• Journal of the Korean Society of Clothing and Textiles
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• v.24 no.2
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• pp.237-244
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• 2000

This study was carried out on 91 obese women who satisfied both of the conditions for obesity: over 1.6 in Rohrer index and over 90cm in bust girth. The purpose of this study was to analyze and classify the lower body of obese women and find out their respective characteristics. Twenty seven measurement items(21 direct measurement items and 6 indirect measurement items) were used for factor-analysis and cluster-analysis. In the study of lower body type, 7 factors were as a result of factor analysis and those factors were comprise 75.9% of total variance. Lower bodyshape were classified 3 types according to the cluster analysis. Type 1 was protrude of the hip, type 2 was short leg and protrude of the abdominal region and type 3 was obese of hip and long leg.

• Journal of The Korean Association For Science Education
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• v.42 no.6
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• pp.611-619
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• 2022

The purpose of this study is to explore the possibility of applying big data analysis to provide appropriate feedback to students using evaluation data in science education at a time when interest in educational data mining has recently increased in education. In this study, we use the evaluation data of 2,576 students who took 24 questions of the national assessment of educational achievement. And we use K-means cluster analysis as a method of unsupervised machine learning for clustering. As a result of clustering, students were divided into six clusters. The middle-ranking students are divided into various clusters when compared to upper or lower ranks. According to the results of the cluster analysis, the most important factor influencing clusterization is academic achievement, and each cluster shows different characteristics in terms of content domains, subject competencies, and affective characteristics. Learning motivation is important among the affective domains in the lower-ranking achievement cluster, and scientific inquiry and problem-solving competency, as well as scientific communication competency have a major influence in terms of subject competencies. In the content domain, achievement of motion and energy and matter are important factors to distinguish the characteristics of the cluster. As a result, we can provide students with customized feedback for learning based on the characteristics of each cluster. We discuss implications of these results for science education, such as the possibility of using this study results, balanced learning by content domains, enhancement of subject competency, and improvement of scientific attitude.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.389-392
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• 2007

In this paper, we propose an algorithm that improve network lifetime by adjusting cluster size according to location information of sensor node in wireless sensor network (WSN) using clustering technique. The sensed information in each cluster transfers to sink node through inter-cluster communications. Cluster head (CH) that nearby located in sink node much more spend own energy than far away CHs, because nearer CH forwards more data, so network lifetime is decreased. Proposed algorithm minimizes energy consumption in adjacent cluster to sink node by decreasing cluster site, and improve CH lifetime by distributing transmission paths. As a result of analysis, the proposed algorithm shows longer network lifetime in WSN.

• The Journal of Fisheries Business Administration
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• v.40 no.3
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• pp.1-28
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• 2009

In recent, the Korean fisheries industry face an overall crisis. Annual fish catch is continuously decreasing for last two decades even though various programs to improve fish population. Moreover, domestic fish market is more and more occupied by imported cheap fish products from abroad due to the consequence of open economic policy, FTA and WTO/DDA entente. Under the circumstances, this study aims to examine the potential for building fisheries cluster as a policy tool to promote fisheries and fisheries-associated industries in Korea. To achieve this goal, the authors firstly reviewed the theoretical concept of Industrial Cluster in the evolutionary economics point of view, secondly, analyzed the main components of Porterian Cluster(or innovation cluster), thirdly, derived the key reasons to induce the improvement of productivity within the cluster network system and lastly evaluated fisheries capability and industrial infrastructures of each province as a basic condition to build a fisheries cluster. The result of the study demonstrates the voluntary accumulation of fish products and processing techniques in Korea, however, it is not enough to make up a Porterian innovation. Therefore, the present is most opportune for applying fisheries cluster as a strategic policy tool. Government supports to establish innovation cluster for fisheries may contribute both fisheries industry and local economy by developing the latent capacity of fisheries and helping concentrate innovation capabilities.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.6
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• pp.1201-1206
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• 2007

In this paper, we propose an algorithm that improve network lifetime by adjusting cluster size according to location information of sensor node in wireless sensor network (WSN) using clustering algorithm. The collected sensing information by sensor nodes in each cluster are transferred to sink node using inter-cluster communications method. Cluster head (CH) that located nearby sink node spend much more energy than those of far from sink node, because nearer CH forwards more data, so network lifetime has a tendency to decrease. Proposed algorithm minimizes energy consumption in adjacent cluster to sink node by decreasing cluster size, and improve CH lifetime by distributing transmission paths. As a result of mathematical analysis, the proposed algorithm shows longer network lifetime in WSN.

