• 대한지역사회영양학회지
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• 제14권6호
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• pp.722-733
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• 2009

The purpose of this study was to explore dietary patterns and compare dietary patterns using cluster and factor analysis in Korean adults. This study analyzed data of 4,182 adult populations who aged 30 and more and had all of socio-demographic, anthropometric, and dietary data from 2005 Korean Health and Nutrition Examination Survey. Socio-demographic data was assessed by questionnaire and dietary data from 24-hour recall method was used. For cluster analysis, the percent of energy intake from each food group was used and 4 patterns were identified: "traditional", "bread, fruit & vegetable, milk", "noodle & egg", and "meat, fish, alcohol". The "traditional" pattern group was more likely to be old, less educated, living in a rural area and had higher percentage of energy intake from carbohydrates than other pattern groups. "Meat, fish, alcohol" group was more likely to be male and higher percentage of energy intake from fat. For factor analysis, mean amount of each food group was used and also 4 patterns were identified; "traditional", "modified", "bread, fruit, milk", and "noodle, egg, mushroom". People who showed higher factor score of "traditional" pattern were more likely to be elderly, less educated, and living in a rural area and higher proportion of energy intake from carbohydrates. In conclusion, three dietary patterns defined by cluster and factor analysis separately were similar and all dietary patterns were affected by socio-demographic factors and nutrient profile.

• International Journal of Internet, Broadcasting and Communication
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• 제15권1호
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• pp.164-170
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• 2023

The purpose of this study is to analyze the big data of Adidas brand participating in the Qatar World Cup in 2022 as a FIFA partner to understand useful information, semantic connection and context from unstructured data. Therefore, this study collected big data generated during the World Cup from Adidas participating in sponsorship as a FIFA partner for the 2022 Qatar World Cup and collected data from major portal sites to understand its meaning. According to text mining analysis, 'Adidas' was used the most 3,340 times based on the frequency of keyword appearance, followed by 'World Cup', 'Qatar World Cup', 'Soccer', 'Lionel Messi', 'Qatar', 'FIFA', 'Korea', and 'Uniform'. In addition, the TF-IDF rankings were 'Qatar World Cup', 'Soccer', 'Lionel Messi', 'World Cup', 'Uniform', 'Qatar', 'FIFA', 'Ronaldo', 'Korea', and 'Nike'. As a result of semantic network analysis and CONCOR analysis, four groups were formed. First, Cluster A named it 'Qatar World Cup Sponsor' as words such as 'Adidas', 'Nike', 'Qatar World Cup', 'Sponsor', 'Sponsor Company', 'Marketing', 'Nation', 'Launch', 'Official', 'Commemoration' and 'National Team' were formed into groups. Second, B Cluster named it 'Group stage' as words such as 'Qatar', 'Uruguay', 'FIFA' and 'group stage' were formed into groups. Third, C Cluster named it 'Winning' as words such as 'World Cup Winning', 'Champion', 'France', 'Argentina', 'Lionel Messi', 'Advertising' and 'Photograph' formed a group. Fourth, D Cluster named it 'Official Ball' as words such as 'Official Ball', 'World Cup Official Ball', 'Soccer Ball', 'All Times', 'Al Rihla', 'Public', 'Technology' was formed into groups.

• 한국생활과학회지
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• 제8권2호
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• pp.313-325
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• 1999

This study aimed to classify the data of children's bodies into several clusters by principal component scores that were extracted through the factor analysis in the former study, and to describe the distribution and body characteristics of the clusters. The sample was 308 elementary school children aged from 6 to 8 and the anthropometric measurements were performed indirectly from the photographs of the subjects, which was the same as the first analysis. The data were analysed statistically using SPSSWIN Ver. 8.0. Through the statistical analysis, 3 clusters were obtained from the data. The first cluster distributed more in the children aged 7 and 8 than in the children aged 6. The somatotype of this group was the tallest among the three groups, and they were the most developed group compared to the two other groups in lateral component as well as in linear component. The second cluster group wasn't well developed in lateral components, and had lowest level in Rohrer Index, so this group had thin figures compared to the other groups. The third cluster revealed dominant distribution in the group aged 6, and the group had the least developed linear components but higher level in Rohrer Index. Each cluster group revealed peculiar somatotype that was dominant in one group but rarely in other cluster groups. Lateral views of these characteristics were showed using the average of the measurements of clusters.

