• Journal of the Korean Home Economics Association
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• v.49 no.9
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• pp.59-72
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• 2011

This study examined whether there are underlying latent classes of growth trajectories of maternal depression in the Korean population. Data from the first phase of the Panel Study of Korean Children (PSKC) of the Institute of Child Care and Education (KICCE) were used for this study. The final sample of participants included 1,471 mothers, who completed three interviews: at birth, at one month, and at four months. A two-class model consisting of depression (12.3%) and non-depression (87.7%) was considered the best-fitting solution using Mplus 3.13. The changes in postnatal depression in the Korean population within four weeks after childbirth, which is the period of "postpartum onset", seem to be important. Logistic regression analysis showed that duration of breast-feeding and planned pregnancy effects were significantly associated with trajectory class membership.

• The Journal of the Korea Contents Association
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• v.22 no.8
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• pp.482-491
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• 2022

The purpose of this study was to classify latent profiles based on satisfaction of student by the campus-life&educational-experiences and to identify factors affecting satisfaction according to each type. For this study, data from the survey of the A univ(1,952 data) were used. To analyze this, a latent profiles analysis was applied to identify subgroups, in which the students by the campus-life&educational-experiences satisfaction, and a multinomial logistic regression model was applied to verify factors affecting group classification. As a result of the analysis, first four groups were classified in the order of 'average·class·highest·relationship satisfaction type'. Second the factors affecting the classification into the remaining three types with 'the average satisfaction type' as a reference group were found to be significant influencing factors(gender, grade, admission process, GPA grade). Based on these results, this study suggested implications for planning and promoting student-tailored education and student support policies at the university level.

• Journal of Animal Environmental Science
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• v.16 no.1
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• pp.29-40
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• 2010

The purpose of the study is to review current studies for economic values on livestock products produced by animal welfare. In order to review the topic, published research papers and reports were reviewed in the world. As the result of the study, the studies for the topic are not researched actively. The main ideas for the studies were consumer survey on meats and egg. Data were questionnaire, Lexis-Nexis databases, consumptions and prices on meats, auction data. Tools for analyses were Random parameters logit and latent class model, WTP analysis, Roterdam model, Pearson's Chi test, Mann-Whitney V-test, Kruskal-Wallis test, structural equation model, regression model, Target-costing, and conjoint analysis.

• Asia Marketing Journal
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• v.14 no.2
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• pp.157-176
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• 2012

Brand switching data frequently used in market structure analysis is adequate to analyze non- durable goods, because it can capture competition between specific two brands. But brand switching data sometimes can not be used to analyze goods like automobiles having long term duration because one of main assumptions that consumer preference toward brand attributes is not changed against time can be violated. Therefore a new type of data which can precisely capture competition among durable goods is needed. Another problem of using brand switching data collected from actual purchase behavior is short of explanation why consumers consider different set of brands. Considering above problems, main purpose of this study is to analyze market structure for durable goods with consideration set. The author uses exploratory approach and latent class clustering to identify market structure based on heterogeneous consideration set among consumers. Then the relationship between some factors and consideration set formation is analyzed. Some benefits and two demographic variables - age and income - are selected as factors based on consumer behavior theory. The author analyzed USA automotive market with top 11 brands using exploratory approach and latent class clustering. 2,500 respondents are randomly selected from the total sample and used for analysis. Six models concerning market structure are established to test. Model 1 means non-structured market and model 6 means market structure composed of six sub-markets. It is exploratory approach because any hypothetical market structure is not defined. The result showed that model 1 is insufficient to fit data. It implies that USA automotive market is a structured market. Model 3 with three market structures is significant and identified as the optimal market structure in USA automotive market. Three sub markets are named as USA brands, Asian Brands, and European Brands. And it implies that country of origin effect may exist in USA automotive market. Comparison between modal classification by derived market structures and probabilistic classification by research model was conducted to test how model 3 can correctly classify respondents. The model classify 97% of respondents exactly. The result of this study is different from those of previous research. Previous research used confirmatory approach. Car type and price were chosen as criteria for market structuring and car type-price structure was revealed as the optimal structure for USA automotive market. But this research used exploratory approach without hypothetical market structures. It is not concluded yet which approach is superior. For confirmatory approach, hypothetical market structures should be established exhaustively, because the optimal market structure is selected among hypothetical structures. On the other hand, exploratory approach has a potential problem that validity for derived optimal market structure is somewhat difficult to verify. There also exist market boundary difference between this research and previous research. While previous research analyzed seven car brands, this research analyzed eleven car brands. Both researches seemed to represent entire car market, because cumulative market shares for analyzed brands exceeds 50%. But market boundary difference might affect the different results. Though both researches showed different results, it is obvious that country of origin effect among brands should be considered as important criteria to analyze USA automotive market structure. This research tried to explain heterogeneity of consideration sets among consumers using benefits and two demographic factors, sex and income. Benefit works as a key variable for consumer decision process, and also works as an important criterion in market segmentation. Three factors - trust/safety, image/fun to drive, and economy - are identified among nine benefit related measure. Then the relationship between market structures and independent variables is analyzed using multinomial regression. Independent variables are three benefit factors and two demographic factors. The result showed that all independent variables can be used to explain why there exist different market structures in USA automotive market. For example, a male consumer who perceives all benefits important and has lower income tends to consider domestic brands more than European brands. And the result also showed benefits, sex, and income have an effect to consideration set formation. Though it is generally perceived that a consumer who has higher income is likely to purchase a high priced car, it is notable that American consumers perceived benefits of domestic brands much positive regardless of income. Male consumers especially showed higher loyalty for domestic brands. Managerial implications of this research are as follow. Though implication may be confined to the USA automotive market, the effect of sex on automotive buying behavior should be analyzed. The automotive market is traditionally conceived as male consumers oriented market. But the proportion of female consumers has grown over the years in the automotive market. It is natural outcome that Volvo and Hyundai motors recently developed new cars which are targeted for women market. Secondly, the model used in this research can be applied easier than that of previous researches. Exploratory approach has many advantages except difficulty to apply for practice, because it tends to accompany with complicated model and to require various types of data. The data needed for the model in this research are a few items such as purchased brands, consideration set, some benefits, and some demographic factors and easy to collect from consumers.

