• The Korean Journal of Applied Statistics
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• v.33 no.3
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• pp.281-296
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• 2020

Repeated outcomes from the same subjects are referred to as longitudinal data. Analysis of the data requires different methods unlike cross-sectional data analysis. It is important to model the covariance matrix because the correlation between the repeated outcomes must be considered when estimating the effects of covariates on the mean response. However, the modeling of the covariance matrix is tricky because there are many parameters to be estimated, and the estimated covariance matrix should be positive definite. In this paper, we consider analysis of multivariate longitudinal data via two modeling methodologies for the covariance matrix for multivariate longitudinal data. Both methods describe serial correlations of multivariate longitudinal outcomes using a modified Cholesky decomposition. However, the two methods consider different decompositions to explain the correlation between simultaneous responses. The first method uses enhanced linear covariance models so that the covariance matrix satisfies a positive definiteness condition; in addition, and principal component analysis and maximization-minimization algorithm (MM algorithm) were used to estimate model parameters. The second method considers variance-correlation decomposition and hypersphere decomposition to model covariance matrix. Simulations are used to compare the performance of the two methodologies.

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.4
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• pp.312-319
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• 2013

Our understanding of the sensitivities of crop responses to changes in carbon dioxide, temperature, and water is limited, which makes it difficult to fully utilize crop models in assessing the impact of climate change on future agricultural production. Genetic coefficients of CERES-Barley model for major domestic cultivars in South Korea (Olbori at Suwon, Albori at Milyang, Saessalbori at Iksan, and Samdobori at Jinju) were estimated from the observed data for daily weather and field trials for more than 10 years by using GenCalc in DSSAT. Data from 1997-2002 annual crop status report (Rural Development Administration, RDA) were used to validate the crop coefficients. The sitecalibrated CERES-Barley model was used to perform crop growth simulation with the 99 treatments of step change combinations in temperature, precipitation and carbon dioxide concentration with respect to the baseline climate (1981-2010) at four sites. The upper boundary corresponds to the 2071-2100 climate outlook from the RCP 8.5 scenario. The response surface of grain yield showed a distinct pattern of model behavior under the combined change in environmental variables. The simulated grain yield was most sensitive to $CO_2$ concentration, least sensitive to precipitation, and showing a variable response to temperature depending on cultivar. The emulated impacts of response surfaces are expected to facilitate assessment of projected climate impacts on a given cultivar in South Korea.

• FLOWER RESEARCH JOURNAL
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• v.19 no.1
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• pp.68-76
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• 2011

This study was conducted to investigate customer taste related to satisfaction of a baby's first birthday party and re-visit of venues. General characteristics of customers were similar in male and female or the married and the unmarried. Mainstream age of respondents was from in their 20's to 30's. Among them, the number of university graduates were the largest in education level. Theoretical model was composed with seven significant variables of design style and composition and design harmony and color sense for flower decoration, accessibility, facility, service and price, satisfaction, and intention of re-visit based on the result of analysis on these factors. Exploratory factor analysis was performed using SPSS 14.0K. Structural equation modeling(SEM) for simultaneous measure of path coefficient in all casualty of study model, measurement model of AMOS 7.0 for evaluation of validity, and reliability and factor analysis method using technical statistics, frequency analysis, and Cronbach's Alpha for data analysis were used. The result of hypothesis verification showed that design style and composition was the most significant item in satisfaction of parameter and it was followed by design harmony and color sense. While service and price had positive effect on satisfaction, accessibility and facility had no relation to it. It means that the most crucial variable was a flower decoration in planning and representation of the celebration of baby's first birthday. In conclusion, the finding of this study suggests that the effective utilization of these variables will contribute to the enhancement of satisfaction affecting improvement service and price or intention of re-visit.

