• Title/Summary/Keyword: cluster value

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A Study of Market Segmentation of Optical Shop Based on Customer's Values (고객의 가치관에 따른 안경원의 시장세분화에 관한 연구)

  • Lee, Jung-Kyu;Cha, Jung-Won
    • Journal of Korean Ophthalmic Optics Society
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    • v.20 no.4
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    • pp.405-414
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    • 2015
  • Purpose: We analyse characteristics of optical shop customer's segmented market by using clustering analysis, and we expect it would be a useful indicator of marketing strategy for optical shops. Methods: Survey was conducted from March 10 to March 31, 2015. The survey asked customers who have visited optical shops in Seoul and Northern Gyeonggi-do regions, and analyzed by utilizing SPSS v.10.0 statistical package program. The analysing methods are frequency analysis, factor analysis about variable of values, clustering analysis for market segmentation, and crosstabs. Results: The market is segmented based on values. In the process of establishing marketing strategy, it is useful to establish strategy by classifying customers into 3 types of cluster; "middle level value oriented cluster", "high level value oriented cluster", "high level value oriented and non-religious cluster". In marketing strategy of progressive lenses, it turned out that the most important strategy is to target self-employed person in "middle level value oriented cluster". Conclusions: As a result of market segmentation by using clustering analysis, it was classified into 3 types of cluster, and we found that most important customer for progressive lenses is self-employed person in "middle level value oriented cluster" who is more than 41 years old.

A study on boron removal for seawater desalination using the combination process of mineral cluster and RO membrane system

  • Cho, Bong-Yeon;Kim, Hye-Won;Shin, Yee-Sook
    • Environmental Engineering Research
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    • v.20 no.3
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    • pp.285-289
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    • 2015
  • Complicated and expensive seawater desalination technology is a big challenge in boron removal process. Conventional seawater desalination process of coagulation utilized for pre-treatment is difficult to remove boron. Boron can be removed more effectively in Reverse Osmosis (RO) process than any other processes. In this study, a coagulant with the name Mineral Cluster was examined its boron removal ability. Boron removal efficiency of Mineral Cluster depended on pH value and Mineral Cluster dosage. Desalination process combines the pre-treatment process with Mineral cluster diluted at the ratio of 1:2500 and the RO membrane process. The original sea water could be desalinated to drinking water quality, 1 mg/L, without any pH adjustments. Therefore, if the Mineral cluster is added without any other chemicals for adjusting pH, the desalination process would be much safer, efficient and economical.

Optimizing the maximum reported cluster size for normal-based spatial scan statistics

  • Yoo, Haerin;Jung, Inkyung
    • Communications for Statistical Applications and Methods
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    • v.25 no.4
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    • pp.373-383
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    • 2018
  • The spatial scan statistic is a widely used method to detect spatial clusters. The method imposes a large number of scanning windows with pre-defined shapes and varying sizes on the entire study region. The likelihood ratio test statistic comparing inside versus outside each window is then calculated and the window with the maximum value of test statistic becomes the most likely cluster. The results of cluster detection respond sensitively to the shape and the maximum size of scanning windows. The shape of scanning window has been extensively studied; however, there has been relatively little attention on the maximum scanning window size (MSWS) or maximum reported cluster size (MRCS). The Gini coefficient has recently been proposed by Han et al. (International Journal of Health Geographics, 15, 27, 2016) as a powerful tool to determine the optimal value of MRCS for the Poisson-based spatial scan statistic. In this paper, we apply the Gini coefficient to normal-based spatial scan statistics. Through a simulation study, we evaluate the performance of the proposed method. We illustrate the method using a real data example of female colorectal cancer incidence rates in South Korea for the year 2009.