• Environmental and Resource Economics Review
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• v.27 no.4
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• pp.695-723
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• 2018

Recently, extreme weather due to climate change has become more frequent, and increase of fine dust has worsen air quality in Korea. Therefore, not only negative perception on coal-fired power generation is dominant, but also the social acceptance of nuclear power generation declines. This study aims at deriving consumer preferences on the mid and long term power mix with various energy sources. Willingness to pay for each generation source was estimated and the preference heterogeneity of consumers was examined by using mixed logit and latent class models. Mixed logit estimation results show that the preference heterogeneity of consumers is especially large for the nuclear power relative to renewable or coal energy. According to the estimation results from the latent class model, group 1 prefers renewable energy while group 2 prefers coal energy. Group 3 shows lexicographic preference which means restricted rationality. As for the policy implication, it is necessary to understand the preference heterogeneity of consumer groups in planning the mid to long term power mix.

• Journal of Environmental Science International
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• v.1 no.1
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• pp.35-43
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• 1992

Handling the emergency problems such as Chemobyl accident require real time prediction of pollutants dispersion. One-point real time sounding at pollutant source and simple model including turbulent-radiation process are very important to predict dispersion at real time. The stability categories obtained by one-dimensional numerical model (including PBL dynamics and radiative process) are good agreement with observational data (Golder, 1972). Therefore, the meteorological parameters (thermal, moisture and momentum fluxes; sensible and latent heat; Monin-Obukhov length and bulk Richardson number; vertical diffusion coefficient and TKE; mixing height) calculated by this model will be useful to understand the structure of stable boundary layer and to handling the emergency problems such as dangerous gasses accident. Especially, this simple model has strong merit for practical dispersion models which require turbulence process but does not takes long time to real predictions. According to the results of this model, the urban area has stronger vertical dispersion and weaker horizontal dispersion than rural area during daytime in summer season. The maximum stability class of urban area and rural area are "A" and "B" at 14 LST, respectively. After 20 LST, both urban and rural area have weak vertical dispersion, but they have strong horizontal dispersion. Generally, the urban area have larger radius of horizontal dispersion than rural area. Considering the resolution and time consuming problems of three dimensional grid model, one-dimensional model with one-point real sounding have strong merit for practical dispersion model.al dispersion model.

• Smart Structures and Systems
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• v.29 no.1
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• pp.41-51
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• 2022

Cables are critical components of cable-stayed bridges. A structural health monitoring system provides real-time cable tension recording for cable health monitoring. However, the measurement data involve multiple sources of variability, i.e., varying environmental and operational factors, which increase the complexity of cable condition monitoring. In this study, a one-class classification method is developed for cable condition assessment using Bayesian factor analysis (FA). The single-peaked vehicle-induced cable tension is assumed to be relevant to vehicle positions and weights. The Bayesian FA is adopted to establish the correlation model between cable tensions and vehicles. Vehicle weights are assumed to be latent variables and the influences of different transverse positions are quantified by coefficient parameters. The Bayesian theorem is employed to estimate the parameters and variables automatically, and the damage index is defined on the basis of the well-trained model. The proposed method is applied to one cable-stayed bridge for cable damage detection. Significant deviations of the damage indices of Cable SJS11 were observed, indicating a damaged condition in 2011. This study develops a novel method to evaluate the health condition of individual cable using the FA in the Bayesian framework. Only vehicle-induced cable tensions are used and there is no need to monitor the vehicles. The entire process, including the data pre-processing, model training and damage index calculation of one cable, takes only 35 s, which is highly efficient.

