Kinematics-Based Determination of the Rolling Region in Roll Bending for Smoothly Curved Plates

2000 ◽  
Vol 123 (2) ◽  
pp. 284-290 ◽  
Author(s):  
Jong Gye Shin ◽  
Joon Tae Park ◽  
Hyunjune Yim
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Systematic Approach ◽  
Linear Regression Analysis ◽  
Forming Process ◽  
Roll Bending ◽  
Bending Process ◽  
Curvature Distribution ◽  
Good Agreement

This paper proposes and develops a kinematics-based, systematic approach to determine the region of a plate to be rolled, in order to fabricate smoothly curved plates. The approach includes a kinematic analysis to calculate the plate’s curvature distribution, and, in addition, a linear regression analysis to determine the initial and final locations of the roller during the roll bending process. Three artificial cases and two real cases have been studied, and the results are in good agreement with field practices. This approach will play an important role in the automation and optimization of the plate forming process.

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.

Correlation between FA and ADC, number and length of the periprostatic neurovascular fibers

2021 ◽  
pp. 039156032110637
Author(s):  
Valerio Di Paola ◽  
Angelo Totaro ◽  
Giacomo Avesani ◽  
Benedetta Gui ◽  
Andrea Boni ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Negative Correlation ◽  
Multivariate Regression ◽  
Linear Regression Analysis ◽  
Multivariate Linear Regression ◽  
Multivariate Linear Regression Analysis ◽  
Independent Variables ◽  
Fiber Tracts ◽  
Good Agreement

Purpose: Our aim was to explore the relation between FA and ADC, number and length of the periprostatic neurovascular fibers (PNF) by means of 1.5 T Diffusion Tensor Imaging (DTI) imaging through a multivariate linear regression analysis model. Methods: For this retrospective study, 56 patients (mean age 63.5 years), who underwent 1.5-T prostate MRI, including DTI, were enrolled between October 2014 and December 2018. Multivariate regression analysis was performed to evaluate the statistically significant correlation between FA values (dependent variable) and ADC, the number and the length of PNF (independent variables), if p-value <0.05. A value of 0.5 indicated poor agreement; 0.5–0.75, moderate agreement; 0.75–0.9, good agreement; 0.61–0.80, good agreement; and 0.9–1.00, excellent agreement. Results: The overall fit of the multivariate regression model was excellent, with R2 value of 0.9445 ( R2 adjusted 0.9412; p < 0.0001). Multivariate linear regression analysis showed a statistically significant correlation ( p < 0.05) for all the three independent variables. The r partial value was −0.9612 for ADC values ( p < 0.0001), suggesting a strong negative correlation, 0.4317 for the number of fiber tracts ( p < 0.001), suggesting a moderate positive correlation, and −0.306 for the length of the fiber tracts ( p < 0.05), suggesting a weak negative correlation. Conclusions: Our multivariate linear regression model has demonstrated a statistically significant correlation between FA values of PNF with other DTI parameters, in particular with ADC.

scholarly journals ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI PROFITABILITAS BANK UMUM SYARIAH DI INDONESIA

2020 ◽  
Vol 6 (8) ◽  
pp. 1607
Author(s):  
Dian Anggraini ◽  
Imron Mawardi
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Commercial Bank ◽  
Confidence Level ◽  
Linear Regression Analysis ◽  
Sampling Technique ◽  
Multiple Linear Regression Analysis ◽  
Coefficient Of Determination

The purpose of this study is to analyze the factors that affect the profitability of Sharia Commercial Bank in Indonesia. The sampling technique used is saturated sampling, so the population and sample is the Sharia Commercial Bank periode October 2014-March 2018 which amounted to 42 months. This study uses a quantitative approach with multiple linear regression analysis technique.The result showed that with 95% confidence level partially variable Financing to Deposit Ratio have significant effect to profitability, while variable Natural Uncertainty Contract Financing, Non Performing Financing, and Equity have no significant effect on profitability of Sharia Commercial Bank in Indonesia. Nevertheless, Natural Uncertainty Contract Financing, Non Performing Financing, Financing to Deposit Ratio and Equity simultaneously have significant effect to the profitability of Sharia Commercial Bank in Indonesia. With the coefficient of determination of 33,2%.Keywords: Natural Uncertainty Contract, Non Performing Financing, Financing to Deposit Ratio, Equity

scholarly journals The Effect of Compensation and Job Promotion on Employee Job Satisfaction at Pt. Permata Jaga Karya, Denpasar