• 한국환경과학회지
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• 제11권12호
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• pp.1281-1289
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• 2002

This study was conducted to evaluate water quality in the Keum River using multivariate analysis. The analysis data in Keum river made use of surveyed data by the ministry of environment from January 1994 to December 2001. Thirteen water quality parameter were determined on each sample. The results was summarized as follow; Water quality in the Keum River could be explained up to 71.39% by four factors which were included in loading of organic matter and nutrients by the tributaries (32.88%), seasonal variation (16.09%), loading of pathogenic bacteria by domestic sewage of Gapcheon (13.39%) and internal metabolism in estuary as lakes(9.03%). For spatial variation of factor score, four group was classified by each factor characterization. Station 1 and 2 was influenced by Daechung dam, station 3 was affected by domestic sewage of Gapcheon, station 10~12 was affected by estuary dyke and the rest station. The result of cluster analysis by station was classified into four group that has different water quality characteristics. In monthly cluster analysis, three group was classified according to seasonal characteristic. Also, in yearly cluster analysis, three group was classified. It is necessary to control the pollutant loadings by Gapcheon inflow domestic sewage in Daejeon city for the sake of water quality management of Keum river.

• 보건행정학회지
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• 제33권2호
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• pp.118-128
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• 2023

Background: Personal socio-economic abilities are crucial as it affects health inequalities. These multidimensional inequalities across the regions have been structured and fixed. This study aimed to analyze health vulnerabilities by regional cluster and identify regional health disparities of self-rated health, using nationally representative cross-sectional data. Methods: This study used personal and regional data. Data from the Community Health Survey 2021 were analyzed. K-means cluster analysis was applied to 250 si-gun-gu using administrative regional data. The clusters were based on three areas: physical environment, health-related behaviors and biological factors, and the psychosocial environment through the conceptual framework for action on the social determinants of health. And binary logistic regression analyses were conducted to examine the differences in self-rated health status by the regional clusters, controlling human biology, environment, lifestyle, and healthcare organization factors. Results: The most vulnerable group was group 3, the moderate vulnerable group was group 1, and the least vulnerable group was group 2. The group 2 was more likely to have high self-rated health status than the moderate vulnerable group (odds ratio [OR], 1.023; p<0.001). And the group 3 showed low self-rated health status than the moderate vulnerable group (OR, 0.775; p<0.001). However, the moderate vulnerable group had significantly higher self-rated health status than the most vulnerable group (group 2: OR, 1.023; p<0.001; group 3: OR, 0.775; p<0.001). Conclusion: These results demonstrate that community members' health status is influenced by regional determinants of health and individual levels. And these contribute to understanding the importance of specific and differentiated interventions like locally tailored support programs considering both individual and regional health determinants.

• 한국유기농업학회지
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• 제25권1호
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• pp.1-22
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• 2017

The purpose of this research is to analysis actual condition of promoting complex industrialization and changes after promoting, and then to classify organic farmer using cluster analysis based on delineated organic farmer's changes factors. This study also aims to investigate differences in socioeconomic characteristics and behavioral intentions among classified groups of organic farmer's changes. Data were obtained by questionnaire. From the factor analysis, four factors were derived as "Economics", "Public benefit", "Environment and philosophical values" and "Establishing management and the regional bedrock". From the cluster analysis, three cluster were derived as "group that has a positive awareness of promoting complex industry", "group that has a negative awareness of promoting complex industry" and "unstable management and a regional base". And the three classifications were significantly different in the satisfaction and behavioral intentions.