• Korean Journal of Construction Engineering and Management
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• v.22 no.1
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• pp.36-46
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• 2021

With an increasing trend toward high-rise modular construction, the simultaneous use of tower cranes at a modular construction site has recently been observed. Tower crane layout planning (TCLP) has a significant effect on cost, duration, safety and productivity of a project. In a modular construction project, particularly, poor decision about the layout of tower cranes is likely to have negative effects like additional employment of cranes and redesign, which will lead to additional costs and possible delays. It is, therefore, crucial to conduct thorough inspection of field conditions, lifting materials, tower crane capacity to make decisions on the layout of tower cranes. However, several challenges exist in planning for a multi-crane construction site in terms of safety and collaboration, which makes planning with experience and intuition complicated. This paper suggests a multi-objective optimization model for selection of the number of tower cranes, their models and locations, which minimizes cost and conflict. The proposed model contributes to the body of knowledge by showing the feasibility of using multi-objective optimization for TCLP decision-making process with consideration of trade-offs between cost and conflict.

• Journal of Biomedical Engineering Research
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• v.43 no.5
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• pp.331-340
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• 2022

Early afterdepolarization (EAD), a significant cause of fatal ventricular arrhythmias including Torsade de Pointes (TdP) in long QT syndromes, is a depolarizing afterpotential at the plateau or repolarization phase in action potential (AP) profile early before completing one pace. AP duration prolongation is related to EAD but is not necessarily accounted for EAD. Several computational studies suggested EAD can form from an abnormality in the late plateau and/or repolarization phase of AP shape. In this sense, we hypothesized the slope during repolarization has the characteristics to predict TdP risk, mainly focusing on the maximum slope during repolarization (dVm/dt_{max_repol}). This study aimed to predict the sensitivity of dVm/dt_{max_repol} to ion channel conductances as a TdP risk metric through a population simulation considering multiple effects of simultaneous reduction in six ion channel conductances of g_NaL, g_Kr, g_Ks, g_to, g_K1, and g_CaL. Additionally, we verified the availability of dVm/dt_{max_repol} for TdP risk prediction through the correlation analysis with qNet, the representative TdP metric. We performed the population simulations based on the methodology of Gemmel et al. using the human ventricular myocyte model of Dutta et al. Among the sixion channel conductances, dVm/dt_{max_repol} and qNet responded most sensitively to the change in g_Kr, followed by g_NaL. Furthermore, dVm/dt_{max_repol} showed a statistically significant high negative correlation with qNet. The dVm/dt_{max_repol} values were significantly different according to three TdP risk levels of high, intermediate, and low by qNet (p<0.001). In conclusion, we suggested dVm/dt_{max_repol} as a new biomarker metric for TdP risk assessment.

• Journal of Korea Water Resources Association
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• v.55 no.11
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• pp.887-901
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• 2022

Estimation of the parameters for individual rainfall-rainfall events can lead to a different set of parameters for each event which result in lack of parameter identifiability. Moreover, it becomes even more ambiguous to determine a representative set of parameters for the watershed due to enhanced variability exceeding the range of model parameters. To reduce the variability of estimated parameters, this study proposed a parameter optimization framework with the simultaneous use of multiple rainfall-runoff events based on NSE as an objective function. It was found that the proposed optimization framework could effectively estimate the representative set of parameters pertained to their physical range over the entire watershed. It is found that the difference in NSE value of optimization when it performed individual and multiple rainfall events, is 0.08. Furthermore, In terms of estimating the observed floods, the representative parameters showed a more improved (or similar) performance compared to the results obtained from the single-event optimization process on an NSE basis.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.35 no.4
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• pp.75-83
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• 2023

Apart from implementing hardware solutions like raising the crest freeboard of coastal structures to efficiently counter wave-overtopping, there is a simultaneous requirement for software-driven disaster mitigation strategies. These tactics involve the swift and accurate dissemination of wave-overtopping information to the inland regions of coastal zones, enabling the regulation of evacuation procedures and movement. In this study, a method was proposed to estimate wave-overtopping by utilizing the temporal variation of wave heights exceeding the structure's crown level, with the aim of developing an on-site wave measurement system for providing wave-overtopping information in the field. Laboratory model experiments were conducted on vertical seawall structures to measure wave-overtopping volumes and wave runup heights under different wave conditions and structural freeboard variations. By assuming that the velocity of water inundation on the top of the structure during wave-overtopping events is equivalent to the long-wave velocity, an overtopping discharge coefficient was introduced. This coefficient was utilized to estimate the rate of wave-overtopping based on the temporal changes in wave runup heights measured at the top of the structure. Upon reasonably calculating the overtopping discharge coefficient, it was verified that the estimation of wave-overtopping could be achieved solely based on the wave runup heights.

