• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.133-137
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• 2005

In this paper, we investigate visual and quantitative analysis of different tastes in the liquids using multi-array chemical sensor (MACS) based on the ion-selective electrodes (ISEs), which is so called the electronic tongue (E-Tongue) system. We apply the Fuzzy C-means (FCM) algorithm combined with Principal Component Analysis (PCA), which can be used to reduce multi-dimensional data to two- or three-dimensional data, to classify visually data patterns detected by E-Tongue system. The proposed technique can be determined the cluster centers and membership grade of patterns through the unsupervised way. The membership grade of an unknown pattern, which does not shown previously, can be visually and analytically determined. Throughout the experimental trails, the E-tongue system combined with the proposed algorithms is demonstrated robust performance for visual and quantitative analysis for different tastes in the liquids.

• 한국환경복원기술학회지
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• 제24권1호
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• pp.53-68
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• 2021

The study aims to propose a locating method of green space for reducing Particulate Matter (PM) in ambient air in conjunction with its source traces and vulnerable groups. In order to carry out the aims and purposes, a literature review was conducted to derive indicators of vulnerable area to PM. Based on the developed indicators, the vulnerable areas and green spaces creation strategies for each cluster were developed for the case of Seongdong-gu, Seoul. As a result, six indicators for vulnerability analysis were came out including the vulnerable groups (children's facilities, old people's facilities), emission sources (air pollutant emission workplaces, roads), and environmental indicators (particulate matter concentration, NDVI). According to the six selected indicators, the target area was divided into 39 hexagons and analyzed to result the most vulnerable areas to particulate matter. As a result of comprehensive vulnerability analysis, the Seongsu-dong area was found to be the most vulnerable to particulate matter, and 5 clusters were derived through k-means cluster analysis. Cluster 1 was analyzed as areas that most vulnerable to particulate matter as a result of the comprehensive analysis, therefore urgent need to create green spaces to reduce particulate matter. Cluster 2 was areas that mostly belonged to the Han River. Cluster 3 corresponds to the largest number of hexagons, and since many vulnerable groups are distributed, it was analyzed as a cluster that required the creation of a green spaces to reduce particulate matter, focusing on facilities for vulnerable groups. Three hexagons are included in cluster 4, and the cluster has many roads and lacks vegetation in common. Cluster 5 has a lot of green spaces and is generally distributed with fewer vulnerable groups and emission sources; however, it has a high level of particulate matter concentration. In a situation where various green spaces creation projects for reducing particulate are being implemented, it is necessary to consider the vulnerable groups and emission sources and to present green space creation strategies for each space characteristic in order to increase the effectiveness of such projects. Therefore, this study is regarded as meaningful in suggesting a method for selecting a green area for reducing PM.

• 품질경영학회지
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• 제44권2호
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• pp.389-408
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• 2016

Purpose: This study was designed to analyze the behavioral change of knowledge structures and the trends of research topics in the quality management field. Methods: The network structure and knowledge structure of the words were visualized in map form using co-word analysis, cluster analysis and strategic diagram. Results: Summarizing the research results obtained in this study are as follows. First, the word network derived from co-occurrence matrix had 106 nodes and 5,314 links and its density was analyzed to 0.95. Average betweenness centrality of word network was 2.37. In addition, average closeness centrality and average eigenvector centrality of word network were 0.01. Second, by applying optimal criteria of cluster decision and K-means algorithm to word co-occurrence matrix, 106 words were grouped into seven clusters such as standard & efficiency, product design, reliability, control chart, quality model, 6 sigma, and service quality. Conclusion: According to the results of strategic diagram analysis over time, the traditional research topics of quality management field related to reliability, 6 sigma, control chart topics in the third quadrant were revealed to be declined for their study importance. Research topics related to product design and customer satisfaction were found to be an important research topic over analysis periods. Research topic related to management innovation was emerging state and the scope of research topics related to process model was extended to research topics with system performance. Research topic related to service quality located in the first quadrant was analyzed as the key research topic.

• Smart Structures and Systems
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• 제18권3호
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• pp.525-540
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• 2016

The CFRP-confined circular concrete-filled steel tubular column is composed of concrete, steel, and CFRP. Its failure mechanics are complex. The most important difficulties are lack of an available method to establish a relationship between a specific damage mechanism and its acoustic emission (AE) characteristic parameter. In this study, AE technique was used to monitor the evolution of damage in CFRP-confined circular concrete-filled steel tubular columns. A fuzzy c-means method was developed to determine the relationship between the AE signal and failure mechanisms. Cluster analysis results indicate that the main AE sources include five types: matrix cracking, debonding, fiber fracture, steel buckling, and concrete crushing. This technology can not only totally separate five types of damage sources, but also make it easier to judge the damage evolution process. Furthermore, typical damage waveforms were analyzed through wavelet analysis based on the cluster results, and the damage modes were determined according to the frequency distribution of AE signals.

