• Journal of Digital Convergence
• /
• v.17 no.4
• /
• pp.355-364
• /
• 2019

The purpose of this study is to present the implications of analyzing users' market segmentation and characteristics based on the tourism SNS lovemarks experience. The results are as follows. First as a result of conducting factor analysis of tourism SNS lovemarks experience, five factors explained namely, mystery, sensuality, intimacy, trust, reputation. Second, as a result of conducting cluster analysis, four cluster groups were identified (reputation/sensuality centered experience group, high lovemarks experience group, intimacy centered experience group, low lovemarks experience group) and each characteristics were profiled. Third, as a result of Chi-square analysis and correspondence analysis, there was a difference in the characteristics of tourism SNS usage by cluster. Fourth, higher tourism SNS lovemarks experience segmented groups were more likely to recognize the degree of experiential value, satisfaction, behavioral intention.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.4
• /
• pp.1773-1795
• /
• 2020

Unmanned aerial vehicles (UAVs) network are a very vibrant research area nowadays. They have many military and civil applications. Limited bandwidth, the high mobility and secure communication of micro UAVs represent their three main problems. In this paper, we try to address these problems by means of secure clustering, and a security clustering algorithm based on integrated trust value for UAVs network is proposed. First, an improved the k-means++ algorithm is presented to determine the optimal number of clusters by the network bandwidth parameter, which ensures the optimal use of network bandwidth. Second, we considered variables representing the link expiration time to improve node clustering, and used the integrated trust value to rapidly detect malicious nodes and establish a head list. Node clustering reduce impact of high mobility and head list enhance the security of clustering algorithm. Finally, combined the remaining energy ratio, relative mobility, and the relative degrees of the nodes to select the best cluster head. The results of a simulation showed that the proposed clustering algorithm incurred a smaller computational load and higher network security.

• Korean Journal of Human Ecology
• /
• v.7 no.2
• /
• pp.63-73
• /
• 1998

To get well-fitted ready-made clothings with beautiful silhouettes, it's better to classify body forms into several forms and to assign sizing within each form than to grade just based on body size regardless of body styles. This study illucidated the importance of drop value in the results of surveying the current values of sizing and grading. Therefore, it's meaningful to get the classification of body form with appropriate distribution of drop values of the body, and the distribution of drop value and the frequency of each form is very helpful to name the combined sizing or coverage of ready-made clothes. This study aimed at classifying body forms with various drop values using multivariate analysis for sizing and grading. Factor analysis and cluster analysis were done using measured values from 346 unmarried women. The results are as follows: 1. The factor which explains body forms was obtained by factor analysis, and the representative major 18 items which have important roles in classifying body forms were selected among the measured values with high factor loading and communality. 2. The body forms were classified into 8 groups based on the charateristics, frequencies and distributions of them obtained from cluster analysis. 3. Each classified body form showed conspicuous difference in drop value and the difference of body form mainly resulted from the difference between waist and hip rather than the difference between bust circumference and waist in Korean unmarried women.

• Journal of the East Asian Society of Dietary Life
• /
• v.20 no.6
• /
• pp.987-996
• /
• 2010

The purpose of this study was to measure customers' perception of the service quality of Korean restaurants and then compare differences in perceived service quality according to customer nationality. Self-administered questionnaires were completed by 2812 subjects, and data were analyzed by frequency, chi-square, t-test, one-way ANOVA, factor, reliability, cluster, and discriminant analysis. Results of the study were as follows. The factor analysis of perceived service quality produced four factors, employee service (5 variables), menu quality (4 variables), price & value (4 variables), and physical environment (4 variables). Cronbach's alpha values for reliability were over 0.8 for all factors. Further, a significant difference was observed in service quality, which was perceived according to customer nationality. A higher mean value of perceived service quality was held by foreigners when compared to Koreans. Especially, the mean value of perceived service quality was significantly low for all items for Japanese compared to foreigners. Cluster analysis divided subjects into two groups based on attitude toward service quality of Korean restaurants: an unfavorable group and favorable group. These two groups differed from each other in general characteristics as well. Limitations and future research directions are also discussed.

• Journal of Intelligence and Information Systems
• /
• v.21 no.2
• /
• pp.93-112
• /
• 2015

