• Journal of Korean Society for Geospatial Information Science
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• v.18 no.4
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• pp.21-30
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• 2010

In this paper, the parallel distributed rainfall runoff model(K-DRUM) using MPI(Message Passing Interface) technique was developed to solve the problem of calculation time as it is one of the demerits of the distributed model for performing physical and complicated numerical calculations for large scale watersheds. The K-DRUM model which is based on GIS can simulate temporal and spatial distribution of surface flow and sub-surface flow during flood period, and input parameters of ASCII format as pre-process can be extracted using ArcView. The comparison studies were performed with various domain divisions in Namgang Dam watershed in case of typoon 'Ewiniar' at 2006. The numerical simulation using the cluster system was performed to check a parallelization effectiveness increasing the domain divisions from 1 to 25. As a result, the computer memory size reduced and the calculation time was decreased with increase of divided domains. And also, the tool was suggested in order to decreasing the discharge error on each domain connections. The result shows that the calculation and communication times in each domain have to repeats three times at each time steps in order to minimization of discharge error.

• Horticultural Science & Technology
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• v.33 no.5
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• pp.737-750
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• 2015

This study was carried out to construct a DNA profile database for 102 watermelon cultivars through the comparison of polymorphism level and genetic relatedness using genomic microsatellite (gMS) and expressed sequence tag (EST)-microsatellite (eMS) markers. Sixteen gMS and 10 eMS primers showed hyper-variability and were able to represent the genetic variation within 102 watermelon cultivars. With gMS markers, an average of 3.63 alleles per marker were detected with a polymorphism information content (PIC) value of 0.479, whereas with eMS markers, the average number of alleles per marker was 2.50 and the PIC value was 0.425, indicating that eMS detects a lower polymorphism level compared to gMS. Cluster analysis and Jaccard's genetic distance coefficients using the unweighted pair group method with arithmetic average (UPGMA) based on the gMS, eMS, and combined data sets showed that 102 commercial watermelon cultivars could be categorized into 6 to 8 major groups corresponding to phenotypic traits. Moreover, this method was sufficient to identify 78 out of 102 cultivars. Correlation analysis with Mantel tests for those clusters using 3 data sets showed high correlation ($r{\geq}0.80$). Therefore, the microsatellite markers used in this study may serve as a useful tool for germplasm evaluation, genetic purity assessment, and fingerprinting of watermelon cultivars.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.2
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• pp.40-51
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• 2021

The purpose of this study is to diagnose urban spatial structures using spatial modeling techniques for balanced urban development as part of sustainable urban growth management. Since urban spatial structure is an interaction of various activities, it is necessary to interpret the analysis results in conjunction with the analysis of changes in spatial structural elements. In this study, population and transportation were approached for research purposes. Population data were applied to the Getis-Ord G_i^* method, a spatial statistical technique, to analyze the concentration-decreasing region of the population. Traffic data analyzed the trend of centrality change by applying commuting traffic O-D data to Social Network Analysis techniques. The analysis showed that urban imbalance was growing, and the centrality of transportation was changing. The results of the analysis of spatial structure elements could be interpreted by linking the results of each factor to each neighborhood unit, predicting changes in urban spatial structure and suggesting directions for sustainable urban growth management.These results could also be used as a decision-making tool for various urban growth management policies introduced to cope with rapid urban development and uncontrollable development in many cities around the world.

• Design Convergence Study
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• v.15 no.3
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• pp.171-186
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• 2016

With the continuous rise of elderly population and rapid progression of aging in our society, greater emphasis is placed on the importance of local seniors welfare centers as representative service space that meets the diverse needs of local residents. In addition, there is a growing tendency among current users to seek high-quality service as their educational level, economic ability and lifestyle have changed for the better compared to past generations. Accordingly, this study analyzed the satisfaction of senior welfare centers according to life-style type of the elderly, using a lifestyle measurement tool which incorporates indicators of gerontographics. A survey was conducted with users of seven senior welfare centers located in Seoul. Analysis results are as follows: First, four types of lifestyle were derived through cluster analysis; independent activity type, protective activity type, active challenge type, and passive challenge type. Second, it was found that the overall satisfaction of seniors welfare centers by the life-style of the elderly is highest for the protective activity type followed by the passive challenge type, the active challenge type, and the independent activity type. Third, upon examining the effect of spatial characteristics of welfare centers on the satisfaction of elderly users by type of lifestyle, it was found that the independent activity type and the passive challenge type users are most influenced by intimacy, the protective activity type users by comfort, and the active challenge type users by convenience.

