• Smart Structures and Systems
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• v.17 no.6
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• pp.1107-1127
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• 2016

Studies on dynamic characteristics of the hanger vibration using field monitoring data are important for the design and evaluation of high-speed railway truss arch bridges. This paper presents an analysis of the hanger's dynamic displacement responses based on field monitoring of Dashengguan Yangtze River Bridge, which is a high-speed railway truss arch bridge with the longest span throughout the world. The three vibration parameters, i.e., dynamic displacement amplitude, dynamic load factor and vibration amplitude, are selected to investigate the hanger's vibration characteristics in each railway load case including the probability statistical characteristics and coupled vibration characteristics. The influences of carriageway and carriage number on the hanger's vibration characteristics are further investigated. The results indicate that: (1) All the eight railway load cases can be successfully identified according to the relationship of responses from strain sensors and accelerometers in the structural health monitoring system. (2) The hanger's three vibration parameters in each load case in the longitudinal and transverse directions have obvious probabilistic characteristics. However, they fall into different distribution functions. (3) There is good correlation between the hanger's longitudinal/transverse dynamic displacement and the main girder's transverse dynamic displacement in each load case, and their relationships are shown in the hysteresis curves. (4) Influences of the carriageway and carriage number on the hanger's three parameters are different in both longitudinal and transverse directions; while the influence on any of the three parameters presents an obvious statistical trend. The present paper lays a good foundation for the further analysis of train-induced hanger vibration and control.

• Journal of the Korea Society of Computer and Information
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• v.26 no.11
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• pp.209-215
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• 2021

The purpose of this study is to identify changing patterns in multicultural adolescent's life satisfaction and to explore longitudinal changes in the effects of acculturation stress, self-esteem and family support on the changes in life satisfaction. For this purpose, the survey data from the 4th to 6th years of the Multicultural Youth Panel Survey were used for the analysis. As a result of the analysis, life satisfaction, self-esteem, and family support decreased for 3 years through each linear change model. As a result of examining the longitudinal mediating effects of self-esteem and family support between acculturation stress and life satisfaction through the multivariate potential growth model, the mediating effect of self-esteem and family support was confirmed. Based on these results, practical implications for improving life satisfaction, self-esteem, and family support of multicultural youth were presented.

• Journal of Korean Academy of Nursing
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• v.49 no.1
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• pp.69-79
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• 2019

Purpose: This study aimed to identify the directionality of the causal relationship and interaction between depression and amount of smoking over time in hardcore smokers using longitudinal descriptive analysis. Methods: Secondary data from the Korean Welfare Panel Study were analyzed using autoregressive cross-lagged modeling. Participants included 342 hardcore smokers who participated in the 8th to 11th waves of the panel study. Results: Analyses revealed that change(s) in depression levels according to time had a significant positive relationship with the total amount of smoking per day (${\beta}=.29$, ${\beta}=.19$, ${\beta}=.17$, p<.001), while change(s) in total amount of smoking per day according to time had a significant positive relationship with depression (${\beta}=.43$, ${\beta}=.50$, ${\beta}=.38$, p<.001). Analysis of the cross-lagged effect between depression and total amount of smoking per day showed that depression at one time point had a significantly positive relationship with the total amount of smoking per day at the next time point (${\beta}=.14$, ${\beta}=.13$, ${\beta}=.13$, p=.021), and that the total amount of smoking per day at one time point had a significant positive relationship with depression at the next time point (${\beta}=.04$, ${\beta}=.04$, ${\beta}=.03$, p=.044). Conclusion: The findings in the present study confirmed a cross-interaction between depression and total amount of smoking per day in hardcore smokers. The present findings could be used to develop appropriate smoking-related interventions.

• Human Ecology Research
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• v.59 no.2
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• pp.233-243
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• 2021

This study examined the longitudinal effects of media usage by early school-age children and of maternal parenting stress on children's school adjustment. The study focused on the mediating effect of executive function difficulty. Longitudinal data to examine the hypothetical model were drawn from the eighth (2015) through tenth (2017) waves of the Panel Study of Korean Children (PSKC) collected by the Korea Institute of Child Care and Education (KICCE). A total of 581 children (293 boys and 288 girls) and their mothers were included. Confirmatory factor analysis, structural equation model, and bootstrapping analysis were applied using SPSS 25.0 and Amos 26.0. The results are as follows. First, no significant correlation was found between early school-age children's media usage and maternal parenting stress. Second, neither media usage by early school-age children nor maternal parenting stress were found to directly affect children's school adjustment. Third, media usage by early school-age children and maternal parenting stress were shown to indirectly affect children's school adjustment via executive function difficulties. In other words, higher levels of media usage by early school-age children and maternal parenting stress during the first grade lead to greater executive function difficulties after a year, which, in turn, lead to a lower level of school adjustment in the third grade. This study indicates the need to develop practical support for the psychological wellbeing of mothers while they are performing their role as a parent and for children in maintaining suitable levels of media usage during early childhood.

