• 한국의류학회지
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• 제27권11호
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• pp.1338-1349
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• 2003

The color of apparels has the close interdependency on the skin colors of the wearers. This study was carried out to group the skin colors of Korean males into several similar skin colors and to analyze their preference colors. The skin colors were measured quantitatively and classified into several clusters that has similar hue, value and chroma with Munsell color system that is internationally used to communicate the colors. Sample size was 420 Korean males. With color spectrometer, JX-777, 4 points of the body were measured. All subjects had been shown with 40 color chips and answered their preference colors. Data were analysed by K-means Cluster analysis, Duncan test, Frequency and Chi square test using SPSS WIN 10 statistical package. Findings were as follows: 1. The skin colors of Korean males were mixed with skin colors of YR, R, and Y. 2. 420 subjects who have YR color were clustered in 3 kinds of skin color groups. 3. The average face color of total subjects was 4.81YR 5.91/4.97 in Munsell color system, 60.74 in L value, 13.71 in a value, 24.54 in b value. 136 observations out of 420 subjects were composed of Type 1: 4.50YR 6.35/4.87 and 192 observations were composed of Type 2: 4.62YR 5.86/5.12 and 92 observations were composed of Type 3: 5.67YR 5.37/4.79. 4. The average skin color of total 420 subjects was 6.26YR 6.07/4.41 and 62.33 in L value, 10.64 in a value, 23.48 in b value. The average skin color of Type 1 was 6.27YR 6.44/4.27 and of Type 2 was 6.15YR 5.91/4.49 and of Type 3 was 6.49YR 5.84/4.43 respectively. 5. 3 groups showed that the most preference color of sport$.$casual was 2.5Y 8/16 and 7.5PB 4/16 and the most preference color to their skins was 7.5PB 4/16 and 7.5YR 7/16.

• 한국조사연구학회지:조사연구
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• 제9권1호
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• pp.69-85
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• 2008

층화는 표본설계 단계에서 예비정보를 활용하는 대표적인 방법으로 대부분의 전국 단위의 표본설계에서 널리 활용된다. 층화의 효율을 극대화시키기 위해서는 조사목적에 부합되는 적절한 층화변수를 선택하는 것이 매우 중요하다. 하나의 표본을 통해 여러 개의 관심변수를 동시에 조사하는 다목적조사에서 다변량 층화변수가 있을 때 층화 전략을 세우는 것은 매우 복잡한 양상을 띤다. 본 연구에서는 관심변수의 수가 매우 많은 다목적조사를 위한 층화전략을 다룬다. 층화를 위해 구체적으로 사용하는 통계적 도구는 요인분석과 군집분석 등의 다변량 통계기법인데, 먼저 요인분석을 통해 적절한 층화변수들을 선정한 후 그 변수들을 이용하여 군집분석을 통해 층화를 하는 전략을 소개한다. 본 연구에서는 구체적으로 해양수산부의 어업비계통생산량조사를 위한 표본설계에서의 층화과정을 다룬다.

• Journal of the Korean Data and Information Science Society
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• 제26권2호
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• pp.367-376
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• 2015

데이터마이닝 기법 중의 하나인 군집분석은 다양한 특성을 지닌 관찰대상에 대해 유사성을 바탕으로 동질적인 군집으로 묶은 후, 동일 군집에 속해 있는 공통된 특성을 조사하는데 이용되는 기법이다. 본 논문에서는 주변 확률을 고려하지 않는 확률적 흥미도 측도 기반 유사성 측도인 Yule I과 II, Michael, Digby, Baulieu, 그리고 Dispersion 측도에 대해 상한 및 하한을 설정함으로써 이들의 대소관계를 규명하였다. 그 결과, 세 가지 유형의 대소 관계가 성립한다는 사실을 수식의 증명뿐만 아니라 실제 데이터 및 모의실험 데이터에 의해서도 확인할 수 있었다. 이들 측도들은 각 경계에 있는 측도와는 더욱 더 유사한 값을 가지므로 각 측도의 상한 및 하한은 여러 가지 측도들을 분류하는 도구가 되며, 실제 값의 관점에서 각 측도들의 관계를 알게 되면 주어진 알고리즘의 안정화에 도움이 될 수 있을 것이다.