• Cartoon and Animation Studies
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• s.29
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• pp.129-149
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• 2012

The purpose of this study was to investigate the clustering and Big Five Personality domains in discriminating groups by level of school-related adjustment, as experienced by Social Sims game users. Social Games are based on web that has simple rules to play in fictional time and space background. This paper is to analyze the relationships between social networks and user behaviors through the social games . In general, characteristics of social games are simple, fun and easy to play, popular to the public, and based on personal connections in reality. These features of social games make themselves different from video games with one player or MMORPG with many unspecific players. Especially Social Game show a noticeable characteristic related to social learning. The object of this research is to provide a possibility that game that its social perspective can be strengthened in social game environment and analyze whether it actually influences on problem solving of real life problems, therefore suggesting its direction of alternative play means and positive simulation game. Data was collected by administering 4 questionnaires (the short version of BFI, Satisfaction with life, Career Decision-.Making Self-.Efficacy, Depression) to the participants who were 20 people in Seoul and Daejeon. For the purposes of the data analysis, both Stepwise Discriminant analysis and Cluster analysis was employed. Neuroticism, Openness, Conscientiousness within the Big Five Personality domains were seen to be significant variables when it came to discriminating the groups. These findings indicated that the short version of the BFI may be useful in understanding for game user behaviors When it comes to cultural research, digital game takes up a significant role. We can see that from the fact that game, which has only been considered as a leisure activity or commercial means, is being actively research for its methodological, social role and function. Among digital game's several meanings, one of the most noticeable ones is the research on its critical, social participating function. According to Jame Paul gee, the most important merit of game is 'projected identity'. This means that experiences from various perspectives is possible.[1] In his recent autobiography , he described gamer as an active problem solver. In addition, Gonzalo Francesca also suggested an alternative game developing method through 'game that conveys critical messages by strengthening critical reasons'. [2] They all provided evidences showing game can be a strong academic tool. Not only does a genre called social game exist in the field of media and Social Network Game, but there are also some efforts to positively evaluate its value Through these kinds of researches, we can study how game can give positive influence along with the change in its general perception, which would eventually lead to spreading healthy game culture and enabling fresh life experience. This would better bring out the educative side of the game and become a social communicative tool. The object of this game is to provide a possibility that the social aspect can be strengthened within the game environment and analyze whether it actually influences the problem solving of real life problems. Therefore suggesting it's direction of alternative play means positive game simulation.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.45-67
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• 2017

