• Journal of Korean Port Research
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• v.14 no.2
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• pp.143-154
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• 2000

In port management, the scale of facilities and port layouts are major factors characterizing the port, which influence port economics and productivities continuously through the port operation. Grouping ports in certain region by their characteristics could be used as the principal informations to establish national policy for port development or investment and also to analyze the competitiveness between ports. Currently Korean ports are divided into two groups such as the local port and the designated port containing foreign trade port and coastal port under the Korean port law. These divisions seem to be used for port administration as the matter of convenience but some qualitative grouping is needed for research of port problems. In this paper, 20 major Korean ports were clustered by the similar characteristics using Fuzzy C-Means and found to be classified 8 qualitative groups.

• Korean Journal of Breeding Science
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• v.42 no.1
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• pp.28-34
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• 2010

Diversity of 30 Korean potato cultivars was evaluated using 14 microsatellite markers. Twelve microsatellite markers representing 12 loci in the potato genome detected 84 polymorphisms among 30 cultivars and revealed alleles with a mean of 7.00 alleles per primer. The polymorphism information content (PIC) value ranged from 0.57 to 0.93 with average of 0.82. Based on polymorphism, cluster analysis was conducted by the unweighted pair-group method with arithmetic average (UPGMA) methods. Thirty potato varieties were distinctly separated into 2 groups and similarity coefficient of cluster ranged from 0.58 to 0.95. Thirty tetraploid cultivars were evaluated for six important agronomic traits. One-way analysis of variance was done to look for the degree of relationships between individual markers and traits. K1 and K2 markers showed a significant association with amylose contents, starch contents, and specific gravity.

• Journal of Information Processing Systems
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• v.20 no.2
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• pp.185-199
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• 2024

In this paper, an improved automated spectral clustering (IASC) algorithm is proposed to address the limitations of the traditional spectral clustering (TSC) algorithm, particularly its inability to automatically determine the number of clusters. Firstly, a cluster number evaluation factor based on the optimal clustering principle is proposed. By iterating through different k values, the value corresponding to the largest evaluation factor was selected as the first-rank number of clusters. Secondly, the IASC algorithm adopts a density-sensitive distance to measure the similarity between the sample points. This rendered a high similarity to the data distributed in the same high-density area. Thirdly, to improve clustering accuracy, the IASC algorithm uses the cosine angle classification method instead of K-means to classify the eigenvectors. Six algorithms-K-means, fuzzy C-means, TSC, EIGENGAP, DBSCAN, and density peak-were compared with the proposed algorithm on six datasets. The results show that the IASC algorithm not only automatically determines the number of clusters but also obtains better clustering accuracy on both synthetic and UCI datasets.

• Asia pacific journal of information systems
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• v.28 no.4
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• pp.308-319
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• 2018

This paper aims at providing valuable insights on Financial Fraud Detection on a mobile money transactional activity. We have predicted and classified the transaction as normal or fraud with a small sample and massive data set using Azure and Spark ML, which are traditional systems and Big Data respectively. Experimenting with sample dataset in Azure, we found that the Decision Forest model is the most accurate to proceed in terms of the recall value. For the massive data set using Spark ML, it is found that the Random Forest classifier algorithm of the classification model proves to be the best algorithm. It is presented that the Spark cluster gets much faster to build and evaluate models as adding more servers to the cluster with the same accuracy, which proves that the large scale data set can be predictable using Big Data platform. Finally, we reached a recall score with 0.73, which implies a satisfying prediction quality in predicting fraudulent transactions.

• Journal of the Korean Society of Clothing and Textiles
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• v.31 no.9_10
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• pp.1321-1332
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• 2007

The purposes of this research were to investigate the influences of shopping value, brand awareness, and the types of sales promotion on the purchase of bundled cosmetics. In experiment, 1) shopping value 2) brand awareness 3) types of sales promotion were manipulated as independent variables, and consumer preference and purchasing intention of bundle of cosmetics were measured as dependent variables. This research was an experimental design which was $2{\times}2{\times}2$ mixed factorial design. For the data analysis, factor analysis, cluster analysis, three-way ANOVA were used by utilizing SAS program. The main results of the study were summarized as follows: First, the results indicated that the consumer of hedonic shopping value have a positive effect on preferring price-cut sales, especially if brand awareness is high. Second, the consumer of utilitarian shopping value preferred price-cut sales to special offer, irrespective of brand awareness. This result indicates that consumers who gets more involved in and enjoys shopping are likely to have more brand awareness than others. This. seems to be the important characteristics of shopping. Consumer who have utilitarian shopping value concerned in price. The result showed the 3-way interaction effects on the consumer preference of bundle of cosmetics.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.1
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• pp.455-460
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• 2014

