• Journal of Korean Home Economics Education Association
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• v.26 no.2
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• pp.15-30
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• 2014

The purpose of this study is to provide basic information on clothing preference to help teachers suggest clothes that help students adapt better to school life, and to get basic data specific to Home Economics curricula and how teenagers' attitude toward clothes correlate with their conformity to school as a whole. The survey of 587 students was conducted between December 17-24, 2012 in Gwangju. The data was analyzed using the SPSS 18.0 for window program: frequency, means, factor analysis, cluster analysis, Chronbach's ${\alpha}$, t-test, and ANOVA. There were significant differences in the many adolescents's adapted to school life based on the clothing behavior conformity and the attitude toward the name-brand. The results showed that, if it is not extreme, adolescents had the more the clothing behavior conformity on peer & mass media than less, they did well adapt on school life. And the group of more preference for the name-brand clothing result in low school discipline adaptation but high peer and teacher relationship. In adaptation of learning, they were not different significantly based on attitudes toward the name brand.

• Korean Journal of Environmental Agriculture
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• v.27 no.1
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• pp.1-9
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• 2008

The main purpose of this study is to accumulate the fundamental data representing groundwater of plastic film houses by means of water quality and its multivariate statistical analysis. Groundwater samples were collected in every two years since 2000 to 2004 from total 211 sites. According to the result of water quality analysis, ground water quality was suitable for irrigation purpose averagely. Correlation analysis showed that EC was highest positively correlated with $Mg^{2+}$ to 0.810(p<0.01), 0.776(p<0.01) in April and July, respectively. $NO_3-N$ was highest positively correlated with T-N to 0.794(p<0.01) in October. This result shows that it can lead to a different result even in similar case sometimes. Four factors were extracted through factor analysis in April and July, but five factors were extracted in October. The proportions of cumulative variance by the factor were 64.9, 60.2, and 70.7 in April, July, and October, respectively. The first factor was highly related to anions and cations such as $Ca^{2+},\;Mg^{2+},\;Cl^-,\;{SO_4}^{2-}$, and EC in contrast to that of stream water. According to the cluster analysis, 211 sites are classified into four groups. Common type of ground water quality was shown in group A. The pH and $PO_4-P$ were highest in Group B. The anions and cations were highest in Group C. $COD_{Cr}$ was highest in Group D.

• Journal of Periodontal and Implant Science
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• v.34 no.3
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• pp.607-622
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• 2004

Recently epidemiologic studies have indicated that the patients with periodontitis may have increased risk of ischemic cardiovascular events, and have suggested the important roles of blood cytokines and acute reactant proteins in the systemic infection and inflammatory response. Periodontitis and coronary heart disease (CHD) may share the common risk factors and the genetic mechanism associated with interleukin(IL)-1A, B and RA genotype may be involved in the production of IL-1. This study was aimed to investigate the relationship between angiographically defined CHD and periodontitis as chronic Gram-negative bacterial infection and to determine whether the IL-1 gene polymorphism is associated in both diseases. Patients under the age of 60 who had undergone diagnostic coronary angiography were enrolled in this study. Subjects were classified as positive CHD (+CHD, n=37) with coronary artery stenosis more than 50% in at least one of major epicardial arteries, and negative CHD (-CHD, n=30) without significant stenosis. After recording the number of missing teeth, periodontal disease severity was measured by means of plaque index (PI), gingival index (GI), bleeding on probing (BOP), probing depth (PD), clinical attachment level (CAL), and radiographic bone loss around all remaining teeth. Gingival crevicular fluid (GCF) was collected from the 4 deepest periodontal pockets and assessed for cytokine ($IL-1{\beta}$, IL-6, IL-1ra, tumor necrosis $factor-{\alpha}$, and prostaglandin $E_2$). Additionally, blood CHD markers, lipid profile, and blood cytokines were analyzed. IL-1 gene cluster genotyping was performed by polymerase chain reaction and enzyme restriction using genomic DNA from buccal swab, and allele 2 frequencies of IL-1A(+4845), IL-1B(+3954), IL-B(-511), and IL-1RA(intron 2) were compared between groups. Even though there was no significant difference in the periodontal parameters between 2 groups, GCF level of $PGE_2$ was significantly higher in the +CHD group(p<0.05). Correlation analysis showed the positive relationship among PD, CAL and coronary artery stenosis(%) and blood $PGE_2$. There was also significant positive relationship between the periodontal parameters (PI, PD, CAL) and the blood CHD markers (leukocyte count, C-reactive protein, and lactic dehyrogenase). IL-1 gene genotyping showed that IL-1A(+3954) allele 2 frequency was significantly higher in the +CHD group compared with the -CHD group (15% vs. 3.3%, OR 5.118,p=0.043). These results suggested that periodontal inflammation is related to systemic blood cytokine and CHD markers, and contributes to cardiovascular disease via systemic inflammatory reaction. IL-1 gene polymorphism might have an influence on periodontal and coronary heart diseases in Korean patients.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.93-107
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• 2014