Depending on the change in consumer's consumption pattern, existing retail shop has evolved in hypermarket or convenience store offering grocery and daily products mostly. Therefore, it is important to maintain the inventory levels and proper product configuration for effectively utilize the limited space in the retail store and increasing sales. Accordingly, this study proposed proper product configuration and inventory level strategy based on RFM(Recency, Frequency, Monetary) model and SOM(self-organizing map) for manage the retail shop effectively. RFM model is analytic model to analyze customer behaviors based on the past customer's buying activities. And it can differentiates important customers from large data by three variables. R represents recency, which refers to the last purchase of commodities. The latest consuming customer has bigger R. F represents frequency, which refers to the number of transactions in a particular period and M represents monetary, which refers to consumption money amount in a particular period. Thus, RFM method has been known to be a very effective model for customer segmentation. In this study, using a normalized value of the RFM variables, SOM cluster analysis was performed. SOM is regarded as one of the most distinguished artificial neural network models in the unsupervised learning tool space. It is a popular tool for clustering and visualization of high dimensional data in such a way that similar items are grouped spatially close to one another. In particular, it has been successfully applied in various technical fields for finding patterns. In our research, the procedure tries to find sales patterns by analyzing product sales records with Recency, Frequency and Monetary values. And to suggest a business strategy, we conduct the decision tree based on SOM results. To validate the proposed procedure in this study, we adopted the M-mart data collected between 2014.01.01~2014.12.31. Each product get the value of R, F, M, and they are clustered by 9 using SOM. And we also performed three tests using the weekday data, weekend data, whole data in order to analyze the sales pattern change. In order to propose the strategy of each cluster, we examine the criteria of product clustering. The clusters through the SOM can be explained by the characteristics of these clusters of decision trees. As a result, we can suggest the inventory management strategy of each 9 clusters through the suggested procedures of the study. The highest of all three value(R, F, M) cluster's products need to have high level of the inventory as well as to be disposed in a place where it can be increasing customer's path. In contrast, the lowest of all three value(R, F, M) cluster's products need to have low level of inventory as well as to be disposed in a place where visibility is low. The highest R value cluster's products is usually new releases products, and need to be placed on the front of the store. And, manager should decrease inventory levels gradually in the highest F value cluster's products purchased in the past. Because, we assume that cluster has lower R value and the M value than the average value of good. And it can be deduced that product are sold poorly in recent days and total sales also will be lower than the frequency. The procedure presented in this study is expected to contribute to raising the profitability of the retail store. The paper is organized as follows. The second chapter briefly reviews the literature related to this study. The third chapter suggests procedures for research proposals, and the fourth chapter applied suggested procedure using the actual product sales data. Finally, the fifth chapter described the conclusion of the study and further research.

• Environmental Engineering Research
• /
• v.15 no.3
• /
• pp.135-140
• /
• 2010

With the various urban characteristics of each city, the existing water demand prediction, which uses average liter per capita day, cannot be used to achieve an accurate prediction as it fails to consider several variables. Thus, this study considered social and industrial factors of 164 local cities, in addition to population and other directly influential factors, and used main substance and cluster analyses to develop a more efficient water demand prediction model that considers unique localities of each city. After clustering, a multiple regression model was developed that proved that the $R^2$ value of the inclusive multiple regression model was 0.59; whereas, those of Clusters A and B were 0.62 and 0.74, respectively. Thus, the multiple regression model was considered more reasonable and valid than the inclusive multiple regression model. In summary, the water demand prediction model using principal component and cluster analyses as the standards to classify localities has a better modification coefficient than that of the inclusive multiple regression model, which does not consider localities.

• Journal of The Korean Astronomical Society
• /
• v.32 no.2
• /
• pp.91-107
• /
• 1999

We present BVRI CCD photometry and near-infrared K photometry of the intermediate-aged open cluster NGC 7790. The reddening, E(B - V) = 0.54 $\pm$ 0.05 and the distance modulus, (m - M)o = 12.45 $\pm$ 0.10 for the cluster were determined by zero-age-main-sequence fitting and theoretical isochrone fitting using not only (V, B - V), (V, V - 1), (V, V - R) but also (V, V - K) color-magnitude diagrams. The reddening corresponded approximately to the average value derived from previous studies, while the distance modulus was found to be almost midway between the CCD photometric results of Romeo et al. (1989) and those of Mateo & Madore (1988). We have used four colors to distinguish members from field stars. The expected colors were calculated using the derived distance modulus, and were then were compared with the observed colors (B - V), (V - 1), (V - R), and (V - K). Thus, a color excess E(B - V) for each star was determined which could give the minimum difference between the calculated and observed colors. Single and binary members of the cluster were determined on the basis of the E(B - V) distribution of stars.

• Development and Reproduction
• /
• v.16 no.4
• /
• pp.315-320
• /
• 2012

The gDNA isolated from Cyclina sinensis from Gochang (GOCHANG), Incheon (INCHEON) and a Chinese site (CHINESE), were amplified by PCR. Here, the seven oligonucleotide decamer primers (BION-66, BION-68, BION-72, BION-73, BION-74, BION-76, and BION-80) were used to generate the unique shared loci to each population and shared loci by the three cyclina clam populations. As regards multiple comparisons of average bandsharing value results, cyclina clam population from Chinese (0.763) exhibited higher bandsharing values than did clam from Incheon (0.681). In this study, the dendrogram obtained by the seven decamer primers indicates three genetic clusters: cluster 1 (GOCHANG 01~GOCHANG 07), cluster 2 (INCHEON 08~INCHEON 14), cluster 3 (CHINESE 15~CHINESE 21). The shortest genetic distance that displayed significant molecular differences was between individuals 15 and 17 from the Chinese cyclina clam (0.049), while the longest genetic distance among the twenty-one cyclina clams that displayed significant molecular differences was between individuals GOCHANG no. 03 and INCHEON no. 12 (0.575). Individuals of Incheon cyclina clam population was somewhat closely related to that of Chinese cyclina clam population. In conclusion, our PCR analysis revealed a significant genetic distance among the three cyclina clam populations.

• Journal of the Korean Society for information Management
• /
• v.21 no.4 s.54
• /
• pp.173-185
• /
• 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 Korean Society of Transportation
• /
• v.29 no.1
• /
• pp.7-15
• /
• 2011

Recently, airport competitiveness measure is not only passenger and cargo throughput but also value-added activities of their hinterland and airport city. That is, airport competitiveness comes from airport versus airport to airport with their own-supplied city and hinterland connected with airport to provide diversified functions. This study surveyed and analyzed how to form a cluster focused on Incheon International Airport and what are important factors to form of cluster in achieving competences. These clusters need government's political support. In this case, there was a shortage of specialized human resources in competent local suppliers, and limited informations sharing.