• Journal of the Korean Society for information Management
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• v.39 no.1
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• pp.91-117
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• 2022

The number of depressed patients in Korea and around the world is rapidly increasing every year. However, most of the mentally ill patients are not aware that they are suffering from the disease, so adequate treatment is not being performed. If depressive symptoms are neglected, it can lead to suicide, anxiety, and other psychological problems. Therefore, early detection and treatment of depression are very important in improving mental health. To improve this problem, this study presented a deep learning-based depression tendency model using Korean social media text. After collecting data from Naver KonwledgeiN, Naver Blog, Hidoc, and Twitter, DSM-5 major depressive disorder diagnosis criteria were used to classify and annotate classes according to the number of depressive symptoms. Afterwards, TF-IDF analysis and simultaneous word analysis were performed to examine the characteristics of each class of the corpus constructed. In addition, word embedding, dictionary-based sentiment analysis, and LDA topic modeling were performed to generate a depression tendency classification model using various text features. Through this, the embedded text, sentiment score, and topic number for each document were calculated and used as text features. As a result, it was confirmed that the highest accuracy rate of 83.28% was achieved when the depression tendency was classified based on the KorBERT algorithm by combining both the emotional score and the topic of the document with the embedded text. This study establishes a classification model for Korean depression trends with improved performance using various text features, and detects potential depressive patients early among Korean online community users, enabling rapid treatment and prevention, thereby enabling the mental health of Korean society. It is significant in that it can help in promotion.

• Geophysics and Geophysical Exploration
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• v.10 no.3
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• pp.191-202
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• 2007

To identify the detailed attenuation structure in the southern Korean Peninsula, a numerical test was conducted for the Q tomography inversion to be applied to the accumulated dataset until 2005. In particular, the stochastic pointsource ground-motion model (STGM model; Boore, 2003) was adopted for the 2D Q tomography inversion for direct application to simulating the strong ground-motion. Simultaneous inversion of the STGM model parameters with a regional single Q model was performed to evaluate the source and site effects which were necessary to generate an artificial dataset for the numerical test. The artificial dataset consists of simulated Fourier spectra that resemble the real data in the magnitude-distance-frequency-error distribution except replacement of the regional single Q model with a checkerboard type of high and low values of laterally varying Q models. The total number of Q blocks used for the checkerboard test was 75 (grid size of $35{\times}44km^2$ for Q blocks); Q functional form of $Q_0f^{\eta}$ ($Q_0$=100 or 500, 0.0 < ${\eta}$ < 1.0) was assigned to each Q block for the checkerboard test. The checkerboard test has been implemented in three steps. At the first step, the initial values of Q-values for 75 blocks were estimated. At the second step, the site amplification function was estimated by using the initial guess of A(f) which is the mean site amplification functions (Yun and Suh, 2007) for the site class. The last step is to invert the tomographic Q-values of 75 blocks based on the results of the first and second steps. As a result of the checkerboard test, it was demonstrated that Q-values could be robustly estimated by using the 2D Q tomography inversion method even in the presence of perturbed source and site effects from the true input model.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.7
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• pp.989-998
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• 1993

In a bursty user traffic mode, ALOHA random multiple access protocol achieves higher performance than any conventional fixed assignment technique. One of central problems in slotted ALOHA is synchronization. Because of the long propagation delay in satellite mobile communication, packet may be spilt over into adjacent slots and thus guard time may be included between packet intervals. In conventional ALOHA channels, simultaneous transmission by two or more users results in a collision : the unsuccessful packets have to be retransmitted according to some retransmission algorithm. However, in a radio environment, users are often at different distances from the receiver : therefore, their received signals have substantially different power levels. The packet arriving with the highest energy now has a good chance of being detected accurately. Similarly, in some spread-spectrum random access systems, the earliest arriving packet dominates later arriving packets and thus captures the channel. In this paper slotted ALOHA channel with non zero guard time and capture probability is studied. Using the Markovian model, the performance of slotted ALOHA with guard time and capture effects is derived and compared with that of the conventional ALOHA via numerical analysis.