• Journal of Convergence for Information Technology
• /
• v.9 no.6
• /
• pp.1-6
• /
• 2019

In this study, the development of a weight estimation model of electronic scale with nonlinear characteristics is presented using polynomial regression analysis. The output voltage of the load cell was measured directly using the reference mass. And a polynomial regression model was obtained using the matrix and curve fitting function of MS Office Excel. The weight was measured in 100g units using a load cell electronic scale measuring up to 5kg and the polynomial regression model was obtained. The error was calculated for simple($1^{st}$), $2^{nd}$ and $3^{rd}$ order polynomial regression. To analyze the suitability of the regression function for each model, the coefficient of determination was presented to indicate the correlation between the estimated mass and the measured data. Using the third order polynomial model proposed here, a very accurate model was obtained with a standard deviation of 10g and the determinant coefficient of 1.0. Based on the theory of multi regression model presented here, it can be used in various statistical researches such as weather forecast, new drug development and economic indicators analysis using logistic regression analysis, which has been widely used in artificial intelligence fields.

• Transactions of Materials Processing
• /
• v.25 no.3
• /
• pp.182-188
• /
• 2016

Flexibly-reconfigurable roll forming (FRRF) is a novel sheet metal forming technology conducive to producing multi-curvature surfaces by controlling the strain distribution along longitudinal direction. In FRRF, a sheet metal is shaped into the desired curvature by using reconfigurable rollers and gaps between the rollers. As FRRF technology and equipment are under development, a simulation model corresponding to the physical FRRF would aid in investigating how the shape of a sheet varies with input parameters. To facilitate the investigation, the current study exploits regression analysis to construct a predictive model for the longitudinal curvature of the sheet. Variables considered as input parameters are sheet compression ratio, radius of curvature in the transverse direction, and initial blank width. Samples were generated by a three-level, three-factor full factorial design, and both convex and saddle curvatures are represented by a quadratic regression model with two-factor interactions. The fitted quadratic equations were verified numerically with R-squared values and root mean square errors.

• Ocean Systems Engineering
• /
• v.13 no.2
• /
• pp.97-121
• /
• 2023

Through-the-thickness stress distribution in a tubular member has a profound effect on the fatigue behavior of tubular joints commonly found in steel offshore structures. This stress distribution can be characterized by the degree of bending (DoB). Although multi-planar joints are an intrinsic feature of offshore tubular structures and the multi-planarity usually has a considerable effect on the DoB values at the brace-to-chord intersection, few investigations have been reported on the DoB in multi-planar joints due to the complexity of the problem and high cost involved. In the present research, data extracted from the stress analysis of 243 finite element (FE) models, verified based on available parametric equations, was used to study the effects of geometrical parameters on the DoB values in two-planar tubular DYT-joints. Parametric FE study was followed by a set of nonlinear regression analyses to develop six new DoB parametric equations for the fatigue analysis and design of axially loaded two-planar DYT-joints.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.13 no.3
• /
• pp.77-82
• /
• 2014

In this study, we carried out the interrupted cutting of carbon steel for a machine structure (SM45C) with a CVD-coated tool and conducted an ANOVA test and a confidence interval analysis to find factors influence the surface roughness and to obtain a regression equation. We found that factor which mostly affects the surface roughness during interrupted cutting was the feed rate. The cutting speed and depth of the cut only had small effect on the surface roughness. From the result of a multi-regression analysis during an interrupted cutting experiment, we obtained regression equation. Its coefficient of determination was 0.918, indicating that the regression equation was predictable. Compared to continuous cutting, if the feed rate increases, the surface roughness will also increase during interrupted cutting.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
• /
• v.18 no.2_spc
• /
• pp.247-260
• /
• 2020

A multi-regression model was developed to estimate the decommissioning cost for Kori unit 1 using foreign nuclear power plant (NPP) decommissioning cost data. First, the decommissioning cost data were collected for 13 boiling water reactors and 16 pressurized water reactors and converted into the values as of November 2019. Then, for the regression model, the decommissioning cost was chosen as the dependent variable, and two variables were selected as independent variables: a contamination factor that was designed to reflect the operational characteristics of the decommissioned NPP and the decommissioning period. A statistical package in the R language was used to derive the regression model. Finally, the regression model was applied to estimate the decommissioning cost for Kori unit 1. The estimated decommissioning cost for Kori unit 1 was 663.40~928.32 million US dollars (782,812~1,095,418 million Korean won).