• Journal of Global Scholars of Marketing Science
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• v.13
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• pp.135-158
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• 2004

On-line consumers have some visit behavior characteristics when they visit internet-shopping mall between visit-stage and purchase-stage. Therefore, information of on-line consumers have influenced on internet-shopping mall's profitabilities at site manager's perspectives. For examples, Are any on-line consumers continuous visiting under any situations? Or are any on-line consumers purchased on any specific internet-shopping mall? Expecially in this paper, researcher tried to understand visit behavioral characteristics of on-line consumers using two-stage mixture regression analysis. Throughout this process, it could be proposed method, which could be reinforced competitiveness of internet-shopping mall by segmental decision-making method. Additionally, it is expected that visit behavioral characteristics' information could be supplied strategic implications between visit-stage and purchase-stage Throughout empirical test it could be proved two-stage decision-making process, which decision-making process of on-line consumers would be processed visit-stage and purchase-stage. In this study, researcher proposed suitable response strategy after understanding visiting behavioral characteristics of on-line consumers. This paper has some academical contributions, which visit behavioral characteristics of on-line consumers could be grasped the meaning by site stickiness and navigation pattern.

• Journal of Veterinary Clinics
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• v.33 no.2
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• pp.102-106
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• 2016

More than 20 years after the first report of porcine reproductive and respiratory syndrome virus (PRRSV) in Korea, the disease is still having major impact on domestic pig health and relevant industries. Although ELISA tests are commonly used by veterinarians to guide herd management, data on diagnostic performance of the test in field settings are very limited. The objective of this study was to evaluate two commercially available PRRSV ELISA (IDEXX PRRS X3 ELISA and Bionote PRRSV ELISA 4.0) to detect antibodies against PRRSV on serum samples. To this end, a total of 1,108 sera were recruited from 35 swine farms located in Gyeonggi province and tested at the Gyeonggi Province Veterinary Service Center. All tests were performed according to the manufacturer's instructions, by laboratory technicians who routinely perform PRRS testing on blood samples. Samples were collected from two sources of swine populations with different PRRS prevalence; 60 samples (5.4%) were originated from breeding farms and the remaining 1,048 samples (94.6%) were from farrow-to-finish farms. We applied Bayesian latent class model (LCM) for two-tests in the two-population when the accuracy of the gold standard is not available. The model estimated that Bionote ELISA was a bit more specific but slightly less sensitive. The estimated sensitivity and specificity of the IDEXX ELISA were 99.8% (95% CI 98.1-100%) and 86.4% (95% CI 81.4-96.5%), respectively. Sensitivity, specificity, positive predictive value and negative predictive value for Bionote kit were 98.7% (95% CI 92.8-100%), 89.8% (95% CI 86.2-93.1%), 93.8% (95% CI 91.5-96.0%), and 97.8% (95% CI 87.1-100%), respectively. Based on the Bayesian 95% credible intervals, the sensitivity and specificity of the two ELISAs were not significantly different each other when assuming that two kits were imperfect, indicating that two kits performed equally well in terms of sensitivity and specificity in our filed setting.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.06a
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• pp.35-36
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• 2016

본 논문에서는 기존 Bag-of-Visual words (BoW) 접근법에서 반영하지 못한 이미지의 공간 정보를 활용하기 위해서 Spatial Pyramid Matching (SPM) 기법을 Latent Dirichlet Allocation (LDA) 모델에 결합하여 이미지를 분류하는 모델을 제안한다. BoW 접근법은 이미지 패치를 시각적 단어로 변환하여 시각적 단어의 분포로 이미지를 표현하는 기법이며, 기존의 방식이 이미지 패치의 위치정보를 활용하지 못하는 점을 극복하기 위하여 SPM 기법을 도입하는 연구가 진행되어 왔다. 또한 이미지 패치를 정확하게 표현하기 위해서 벡터 양자화 대신 희소 부호화 기법을 이용하여 이미지 패치를 시각적 단어로 변환하였다. 제안하는 모델은 BoW 접근법을 기반으로 위치정보를 활용하는 SPM 을 LDA 모델에 적용하여 시각적 단어의 토픽을 추론함과 동시에 multi-class SVM 분류기를 이용하여 이미지를 분류한다. UIUC 스포츠 데이터를 이용하여 제안하는 모델의 분류 성능을 검증하였다.