Background: The purpose of the present study was to determine geographic clustering of breast cancer incidence in Kanagawa Prefecture, using cancer registry data. The study also aimed at examining the association between socio-economic factors and any identified cluster. Materials and Methods: Incidence data were collected for women who were first diagnosed with breast cancer during the period from January to December 2006 in Kanagawa. The data consisted of 2,326 incidence cases extracted from the total of 34,323 Kanagawa Cancer Registration data issued in 2011. To adjust for differences in age distribution, the standardized mortality ratio (SMR) and the standardized incidence ratio (SIR) of breast cancer were calculated for each of 56 municipalities (e.g., city, special ward, town, and village) in Kanagawa by an indirect method using Kanagawa female population data. Spatial scan statistics were used to detect any area of elevated risk as a cluster for breast cancer deaths and/or incidences. The Student t-test was performed to examine differences in socio-economic variables, viz, persons per household, total fertility rate, age at first marriage for women, and marriage rate, between cluster and other regions. Results: There was a statistically significant cluster of breast cancer incidence (p=0.001) composed of 11 municipalities in southeastern area of Kanagawa Prefecture, whose SIR was 35 percent higher than that of the remainder of Kanagawa Prefecture. In this cluster, average value of age at first-marriage for women was significantly higher than in the rest of Kanagawa (p=0.017). No statistically significant clusters of breast cancer deaths were detected (p=0.53). Conclusions: There was a statistically significant cluster of high breast cancer incidence in southeastern area of Kanagawa Prefecture. It was suggested that the cluster region was related to the tendency to marry later. This study methodology will be helpful in the analysis of geographical disparities in cancer deaths and incidence.

• Culinary science and hospitality research
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• v.18 no.4
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• pp.47-58
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• 2012

This study, targeting the students of "K" university in Busan City area, was performed to draw the groups by food-related lifestyle types and to identify the correlation between each group's attributes of selecting places to eat out and obesity index. The purpose of the study was achieved by means of the PASW Statistic 18.0(Predictive Analytics Software) which conducted frequency analysis, factor analysis, reliability analysis, t-test, ${\chi}^2$-test, non-hierarchical cluster analysis and ANOVA. It turned out that the male university students were 175.59 cm tall and weigh 69.53 kg on average. And the female university students showed their average height of 162.81 cm and weight of 53.42 kg. When examined by the body mass index(BMI), male students were composed of 1.7% of underweight, 64.6% of normal weight, 19.7% of overweight and 14.0% of obese. As for the female students, 22.9% were classified as underweight, 62.7% as normal weight, 8.5% as overweight and 5.9% as obese. The food-related lifestyle categories were divided into five factors; health seeking type, safety seeking type, mood seeking type, taste seeking type, and western food seeking type. The four attributes of selecting places to eat out included quality of food and service, price reasonableness, accessibility and atmosphere, and experience to have eaten. With regard to food-related lifestyle, the groups were named by cluster 1 [careless diet group], Cluster 2 [health oriented group], and cluster3 [careless healthcare group]. In terms of the correlation between the clusters by food-related lifestyle and their attributes of selecting places to eat out, Cluster 1 had a high mean value in experience to have eaten, Cluster 2 quality of food and service, Cluster 3 accessibility and atmosphere.

• Journal of the Korea Society of Computer and Information
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• v.14 no.11
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• pp.105-111
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• 2009

The study aims to propose the intelligent clustering technique that calculates the distance by improving the problems of multi-hop clustering technique for inter-vehicular secure communications. After calculating the distance between vehicles with no connection for rapid transit and clustering it, the connection between nodes is created through a set distance vale. Header is selected by the distance value between nodes that become the identical members, and the information within a group is transmitted to the member nodes. After selecting the header, when the header is separated due to its mobility, the urgent situation may occur. At this time, the information transfer is prepared to select the new cluster header and transmit it through using the intelligent cluster provided from node by the execution of programs included in packet. The study proposes the cluster technique of the intelligent distance estimation for the mobile Ad-hoc network that calculates the cluster with the Store-Compute-Forward method that adds computing ability to the existing Store-and-Forward routing scheme. The cluster technique of intelligent distance estimation for the mobile Ad-hoc network suggested in the study is the active and intelligent multi-hop cluster routing protocol to make secure communications.

