scholarly journals Comparison of Several Regression Procedures for Method Comparison Studies and Determination of Sample Sizes Application of linear regression procedures for method comparison studies in Clinical Chemistry, Part II

1984 ◽  
Vol 22 (6) ◽  
Author(s):  
H. Passing ◽  
W. Bablok
Keyword(s):  
Linear Regression ◽  
Clinical Chemistry ◽  
Method Comparison ◽  
Sample Sizes

scholarly journals Non-Destructive Micromagnetic Determination of Hardness and Case Hardening Depth Using Linear Regression Analysis and Artificial Neural Networks

Metals ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 18
Author(s):  
Rahel Jedamski ◽  
Jérémy Epp
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Regression Analysis ◽  
Artificial Neural Networks ◽  
Linear Regression ◽  
Linear Regression Analysis ◽  
Case Hardening ◽  
Artificial Neural ◽  
Non Destructive

Non-destructive determination of workpiece properties after heat treatment is of great interest in the context of quality control in production but also for prevention of damage in subsequent grinding process. Micromagnetic methods offer good possibilities, but must first be calibrated with reference analyses on known states. This work compares the accuracy and reliability of different calibration methods for non-destructive evaluation of carburizing depth and surface hardness of carburized steel. Linear regression analysis is used in comparison with new methods based on artificial neural networks. The comparison shows a slight advantage of neural network method and potential for further optimization of both approaches. The quality of the results can be influenced, among others, by the number of teaching steps for the neural network, whereas more teaching steps does not always lead to an improvement of accuracy for conditions not included in the initial calibration.

Methodology of Estimation of Fire Separation Distances between Construction Facilities by Calculation

2020 ◽  
Vol 1006 ◽  
pp. 93-100
Author(s):  
Vadym Nizhnyk ◽  
Yurii Feshchuk ◽  
Volodymyr Borovykov
Keyword(s):  
Mathematical Model ◽  
Heat Flux ◽  
Linear Regression ◽  
Ignition Temperature ◽  
Oil Products ◽  
Regression Equations ◽  
Fire Load ◽  
Literary Sources ◽  
Tabular Method

Based on analysis of appropriate literary sources we established that estimation of fire separation distances was based of two criteria: heat flux and temperature. We proposed to use “ignition temperature of materials” as principal criterion when determining fire separation distances between adjacent construction facilities. Based on the results derived while performing complete factorial we created mathematical model to describe trend of changing fire separation distances depending on caloric power of fire load (Q), openings factor of the external enclosing structures (k) and duration of irradiation (t); moreover, its adequacy was confirmed. Based on linear regression equations we substantiated calculation and tabular method for the determination of fire separation distances for a facility being irradiated which contains combustible or otherwise non-combustible façade and a facility where liquid oil products turn. We developed and proposed general methodology for estimation of fire separation distances between construction facilities by calculation.

scholarly journals Chemometric approach in the development of the colorimetric method for the estimation of food colorants in meat products

2014 ◽  
Vol 68 (6) ◽  
pp. 781-791 ◽  
Author(s):  
Radivoj Petronijevic ◽  
Vesna Matekalo-Sverak ◽  
Aurelija Spiric ◽  
Ilija Vukovic ◽  
Jelena Babic ◽  
...  
Keyword(s):  
Linear Regression ◽  
Mathematical Models ◽  
Multiple Linear Regression ◽  
Linear Models ◽  
Colorimetric Method ◽  
Meat Products ◽  
Food Colorants ◽  
Food Colorant ◽  
Control Batch

The aim of this research was to develop a novel colorimetric method based on mathematical models, by multiple linear regression (MLR), from the CIE L*a*b* measurements and data of the HPLC determination of food colorants. Calibration set of 10 production batches of finely grinded cooked sausage with food colorants added was manufactured in industrial conditions as follows: one control batch and 9 products with various quantities of added food colorants: E120 (3.4, 7.5 and 12.5 mg/kg), E 124 (5.0, 15.0, 25.0 mg/kg) and E 129 (5.0, 15.0, 25.0 mg/kg). The estimation of the added food colorants was assessed by measuring L*, a*, b* parameters of cross-section. The quantification of food colorants was achieved by HPLC-PDA. Food colorants were extracted from meat products using Accelerated Solvent Extraction (ASE). Quantification of food colorants was achieved in the range from 1 to 100 mg / kg, and recovery values were from 76.15% to 107.04%, for E 120, from 97.61% to 101.03%, for E 124 and from 99.91% to 101.67%, for E 129. Correlation of the results obtained using HPLC and colorimetric measuring data was assessed by Multiple Linear Regression (MLR). The results from colorimetric and chromatographic determinations in four experimental batches (three batches with different quantities of food colorants and one control batch) were used for calibration. Coefficients of determination (R2) for linear models in experimental batches were 0.954, for E 124, 0.987, for E 120 and 0.993, for E 129. Correlation functions of food colorant quantities and corresponding L*a*b* values were established. The obtained mathematical models were tested for the estimation of the content of dyes in 21 samples of finely grinded cooked sausages purchased in retail stores. Food colorants were confirmed in 20 samples (95.24 %), and one sample (4.76 %) did not contain any of these compounds. Out of the positive samples, sixteen samples (80.00 %) contained E 120, while four samples (20.00 %) contained E 129. Food colorant E124 was not established in any of the analyzed samples. Colorimetric CIE L*a*b* method might be used during sensory evaluation of meat products for the assessment of the added food colorants.

scholarly journals Validation of Velocity Measuring Devices in Velocity Based Strength Training

2021 ◽  
Vol 20 (1) ◽  
pp. 106-118
Author(s):  
Thorben Menrad ◽  
Jürgen Edelmann-Nusser
Keyword(s):  
Linear Regression ◽  
Strength Training ◽  
Mean Value ◽  
Coefficient Of Determination ◽  
Regression Analyses ◽  
Measuring Devices ◽  
Strength Exercises ◽  
Measurement Units ◽  
Velocity Measuring

Abstract To control and monitor strength training with a barbell various systems are on the consumer market. They provide the user with information regarding velocity, acceleration and trajectory of the barbell. Some systems additionally calculate the 1-repetition-maximum (1RM) of exercises and use it to suggest individual intensities for future training. Three systems were tested: GymAware, PUSH Band 2.0 and Vmaxpro. The GymAware system bases on linear position transducers, PUSH Band 2.0 and Vmaxpro base on inertial measurement units. The aim of this paper was to determine the accuracy of the three systems with regard to the determination of the average velocity of each repetition of three barbell strength exercises (squat, barbell rowing, deadlift). The velocity data of the three systems were compared to a Vicon system using linear regression analyses and Bland-Altman-diagrams. In the linear regression analyses the smallest coefficient of determination (R2.) in each exercise can be observed for PUSH Band 2.0. In the Bland-Altman diagrams the mean value of the differences in the average velocities is near zero for all systems and all exercises. PUSH Band 2.0 has the largest differences between the Limits of Agreement. For GymAware and Vmaxpro these differences are comparable.

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