• Journal of the Korean Society of Safety
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• v.29 no.4
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• pp.153-159
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• 2014

Low back pain is one of major issues in musculoskeletal diseases mainly caused by MMH (Manual Material Handling) tasks. In Korea, the standards of NIOSH(National Institute for Occupational Safety and Health) Lift Equations in U. S. A. have been most widely used. However, there is no standard in case the height of one feet is higher than that of another one. Moreover, since the standards are developed in U. S. A., there are many limitations for the applicability of Korean workers. In this study, MVC(Maximum Voluntary Contraction) for four postures are measured and an empirical model based on SVR(Support Vector Regression) is constructed. Constructing SVR model, PSO(Particle Swarm Optimization) is employed to investigate the optimal parameters of SVR. The results show that the performance of this empirical model is approximately accurate, even if the deviation of experimental values is large due to the individual differences. This empirical model may contribute to establish the standards of MMH tasks in Korea.

• Earthquakes and Structures
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• v.22 no.6
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• pp.609-623
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• 2022

To study the empirical seismic fragility of a reinforced concrete girder bridge, based on the theory of numerical analysis and probability modelling, a regression fragility method of a rapid fragility prediction model (Gaussian first-order regression probability model) considering empirical seismic damage is proposed. A total of 1,069 reinforced concrete girder bridges of 22 highways were used to verify the model, and the vulnerability function, plane, surface and curve model of reinforced concrete girder bridges (simple supported girder bridges and continuous girder bridges) considering the number of samples in multiple intensity regions were established. The new empirical seismic damage probability matrix and curve models of observation frequency and damage exceeding probability are developed in multiple intensity regions. A comparative vulnerability analysis between simple supported girder bridges and continuous girder bridges is provided. Depending on the theory of the regional mean seismic damage index matrix model, the empirical seismic damage prediction probability matrix is embedded in the multidimensional mean seismic damage index matrix model, and the regional rapid prediction matrix and curve of reinforced concrete girder bridges, simple supported girder bridges and continuous girder bridges in multiple intensity regions based on mean seismic damage index parameters are developed. The established multidimensional group bridge vulnerability model can be used to quantify and predict the fragility of bridges in multiple intensity regions and the fragility assessment of regional group reinforced concrete girder bridges in the future.

• International Journal of Highway Engineering
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• v.19 no.5
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• pp.49-58
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• 2017

PURPOSES : The objective of this study is to develop a simple regression model in designing the asphalt concrete (AC) overlay thickness using the Mechanistic-empirical pavement design guide (MEPDG) program. METHODS : To establish the AC overlay design equation, multiple regression analyses were performed based on the synthetic database for AC thickness design, which was generated using the MEPDG program. The climate in Seoul city, a modified Hirsh model for determining dynamic modulus of asphalt material, and a new damaged master curve approach were used in this study. Meanwhile, the proposed rutting model developed in Seoul city was then used to calibrate the rutting model in the MEPDG program. The AC overlay design equation is a function of the total AC thickness, the ratio of AC overlay thickness and existing AC thickness, the ratio of existing AC modulus and AC overlay modulus, the subgrade condition, and the annual average daily truck traffic (AADTT). RESULTS : The regression model was verified by comparing the predicted AC thickness, the AADTT from the model and the MEPDG. The regression model shows a correlation coefficient of 0.98 in determining the AC thickness and 0.97 in determining AADTT. In addition, the data in Seoul city was used to validate the regression model. The result shows that correlation coefficient between the predicted and measured AADTT is 0.64. This indicates that the current model is more accuracy than the previous study which showed a correlation coefficient of 0.427. CONCLUSIONS:The high correlation coefficient values indicate that the regression equations can predict the AC thickness accurately.

• Journal of the Earthquake Engineering Society of Korea
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• v.22 no.2
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• pp.95-101
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• 2018

Diagonally reinforced concrete coupling beams (DRCB) play an important role in coupled shear wall systems since these elements dissipate most of seismic input energy under earthquake loading. For reliable seismic performance evaluation using nonlinear response history analysis, it is important to use an accurate analytical model for DRCBs. In this study, the Pinching4 model is used as a base model to simulate the cyclic behavior of DRCBs. For simulating the cyclic behavior of DRCBs using the Pinching4 model, the analytical parameters for backbone curve, pinching and cyclic deterioration in strength and stiffness should be computed. To determine the proper values of the constituent analytical parameters efficiently and accurately, this study proposes the empirical equations for the analytical parameters using regression analyses. It is shown that the hysteretic behavior of coupling beams can be simulated efficiently and accurately using the proposed numerical model with the proposed empirical equations of model parameters.

