• The Korean Journal of Applied Statistics
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• v.20 no.2
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• pp.229-244
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• 2007

Among the small area estimation methods, it has been known that hierarchical Bayesian(HB) approach is the most reasonable and effective method. However any model based approaches need good explanatory variables and finding them is the key role in the model based approach. As the lacking of explanatory variables, adopting the spatial terms in the model was introduced. Here in this paper, we evaluate the model based methods with/without spatial terms using the diagnostic methods which were introduced by Brown et al. (2001). And Economic Active Population Survey(2005) is used for data analysis.

• Journal of Korea Multimedia Society
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• v.6 no.7
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• pp.1189-1199
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• 2003

This paper presents a new method for the motion detection of vehicles using hierarchical motion estimation and parallel processing. It captures the road image by using a CMOS sensor. It divides the captured image into small blocks and detects the motion of each block by using a block-matching method which is based on a hierarchical motion estimation and parallel processing for the real-time processing. The parallelism is achieved by using tile pipeline and the data flow technique. The proposed method has been implemented by using an embedded system. The proposed block matching algorithm has been implemented on PLDs(Programmable Logic Device) and clustering algorithm has been implemented by ARM processor. Experimental results show that the proposed system detects the motion of vehicles in real-time.

• Journal of the Korean Society of Clothing and Textiles
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• v.34 no.8
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• pp.1352-1363
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• 2010

This study analyzes how the organizational culture of TV home shopping companies influence the job satisfaction, commitment, and intention of turnover. It ascertains the differences the job satisfaction, commitment, and intention of turnover according to tenure of office and turnover time. The survey was conducted from May $3^{rd}$ to $31^{rt}$ in 2010, and 356 responses were used in the data analysis. The statistical analysis methods were frequency analysis, factor analysis, reliability analysis, ANOVA, and multiple regression analysis. As a result, the organizational culture of TV home shopping companies was classified by the innovation culture, group culture, rational culture, and hierarchical culture. The innovation culture, group culture, and hierarchical culture of TV home shopping companies influenced job satisfaction and commitment. The rational culture and hierarchical culture of TV home shopping companies influenced the intention of turnover. There were differences in the intention of turnover according to the tenure of office and the job commitment according to turnover time.

• Journal of Korea Multimedia Society
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• v.19 no.12
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• pp.1960-1969
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• 2016

In this paper, we propose an automatic hierarchical organ segmentation method on abdominal CT images. First, similar atlases are selected using bone-based similarity registration and similarity of liver, kidney, and pancreas area. Second, each abdominal organ is roughly segmented using image-based similarity registration and intensity-based locally weighted voting. Finally, the segmented abdominal organ is refined using mask-based affine registration and intensity-based locally weighted voting. Especially, gallbladder and pancreas are hierarchically refined using location information of neighbor organs such as liver, left kidney and spleen. Our method was tested on a dataset of 12 portal-venous phase CT data. The average DSC of total organs was $90.47{\pm}1.70%$. Our method can be used for patient-specific abdominal organ segmentation for rehearsal of laparoscopic surgery.

• Journal of Navigation and Port Research
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• v.40 no.2
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• pp.67-72
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• 2016

Vietnam's sea-port industry has experienced a significant development in recent years. Especially in Northern Vietnam, both the demand and supply of handling services for containerized cargoes have increased at a considerable rates. Accompany with such movement, the competition among container terminals in the area becomes fiercer. In this paper, Hierarchical Cluster Analysis is employed to classify all 11 container terminals in Northern Vietnam by collecting data concerning terminal competitiveness. After the classification, each group will be discussed in order to reveal more details about their competitive characteristics. The paper consists of five sections. Section 1 is the general introduction. Section 2 provides a general literature review about competitiveness and factors to evaluate competitiveness. Section 3 explains variables and methodology applied to do the analysis. Section 4 presents the results with linkage to the current condition. Section 5 summarizes the analysis results. It is shown that container terminals in Northern Vietnam should not only pay attention to their service qualities but also have to find out an appropriate mechanism to avoid unhealthy competition. The paper is expected to contribute a background for further researches in container terminals' competition in the region as well as hints for operators in planning and making decisions.