• 한국응용과학기술학회지
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• 제39권1호
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• pp.63-73
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• 2022

본 연구는 초등학생의 골연령에 따라 군집화 시켜 각 군집 그룹의 체격, 체력 및 골성숙도를 분석하고 자료 분석을 통해 초등학생들의 균형적인 발달을 위한 기초자료를 제공하는 데 있다. 연구대상은 8세~13세에 해당하는 2243명을 대상으로 하였으며 골성숙도 산출을 위해 X-ray필름을 촬영한 후 TW3 방법 점수 환산표에 적용시켜 골성숙도를 산출했다. 신장계(Hanebio, Korea, 2021)와 Inbody 270(Biospace, Korea, 2019)를 사용하여 총 2개의 체격 요소를 측정하였으며, 체력은 근력(악력), 평형성(외발서기), 민첩성(플랫테핑), 순발력(제자리멀리뛰기), 유연성(좌전굴), 근지구력(윗몸일으키기), 심폐지구력(셔틀런)으로 총 7개 체력 요소의 종목을 측정하였다. 자료처리 방법은 SPSS PC/Program(Version 26.0)과 Britics Studio Tool을 이용하여 K-Means 클러스터링 기법, 교차분석, 일원변량분석(One-Way ANOVA)을 실시하였으며, p< .05 수준에서 유의한 것으로 간주하였다. 본 연구의 결과는 다음과 같다. 첫째, 미숙, 보통, 조숙의 3가지 골성숙도를 사용하여 군집화한 결과, 군집 1(미숙)은 근력, 평형성, 민첩성에서 높게 나타났다. 군집 2(보통)는 유연성에서 낮게 나타났으며, 군집 3(조숙)은 근력에서 높게 나타났다. 둘째, 초등학생의 개인특성별 군집화에 따른 체격 차이를 분석한 결과, 신장, 체중, 체지방률 모두 군집 3(조숙)이 높게 나타났다. 셋째, 초등학생의 개인특성별 군집화에 따른 체력 차이를 분석한 결과, 악력검사(좌, 우)는 군집 3(조숙)이 높게 나타났고 외발서기의 경우 군집 1(미숙)이 높게 나타났으며, 제자리멀리뛰기의 경우 군집 3(조숙)이 높게 나타났다.

• 한국콘텐츠학회논문지
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• 제10권3호
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• pp.364-372
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• 2010

본 연구의 목적은 자연휴양림의 방문한 이용객들의 방문동기를 통한 군집분석을 통하여 이용객을 분류하고 그에 따른 행동의도간의 차이를 검증하여 그에 따른 세분화된 이용객들의 차별화된 마케팅 및 경영전략을 수립하는데 그 목적이 있다고 할 수 있다. 이의 측정을 위하여 1년 이내에 자연휴양림을 이용한 적이 있는 방문객들을 대상으로 자연휴양림 방문동기에 대한 요인 분석을 실시한 후 군집분석을 실시하여 군집을 분류하였으며, 분류된 군집을 인구통계학적 특성과의 교차분석을 실시하여 군집의 유형화를 실시하였다. 유형화된 군집을 통하여 만족도, 재방문 및 추천의도에 대한 차이검정을 실시하였다. 분석결과 방문동기에 대한 요인분석 결과 3개의 요인으로 분류되었으며, 이를 통해 계층적 군집분석과 K-means군집분석을 통하여 2개의 군집을 도출하였으며, 2개의 군집을 다시 교차분석을 통하여 군집의 유형화를 실시하여 미혼의 100만원 미만의 군집과 기혼의 200~300만원의 군집 집단으로 유형화를 실시하였다. 이 군집을 자연휴양림 방문 후 행동의도간의 차이분석을 실시하였으며, 그 결과 전반적으로 만족, 즐거운 시간을 보냄, 방문은 현명한 선택, 재방문의도, 추천의도 모두 유의한 차이가 있는 것으로 나타났다. 군집 2인 기혼의 200~300만원의 집단에 더 높은 행동의도를 보이고 있는 것으로 나타나 차별화된 마케팅 전략이 필요시 되며, 또한 자연휴양림 공익적 성격을 고려하여 각 집단에 대하여 모두 소구할 수 있는 서설 및 서비스의 개발이 요구 된다.