2019 ◽  
Vol 10 (12) ◽  
pp. 21683-21692
Author(s):  
Sapta Rini Widyawati ◽  
I Dewa Made Adnyana ◽  
I Nyoman Mustika
Keyword(s):  
Job Satisfaction ◽  
Regression Analysis ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Analytical Tool ◽  
Employee Job Satisfaction ◽  
Job Promotion

This study aims to determine the effect of compensation and job promotions on employee job satisfaction at PT. Permata Jaga Karya, Denpasar. The number of research samples were 84 employees. Determination of the sample using saturated or census means that all employees are respondents. The analytical tool used is multiple linear regression analysis with the help of SPSS version 23.0. The results of the analysis showed that compensation had a significant positive and significant effect on employee job satisfaction at PT. Permata Jaga Karya, Denpasar, this is evidenced by the value of the coefficient B for X1 is positive and the significant value of t (X1) <0.05. Similarly, promotion has a significant positive and significant effect on employee job satisfaction at PT. Permata Jaga Karya, Denpasar, this is evidenced by the value of the coefficient B X2 is positive and the significant value of t (X2) <0.05.

Evaluation and comparison of a radiative energy attenuation method for determining cholesterol in serum.

1985 ◽  
Vol 31 (4) ◽  
pp. 605-608 ◽  
Author(s):  
P L Cary ◽  
C A Johnson ◽  
P D Whitter ◽  
J W Parker
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
High Performance ◽  
Linear Regression Analysis ◽  
Radiative Energy ◽  
Comparison Methods ◽  
Analytical Recovery ◽  
Wide Range

Abstract Determination of cholesterol by a radiative energy attenuation (REA) technique was evaluated and compared with results obtained by the Boehringer Mannheim High Performance Cholesterol Assay and the Du Pont aca. Within-assay and between-assay CVs for the REA method, for two sets of controls, were both less than 5%. We observed no interference with lipemic samples. Analytical recovery averaged 102.8%. We used all three methods for parallel determinations of 217 patients' samples containing a wide range of cholesterol concentrations. Linear regression analysis of the REA results vs those of the comparison methods were as follows: REA = 1.03 Boehringer - 0.072 (r = 0.993) and REA = 1.02 aca - 0.048 (r = 0.995). We also discuss bilirubin interference with the REA method for cholesterol.

Determination of sulphur species in solidified cryolite melts

2012 ◽  
Vol 66 (7) ◽  
Author(s):  
Marta Ambrová ◽  
Jana Jurišová ◽  
Pavel Fellner ◽  
Jomar Thonstad
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Ion Chromatography ◽  
Linear Regression Analysis ◽  
Sulphide Ions ◽  
Soluble Sulphate ◽  
Industrial Samples ◽  
Sulphur Species

AbstractSolidified cryolite melts containing a known amount of Na2SO4 (0–713 mg kg−1 SO42−), Na2S, FeS, and CdS (0–400 mg kg−1 S2−) together with industrial electrolyte samples were tested for the content of sulphate and sulphide ions by ion chromatography. Added and analytically determined contents of sulphate and sulphide were compared and processed by means of linear regression analysis. It was found that the method of ion chromatography yields satisfying results (uncertainty below 1.1 %) and that it is especially suitable for the determination of low content of soluble sulphate or sulphide in solidified cryolite electrolytes. The method can be used for the estimation of insoluble sulphide content in cryolite melts as well. Results of industrial samples analysis showed that the content of sulphate and sulphide in the samples is influenced by their treatment before the analysis.

scholarly journals Analysis of kinetic data for irreversible enzyme inhibition

1989 ◽  
Vol 257 (2) ◽  
pp. 419-424 ◽  
Author(s):  
P J Gray ◽  
R G Duggleby
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Enzyme Inhibition ◽  
Kinetic Data ◽  
Organophosphorus Compounds ◽  
Linear Regression Analysis ◽  
Irreversible Inhibitors ◽  
Progress Curve ◽  
Inhibition Kinetic

Many organophosphorus compounds are irreversible inhibitors of acetylcholinesterase. The methods used in the literature to determine the inhibition kinetic constants usually involve either manual determination of the slope at various points along the inhibition progress curve or fitting polynomials to the curve. The present study investigates the use of non-linear-regression analysis to determine the various parameters. A method is suggested that yields accurate values for the inhibition constants under a range of circumstances.

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