• International Journal of Contents
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• v.13 no.3
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• pp.65-74
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• 2017

Women's menopause is a natural process that every woman must eventually experience, but changes in hormones before and after menopause can serve to produce life-threatening crises in some situations, with individual differences. Data for the study was elicited from 22,610 Korean women ranging in age from 45 to 55 years in the 2013 Korean Community Health Survey. Statistical analyses was performed using descriptive, t-test, ANOVA, and hierarchical regression analysis using SPSS IBM 20.0 version. Individual characteristics, lifestyle, history of chronic disease(s), psychological and environmental factors were included as independent and EQ5D weights of Koreans were used as dependent variables. The survey subjects consisted of a total 15,505(58.3%) in their 50s, 1,765 (66.5%) in middle and high school dropouts or graduates, 22,174 (83.3%) living in spouses and 10,534(39.6%) in wages. There was a significant difference in HRQOL among all independent variables except drinking and residential areas. Hierarchical regression analysis showed that age, smoking, obesity and other incidental disease factors (fall, angina, asthma, arthritis, osteoporosis, stroke) had a negative effect on HRQOL. The selected independent variables accounted for 22.7% of HRQOL. It is necessary to find a way to improve HRQOL of Korean perimenopausal women, focusing on the significant variables revealed by the study results.

• Journal of the Korean Society for information Management
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• v.21 no.4 s.54
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• pp.173-185
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• 2004

Fast and high-quality document clustering algorithms play an important role in providing data exploration by organizing large amounts of information into a small number of meaningful clusters. Many papers have shown that the hierarchical clustering method takes good-performance, but is limited because of its quadratic time complexity. In contrast, with a large number of variables, K-means has a time complexity that is linear in the number of documents, but is thought to produce inferior clusters. In this paper, Condor system using K-Means algorithm Compares with regular method that the initial centroids have been established in advance, our method performance has been improved a lot.

• Journal of Multimedia Information System
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• v.1 no.1
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• pp.55-67
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• 2014

Image topic and emotion analysis is an important component of online image retrieval, which nowadays has become very popular in the widely growing social media community. However, due to the gaps between images and texts, there is very limited work in literature to detect one image's Topics and Emotions in a unified framework, although topics and emotions are two levels of semantics that often work together to comprehensively describe one image. In this work, a unified model, Joint Topic/Emotion Multi-Modal Hierarchical Latent Dirichlet Allocation (JTE-MMHLDA) model, which extends previous LDA, mmLDA, and JST model to capture topic and emotion information at the same time from heterogeneous data, is proposed. Specifically, a two level graphical structured model is built to realize sharing topics and emotions among the whole document collection. The experimental results on a Flickr dataset indicate that the proposed model efficiently discovers images' topics and emotions, and significantly outperform the text-only system by 4.4%, vision-only system by 18.1% in topic detection, and outperforms the text-only system by 7.1%, vision-only system by 39.7% in emotion detection.

• Journal of Korea Multimedia Society
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• v.20 no.6
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• pp.845-852
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• 2017

In this paper, we propose a binarization algorithm using LVQ-Merge clustering method for fast and accurate extraction of cells from cell images. The proposed method clusters pixel data of a given image by using LVQ to remove noise and divides the result into two clusters by applying a hierarchical clustering algorithm to improve the accuracy of binarization. As a result, the execution speed is somewhat slower than that of the conventional LVQ or Otsu algorithm. However, the results of the binarization have very good quality and are almost identical to those judged by the human eye. Especially, the bigger and the more complex the image, the better the binarization quality. This suggests that the proposed method is a useful method for medical image processing field where high-resolution and huge medical images must be processed in real time. In addition, this method is possible to have many clusters instead of two cluster, so it can be used as a method to complement a hierarchical clustering algorithm.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.120-122
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• 2006

The paper concerns the hybrid optimization of fuzzy inference systems that is based on Hierarchical Fair Competition-based Parallel Genetic Algorithms (HFCGA) and information data granulation. The granulation is realized with the aid of the Hard C-means clustering and HFCGA is a kind of multi-populations of Parallel Genetic Algorithms (PGA), and it is used for structure optimization and parameter identification of fuzzy model. It concerns the fuzzy model-related parameters such as the number of input variables to be used, a collection of specific subset of input variables, the number of membership functions, the order of polynomial, and the apexes of the membership function. In the hybrid optimization process, two general optimization mechanisms are explored. Thestructural optimization is realized via HFCGA and HCM method whereas in case of the parametric optimization we proceed with a standard least square method as well as HFCGA method as well. A comparative analysis demonstrates that the proposed algorithm is superior to the conventional methods.