• 지능정보연구
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• 제20권4호
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• pp.107-120
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• 2014

본 연구에서는 사회연결망분석기법 중 하나인 구조적 공백 분석 결과를 이용하여 추천과정에 사용자의 정성적이고 감성적인 정보를 반영할 수 있는 협업필터링 기반의 추천시스템을 제안한다. 협업필터링은 추천기술 중 가장 많이 활용되고 있지만 전통적으로 확장성과 희박성 등의 문제점뿐 만 아니라 사용자-상품 매트릭스의 선호도만을 이용하여 추천을 함으로써 사용자의 정성적이고 감성적인 정보를 추천과정에 반영하지 못한다는 한계점이 있다. 본 연구에서 제안하는 추천시스템은 사회연결망분석에서 중심성 분석과 함께 연결망 내의 주요개체를 탐지할 수 있는 구조적 공백 분석을 이용하여 연결망 내의 대표 사용자들을 추출한 후 이들을 중심으로 군집을 형성한 후 각 군집색인 협업필터링을 수행하는 과정을 통해 전통적인 협업필터링에서 반영하지 못했던 정성적, 감성적 정보를 반영한다. 한편, 군집색인 협업필터링을 수행함으로써 추천의 효율성을 높일 수 있는 장점도 있다. 본 연구에서는 실제 사용자들의 상품에 대한 선호도 평가점수와 사용자들의 사회연결망 정보를 수집하여 실험을 수행하고 전통적인 협업필터링과 다양한 형태의 협업필터링과의 추천성과 비교를 통하여 제안하는 시스템의 유용성을 확인한다. 비교모형으로는 전통적인 협업필터링, 임의 군집색인 기반 협업필터링, k평균 군집색인 기반 협업필터링을 이용한 추천시스템이며, 실험 결과, 제안한 모형이 다른 비교모형에 비해 추천성과의 정확도가 가장 우수하였다. 추천성과의 차이에 대한 통계적 유의성 검정 결과, 제안 모형은 전통적인 협업필터링 기반의 추천시스템과는 통계적으로 유의한 성과 차이가 없었으나, 다른 두 모형에 대해서는 통계적으로 유의한 성과의 차이가 있는 것으로 나타났다.

• 한국식품조리과학회지
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• 제28권6호
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• pp.721-729
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• 2012

This paper aimed to investigate the influence of consumer lifestyle on consumer selection of bakery cafe attributes. Data were collected through a self-administered questionnaire by 403 random consumers between the ages 20s and 30s in several bakery cafes in Seoul and Gyonggi area. Different methods of statistical analysis had been used such as frequency analysis, factor analysis, k-means clustering analysis, cross tabulation, one way ANOVA and Duncan's multiple range test with SPSS for Window 13.0 package. First, when analyzing the 16 questions of comsumer lifestyles, four factors were extracted: 'dining out-oriented factor', 'achievement-oriented factor', 'brand-oriented factor', and 'health-oriented factor'. Second, the respondents were divided into three groups by k-means cluster analysis: no interest group, dining-out & value oriented group, and health-brand oriented group. Third, consumer's bakery cafe attributes were categorized into five factors including 'food', 'convenience and image', 'store promotion', 'positive dining experience', and 'menu & merchandises'. Finally when analyzing the differences in the selection of bakery cafe attributes according to consumer's lifestyles, it showed a significant differences.

• Journal of Information Processing Systems
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• 제14권5호
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• pp.1167-1175
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• 2018

Microarray data plays an essential role in diagnosing and detecting cancer. Microarray analysis allows the examination of levels of gene expression in specific cell samples, where thousands of genes can be analyzed simultaneously. However, microarray data have very little sample data and high data dimensionality. Therefore, to classify microarray data, a dimensional reduction process is required. Dimensional reduction can eliminate redundancy of data; thus, features used in classification are features that only have a high correlation with their class. There are two types of dimensional reduction, namely feature selection and feature extraction. In this paper, we used k-means algorithm as the clustering approach for feature selection. The proposed approach can be used to categorize features that have the same characteristics in one cluster, so that redundancy in microarray data is removed. The result of clustering is ranked using the Relief algorithm such that the best scoring element for each cluster is obtained. All best elements of each cluster are selected and used as features in the classification process. Next, the Random Forest algorithm is used. Based on the simulation, the accuracy of the proposed approach for each dataset, namely Colon, Lung Cancer, and Prostate Tumor, achieved 85.87%, 98.9%, and 89% accuracy, respectively. The accuracy of the proposed approach is therefore higher than the approach using Random Forest without clustering.

• 패션비즈니스
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• 제18권4호
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• pp.97-113
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• 2014

This study investigates consumer's traits of market segmentation based on the apparel benefits. The subjects were 302 college students living in Yunnam, China. The mean, ANOVA, factor analysis, Duncan test, and K-means cluster analysis were used for statisticals analysis. The results of this study are as follows. The college students were classified, into six subdivisions, according to the apparel benefits by cluster analysis: indifference group, utility pursuit group, hedonic/brand pursuit group, individuality pursuit group, social recognition/fashion pursuit group, and pursuit benefits-minded group. In the factors of happiness-pursuing and life-centered of materialism, significant differences were found according to the groups of apparel benefits, and all factors of symbolic consumption and brand loyalty were found to have significant differences according to the groups of apparel benefits. The evaluation criteria of clothing were significantly different, depending on apparel benefits subdivision in criteria of aesthetic, socio-psychological, and utility. The use of information was shown to have significant differences, according to the groups of apparel benefits. The study results are highly expected to be utilized as useful sources in marketing plans for the midwest of China.