• Animal Bioscience
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• v.36 no.11
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• pp.1727-1737
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• 2023

Objective: The poultry industry is a primary source of animal protein worldwide. The gut microbiota of poultry birds, such as chickens and ducks, is critical in maintaining their health, growth, and productivity. This study aimed to identify longitudinal changes in the gut microbiota of laying hens from birth to the pre-laying stage. Methods: From a total of 80 Hy-Line Brown laying hens, birds were selected based on weight at equal intervals to collect feces (n = 20 per growth) and ileal contents (n = 10 per growth) for each growth stage (days 10, 21, 58, and 101). The V4 regions of the 16S rRNA gene were amplified after extracting DNA from feces and ileal contents. Amplicon sequencing was performed using Illumina, followed by analysis. Results: Microbial diversity increased with growth stages, regardless of sampling sites. Microbial community analysis indicated that Firmicutes, Proteobacteria, and Bacteroidetes were the dominant phyla in the feces and ileal. The abundance of Lactobacillus was highest on day 10, and that of Escherichia-shigella was higher on day 21 than those at the other stages at the genus level (for the feces and ileal contents; p<0.05). Furthermore, Turicibacter was the most abundant genus after changing feed (for the feces and ileal contents; p<0.05). The fecal Ruminococcus torques and ileal Lysinibacillus were negatively correlated with the body weights of chickens (p<0.05). Conclusion: The gut microbiota of laying hens changes during the four growth stages, and interactions between microbiota and feed may be present. Our findings provide valuable data for understanding the gut microbiota of laying hens at various growth stages and future applied studies.

• Journal of the Korean Data and Information Science Society
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• v.25 no.5
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• pp.1117-1125
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• 2014

In a longitudinal study, subjects can experience same type of events repeatedly. Also, there may exist intermittent dropouts resulting in repeated observation gaps during which no recurrent events are observed. Furthermore, when such observation gaps have incomplete forms caused by the unknown termination times of observation gaps, ordinary approaches result in biased estimates. In this study, we investigate the effect of ignoring observation gaps and propose methods to overcome this problem. For estimating the distribution of unknown termination times, an interval-censored mechanism is applied and two cases are considered. Simulation studies are carried out to evaluate the performance of the proposed method. Conviction data of young drivers with several suspensions are analyzed to illustrate the suggested approach.

• Communications for Statistical Applications and Methods
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• v.26 no.4
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• pp.371-383
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• 2019

Panel data sets have been developed in various areas, and many recent studies have analyzed panel, or longitudinal data sets. Maximum likelihood (ML) may be the most common statistical method for analyzing panel data models; however, the inference based on the ML estimate will have an inflated Type I error because the ML method tends to give a downwardly biased estimate of variance components when the sample size is small. The under estimation could be severe when data is incomplete. This paper proposes the restricted maximum likelihood (REML) method for a random effects panel data model with a censored dependent variable. Note that the likelihood function of the model is complex in that it includes a multidimensional integral. Many authors proposed to use integral approximation methods for the computation of likelihood function; however, it is well known that integral approximation methods are inadequate for high dimensional integrals in practice. This paper introduces to use the moments of truncated multivariate normal random vector for the calculation of multidimensional integral. In addition, a proper asymptotic standard error of REML estimate is given.

• Journal of Internet Computing and Services
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• v.20 no.1
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• pp.17-24
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• 2019

Since the information of $4^{th}$ Industrial Revolution is introduced in WEF (World Economic Forum) in 2016, IoT, AI, Big Data, 5G, Cloud Computing, 3D/4DPrinting, Robotics, Nano Technology, and Bio Engineering have been rapidly developed as business applications as well as technologies themselves. Among the diverse business applications for IoT, wearable devices are recognized as the leading application devices for final customers. This longitudinal study is compared to the results of the 1st study conducted to identify customer needs of activity trackers, and links the identified users' needs with the well-known marketing frame of marketing mix. For this longitudinal study, a survey was applied to university students in June, 2018, and ANOVA were applied for major variables on usable features. Further, potential customer needs were identified and visualized by Word Cloud Technique. According to the analysis results, different from other high tech IT devices, activity trackers have diverse and unique potential needs. The results of this longitudinal study contribute primarily to understand usable features and their changes according to product maturity. It would provide some valuable implications in dynamic manner to activity tracker designers as well as researchers in this arena.

• Journal of Digital Convergence
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• v.18 no.11
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• pp.31-41
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• 2020

This study analyzed parents' school satisfaction longitudinally using data from the 1st, 3rd, and 5th wave data of the Korea Education Longitudinal Study(KELS)2013. The subjects of analysis are parents who responded without dropping out in the first, third and fifth panel of the KELS2013, and 4,227 cases that had no missing values in the variables were selected for the sample to input for analysis of the latent growth modeling(LGM). As a result, it is confirmed that the parents' education, educational support, and children's academic achievement have a positive effect on the parents' school satisfaction. But the parents' educational view and education cost have a negative effect on that. The results of this study are expected to be important information to help enhance the primary function of the school.

• Korean Journal of Social Welfare
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• v.68 no.3
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• pp.105-125
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• 2016

School absenteeism is considered one of the early predictors of school drop-out and serious delinquency or criminal behavior. The primary goal of the current study was to explore the protective and risk factors related to changing school absenteeism over time based on the ecological-systemic perspective. The data was derived from the Korean Children and Youth Panel Survey (KCYPS) using the 2011 and 2012 survey waves collected from 2,378 elementary school students. Using this data, Panel Fixed Effects Analysis was conducted. Major findings indicated that daily computer usage, parental abuse, school activity attendance, and school grades had an effect on students missing school days over time. Specifically, high levels of computer usage and parental abuse were related to increased school absenteeism, while high levels of school activity attendance and school grades were associated with decreased school absenteeism. These findings emphasized the importance of predictive intervention for children and suggested the need to construct a school absenteeism monitoring system in South Korea.