• 한국의류학회지
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• 제28권7호
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• pp.1019-1028
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• 2004

The purpose of this study was to compare the body measurements of cyclists and non-cyclists and to classify cyclists＇ body types to offer basic information for the bicycle apparel manufacturer in Korea. The anthropometric data was collected including both direct and indirect measurements of 81 cyclists (40 female, 41 male) aged from 19 to 24. Anthropometric measurements were analyzed using percentiles, T-test, factor and cluster analysis. The results were as follows; Comparison of anthropomeoic data between cyclist and non-cyclist was to clarify that cyclists have bigger size than non-cyclists; especially the thigh circumference shows big differences. As the result of factor analysis, 5 factors, which explain 74% of variance, were extracted from all items for male and female cyclists. The results of cluster analysis classified body types into 3 groups. Cluster 1 among three female cyclist groups has biggest torso and had an erect back. Cluster 2 has small size among three female group and drooping shoulders. Cluster 3 has the bended forward shoulders and shows the protrusion back. In case of male cyclists, cluster 1 has thin body type owing to big height measurements and small girth measurements. Cluster 2 among three male groups has the biggest torso and thigh circumference. Cluster 3 has big forward angle of shoulders and shows the protrusion of the back as female cyclist.

• 한국국방경영분석학회지
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• 제6권2호
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• pp.89-127
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• 1980

The multivariate analysis techniques of cluster analysis are examined in this article. The theory and applications of the techniques and computer software concerning these techniques are discussed and sample jobs are included. A hierarchical cluster analysis algorithm, available in the IMSL software package, is applied to a set of data extracted from a group of subjects for the purpose of partitioning a collection of 26 attributes of a weapon system into six clusters of superattributes. A nonhierarchical clustering procedure were applied to a collection of data of tanks considering of twenty-four observations of ten attributes of tanks. The cluster analysis shows that the tanks cluster somewhat naturally by nationality. The principal componant analysis and the discriminant analysis show that tank weight is the single most important discriminator among nationality although they are not shown in this article because of the space restriction. This is a part of thesis for master's degree in operations research.

• 한국의류학회지
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• 제17권4호
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• pp.602-607
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• 1993

Concept of the comfort and fitness becomes a major concern in the basic function of the ready-made clothes. This research was performed to classify and characterize Korean adult males anthropometrically. Sample size was 1290 subjects and their age range was from 19 to 54 years old. Sampling was carried out by the stratified sampling method. 75 variables in total were applied to classify the bodytypes. Data were analyzed by the multivariate method, especially factor and cluster analysis. The high factor loading items extracted by factor analysis were based to determine the variables of the cluster analysis for the similar bodytypes respectively. In the part of the lower body, 14 variables from the data were applied to classify the bodytypes of lower part by Ward's minimum variance method. The group fanning a cluster were subdivided into 5 sets by cross-tabulation extracted by the hierarchical cluster analysis. Type 3 and 4 in lower body were composed of the majority of 53.1% of the subjects. The Korean adult males had relatively well-balanced in lower body.

• 대한인간공학회지
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• 제13권2호
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• pp.25-31
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• 1994

This research examines classifying and characterizing breast form's classification on elderly women, 242 subjects from 55 to 75 years of age participated. 27 direct anthropometric measurement were applied to classify the breast typesl. We analyzed measurement data using factor analysis, cluster analysis, analysis of variance. The results of the study were as follows. 1) 55-64 aged group was taller and higher than 65-79 aged group. Typical breast form in 55-64 aged group was more obese than breast form in 65-79 aged group. 2) We extracted 5 factors(obesity of breast, height of breast, height of breast items, location & size of breast, width of upper chest & shouldet length, height of breast & lower length of nipples) from total items through factor analysis. 3) Through cluster analysis, we categorized 3 clusters. Namely, type 1; characterized the best slender type, type 2; characterized middle sized type, type 3: characterized obesity type. Type 2 is the typical type on elderly women.