• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.1
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• pp.57-64
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• 2002

Three kinds of viscoelastic damper model, which has a non-linear spring as an element is studied analytically and numerically The behavior of the damper model shows non-linear hysteresis curves which is qualitatively similar to those of real viscoelastic materials. The motion is governed by a non-linear constitutive equation and an additional equation of motion. Harmonic balance method is applied to get analytical solutions of the system. The frequency-response curves sallow that multiple solutions co-exist and that the jump phenomena can occur. In addition, it is shown that separate solution branch exists and that it can merge with the primary response curve. Saddle-node bifurcation sets explain the occurrences of such non-linear Phenomena.

• Laboraroty Animal Research
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• v.34 no.4
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• pp.203-210
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• 2018

Stress severely disturbs physiological and mental homeostasis which includes adult neurogenesis in hippocampus. Neurogenesis in hippocampus is a key feature to adapt to environmental changes and highly regulated by multiple cellular signaling pathways. The primary cilium is a cellular organelle, which acts as a signaling center during development and neurogenesis in adult mice. However, it is not clear how the primary cilia are involved in the process of restraint (RST) stress response. Using a mouse model, we examined the role of primary cilia in repeated and acute RST stress response. Interestingly, RST stress increased the number of ciliated cells in the adult hippocampal dentate gyrus (DG). In our RST model, cell proliferation in the DG also increased in a time-dependent manner. Moreover, the analysis of ciliated cells in the hippocampal DG with cell type markers indicated that cells that were ciliated in response to acute RST stress are neurons. Taken together, these findings suggest that RST stress response is closely associated with an increase in the number of ciliated neurons and leads to an increase in cell proliferation.

• Communications for Statistical Applications and Methods
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• v.29 no.2
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• pp.239-250
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• 2022

In many applications, we frequently encounter correlated multiple outcomes measured on the same subject. Joint modeling of such multiple outcomes can improve efficiency of inference compared to independent modeling. For instance, in developmental toxicity studies, fetal weight and number of malformed pups are measured on the pregnant dams exposed to different levels of a toxic substance, in which the association between such outcomes should be taken into account in the model. The number of malformations may possibly have many zeros, which should be analyzed via zero-inflated count models. Motivated by applications in developmental toxicity studies, we propose a Bayesian joint modeling framework for continuous and count outcomes with excess zeros. In our model, zero-inflated Poisson (ZIP) regression model would be used to describe count data, and a subject-specific random effects would account for the correlation across the two outcomes. We implement a Bayesian approach using MCMC procedure with data augmentation method and adaptive rejection sampling. We apply our proposed model to dose-response analysis in a developmental toxicity study to estimate the benchmark dose in a risk assessment.

• ETRI Journal
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• v.25 no.1
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• pp.9-18
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• 2003

We mathematically analyze the passband vestigial sideband (VSB) system for the Advanced Television Systems Committee (ATSC) digital television standard and present a baseband-equivalent VSB model. The obtained baseband VSB model is represented by convolution of the transmission signal (before modulation) and the baseband equivalent of the complex VSB channel. Due to the operation of the physical channel as an RF passband and the asymmetrical property of VSB modulation, it is necessary to use a complex model. However, the passband channel may be reduced to an equivalent baseband. We show how to apply standard channel model information such as delay, gain, and phase for multiple signal paths to compute both the channel frequency response with a given carrier frequency and the resulting demodulated impulse response. Simulation results illustrate that the baseband VSB model is equivalent to the passband VSB model.

• Earthquakes and Structures
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• v.17 no.1
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• pp.75-89
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• 2019

The paper presents experimental and numerical studies carried out on low-rise RC frames, typically found in developing countries. Shake table tests were conducted on 1:3 reduced scaled two-story RC frames that included a code conforming SMRF model and another non-compliant model. The later was similar to the code conforming model, except, it was prepared in concrete having strength 33% lower than the design specified, which is commonly found in the region. The models were tested on shake table, through multiple excitations, using acceleration time history of 1994 Northridge earthquake, which was linearly scaled for multi-levels excitations in order to study the structures' damage mechanism and measure the structural response. A representative numerical model was prepared in finite element based program SeismoStruct, simulating the observed local damage mechanisms (bar-slip and joint shear hinging), for seismic analysis of RC frames having weaker beam-column joints. A suite of spectrum compatible acceleration records was obtained from PEER for incremental dynamic analysis of considered RC frames. The seismic performance of considered RC frames was quantified in terms of seismic response parameters (seismic response modification, overstrength and displacement amplification factors), for critical comparison.