Cluster Group Multicast by Weighted Clustering Algorithm in Mobile Ad-hoc Networks (이동 에드-혹 네트워크에서 조합 가중치 클러스터링 알고리즘에 의한 클러스터 그룹 멀티캐스트)

  • 박양재;이정현
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.41 no.3
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    • pp.37-45
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    • 2004
  • In this paper we propose Clustered Group Multicast by Clustering Algorithm in Wireless Mobile Ad-hoc Network. The proposed scheme applies to Weighted Cluster Algorithm Ad-hoc network is a collection of wireless mobile hosts forming a temporary network without the aid of any centralized administration or reliable support services such as wired network and base station. In ad hoc network muting protocol because of limited bandwidth and high mobility robust, simple and energy consume minimal. WCGM method uses a base structure founded on combination weighted value and applies combination weight value to cluster header keeping data transmission by seeped flooding, which is the advantage of the exiting FGMP method. Because this method has safe and reliable data transmission, it shows the effect to decrease both overhead to preserve transmission structure and overhead for data transmission.

Bonded-cluster simulation of tool-rock interaction using advanced discrete element method

  • Liu, Weiji;Zhu, Xiaohua;Zhou, Yunlai;Li, Tao;Zhang, Xiangning
    • Structural Engineering and Mechanics
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    • v.72 no.4
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    • pp.469-477
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    • 2019
  • The understanding of tool-rock interaction mechanism is of high essence for improving the rock breaking efficiency and optimizing the drilling parameters in mechanical rock breaking. In this study, the tool-rock interaction models of indentation and cutting are carried out by employing the discrete element method (DEM) to examine the rock failure modes of various brittleness rocks and critical indentation and cutting depths of the ductile to brittle failure mode transition. The results show that the cluster size and inter-cluster to intra-cluster bond strength ratio are the key factors which influence the UCS magnitude and the UCS to BTS ratio. The UCS to BTS strength ratio can be increased to a more realistic value using clustered rock model so that the characteristics of real rocks can be better represented. The critical indentation and cutting depth decrease with the brittleness of rock increases and the decreasing rate reduces dramatically against the brittleness value. This effort may lead to a better understanding of rock breaking mechanisms in mechanical excavation, and may contribute to the improvement in the design of rock excavation machines and the related parameters determination.

A Comparison Study of Ensemble Approach Using WRF/CMAQ Model - The High PM10 Episode in Busan (앙상블 방법에 따른 WRF/CMAQ 수치 모의 결과 비교 연구 - 2013년 부산지역 고농도 PM10 사례)

  • Kim, Taehee;Kim, Yoo-Keun;Shon, Zang-Ho;Jeong, Ju-Hee
    • Journal of Korean Society for Atmospheric Environment
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    • v.32 no.5
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    • pp.513-525
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    • 2016
  • To propose an effective ensemble methods in predicting $PM_{10}$ concentration, six experiments were designed by different ensemble average methods (e.g., non-weighted, single weighted, and cluster weighted methods). The single weighted method was calculated the weighted value using both multiple regression analysis and singular value decomposition and the cluster weighted method was estimated the weighted value based on temperature, relative humidity, and wind component using multiple regression analysis. The effects of ensemble average methods were significantly better in weighted average than non-weight. The results of ensemble experiments using weighted average methods were distinguished according to methods calculating the weighted value. The single weighted average method using multiple regression analysis showed the highest accuracy for hourly $PM_{10}$ concentration, and the cluster weighted average method based on relative humidity showed the highest accuracy for daily mean $PM_{10}$ concentration. However, the result of ensemble spread analysis showed better reliability in the single weighted average method than the cluster weighted average method based on relative humidity. Thus, the single weighted average method was the most effective method in this study case.

A Study for the Consumption Competencies According to the Shopping Value Types of College Students (대학생의 쇼핑가치유형 및 소비능력에 관한 연구)