• Fashion & Textile Research Journal
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• v.12 no.1
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• pp.80-85
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• 2010

The purpose of this study was to examine the characteristics of armscye circumference which will be used to develop total contents for the apparel industry. The subjects of this study were 16- to 49-year-old women whose 3D body shape data were analyzed. 72 length and length-ratio measurements were taken to each subject' armscye circumference. The used analysis methods are descriptive statistics, principal component analysis, and cluster analysis. The results are follows; 1. Considering the Length of armscye circumference, the result of principal component analysis were extracted 3 factors and those factors comprised 95% of total variance. As the result of the cluster analysis of factor scores, subjects were classified into 4 cluster by their size characteristic. 2. Considering the length-ratio of armscye circumference, the result of principal component analysis were extracted 5 factors and those factors comprised 96.45% of total variance. As the result of the cluster analysis of factor scores, subjects were classified into 5 cluster by their shape characteristic. So that, this research could be useful to manufacture garment which reflected 3D body figure and improved fitting.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.1
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• pp.59-67
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• 2015

Because reservoirs that supply irrigation water play an important role in water resource management, it is necessary to evaluate the vulnerability of this particular water supply resource. The purpose of this study is to provide water supply risk maps of agricultural reservoirs in South Korea using irrigation vulnerability model and cluster analysis. To quantify water supply risk, irrigation vulnerability indices are estimated to evaluate the performance of the water supply on the agricultural reservoir system using a probability theory and reliability analysis. First, the irrigation vulnerability probabilities of 1,346 reservoirs managed by Korea Rural Community Corporation (KRC) were analyzed using meteorological data on 54 meteorological stations over the past 30 years (1981-2010). Second, using the K-mean method of non-hierarchical cluster analysis and pre-simulation approach, cluster analysis was applied to classify into three groups for characterizing irrigation vulnerability in reservoirs. The morphology index, watershed area, irrigated area, and ratio between watershed and irrigated area are selected as the clustering analysis parameters. It is suggested that the water supply risk map be utilized as a basis for the establishment of risk management measures, and could provide effective information for a reasonable decision making on drought risk mitigation.

• Korean Journal of Community Nutrition
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• v.14 no.6
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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.

• Journal of Korean Society on Water Environment
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• v.37 no.6
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• pp.520-530
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• 2021

Multivariate statistical analysis and an environmental hydrological model were applied for investigating the causes of water pollution and providing best management practices for water quality improvement in urban and agricultural watersheds. Principal component analysis (PCA) and cluster analysis (CA) for water quality time series data show that chemical oxygen demand (COD), total organic carbon (TOC), suspended solids (SS) and total phosphorus (T-P) are classified as non-point source pollutants that are highly correlated with river discharge. Total nitrogen (T-N), which has no correlation with river discharge and inverse relationship with water temperature, behaves like a point source with slow and consistent release. Biochemical oxygen demand (BOD) shows intermediate characteristics between point and non-point source pollutants. The results of the PCA and CA for the spatial water quality data indicate that the cluster 1 of the watersheds was characterized as upstream watersheds with good water quality and high proportion of forest. The cluster 3 shows however indicates the most polluted watersheds with substantial discharge of BOD and nutrients from urban sewage, agricultural and industrial activities. The cluster 2 shows intermediate characteristics between the clusters 1 and 3. The results of hydrological simulation program-Fortran (HSPF) model simulation indicated that the seasonal patterns of BOD, T-N and T-P are affected substantially by agricultural and livestock farming activities, untreated wastewater, and environmental flow. The spatial analysis on the model results indicates that the highly-populated watersheds are the prior contributors to the water quality degradation of the river.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.3
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• pp.68-84
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• 2020

This study analyzed the relationship between spatial characteristics and heat waves in the distribution area of the elderly population in Changwon, Gyeongsangnam-do. For analysis, the Statistics Census data, the Ministry of Environment land cover, Landsat 8 surface temperature, and the Meteorological Agency's heat wave days data were used. The spatial characteristics of the distribution of the elderly population was classified into 5 types through K-mean cluster analysis considering the land use types. The characteristics of the elderly population by spatial type were higher in the urbanized type(cluster-3), but the proportion of the elderly population was higher in the agricultural and forest area types(cluster-1, cluster-2). In the characteristics of the surface temperature and the heat wave days, the surface temperature was the highest in the urban area, but heat wave days were the highest in the rural area. As a result of analyzing the heat wave characteristics according to the spatial type of the distribution area of elderly population, cluster-2 with the largest area in agricultural areas was highest at 15.95 days, and cluster-3 with a large area in urbanized types was the lowest at 9.41 days and 9.18 days. In other words, the elderly population living in rural areas is more exposed to heat waves than the elderly population living in urban areas, and the damage is expected to increase. The results of this study could be used as basic data to prepare various policy measures for effective management and prevention of vulnerable areas in summer.