• Earthquakes and Structures
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• v.25 no.6
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• pp.469-479
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• 2023

A probabilistic seismic damage analysis is an essential procedure to identify seismically vulnerable structures, prioritize the seismic retrofit, and ultimately minimize the overall seismic risk. To assess the seismic risk of multiple structures within a region, a large number of nonlinear time-history structural analyses must be conducted and studied. As a result, each assessment requires high computing resources. To overcome this limitation, we explore a deep learning-based metamodel to enable the prediction of the mean and the standard deviation of the seismic damage distribution of track-on steel-plate girder railway bridges in Korea considering the geometric variation. For machine learning training, nonlinear dynamic time-history analyses are performed to generate 800 high-fidelity datasets on the seismic response. Through intensive trial and error, the study is concentrated on developing an optimal machine learning architecture with the pre-identified variables of the physical configuration of the bridge. Additionally, the prediction performance of the proposed method is compared with a previous, well-defined, response surface model. Finally, the statistical testing results indicate that the overall performance of the deep-learning model is improved compared to the response surface model, as its errors are reduced by as much as 61%. In conclusion, the model proposed in this study can be effectively deployed for the seismic fragility and risk assessment of a region with a large number of structures.

• Communications for Statistical Applications and Methods
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• v.31 no.2
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• pp.191-202
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• 2024

The goal of this paper is to show how multivariate regression analysis with high-dimensional responses is facilitated by the response dimension reduction. Multivariate regression, characterized by multi-dimensional response variables, is increasingly prevalent across diverse fields such as repeated measures, longitudinal studies, and functional data analysis. One of the key challenges in analyzing such data is managing the response dimensions, which can complicate the analysis due to an exponential increase in the number of parameters. Although response dimension reduction methods are developed, there is no practically useful illustration for various types of data such as so-called large p-small n data. This paper aims to fill this gap by showcasing how response dimension reduction can enhance the analysis of high-dimensional response data, thereby providing significant assistance to statistical practitioners and contributing to advancements in multiple scientific domains.

• Journal of Mechanical Science and Technology
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• v.15 no.7
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• pp.1002-1012
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• 2001

The work reported here is an extensive study of tendon response to multiple cyclic tests including 3% constant peak strain level test (A-type test), 3% constant peak strain level test with two rest periods (B-type test), and 3∼4% different peak strain level test (C-type test). A sufficient number of specimens were tested at each type of the test to statistically evaluate many changes in response during testing and differences in response between each type of the test. In cyclic tests, there were decreses (relaxations) in the peak stresses and hysteresis, increases in the slack strains, and during lower peak strain level (3%) cyclic block after higher peak strain level (4%) cyclic block in the C-type tests. Considering the results of this study and those of the other study of multiple cyclic tests with rest periods by Hubbard and Chun, 1985, recovery phenomena during the rest periods occurred predominantly at the beginning of the rest periods. Consistently in both studies, the effects of rest periods were small and transient compared to the effects of the cyclic extensions. The recovery with cycles at lower peak strain level (3%) after higher peak strain level (4%) in the C-type test has not been previously documented. This recovery seems to be a natural phenomena in tissue behavior so that collagenous structures recover during periods of decreased demand.

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.3
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• pp.361-369
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• 2018

This paper proposes a design of asymmetric time division multiple access method for tactical radio communication. Typical tactical radio communication has a limited execution of transmission, because uplink message requires more extended response time than downlink message. In order to solve this problem, this paper analyzes operational environment of Korean tactical radio communication and proposes an asymmetric TDMA based on it for performance of tactical communication. The simulation model is used to investigate constraints of real experiments for proving effectiveness of the proposed approach. Simulations results show that the proposed scheme outperforms the conventional scheme in terms of throughput, response time, and delay.

• Smart Structures and Systems
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• v.21 no.4
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• pp.521-535
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• 2018

The main purpose of this paper is to predict missing absolute out-of-plane displacements and failure limits of infill walls by artificial neural network (ANN) models. For this purpose, two shake table experiments are performed. These experiments are conducted on a 1:1 scale one-bay one-story reinforced concrete frame (RCF) with an infill wall. One of the experimental models is composed of unreinforced brick model (URB) enclosures with an RCF and other is composed of an infill wall with bed joint reinforcement (BJR) enclosures with an RCF. An artificial earthquake load is applied with four acceleration levels to the URB model and with five acceleration levels to the BJR model. After a certain acceleration level, the accelerometers are detached from the wall to prevent damage to them. The removal of these instruments results in missing data. The missing absolute maximum out-of-plane displacements are predicted with ANN models. Failure of the infill wall in the out-of-plane direction is also predicted at the 0.79 g acceleration level. An accuracy of 99% is obtained for the available data. In addition, a benchmark analysis with multiple regression is performed. This study validates that the ANN-based procedure estimates missing experimental data more accurately than multiple regression models.