• Journal of Korean Neurosurgical Society
• /
• v.66 no.4
• /
• pp.382-392
• /
• 2023

Objective : The use of indocyanine green videoangiography (ICG-VA) to assess blood flow in the brain during cerebrovascular surgery has been increasing. Clinical studies on ICG-VA have predominantly focused on qualitative analysis. However, quantitative analysis numerical modelling for time profiling enables a more accurate evaluation of blood flow kinetics. In this study, we established a multiple exponential modified Gaussian (multi-EMG) model for quantitative ICG-VA to understand accurately the status of cerebral hemodynamics. Methods : We obtained clinical data of cerebral blood flow acquired the quantitative analysis ICG-VA during cerebrovascular surgery. Varied asymmetric peak functions were compared to find the most matching function form with clinical data by using a nonlinear regression algorithm. To verify the result of the nonlinear regression, the mode function was applied to various types of data. Results : The proposed multi-EMG model is well fitted to the clinical data. Because the primary parameters-growth and decay rates, and peak center and heights-of the model are characteristics of model function, they provide accurate reference values for assessing cerebral hemodynamics in various conditions. In addition, the primary parameters can be estimated on the curves with partially missed data. The accuracy of the model estimation was verified by a repeated curve fitting method using manipulation of missing data. Conclusion : The multi-EMG model can possibly serve as a universal model for cerebral hemodynamics in a comparison with other asymmetric peak functions. According to the results, the model can be helpful for clinical research assessment of cerebrovascular hemodynamics in a clinical setting.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.22 no.6
• /
• pp.564-573
• /
• 2012

The objective of this study is to determine the effect for the sound quality according to the noise source and to build the sound quality index of the laundry noise. In order to compare laundry noise among the influence of noise sources, we made virtual laundry noises by synthesizing an actual laundry noise and each noise source such as a dropping noise, water noise, motor noise and circulation pump noise. We conducted a listening test by customers using virtual laundry noises. As a result of listening test, we found that the dropping noise has a decisive effect on the sound quality of the laundry noise. We conducted the multi regression analysis of sound quality for the laundry noise using the statistical data processing. It is verified to the reliability of the multi regression index by comparison with listening results and index results of other actual laundry noises. This study is expected to provide a guide line for improvement of the laundry noise.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.35 no.6
• /
• pp.351-356
• /
• 2022

In this paper, we present the regression analysis and design optimization for improving the permeability of 3D woven materials based on numerical analysis data. First, the parametric analysis model is generated with variables that define the gap sizes between each directional wire of the woven material. Then, material properties such as bulk modulus, thermal conductivity coefficient, and permeability are calculated using numerical analysis, and these material data are used in the polynomial-based regression analysis. The Pareto optimal solution is obtained between bulk modulus and permeability by using multi-objective optimization and shows their trade-off relation. In addition, gradient-based design optimization is applied to maximize the fluid permeability for 3D woven materials, and the optimal designs are obtained according to the various minimum bulk modulus constraints. Finally, the optimal solutions from regression equations are verified to demonstrate the accuracy of the proposed method.

• Journal of Ocean Engineering and Technology
• /
• v.23 no.3
• /
• pp.14-19
• /
• 2009

The present study developed a model to estimate the light weight of an ultra-large container ship. The weight estimation model utilized container ship data obtained from shipyards and the subdivided this weight data into appropriate weight groups. Parameters potentially affecting the group weight were selected and expanded based on experience for weight estimation, and a correlation analysis was performed by the SPSS program to determine the key parameters characterizing the group weight. A weight estimation model applying the multi-regression analysis was proposed to assess the weight of an ultra-large container ship at the preliminary design stage, and the results obtained by the suggested method showed good agreement with the shipyard data.

• Journal of Welding and Joining
• /
• v.20 no.1
• /
• pp.83-90
• /
• 2002

Metal Transfer in gas metal arc (GMA) welding is a complex phenomenon affected by many parameters of the welding conditions and material properties. In this research, the correlation equation between the welding condition and detaching droplet size and detaching velocity in GMA welding was studied via recession analysis on the results of numerical analysis using the volume-of-fluid (VOF) method. Welding parameters and material properties were grouped into three dimensionless numbers and detaching droplet size was expressed as the function of them. Second order and exponential multi-variable correlation forms were assumed, and the coefficients of these equations were calculated for globular and spray modes as well as entire transfer modes. Applying correlation equation into available experimental data, it shows good agreement.