• 전자공학회논문지CI
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• 제40권1호
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• pp.30-38
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• 2003

본 논문은 비디오 영상에서 움직이는 물체를 분할하는 방법을 제안한다. 물체들의 크기가 작거나 서로 겹쳐있을 경우(occlusion), 또는 잡음이 많은 경우에도 안정적인 이 방법은 움직임 검출(motion detection)과 움직임 분할(motion segmentation) 두 단계로 구성되어 있다. 움직임 검출을 하기 위하여 인접 영상간의 차영상(difference image) 분석을 통해 움직임이 있는 부분을 추출하며, 이때 적응적 임계치 방법을 이용하여 빛의 변화나 노이즈가 포함된 환경에서도 안정적으로 추출한다. 움직임 분할 단계에서는 움직임이 검출된 부분을 초기영역으로 분할 한 뒤, 이 영역들의 모션정보에 따라 이웃 한 영역들을 병합함으로써 독립적으로 움직이는 물체를 분할한다. 이러한 방법은 검출된 영역에 대해서만 움직임 분할을 함으로 많은 계산효과를 얻을 수 있으며 실제 도로영상에서 제안된 방법을 실험해본 결과 비디오 감시시스템에 적합함을 알 수 있었다.

• 한국항만경제학회지
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• 제34권2호
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• pp.51-68
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• 2018

본 연구는 물류시장의 업종 간의 경영성과 차이를 비교하는 동시에 물류기업의 사업특성 차이를 분석하였다. 나아가 업종과 사업특성의 차이가 경영성과에 미치는 영향을 검정하였다. 분석 방법으로는 분산분석, 군집분석을 이용하였고, 연구의 시사점은 다음과 같다. 첫째. 일본의 물류시장은 업종 간 경영성과 차이가 나타났고, 창고서비스업이 타 업종에 비해 수익성과 안정성이 높았다. 둘째, 업종별 사업행동의 차이가 나타났고, 타 업종에 비해 해상화물운송업은 자본집약도가 높았고, 창고서비스업은 사업선도력과 신용거래도가 높았다. 마지막으로 업종과 사업특성 군집의 두 요인은 경영성과에 미치는 상호작용이 유의미하게 검정되었는데, 수익성에 있어 화물운송업과 창고서비스업의 사업특성의 작용이 달랐다. 반면, 안정성에 있어 전 업종은 공통적으로 자본집약도를 낮추고 사업선도력을 재고하는 사업특성이 유효하게 작용하였다.

• 대한원격탐사학회지
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• 제26권3호
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• pp.317-324
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• 2010

In recent years, many automatic classification approaches have been employed. An automatic classification method can be effective, time-saving and can produce objective results due to the exclusion of operator intervention. This paper proposes a classification method based on automated training for high resolution multispectral images using ancillary data. Generally, it is problematic to automatically classify high resolution images using ancillary data, because of the scale difference between the high resolution image and the ancillary data. In order to overcome this problem, the proposed method utilizes the classification results of a Landsat image as a medium for automatic classification. For the classification of a Landsat image, a maximum likelihood classification is applied to the image, and the attributes of ancillary data are entered as the training data. In the case of a high resolution image, a K-means clustering algorithm, an unsupervised classification, was conducted and the result was compared to the classification results of the Landsat image. Subsequently, the training data of the high resolution image was automatically extracted using regular rules based on a RELATIONAL matrix that shows the relation between the two results. Finally, a high resolution image was classified and updated using the extracted training data. The proposed method was applied to QuickBird and SPOT-5 images of non-accessible areas. The result showed good performance in accuracy assessments. Therefore, we expect that the method can be effectively used to automatically construct thematic maps for non-accessible areas and update areas that do not have any attributes in geographic information system.

• 대한원격탐사학회지
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• 제35권1호
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• pp.57-81
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• 2019

Satellite images can be integrated into a crop model to strengthen the advantages of each technique for crop monitoring and to compensate for weaknesses of each other, which can be systematically applied for monitoring inaccessible croplands. The objective of this study was to outline the productivity of paddy rice based on simulation of the yield of all paddy fields in North Korea, using a grid crop model combined with optical satellite imagery. The grid GRAMI-rice model was used to simulate paddy rice yields for inaccessible North Korea based on the bidirectional reflectance distribution function-adjusted vegetation indices (VIs) and the solar insolation. VIs and solar insolation for the model simulation were obtained from the Geostationary Ocean Color Imager (GOCI) and the Meteorological Imager (MI) sensors of the Communication Ocean and Meteorological Satellite (COMS). Reanalysis data of air temperature were achieved from the Korea Local Analysis and Prediction System (KLAPS). Study results showed that the yields of paddy rice were reproduced with a statistically significant range of accuracy. The regional characteristics of crops for all of the sites in North Korea were successfully defined into four clusters through a spatial analysis using the K-means clustering approach. The current study has demonstrated the potential effectiveness of characterization of crop productivity based on incorporation of a crop model with satellite images, which is a proven consistent technique for monitoring of crop productivity in inaccessible regions.

