• 한국의류산업학회지
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• 제19권4호
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• pp.468-478
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• 2017

The purpose of this study is to examine the differences in appearance management behaviors and demographic variables among groups classified by the appearance management motives. The questionaries are administerd to 493 female and male adults above 20 years old in Seoul, Kyeonggi-do, Daegu and Kyungpook regions. For analysis of data from 478 respondents, descriptive statistics, factor analysis, cluster analysis, Cronbach's ${\alpha}$, ANOVA, Duncan test and ${\chi}^2$ test were applied. We show the following results: First, factor analysis for appearance management motives extracted three factors such as self-development, emphasis on the trendy appearance, and sexual appealing motive. Factor analysis for appearance management behaviors extracted four factors such as weight training, surgery/skin care, hair care and clothing selection. Second, three groups of the appearance management motives were classified into such as the social self-management type, the sexual appealing self-management type, the passive appearance management type. The social self-management groups are more interested in self-development, emphasis on the trendy appearance, and sexual appealing motive. And they are also more involved in appearance management behaviors: clothing selection is the most pursuing appearance management behavior. Third, among the demographic variables, the single and female in 20s and 30s with higher level of education belonged to the social self-management group. In this contribution, we find significant differences in the appearance management behavior and demographic variables classified by the appearance management motives.

• 전자공학회논문지B
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• 제33B권5호
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• pp.41-51
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• 1996

In this paper, anew parallel processing system based on a cluster architecture which provides scalability of a parallel processing system while maintains shared memory multiprocessor characteristics is proposed. In recent days low cost, high performnce microprocessors have led to construction of large scale parallel processing systems. Such parallel processing systems provides large scalability but are mainly used for scientific applications which have large data parallelism. A shared memory multiprocessor system like TICOM is currently used as aserver for the commercial application, however, the shared memory multiprocessor system is known to have very limited scalability. The proposed architecture can support scalability and performance of the parallel processing system while it provides adaptability for the commerical application, hence it can overcome the limitation of the shared memory multiprocessor. The architecture and characteristics of the proposed system shall be described. A proprietary hierarchical crsossbar network is designed for this system, of which the protocol, routing and switching technique and the signal transfer technique are optimized for the proposed architecture. The design trade-offs for the network are described in this paper and with simulation usihng the SES/workbench, it is explored that the network fits to the proposed architecture.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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• pp.25-29
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• 2001

There are so many researches about the search method for the most compatible dispatching rule to a manufacturing system state. Most of researches select the dispatching rule using simulation results. This paper touches upon two research topics: the clustering method for manufacturing system states using simulation, and the search method for the most compatible dispatching rule to a manufacturing system state. The manufacturing system state variables are given to ART II neural network as input. The ART II neural network is trained to cluster the system state. After being trained, the ART II neural network classifies any system state as one state of some clustered states. The simulation results using clustered system state information and those of various dispatching rules are compared and the most compatible dispatching rule to the system state is defined. Finally there are made two knowledge bases. The simulation experiments are given to compare the proposed methods with other scheduling methods. The result shows the superiority of the proposed knowledge base.

• 한국CDE학회논문집
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• 제13권1호
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• pp.1-7
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• 2008

Data compression becomes increasingly an important issue for reducing data storage spaces as well as transmis-sion time in network environments. In 3D geometric models, the normal vectors of faces or meshes take a major portion of the data so that the compression of the vectors, which involves the trade off between the distortion of the images and compression ratios, plays a key role in reducing the size of the models. So, raising the compression ratio when the normal vector is compressed and minimizing the visual distortion of shape model's shading after compression are important. According to the recent papers, normal vector compression is useful to heighten com-pression ratio and to improve memory efficiency. But, the study about distortion of shading when the normal vector is compressed is rare relatively. In this paper, new normal vector compression method which is clustering normal vectors and assigning Representative Normal Vector (RNV) to each cluster and using the angular deviation from actual normal vector is proposed. And, using this new method, Visually Undistinguishable Lossy Compression (VULC) algorithm which distortion of shape model's shading by angular deviation of normal vector cannot be identified visually has been developed. And, being applied to the complicated shape models, this algorithm gave a good effectiveness.

• 한국항만학회지
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• 제14권1호
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• pp.57-64
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• 2000

For composing the structure model of national maritime power system by system structural modeling, in this study, the 50 basic factors are selected by survey of the extensive and through literatures on maritime, sea, maritime power and sea power. And the basic factors are classified into 36 component factors by cluster method. The 9 attributes are extracted by the application of the principle component analysis method, one of the factor analysis method in system engineering, to component factors. In this study, we define the attributes composing the national maritime power system by integrating the result of this study and existed our studies relating to this topic. Which are showed in Table 2. and we show the structure model of national maritime power system in Fig. 3. In Table 2, the 9 attributes are as follows : the fundamental power of maritime, shipping and port power, naval power, fishing power, shipbuilding power, the power of ocean research and development, dependency on seaborne trade, the protection power of ocean environment and the will and inclination of govemment. Also, in the case of evaluating this system, we conform the importance of considering the interactions among the attributes which have strong interactions in structure model of national maritime power system.

