• Bulletin of the Korean Mathematical Society
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• v.45 no.2
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• pp.339-353
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• 2008

The distributions of products and ratios of random variables are of interest in many areas of the sciences. In this paper, the exact distributions of the product |XY| and the ratio |X/Y| are derived when X and Y are independent Pearson type VII random variables.

• Communications of the Korean Mathematical Society
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• v.22 no.3
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• pp.441-452
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• 2007

The exact distributions of X + Y, XY and X/(X + Y) are derived when X and Y are independent generalized Planck random variables.

• ETRI Journal
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• v.32 no.6
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• pp.965-968
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• 2010

In this letter, we derive the distribution functions of five ratios involving two correlated Gaussian random variables by using the rotation of Cartesian coordinates. The results can be used in evaluating the various probability performances of wireless communications systems.

• Smart Structures and Systems
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• v.9 no.6
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• pp.505-534
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• 2012

The present work deals with second order statistics of post buckling response of piezoelectric laminated composite cylindrical shell panel subjected to hygro-thermo-electro-mechanical loading with random system properties. System parameters such as the material properties, thermal expansion coefficients and lamina plate thickness are assumed to be independent of the temperature and electric field and modeled as random variables. The piezoelectric material is used in the forms of layers surface bonded on the layers of laminated composite shell panel. The mathematical formulation is based on higher order shear deformation shell theory (HSDT) with von-Karman nonlinear kinematics. A efficient $C^0$ nonlinear finite element method based on direct iterative procedure in conjunction with a first order perturbation approach (FOPT) is developed for the implementation of the proposed problems in random environment and is employed to evaluate the second order statistics (mean and variance) of the post buckling load of piezoelectric laminated cylindrical shell panel. Typical numerical results are presented to examine the effect of various environmental conditions, amplitude ratios, electrical voltages, panel side to thickness ratios, aspect ratios, boundary conditions, curvature to side ratios, lamination schemes and types of loadings with random system properties. It is observed that the piezoelectric effect has a significant influence on the stochastic post buckling response of composite shell panel under various loading conditions and some new results are presented to demonstrate the applications of present work. The results obtained using the present solution approach is validated with those results available in the literature and also with independent Monte Carlo Simulation (MCS).

• Advances in Computational Design
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• v.2 no.3
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• pp.165-194
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• 2017

The present work proposes the thermo mechanically induced statistics of nonlinear transverse central deflection of elastically supported functionally graded (FG) plate subjected to static loadings with random system properties. The FG plate is supported on two parameters Pasternak foundation with Winkler cubic nonlinearity. The random system properties such as material properties of FG material, external loading and foundation parameters are assumed as uncorrelated random variables. The material properties are assumed as non-uniform temperature distribution with temperature dependent (TD) material properties. The basic formulation for static is based on higher order shear deformation theory (HSDT) with von-Karman nonlinear strain kinematics through Newton-Raphson method. A second order perturbation technique (SOPT) and direct Monte Carlo simulation (MCS) are used to compute the nonlinear governing equation. The effects of load parameters, plate thickness ratios, aspect ratios, volume fraction, exponent, foundation parameters, and boundary conditions with random system properties are examined through parametric studies. The results of present approaches are compared with those results available in the literature and by employing direct Monte Carlo simulation (MCS).

• Advances in aircraft and spacecraft science
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• v.4 no.5
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• pp.585-611
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• 2017

This article covenants with the post buckling witticism of carbon nanotube reinforced composite (CNTRC) beam supported with an elastic foundation in thermal atmospheres with arbitrary assumed random system properties. The arbitrary assumed random system properties are be modeled as uncorrelated Gaussian random input variables. Unvaryingly distributed (UD) and functionally graded (FG) distributions of the carbon nanotube are deliberated. The material belongings of CNTRC beam are presumed to be graded in the beam depth way and appraised through a micromechanical exemplary. The basic equations of a CNTRC beam are imitative constructed on a higher order shear deformation beam (HSDT) theory with von-Karman type nonlinearity. The beam is supported by two parameters Pasternak elastic foundation with Winkler cubic nonlinearity. The thermal dominance is involved in the material properties of CNTRC beam is foreseen to be temperature dependent (TD). The first and second order perturbation method (SOPT) and Monte Carlo sampling (MCS) by way of CO nonlinear finite element method (FEM) through direct iterative way are offered to observe the mean, coefficient of variation (COV) and probability distribution function (PDF) of critical post buckling load. Archetypal outcomes are presented for the volume fraction of CNTRC, slenderness ratios, boundary conditions, underpinning parameters, amplitude ratios, temperature reliant and sovereign random material properties with arbitrary system properties. The present defined tactic is corroborated with the results available in the literature and by employing MCS.