• 대한간호학회지
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• 제49권4호
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• pp.449-460
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• 2019

Purpose: This study aims to provide base data for designing education and counseling programs for child-raising by identifying the types, characteristics and predictors of parenting behaviors of married immigrant women. Methods: We used a self-report questionnaire to survey 126 immigrant mothers of young children, who agreed to participate, and who could speak Korean, Vietnamese, Chinese, Filipino, or English, at two children's hospitals and two multicultural support centers. Statistical analysis was conducted using descriptive analysis, K-means clustering, ${\chi}^2$ test, Fisher's exact test, one-way ANOVA, $Sch{\acute{e}}ffe^{\prime}s$ test, and multinominal logistic regression. Results: We identified three clusters of parenting behaviors: 'affectionate acceptance group' (38.9%), 'active engaging group' (26.2%), and 'passive parenting group' (34.9%). Passive parenting and affectionate acceptance groups were distinguished by the conversation time between couples (p=.028, OR=5.52), ideology of motherhood (p=.032, OR=4.33), and parenting stress between parent and child (p=.049, OR=0.22). Passive parenting was distinguished from active engaging group by support from spouses for participating in multicultural support centers or relevant programs (p=.011, OR=2.37), and ideology of motherhood (p=.001, OR=16.65). Ideology of motherhood was also the distinguishing factor between affectionate acceptance and active engaging groups (p=.041, OR=3.85). Conclusion: Since immigrant women's parenting type depends on their ideology of motherhood, parenting stress, and spousal relationships in terms of communication and support to help their child-raising and socio-cultural adaptation, it is necessary to provide them with systematic education and support, as well as interventions across personal, family, and community levels.

• 한국정보통신학회논문지
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• 제26권3호
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• pp.341-346
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• 2022

지구온난화 및 이상 기후로 인해 홍수의 빈도 및 피해 규모가 늘어나고 있으며, 홍수 취약 지역에 노출된 사람이 2000년도에 비하여 25% 증가하였다. 홍수는 막대한 금전적, 인명적 손실을 유발하며, 홍수로 인한 손실을 줄이기 위해 홍수를 미리 예측하고 빠른 대피를 결정해야 한다. 본 논문은 홍수 예측을 위한 핵심 데이터인 강우량과 수위 데이터를 활용하여 시기적절한 대피 결정이 이루어질 수 있도록 CNN기반 분류 모델을 활용하여 홍수 위험도 판별 모델을 제안한다. 본 논문에서 제안한 CNN 기반 분류 모델과 DNN 기반의 분류 모델의 결과를 비교하여 더 좋은 성능을 보이는 것을 확인하였다. 이를 통해 홍수의 위험도를 판별하여, 대피 여부 판단하며 최적의 시기에 대피 결정을 내릴 수 있도록 하는 초기 연구로서 활용할 수 있을 것으로 사료된다.

• 보건행정학회지
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• 제32권2호
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• pp.205-215
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• 2022

Background: The purpose of this study is to identify the factors infecting the medical care utilization from a new perspective by newly classifying the categories of administrative districts using the urban decline index and medical vulnerability index as indicators. Methods: This study targeted 150,940 people who used medical services using the 2015 cohort database (DB), 2010-2015 urban regeneration analysis index DB, and 2014-2015 public health and medical statistics DB. The decline of the region was classified using the urban decline index typed using k-means clustering and the medical vulnerability index typed using the quantile score calculation. Regression analysis was performed 3 times with medical expenditure, length of stay, and the number of outpatient visits as dependent variables. Results: There were 37 stable region (47.4%), 29 health vulnerable region (37.2%), and 12 decline region (15.4%). The health vulnerable region had lower medical expenditure, fewer outpatient visits, and a higher length of stay than the stable region. The decline region was all higher than the stable region but had no significant effect. Conclusion: The factors that cause the health disparity between regions are not only factors related to individual health behavior but also environmental factors of the local community. Therefore, there is a need for a systematic alternative that properly considers the resources within the community and reflects the characteristics of the population.