In this paper, we report what we have observed with regard to user-perspective issue clustering based on multi-layered two-mode network analysis. This work is significant in the context of data collection by companies about customer needs. Most companies have failed to uncover such needs for products or services properly in terms of demographic data such as age, income levels, and purchase history. Because of excessive reliance on limited internal data, most recommendation systems do not provide decision makers with appropriate business information for current business circumstances. However, part of the problem is the increasing regulation of personal data gathering and privacy. This makes demographic or transaction data collection more difficult, and is a significant hurdle for traditional recommendation approaches because these systems demand a great deal of personal data or transaction logs. Our motivation for presenting this paper to academia is our strong belief, and evidence, that most customers' requirements for products can be effectively and efficiently analyzed from unstructured textual data such as Internet news text. In order to derive users' requirements from textual data obtained online, the proposed approach in this paper attempts to construct double two-mode networks, such as a user-news network and news-issue network, and to integrate these into one quasi-network as the input for issue clustering. One of the contributions of this research is the development of a methodology utilizing enormous amounts of unstructured textual data for user-oriented issue clustering by leveraging existing text mining and social network analysis. In order to build multi-layered two-mode networks of news logs, we need some tools such as text mining and topic analysis. We used not only SAS Enterprise Miner 12.1, which provides a text miner module and cluster module for textual data analysis, but also NetMiner 4 for network visualization and analysis. Our approach for user-perspective issue clustering is composed of six main phases: crawling, topic analysis, access pattern analysis, network merging, network conversion, and clustering. In the first phase, we collect visit logs for news sites by crawler. After gathering unstructured news article data, the topic analysis phase extracts issues from each news article in order to build an article-news network. For simplicity, 100 topics are extracted from 13,652 articles. In the third phase, a user-article network is constructed with access patterns derived from web transaction logs. The double two-mode networks are then merged into a quasi-network of user-issue. Finally, in the user-oriented issue-clustering phase, we classify issues through structural equivalence, and compare these with the clustering results from statistical tools and network analysis. An experiment with a large dataset was performed to build a multi-layer two-mode network. After that, we compared the results of issue clustering from SAS with that of network analysis. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The sample dataset contains 150 million transaction logs and 13,652 news articles of 5,000 panels over one year. User-article and article-issue networks are constructed and merged into a user-issue quasi-network using Netminer. Our issue-clustering results applied the Partitioning Around Medoids (PAM) algorithm and Multidimensional Scaling (MDS), and are consistent with the results from SAS clustering. In spite of extensive efforts to provide user information with recommendation systems, most projects are successful only when companies have sufficient data about users and transactions. Our proposed methodology, user-perspective issue clustering, can provide practical support to decision-making in companies because it enhances user-related data from unstructured textual data. To overcome the problem of insufficient data from traditional approaches, our methodology infers customers' real interests by utilizing web transaction logs. In addition, we suggest topic analysis and issue clustering as a practical means of issue identification.

• Korean Journal of Social Welfare Studies
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• v.40 no.3
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• pp.327-348
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• 2009

The purpose of this study is to understand the diverse lifestyles of Korean older adults by analyzing the consumption pattern of older households and its determinants. The 9th wave of the Korea Labor and Income Panel Study(KLIPS) data was used for analysis. The twenty consumption items provided by the dataset was reduced to thirteen according to the consumption purpose inherent in the item. K-means cluster analysis and multinomial logistic regression was employed to categorize the consumption pattern of older households and to analyze the determinants. The results are as follows. The consumption pattern of Korean older adults was clustered into six distinctive groups named Breadwinner, Leisure-time pursuer, Friendly outgoes, Daily-life survivor, Illness sufferer and Shelter seeker. Breadwinner, Leisure-time pursuer and Friendly outgoes were lifestyles that earn and spend more compared to the other three. Nevertheless, they differed according to the family size, indicating that the parenting burden might have direct influence on the lifestyle of Korean older adults. Older adults without parenting burden and with high level of education and economic capacity were likely to show Friendly outgoes lifestyle. On the other hand, Daily-life survivor, Illness sufferer and Shelter seeker showed lower level of spending, indicating that for those lacking in economic capacity, urgent needs such as medical need or housing need dominates the lifestyle. The results call for adequate custom policies that best fit the needs of older adults.

