Influence of a fat layer on muscle oxygenation measurement using near-IR spectroscopy: quantitative analysis based on two-layered phantom experiments and Monte Carlo simulation

2000 ◽  
Vol 10 (1) ◽  
pp. 43-58 ◽  
Author(s):  
Toshikazu Shiga ◽  
Ling Lin ◽  
Makoto Takahashi ◽  
Katsuyuki Yamamoto ◽  
Masatsugu Niwayama ◽  
...  
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Quantitative Analysis ◽  
Ir Spectroscopy ◽  
Muscle Oxygenation ◽  
Near Ir ◽  
Phantom Experiments

scholarly journals Analysis of modern construction projects using montecarlo simulation technique

2018 ◽  
Vol 7 (2.19) ◽  
pp. 41
Author(s):  
A. M. Arunmohan ◽  
M. Lakshmi
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Quantitative Analysis ◽  
Construction Projects ◽  
Project Success ◽  
Risk Identification ◽  
Project Schedule ◽  
Montecarlo Simulation ◽  
Total Project Cost ◽  
Total Project

Today, Construction based Industry is the prospering industry which has a high economical influence on any nation. Delay in the huge construction project increases the total project cost. Henceforth, uncertainties as well as risks must be significantly regarded during the project. For organizing and completing the projects in a financially, timely and qualitatively accountable manner, careful scheduling of projects is compulsory. Effectual scheduling of project assures project success. This study concentrates on qualitative analysis, risk identification, together with quantitative analysis. The targets are i) to ascertain the key risk aspects that disturb the project schedule, and ii) to find the probability of finishing the project within specified time. Questionnaires are distributed amongst 20 industry practitioners with disparate experience from [1] to [25] years.  Quantitative analysis is made by the methods like Monte Carlo simulation (MCS) and PERT. @RISK by Palisade corp. is utilized for MCS.

Investigation of the particle size-dependent near-infrared spectral features of binary mixture samples in conjunction with Monte Carlo simulation and the influence of particle size on the accuracy of quantitative analysis

The Analyst ◽  
2018 ◽  
Vol 143 (18) ◽  
pp. 4306-4315 ◽  
Author(s):  
Pham K. Duy ◽  
Seulah Chun ◽  
Yoonjeong Lee ◽  
Hoeil Chung
Keyword(s):  
Monte Carlo Simulation ◽  
Particle Size ◽  
Monte Carlo ◽  
Quantitative Analysis ◽  
Near Infrared ◽  
Spectral Variation ◽  
Spectral Features ◽  
Size Dependent ◽  
Infrared Spectral ◽  
Mixture Samples

The origin of particle size-induced near-infrared (NIR) spectral variation, which is fundamental for robust quantitative analysis, was systematically studied in conjunction with Monte Carlo simulation.

Research on Method about Determination of Condition-Based Maintenance Objects by Quantitative Analysis

2014 ◽  
Vol 635-637 ◽  
pp. 2023-2028
Author(s):  
Xiang Zan ◽  
Shi Xin Zhang ◽  
Yi Zheng ◽  
Yan Chao Liu
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Regression Analysis ◽  
Quantitative Analysis ◽  
Essential Role ◽  
Condition Based Maintenance ◽  
Traditional Methods

As an essential role in determination of condition-based maintenance (CBM) objects ,necessity and applicability analysis are both important. Necessity analysis is first and applicability analysis is second is proposed. Due to shortcoming of traditional methods, a quantitative is proposed. The key of method are criticality evaluation based on Monte Carlo simulation and applicability analysis based on regression analysis, which can solve the problem short of unite standard and influence by subjective factors. The result shows the model works well.

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