• Human Ecology Research
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• v.53 no.6
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• pp.641-654
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• 2015

This study identifies and tracks changes gender differences in adolescent users' problematic online behavior. This study used Korea Youth Panel Survey (KYPS), which has tracked respondents over 7 years, with self-control theory and social learning theory applied as a theoretical framework. The model included individual-level variables such as self-control and respondent's experience of problematic behavior (offline), as well as socialization variables such as the number close friends who engaged in problematic offline behavior, parent-child relationships, and parental monitoring. Dependent variables included problematic online behavior, unauthorized ID use (ID theft) and cyberbullying (cursing/insulting someone in a chat room or on a bulletin board). Control variables consisted of academic performance, time spent on a computer, monthly household income, and father's educational attainment. Random and fixed effects models were performed by gender. Results supported self-control theory even for the within-level analysis (fixed effects models) regardless of gender, while social learning theory was partially supported. Only peer effects were found significant (except for unauthorized ID use) among girls. Year dummy variables showed significant negative associations; however, academic performance and time spent using computers were significant in some models. Father's educational attainment and monthly household income were found insignificant, even in the random effects models. We also discuss implications and suggestions for future research and policy makers.

• Journal of the Korean Data and Information Science Society
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• v.19 no.4
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• pp.1327-1334
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• 2008

Mixed effect binomial regression models are widely used for analysis of correlated count data in which the response is the result of a series of one of two possible disjoint outcomes. In this paper, we consider kernel extensions with nonparametric fixed effects and parametric random effects. The estimation is through the penalized likelihood method based on kernel trick, and our focus is on the efficient computation and the effective hyperparameter selection. For the selection of hyperparameters, cross-validation techniques are employed. Examples illustrating usage and features of the proposed method are provided.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.11a
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• pp.235-238
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• 2006

For high-speed aircraft and high-speed civil transport planes, certain structural skin components are subjected to very large acoustic loads in an elevated thermal environment. In this study, we used the single-mode Fokker-Panck distribution to predict displacements of isotropic plates subject to thermo-acoustic combined load. The single mode was formulated to predict the nonlinear dynamic responses of postbuckled plates under acoustic random excitation. Acoustic random excitation was used with Gauss distribution. Some important effects of the snap-through motion on the dynamic responses of the postbuckled plates are described.

• IE interfaces
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• v.12 no.3
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• pp.401-405
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• 1999

We present a simulation model to generate the spatial distribution of mobiles in cellular communication network. Three types of spatial distributions are considered; biased, random, and ratio-based distributions. This study also points out and corrects the critical errors performed by Das and Morgera(1997) in getting random location of mobiles. By applying a simple path loss model, the effects of our correction on the signal-to-interference(SIR) ratio are discussed. The numerical results indicate that the variation of SIR in the Das's biased distribution is larger than that of other distributions. As compared with the random distribution, the average SIR error of the biased distribution is 91.1%.

• Structural Engineering and Mechanics
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• v.43 no.6
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• pp.835-845
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• 2012

This paper focuses on the stochastic response analysis of industrial masonry chimneys to surface blast-induced random ground motions by using a three dimensional finite element model. Underground blasts induce ground shocks on nearby structures. Depending on the distance between the explosion centre and the structure, masonry structures will be subjected to ground motions due to the surface explosions. Blast-induced random ground motions can be defined in terms of the power spectral density function and applied to each support point of the 3D finite element model of the industrial masonry system. In this paper, mainly a parametric study is conducted to estimate the effect of the blast-induced ground motions on the stochastic response of a chimney type masonry structure. With this purpose, different values of charge weight and distance from the charge centre are considered for the analyses of the chimney. The results of the study underline the remarkable effect of the surface blast-induced ground motions on the stochastic behaviour of industrial masonry type chimneys.

• Bulletin of the Korean Mathematical Society
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• v.40 no.2
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• pp.269-279
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• 2003

We prove an empirical LIL for the Kaplan-Meier integral process constructed from the random censorship model under bracketing entropy and mild assumptions due to censoring effects. The main method in deriving the empirical LIL is to use a weak convergence result of the sequential Kaplan-Meier integral process whose proofs appear in Bae and Kim [2]. Using the result of weak convergence, we translate the problem of the Kaplan Meier integral process into that of a Gaussian process. Finally we derive the result using an empirical LIL for the Gaussian process of Pisier [6] via a method adapted from Ossiander [5]. The result of this paper extends the empirical LIL for IID random variables to that of a random censorship model.

• Structural Engineering and Mechanics
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• v.6 no.6
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• pp.673-691
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• 1998

In this paper, an analytic method to examine the random vibration of multispan Timoshenko frames due to a concentrated load traversing at a constant velocity is presented. A load's magnitude is a stationary process in time with a constant mean value and a variance. Two types of variances of this load are considered: white noise process and cosine process. The effects of both velocity and statistical characteristics of load and span number of the frame on both the mean value and variance of deflection and moment of the structure are investigated. Results obtained from a multispan Timoshenko frame are compared with those of a multispan Bernoulli-Euler frame.

• JSTS:Journal of Semiconductor Technology and Science
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• v.14 no.3
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• pp.268-273
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• 2014

The forming, reset and set operation of bipolar resistive random access memory (RRAM) have been predicted by using a finite element (FE) model which includes interface effects. To the best of our knowledge, our bipolar RRAM model is applicable to realistic cell structure optimization because our model is based on the FE method (FEM) unlike precedent models.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1989.10a
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• pp.40-45
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• 1989

In order to take account of the statistical properties of random variables used in the structural analysis, the conventional approach usually adopts the safety factor based on past experiences for the qualitative assessment of structural safety problem. Recently, new approach based on the probabilistic concept has been applied to the assessment of structural safety in order to circumvent the difficulties of the conventional approach in choosing the appropriate safety factor. Thus, computer program called "Probabilistic finite element method" is developed by incorporation the probabilistic concept into the conventional matrix method in order to investigate the effects of the random variables on the final output of the structural analysis. From the comparison of some examples, it can be concluded that the PFEM developed in this study deals with consistently with the uncertainty of random variables and provides the rational tool for the assessment of structural safety of plane frame.

• Proceedings of the Korean Statistical Society Conference
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• 2003.05a
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• pp.79-84
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• 2003

Likelihood estimation in random-effect models is often complicated because the marginal likelihood involves an analytically intractable integral. Numerical integration such as Gauss-Hermite quadrature is an option, but is generally not recommended when the dimensionality of the integral is high. An alternative is the use of hierarchical likelihood, which avoids such burdensome numerical integration. These two approaches for fitting binary data are compared and the advantages of using the hierarchical likelihood are discussed. Random-effect models for binary outcomes and for bivariate binary-continuous outcomes are considered.