• 한국노년학
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• v.29 no.1
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• pp.291-307
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• 2009

This study investigated the family network of elderly and its effects on the subjective life satisfaction in Rural Area. In order to classify the family network, the authors used the analysis technique of social network including to a spouse, children and grandchildren. In addition, the authors described basic characteristics of family network on the family type, interaction frequency, and interaction content. And then family network typified four types by K-means cluster analysis method according to characteristics of family network and examined difference on life satisfaction of the elderly persons according to the type of family network. The major results were as following. First, the elderly did contact his/her children often, emotional support revealed that highest support expectation of elderly. Second, The family network of elderly could be typified four types ; 'relation estranged type', 'children-grandchildren centered type', 'family dependent type', 'couples centered type' and statistically significant difference showed in life satisfaction according to each type. The result, in the 'couples centered type', the life satisfaction was highest; on the contrary, 'relation estranged type', it was lowest. Third, Influencing factors on life satisfaction of the old person were economic conditions, physical conditions, education level, sex, more frequent contacts with grandchild, emotional support expectation of spouses. The results of this study suggest that social welfare political and institutional efforts are needed to improve the relationship between older persons and their children, grandchildren and spouses and life satisfaction of the elderly.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.6
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• pp.533-538
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• 2013

The damage caused by Recent frequently occurring locality torrential rains is increasing rapidly. In case of densely populated metropolitan area, casualties and property damage is a serious due to landslides and debris flows and floods. Therefore, the importance of predictions about the torrential is increasing. Precipitation characteristic of the bad weather in Korea is divided into typhoons and torrential rains. This seems to vary depending on the duration and area. Rainfall is difficult to predict because regional precipitation is large volatility and nonlinear. In this paper, Very short-term precipitation forecasting pattern model is implemented using KLAPS data used by Korea Meteorological Administration. we designed very short term precipitation forecasting pattern model using GA-based RBFNNs. the structural and parametric values such as the number of Inputs, polynomial type,number of fcm cluster, and fuzzification coefficient are optimized by GA optimization algorithm.

• Horticultural Science & Technology
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• v.32 no.6
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• pp.853-863
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• 2014

This study was carried out to construct a DNA profile database of 100 strawberry cultivars using microsatellite markers. Two hundred seventy four microsatellite primer pairs were screened with a set of 21 strawberry cultivars with different morphological traits. Twenty five primer pairs were selected because they produced reliable and reproducible fingerprints. These primer pairs were used to develop DNA profiles of 100 strawberry cultivars. Three to thirteen alleles were detected by each marker with an average of 7.50. The average polymorphism information content varied from 0.331 to 841 (average 0.706). Cluster analysis showed that the 100 cultivars were divided into 7 major groups reflecting geographic origin and pedigree information. Moreover, most of the cultivars could be discriminated by marker genotypes. These markers will be useful as a tool for the protection of plant breeders' intellectual property rights in addition to providing the means to intervene seed disputes relating to variety authentication.

• The Korean Journal of Elementary Counseling
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• v.9 no.2
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• pp.143-162
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• 2010

The purpose of this study is to construct Parent Attachment Scale for Children. Adapting the item consisting method used in Experiences in Close Relationships-Revised(ECR-R), Parent Attachment Scale for Children was constructed to measure child's attachment style with their parent, reliably and validly. Also, reliability and item trait informations based on item response theory were reviewed. First preliminary items were derived from the original items of ECR-R and existing Attachment Inventories. These items were modified and complemented to be easier and keep the original meaning of each item. Second preliminary items were administrated to 4~6th grades students(N=576). Finally, Parent Attachment Scale for Children were consisted with 30 items based on two-parameter graded response model. Internal consistency ranges of the scales of Parent Attachment Scale for Children are as follows : Avoidance scale is .94~.96; Anxiety scale is .85~.88. Test-retest reliability ranges are as follows; Avoidance scale is .71~.80; Anxiety scale is .53~.68. Item discrimination and item information value were within an appropriated range. Hierarchical cluster analysis with Ward's Method revealed four types of attachment style : Secure, Dismissing, Preoccupied, Fearful. Other implications and limitations of this study were discussed.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.193-202
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• 2022

The purpose of this study is to propose an effective informatization policy by categorizing consumer groups according to the level of digital divide and identifying the characteristics of each type. For this end, a total of 402 data were collected through an online and on-site surveys targeting consumers with internet experience, and the data were analyzed using the SPSS 26.0 program. As a result of conducting a K-means cluster analysis based on access to, capability, and utilization of digital devices, four consumer groups were categorized: 'device lover', 'proficient user', 'general user', and 'digital alienated'. By consumer type, significant differences were found in demographic characteristics, social capital, perception of the future information society, attitude toward technology as innovativeness, discomfort and familiarity, which are the antecedent variables of the digital divide. Significant differences in digital device satisfaction and intention to use, which are outcome variables of the digital divide, were also confirmed by consumer type. This study is academically and practically valuable in that it proposes customized informatization policies for each consumer group according to the level of digitization.