• Journal of Family Resource Management and Policy Review
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• v.10 no.1
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• pp.83-105
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• 2006

The purposes of this study were to classify types of consumption values and to examine 5 types of art appreciation of university students in Seoul. Five types of art appreciation included fine art exhibition(including photographs, architects, calligraphy works), classical and opera performance, traditional Korean music performance, drama and musical performance, dance performance. The sample for this study consisted of 422 university students of five universities in Seoul. The data were collected using the structured questionnaires. The statistical methods used for the analysis were descriptive statistics, chi-square, factor analysis, and cluster analysis. The major findings are as follows. 1. The result of factors for consumption values of students emerged four factors. These were called as 'materialism', 'honor centered', 'family centered', 'hedonism' value. 2. The cluster analysis was conducted based on these four factors. The result showed 3 groups of consumption value which were called as 'material' honor value group', 'family value group', 'hedonic value group'. 3. The consumption value of university students did not significantly differ according to their demographic variables. 4. The behavior of art appreciation of university students significantly differed by their demographic characteristics and consumption value. The material' honor valued group showed the least chances to make decisions on art appreciation for one's own, which reflected that this group appreciate art to satisfy their honors rather than to enjoy art itself. They also showed the most chances to consider the renownedness of the art work or artists among three groups. And they showed the least chances to pay for the tickets for art appreciation, all of those meant that they appreciate arts unvoluntarily in situational condition. The family valued group showed the most chances to pay for the tickets when they appreciate arts. And therefore they were most susceptible for the prices. The hedonic valued group showed the most interests in art. They decided to appreciate art for their own, and they considered the contents and the highness in the level of the art the most when they appreciate art. And they show the most intention of participation in drama/musical performances, which reflect their interests in hedonic values. Based on these results of this study concluded that the consumption values of university students affected their behavior of art appreciation. Thus, university students' behavior on art appreciation can be effectively developed by education according to their consumption values.

• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.2
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• pp.303-314
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• 2002

The colors of apparel have become an important element to be used strategically in order to give differentiated character at the level of fiber and fabric production. The colors of apparel have a close relationship with the skin colors of consumers and their preference colors. This study was carried out to classify the skin colors of Korean elderly women into several similar skin colors and to analyse their preference colors. Sample size was 471 Korean elderly women. With color spectrometer, JX-777, we measured 4 points of the body; cheek with removing cosmetics off, forehead, rear neck and arm on the interior part near elbow. All subjects had been shown with 40 color chips and answered the preference colors of apparel and the preference colors. Data weirs analysed to classify skin colors using K-means Cluster Analysis and Duncan test. Independent variables for Cluster Analysis were 12 variables out of L value, a value and b value of 4 points. In doing so, we used SPSS WIN 10 statistical package. Findings were as follows: 1) The skin colors of the Korean elderly women were composed of skin colors of YR, R, and Y. 2) 355 subjects were classified into 4 kinds of skin color groups. 3) The average face color of type 1 was 6.7YR 5.1/4.3 and 56 observations out of 355 subjects were composed of Type 1 and of Type 2 was 6.1YR 6.1/4.5 and 166 observations out of 355 and of 3 Type 6. YR 4.8/4.2 and 75 observations out of 355 and of Type was 6.17 YR 5.7/4.7 and 58 observations out of 355. 4) The average skin color of Type 1 was 7.0YR 5.9/4.4 and of Type 2 was 7.2YR 6.3/4.2 and of Type 3 was 7.0YR 6.2/4.2 and of Type 4 was 7.6YR 5.4/4.2 respectively. 5) The mean values of 12 variables between the 4 classified face color and skin color groups showed significantly different except H value of skin color. 6) All 4 groups showed that the most preference color of apparel and the most preference color were 2.5R 5/14 respectively.