• Journal of the Korean Institute of Telematics and Electronics
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• v.22 no.5
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• pp.57-61
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• 1985

The e(lect of capacitance error on the A/D conversion accuracy in the A/D converter using binary-weighted capacitor array was scruntized. Besides the Monte-Carlo method considering the inter-capacitance ratios as random variables, " correlation approach" con-sidering the correlation coefficient between capacitances is proposed in this paper. Bt was observed by the measurement of capacitances of monolithic MO5 capacitors that the correla-tion coefficient between capacitors decreases as the capacitor size incrrases. It was also verified that the parallel connection of unit capacitors and the common centroid layout scheme signi(icantly increase the inter-capacitance correlation coefficients.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.15 no.2
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• pp.86-96
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• 2003

A fracture or breakage of the concrete armor units in the primary cover layer of breakwaters is studied by using the reliability analysis which may be defined as the structural stability. The reliability function can be derived as a function of the angle of rotation that represents the rocking of armor units quantitatively. The relative influences of all of random variables related to the material and geometric properties on the fracture of armor units is analyzed in detail. In addition, the probability of failure for the fracture of individual armor unit can be evaluated as a function of the incident wave height. Finally, Bernoulli random process and the allowable fracture ratio may be introduced together in this paper, by which the probability of failure of a breakwater due to the fracture of armer units can be obtained straightforwardly. It is found that the probability of failure of a breakwater due to the fracture of armor units may be varied with the several allowable fracture ratios. Therefore, it should be necessary to consider the structural stability as well as the hydraulic stability for the design of breakwaters with multi-leg slender concrete armor units of large size under wave action in deep water.

• The Korean Journal of Applied Statistics
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• v.37 no.3
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• pp.381-393
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• 2024

This study investigates the impact of pseudonymization of personal information and its effect on the accuracy of data analysis. We quantitatively evaluated the relationship between the degree of pseudonymization and the accuracy of data analysis using logistic regression models, decision trees, and random forests. Through this, we confirmed that pseudonymizing sensitive information can realize personal information protection without significantly damaging data quality. However, we recognized limitations such as single sample data and consistent application of pseudonymization ratios. To overcome these limitations, additional research on diverse datasets is necessary to strengthen the generalizability of results. Moreover, we propose developing and applying methodologies to find optimal pseudonymization ratios for individual variables. The results from this study provide new insights into maintaining usability of data while achieving regulatory compliance and personal information protection.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.1
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• pp.229-249
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• 2022

This paper investigates machine learning models for predicting the designation of administrative issues in the KOSDAQ market through various techniques. When a company in the Korean stock market is designated as administrative issue, the market recognizes the event itself as negative information, causing losses to the company and investors. The purpose of this study is to evaluate alternative methods for developing a artificial intelligence service to examine a possibility to the designation of administrative issues early through the financial ratio of companies and to help investors manage portfolio risks. In this study, the independent variables used 21 financial ratios representing profitability, stability, activity, and growth. From 2011 to 2020, when K-IFRS was applied, financial data of companies in administrative issues and non-administrative issues stocks are sampled. Logistic regression analysis, decision tree, support vector machine, random forest, and LightGBM are used to predict the designation of administrative issues. According to the results of analysis, LightGBM with 82.73% classification accuracy is the best prediction model, and the prediction model with the lowest classification accuracy is a decision tree with 71.94% accuracy. As a result of checking the top three variables of the importance of variables in the decision tree-based learning model, the financial variables common in each model are ROE(Net profit) and Capital stock turnover ratio, which are relatively important variables in designating administrative issues. In general, it is confirmed that the learning model using the ensemble had higher predictive performance than the single learning model.