• The Transactions of the Korea Information Processing Society
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• v.4 no.10
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• pp.2640-2650
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• 1997

In this paper we propose new image coding using wavelet transform. The new method constructs hierarchical bit plane and progressively transports each bit plane. The proposed algorithms not only supports multi-resolution, dividing original image into special band and various resolution but also reduces blocking effects that come int JPEG. In encoding time this algorithm considers each band characters and priority of transport order, and applies to fast search of image.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2084-2086
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• 2001

This study uses distributed parameter systems as the spatial discretization technique, modelling in lumped parameter systems, and applies orthogonal transform and the Picard's iteration method to high order partial differential equations and matrix partial differential equations. In exercising optimal control of distributed parameter systems, excellent consequences are found without using the existing decentralized control or hierarchical control method.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.6
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• pp.766-771
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• 2006

In this paper, we focus on the building domain ontology from corpus by extracting concepts and properties relationships based on linguistic patterns. The pharmacy field is selected as an experiment domain and we present an algorithm to extract hierarchical structure for terminology based on the noun/suffix patterns of terminology in domain texts. In order to show usefulness of our domain ontology, we compare a typical keyword based retrieval method with an ontology based retrieval mettled which uses related information in an ontology for a related feedback. As a result, our method shows the improvement of precision by 4.97% without losing recall.

• Korean Journal of Remote Sensing
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• v.20 no.5
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• pp.353-359
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• 2004

This study proposes an approach to unsupervisedly estimate the number of classes and the parameters of defining the classes in order to train the classifier. In the proposed method, the image is segmented using a spatial region growing based on hierarchical clustering, and fuzzy training is then employed to find the sample classes that well represent the ground truth. For cluster validation, this approach iteratively estimates the class-parameters in the fuzzy training for the sample classes and continuously computes the log-likelihood ratio of two consecutive class-numbers. The maximum ratio rule is applied to determine the optimal number of classes. The experimental results show that the new scheme proposed in this study could be used to select the regions with different characteristics existed on the scene of observed image as an alternative of field survey that is so expensive.

• International Journal of Advanced Culture Technology
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• v.7 no.1
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• pp.14-19
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• 2019

Stress affects the type of adaptation required for each case and the type of social support is also different. In order for social support to have a buffer effect on stress, we want to understand how to measure social support and support according to specific stress situations. Therefore, this study examines coping behaviors of community service workers exposed to these job stresses and examines the effect of support system (family support, peer support, superior support) on coping behavior. The purpose of this study is to investigate the effects of stress, coping resources and coping behaviors of community service workers. In this study, self - report method was used to investigate the questionnaire using structured questionnaires. In this study, the statistical program was used for data analysis and hierarchical regression analysis.

• Child Health Nursing Research
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• v.25 no.1
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• pp.65-73
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• 2019

Purpose: This study aimed to identify factors associated with maternal attachment of breastfeeding mothers, with a focus on the mothers' breastfeeding characteristics. Methods: Data were collected from 217 mothers who breastfed their healthy baby for 1 month after childbirth and had no postpartum complications. The data were analyzed by hierarchical regression analysis. Results: The factors significantly associated with maternal attachment were an emotional exchange with one's baby (${\beta}=.41$, p<.001), breastfeeding confidence (${\beta}=.20$, p=.022), depression ('quite a bit or more', ${\beta}=-.18$, p=.005), and depression ('a little', ${\beta}=-.14$, p=.024). The model explained 38.4% of variance in maternal attachment. Conclusion: In order to improve attachment, nurses should be actively supported in helping mothers in the first month postpartum adapt to breastfeeding. Interventions to prevent postpartum depression should also be conducted.

• English & American cultural studies
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• v.18 no.4
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• pp.189-213
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• 2018

This paper aims to show how Thomas Hardy overturns conventional ideas in opposition and eventually disrupts the hierarchical order of ideas in the Victorian society of Tess of the D'Urbervilles. Divided into four sections, such as feeling/reason, purity/impurity, femininity/masculinity, and death/life, it examines how these binaries are deconstructed in the heroine's tragic life journey. The heroine Tess of the book, who boldly crosses the boundaries marked by traditional society, turns her image as a fallen woman into that of divinity, erasing the boundary between evil and good. In doing so, Hardy leads the reader to question the system of established values and reveals the illegitimacy of absolute values, thence stressing what all one can grasp in this world is nothing else than an absence of a central value. The relativity of truth and the power of overturning established value systems advertised in the book have significant implications for today's readers as well as for the Victorians.

• International Journal of Advanced Culture Technology
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• v.9 no.1
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• pp.114-120
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• 2021

This study aims to discover how self-esteem and social competence in early childhood affect school adjustment in elementary school. This study used the 7th year (2014) and 10th year (2017) of the panel study on Korean children, which are longitudinal research data from the Korea Institute of Child Care and Education (KICCE). Pearson's correlation analysis and hierarchical regression analysis were used as the main statistical analysis methods. The analysis was performed using the the Spss 21.0 program. As a result of this study, peer acceptance among early childhood's self-esteem, assertion, cooperation, and self-control among social competence have influences on adjustment to elementary school life. This study is meaningful in that it is a longitudinal study conducted with a time difference for 3 years with the same subjects in order to investigate the influence of the inner factors of early childhood on school adjustment in elementary school.

• International Journal of Advanced Culture Technology
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• v.9 no.4
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• pp.219-225
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• 2021

This study was a cross-sectional reaserch that analyzed the factors that most affect COVID-19 knowledge in nursing college students who are relatively at high risk for recent prevalence of COVID-19 exposure in relation to clinical practice of nursing college students. A total of 249 nursing students participated in this study, 93 male students and 156 female students. The period for collecting data from structured questionnaires was from October 1 to October 20, 2021. The collected data were frequency analysis, Pearson correlation analysis, simple regression analysis, and hierarchical regression analysis using SPSS 18.0. As a result of the analysis, infection prevention behavior(𝛽=0.06, p=0.006) had the most influence on COVID-19 knowledge, and the second was professional intuition(𝛽=-.162, p=0.018). Based on the results of this study, in order to improve the knowledge of COVID-19 among nursing students, it is proposed to develop an infection prevention behavior education program and a professional intuition improvement program.

• Communications for Statistical Applications and Methods
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• v.29 no.3
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• pp.373-391
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• 2022

The distribution of observations in most econometric studies with spatial heterogeneity is skewed. Usually, a single transformation of the data is used to approximate normality and to model the transformed data with a normal assumption. This assumption is however not always appropriate due to the fact that panel data often exhibit non-normal characteristics. In this work, the normality assumption is relaxed in spatial mixed models, allowing for spatial heterogeneity. An inference procedure based on Bayesian mixed modeling is carried out with a multivariate skew-elliptical distribution, which includes the skew-t, skew-normal, student-t, and normal distributions as special cases. The methodology is illustrated through a simulation study and according to the empirical literature, we fit our models to non-life insurance consumption observed between 1998 and 2002 across a spatial panel of 103 Italian provinces in order to determine its determinants. Analyzing the posterior distribution of some parameters and comparing various model comparison criteria indicate the proposed model to be superior to conventional ones.