  • Seo, In-Joo
    • Journal of Family Resource Management and Policy Review
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    • v.14 no.3
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    • pp.1-14
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    • 2010
  • The purpose of this study was (1) to investigate the changes in consumer competencies according to the types of shopping value, (2) to reveal the effects of shopping value on consumer competencies. The subjects of this study were 266 university students dwelling in Seoul. A questionnaire was used as the survey method. The data was analyzed by Cronbach's alpha, frequencies, percentile, mean, factor analysis, K-mean cluster analysis, t-test, ANOVA and Duncan's multiple range tests, multiple linear regressions. Computations were conducted by SPSS WIN 12.0. The study produced the following results. First, college students can be categorized into 3 shopping values by K-means Cluster analysis of 13 items: the hedonic shopper (shopping value), the utilitarian shopper (shopping value) and the balanced shopper (shopping value). Second, there were significant differences in grades, satisfaction with life and shopping value. That is, grade 3and utilitarian shopping value group had a higher level of consumer competency. Third, the variable that influenced consumer competency was the utilitarian shopping value, influencing consumer attitude and consumer skill. These results imply that consumers should be constantly educated and that there needs to be a campaign to promote utilitarian shopping value.

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Fuzzy Neural Newtork Pattern Classifier

  • Kim, Dae-Su;Hun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.1 no.3
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    • pp.4-19
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    • 1991
  • In this paper, we propose a fuzzy neural network pattern classifier utilizing fuzzy information. This system works without any a priori information about the number of clusters or cluster centers. It classifies each input according to the distance between the weights and the normalized input using Bezdek's [1] fuzzy membership value equation. This model returns the correct membership value for each input vector and find several cluster centers. Some experimental studies of comparison with other algorithms will be presented for sample data sets.

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Similarity Analysis of Exports Value Added by Country and Implication for Korea's Global Value Added Chains

  • Cho, Jung-Hwan
    • Journal of Korea Trade
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    • v.23 no.4
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    • pp.103-114
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    • 2019
  • Purpose - This paper investigates the structure of exports across countries in terms of value added. Exports value added is examined under two categories, domestic and overseas. Using a statistical classification method by distance based on these two value added categories, this paper estimates the similarity of exports value added across countries including Korea. Design/methodology - The model of study is to employ a generalized distance function and then derive the Manhattan and Euclidean distances. The paper also performs cluster analysis using the Partitioning Around Medoids (PAM) and hierarchical methods to classify the 44 sample countries considered in this study. Findings - Our main findings are as follows. The 44 countries can be classified under 5 groups by their domestic and overseas value added in exports. Korea has a sandwich global value chains (GVCs) position between Japan, China, and Taiwan in the East Asian region. Originality/value - Existing papers point out the double counting problem of trade statistics as the intermediate goods trade across borders increases. This paper addresses the double counting problem by using the World Input-Output Table. The paper shows the need to explore the similarity of value added in exports structure across countries and investigate the GVCs position and role of each country.

Preference of Women Cosmetics Consumption Value on SNS Features of Cosmetics Brands (여성의 화장품 소비가치에 따른 화장품 브랜드의 SNS 특성 선호도)

  • Kim, Cho-Rong;Kwak, Tai-Gi
    • Journal of the Korea Fashion and Costume Design Association
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    • v.18 no.3
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    • pp.99-111
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    • 2016
  • In order to use cosmetics brands SNS effectively and establish strategy, the purpose of this study is to provide consumer date. According to cosmetics consumption value groups, this study examined each cosmetics consumption value group's level of concern of three cosmetics brands SNS features, informativity, enjoyment and interactivity. For the data, questionnaire was collected by 198 women, and the data were measured by ANOVA, factor analysis, cluster analysis and Ducan test. According to cluster analysis cosmetics consumption value groups were divided into four groups, unconcern group, hedonic value pursuit group, function of brand value pursuit group, high concern group. The results of the study are as follows: First, high concern group thought highly of all cosmetics brands SNS features, including informativity, enjoyment and interactivity. In addition all consumer groups were concerned informativity rather then enjoyment and interactivity. Second, comparing with high concern group, other groups which include unconcern group, hedonic value pursuit group and function of brand value pursuit group were not concerned about cosmetics brands SNS features' enjoyment and interactivity. Except informativity, hedonic value pursuit group and unconcern group were more concerned interactivity than enjoyment. While, high concern group and function of brand value pursuit group were more concerned enjoyment than interactivity.

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