According to the Internet Usage Research performed in 2016, the number of internet users and the internet usage have been increasing. Smartphone, compared to the computer, is taking a more dominant role as an internet access device. As the number of smart devices have been increasing, some views that the demand on high-speed internet will decrease; however, Despite the increase in smart devices, the high-speed Internet market is expected to slightly increase for a while due to the speedup of Giga Internet and the growth of the IoT market. As the broadband Internet market saturates, telecom operators are over-competing to win new customers, but if they know the cause of customer exit, it is expected to reduce marketing costs by more effective marketing. In this study, we analyzed the relationship between the cancellation rates of telecommunication products and the factors affecting them by combining the data of 3 cities, Anyang, Gunpo, and Uiwang owned by a telecommunication company with the regional data from KOSIS(Korean Statistical Information Service). Especially, we focused on the assumption that the neighboring areas affect the distribution of the cancellation rates by coupling type, so we conducted spatial cluster analysis on the 3 types of cancellation rates of each region using the spatial analysis tool, SatScan, and analyzed the various relationships between the cancellation rates and the regional data. In the analysis phase, we first summarized the characteristics of the clusters derived by combining spatial information and the cancellation data. Next, based on the results of the cluster analysis, Variance analysis, Correlation analysis, and regression analysis were used to analyze the relationship between the cancellation rates data and regional data. Based on the results of analysis, we proposed appropriate marketing methods according to the region. Unlike previous studies on regional characteristics analysis, In this study has academic differentiation in that it performs clustering based on spatial information so that the regions with similar cancellation types on adjacent regions. In addition, there have been few studies considering the regional characteristics in the previous study on the determinants of subscription to high-speed Internet services, In this study, we tried to analyze the relationship between the clusters and the regional characteristics data, assuming that there are different factors depending on the region. In this study, we tried to get more efficient marketing method considering the characteristics of each region in the new subscription and customer management in high-speed internet. As a result of analysis of variance, it was confirmed that there were significant differences in regional characteristics among the clusters, Correlation analysis shows that there is a stronger correlation the clusters than all region. and Regression analysis was used to analyze the relationship between the cancellation rate and the regional characteristics. As a result, we found that there is a difference in the cancellation rate depending on the regional characteristics, and it is possible to target differentiated marketing each region. As the biggest limitation of this study and it was difficult to obtain enough data to carry out the analyze. In particular, it is difficult to find the variables that represent the regional characteristics in the Dong unit. In other words, most of the data was disclosed to the city rather than the Dong unit, so it was limited to analyze it in detail. The data such as income, card usage information and telecommunications company policies or characteristics that could affect its cause are not available at that time. The most urgent part for a more sophisticated analysis is to obtain the Dong unit data for the regional characteristics. Direction of the next studies be target marketing based on the results. It is also meaningful to analyze the effect of marketing by comparing and analyzing the difference of results before and after target marketing. It is also effective to use clusters based on new subscription data as well as cancellation data.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.95-118
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• 2017

Recent centrally the downtown area, the transaction between the row housing and multiplex housing is activated and platform services such as Zigbang and Dabang are growing. The row housing and multiplex housing is a blind spot for real estate information. Because there is a social problem, due to the change in market size and information asymmetry due to changes in demand. Also, the 5 or 25 districts used by the Seoul Metropolitan Government or the Korean Appraisal Board(hereafter, KAB) were established within the administrative boundaries and used in existing real estate studies. This is not a district classification for real estate researches because it is zoned urban planning. Based on the existing study, this study found that the city needs to reset the Seoul Metropolitan Government's spatial structure in estimating future housing prices. So, This study attempted to classify the area without spatial heterogeneity by the reflected the property price characteristics of row housing and Multiplex housing. In other words, There has been a problem that an inefficient side has arisen due to the simple division by the existing administrative district. Therefore, this study aims to cluster Seoul as a new area for more efficient real estate analysis. This study was applied to the hedonic model based on the real transactions price data of row housing and multiplex housing. And the K-Means Clustering algorithm was used to cluster the spatial structure of Seoul. In this study, data onto real transactions price of the Seoul Row housing and Multiplex Housing from January 2014 to December 2016, and the official land value of 2016 was used and it provided by Ministry of Land, Infrastructure and Transport(hereafter, MOLIT). Data preprocessing was followed by the following processing procedures: Removal of underground transaction, Price standardization per area, Removal of Real transaction case(above 5 and below -5). In this study, we analyzed data from 132,707 cases to 126,759 data through data preprocessing. The data analysis tool used the R program. After data preprocessing, data model was constructed. Priority, the K-means Clustering was performed. In addition, a regression analysis was conducted using Hedonic model and it was conducted a cosine similarity analysis. Based on the constructed data model, we clustered on the basis of the longitude and latitude of Seoul and conducted comparative analysis of existing area. The results of this study indicated that the goodness of fit of the model was above 75 % and the variables used for the Hedonic model were significant. In other words, 5 or 25 districts that is the area of the existing administrative area are divided into 16 districts. So, this study derived a clustering method of row housing and multiplex housing in Seoul using K-Means Clustering algorithm and hedonic model by the reflected the property price characteristics. Moreover, they presented academic and practical implications and presented the limitations of this study and the direction of future research. Academic implication has clustered by reflecting the property price characteristics in order to improve the problems of the areas used in the Seoul Metropolitan Government, KAB, and Existing Real Estate Research. Another academic implications are that apartments were the main study of existing real estate research, and has proposed a method of classifying area in Seoul using public information(i.e., real-data of MOLIT) of government 3.0. Practical implication is that it can be used as a basic data for real estate related research on row housing and multiplex housing. Another practical implications are that is expected the activation of row housing and multiplex housing research and, that is expected to increase the accuracy of the model of the actual transaction. The future research direction of this study involves conducting various analyses to overcome the limitations of the threshold and indicates the need for deeper research.

• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.145-148
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• 2006

This study aimed at preventing women from suffering from health problems and stress due to excessive lookism and encouraging them to participate in sports activities to form desirable body image and eventually to live a healthy and sound life. To achieve this goal, this study formed a population with members of sports centers located in Seoul and Daejeon areas as of 2006 and made a sample of 450 participants in physical exercise at a sports center through stratified cluster random sampling and that of 450 non-participants through a survey with mothers and sisters of those students from elementary and secondary schools within the areas for sampling the participants' group, thereby analyzing the data on a total of 900 persons. A questionnaire was used as a tool to collect data; a reliability test presented weight-, health-, and figure-related factors as a=.807, a=.819, and a=.784, respectively. This study used such statistical analysis methods as t-test, One-way ANOVA, and the Analysis of Covariance to analyze data. This study produced the following conclusions through these research methods and procedure. Pticipation in physical exercise has a positive effect on body image. Pticipation in physical exercise at a sports center show higher satisfaction with body image than non-participats.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.47-64
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• 2021

The global spread of COVID-19 around the world has not only affected many parts of our daily life but also has a huge impact on many areas, including the economy and society. As the number of confirmed cases and deaths increases, medical staff and the public are said to be experiencing psychological problems such as anxiety, depression, and stress. The collective tragedy that accompanies the epidemic raises fear and anxiety, which is known to cause enormous disruptions to the behavior and psychological well-being of many. Long-term negative emotions can reduce people's immunity and destroy their physical balance, so it is essential to understand the psychological state of COVID-19. This study suggests a method of monitoring medial news reflecting current days which requires striving not only for physical but also for psychological quarantine in the prolonged COVID-19 situation. Moreover, it is presented how an easier method of analyzing social media networks applies to those cases. The aim of this study is to assist health policymakers in fast and complex decision-making processes. News plays a major role in setting the policy agenda. Among various major media, news headlines are considered important in the field of communication science as a summary of the core content that the media wants to convey to the audiences who read it. News data used in this study was easily collected using "Bigkinds" that is created by integrating big data technology. With the collected news data, keywords were classified through text mining, and the relationship between words was visualized through semantic network analysis between keywords. Using the KrKwic program, a Korean semantic network analysis tool, text mining was performed and the frequency of words was calculated to easily identify keywords. The frequency of words appearing in keywords of articles related to COVID-19 emotions was checked and visualized in word cloud 'China', 'anxiety', 'situation', 'mind', 'social', and 'health' appeared high in relation to the emotions of COVID-19. In addition, UCINET, a specialized social network analysis program, was used to analyze connection centrality and cluster analysis, and a method of visualizing a graph using Net Draw was performed. As a result of analyzing the connection centrality between each data, it was found that the most central keywords in the keyword-centric network were 'psychology', 'COVID-19', 'blue', and 'anxiety'. The network of frequency of co-occurrence among the keywords appearing in the headlines of the news was visualized as a graph. The thickness of the line on the graph is proportional to the frequency of co-occurrence, and if the frequency of two words appearing at the same time is high, it is indicated by a thick line. It can be seen that the 'COVID-blue' pair is displayed in the boldest, and the 'COVID-emotion' and 'COVID-anxiety' pairs are displayed with a relatively thick line. 'Blue' related to COVID-19 is a word that means depression, and it was confirmed that COVID-19 and depression are keywords that should be of interest now. The research methodology used in this study has the convenience of being able to quickly measure social phenomena and changes while reducing costs. In this study, by analyzing news headlines, we were able to identify people's feelings and perceptions on issues related to COVID-19 depression, and identify the main agendas to be analyzed by deriving important keywords. By presenting and visualizing the subject and important keywords related to the COVID-19 emotion at a time, medical policy managers will be able to be provided a variety of perspectives when identifying and researching the regarding phenomenon. It is expected that it can help to use it as basic data for support, treatment and service development for psychological quarantine issues related to COVID-19.