keyword(s):  
Isogeometric Analysis ◽  
Cubic Splines ◽  
Quadrature Rules

Glucose Calibration Modeling in Blood with Spline Regression Approaching to Non-Invasive Tools

2018 ◽  
pp. 144-149
Author(s):  
Ria Hayatun Nur ◽  
Indahwati A ◽  
Erfiani A
Keyword(s):  
Diabetes Mellitus ◽  
Linear Regression ◽  
Good Health ◽  
Cubic Spline ◽  
The Body ◽  
Spline Regression ◽  
Linear Quadratic ◽  
Important Thing ◽  
Non Invasive

In this globalization era, health is the most important thing to be able to run various activities. Without good health, this will hinder many activities. Diabetes mellitus is one of the diseases caused by unhealty lifestyle.There are many treatments that can be done to prevent the occurrence of diabetes. The treatments are giving the insulin and also checking the glucose rate to the patients.Checking the glucose rate needs the tools which is safety to the body. This research want to develop non invasive tool which is safety and do not injure the patient. The purpose of this research is also finding the best model which derived from Linear, Quadratic, and Cubic Spline Regression. Some respondents were taking to get the glucose measuring by invasive and non invasive tools. It could be seen clearly that Spline Linear Regression was the best model than Quadratic and Cubic Spline Regression. It had 70% and 33.939 for R2 and RMSEP respectively.

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