• Korea Trade Review
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• v.46 no.6
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• pp.211-224
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• 2021

Based on the perspective of international trade and cross-border e-commerce development, this paper explores the impact of cross-border e-commerce on international trade. This paper first describes the current situation of China's cross-border e-commerce and proposes a theoretical model of the influence of China's cross-border e-commerce on its international trade based on the research and summary of a large number of relevant documents. This paper establishes an extended gravity model based on the proposed theoretical model. Relevant data of 13 trading partner countries were used as sample data, and OLS regression analysis and heterogeneity analysis were conducted on gravity model by using Eviews 11.0. Then, in order to study the influence of each variable on import and export trade volume, import and export trade volume were respectively taken as explained variables and further studied by OLS regression analysis. To test the robustness of the model, the empirical analysis results show that cross-border e-commerce does promote the volume of China's international trade.

• Communications for Statistical Applications and Methods
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• v.13 no.1
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• pp.141-150
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• 2006

Penalized likelihood regression for exponential families have been considered by Kim (2005) through smoothing parameter selection and asymptotically efficient low dimensional approximations. We derive approximate Bayesian confidence intervals based on Bayes model associated with lower dimensional approximations to provide interval estimates in penalized likelihood regression and conduct empirical studies to access their properties.

• Journal of the Korean Statistical Society
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• v.5 no.1
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• pp.19-28
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• 1976

In empirical study for fitting a multiple linear regression model for successive cross-sections data observed on the same set of independent variables over several time periods, one often faces the problem of poor $R^2$, the multiple coefficient of determination, which provides a standard measure of how good a specified regression line fits the sample data.

• Wind and Structures
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• v.21 no.1
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• pp.85-103
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• 2015

Aerodynamic forces of vortex-induced vibration and galloping are going to be coupled when their onset velocities are close to each other, which will induce the cross-wind amplitudes of the structures increased continuously with ever-increasing wind velocities. The main purpose of the present work is going to propose an empirical formula to predict the response amplitude of VIV-galloping interaction. Firstly, two typical mathematical models for the coupled oscillations, i.e., Tamura & Shimada model and Parkinson & Corless model are comparatively summarized. Then, the key parameter affecting response amplitude is determined through comparative numerical simulations with Tamura & Shimada model. For rectangular cylinders with the side ratio from 0.5 to 2.5, which are actually prone to develop the VIV and galloping induced interaction responses, an empirical amplitude prediction formula is proposed after regression analysis on comprehensively collected experimental data with the predetermined key parameter.

• Journal of Korean Institute of Industrial Engineers
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• v.42 no.5
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• pp.314-326
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• 2016

The purpose of variable selection techniques is to select a subset of relevant variables for a particular learning algorithm in order to improve the accuracy of prediction model and improve the efficiency of the model. We conduct an empirical analysis to evaluate and compare seven well-known variable selection techniques for multiple linear regression model, which is one of the most commonly used regression model in practice. The variable selection techniques we apply are forward selection, backward elimination, stepwise selection, genetic algorithm (GA), ridge regression, lasso (Least Absolute Shrinkage and Selection Operator) and elastic net. Based on the experiment with 49 regression data sets, it is found that GA resulted in the lowest error rates while lasso most significantly reduces the number of variables. In terms of computational efficiency, forward/backward elimination and lasso requires less time than the other techniques.

• Proceedings of the KWS Conference
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• 2006.10a
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• pp.271-273
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• 2006

This paper focuses on the developed empirical models for the prediction on top-bead width in GMA(Gas Metal Arc) welding process. Three empirical models have been developed: linear, curvilinear and an intelligent model. Regression analysis was employed fur optimization of the coefficients of linear and curvilinear model, while Genetic Algorithm(GA) was utilized to estimate the coefficients of intelligent model. Not only the fitting of these models were checked, but also the prediction on top-bead width was carried out. ANOVA analysis and contour plots were respectively employed to represent main and interaction effects between process parameters on top-bead width.