• 유통과학연구
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• 제16권5호
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• pp.45-59
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• 2018

Purpose - This paper aims to analyze the distinct pattern of clustering of imported automobile distributors and provide evidence for the phenomenon using Korean data. Research design, data, and methodology - In this paper, we use data from Korea Automobile Importers & Distributors Association of 23 foreign automobile brands to evaluate the degree of concentration of showrooms using locational Gini index. We identify possible causes for the high level of clustering from two perspectives; 1) on the distributors' side and 2) on the customers' side. Results - We find a very strong locational concentration of imported automobile showrooms within close vicinity in the major cities and districts in Korea. Locational Gini coefficients are 0.1024 at the national level, 0.1836~0.3763 at city level, and 0.3941~0.4311 at district level on a [0,0.5] scale. Conclusions - Luxury foreign automobile customers tend to shop extensively around multiple brands prior to their ideal model selection. Accordingly, the imported automobile distributors cluster together close to their direct competitors in order to give a good comparison opportunity for the potential customers. This will maximize the probability of the visits of potential customers and lead to successful sales performance.

• 한국생활과학회지
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• 제21권5호
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• pp.837-848
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• 2012

This study evaluated the types of daily routines that occurred in child care centers based on four general categorizations: time spent on indoor free choice activities, outdoor activities, group activities and special activities. In addition, resulting child care teacher behaviors were examined based on daily routine types. A total 23 classes' activity times and teacher behaviors were observed. The collected data were analyzed using descriptive statistics, hierarchical cluster, and Mann-Whitney U. Results indicated that there were 2 principle daily routine, 'indoor/outdoor activity time oriented' and 'group activity time oriented'. Analysis showed that teachers who belonged to the 'indoor/outdoor activity time oriented' type showed more positive affect, positive guidance, neural guidance, and less non-involved behavior. Results suggest the importance of time spent on free choice activities in the context of daily routine for quality childcare.

• International Journal of Contents
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• 제12권4호
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• pp.76-82
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• 2016

This study aims to evaluate the effectiveness of the dual-punishment system by analysis of the financial performance of pharmaceutical companies before and after introduction of the dual-punishment system. This study analyzed the business performance of 136 pharmaceutical companies from 2009 to 2011. The results from paired t-tests found that sales, operating cost, and EBITDA showed significant differences in performance, and, according to the variance analysis, the five groups obtained through a hierarchical cluster analysis differed from each other in sales, operating cost, EBITDA, and research and development cost. Differences in financial performance among the groups seem to be related to the strategy for response to the regulation. The introduction of the dual-punishment system is generally acknowledged to have had positive effects on the pharmaceutical industry. However, some companies appear to be continuing kickback practices.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 1999년도 추계학술대회논문집
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• pp.153-161
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• 1999

For composing the structure model of national maritime power system by system structural modelling, in this study, the 50 basic factors are selected by survey of the extensive and thorough literatures on maritime, sea, maritime power and sea power. And the basic factors are classified into 36 component factors by cluster method. The 9 attributes are extracted by the application of the principle component analysis method, one of the factor analysis method in system engineering, to component factors. We defined the attributes composing the national maritime power system by integration the result of this study and existed our studies relate to this topic. Which are showed in table 8. and we showed the structure model of national maritime power system in figure 3. In table 8, the 9 attributes are as follows: the fundamental power of maritime, shipping and port power, naval power, fishing power, shipbuilding power, the power of ocean research and development, dependency on seaborne trade, the protection power of ocean environment and the will and inclination of government.

• Journal of Information Processing Systems
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• 제18권5호
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• pp.637-649
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• 2022

Investors aim to increase their profitability by investing in the stock market. An adroit strategy for minimizing related risk lies through diversifying portfolio operationalization. In this paper, we propose a six-step stocks portfolio selection model. This model is based on data mining clustering techniques that reflect the ensuing impact of the political, economic, legal, and corporate governance in Mongolia. As a dataset, we have selected stock exchange trading price, financial statements, and operational reports of top-20 highly capitalized stocks that were traded at the Mongolian Stock Exchange from 2013 to 2017. In order to cluster the stock returns and risks, we have used k-means clustering techniques. We have combined both k-means clustering with Markowitz's portfolio theory to create an optimal and efficient portfolio. We constructed an efficient frontier, creating 15 portfolios, and computed the weight of stocks in each portfolio. From these portfolio options, the investor is given a choice to choose any one option.