• 한국컴퓨터정보학회논문지
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• 제26권1호
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• pp.201-208
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• 2021

본 연구에서는 2009-2016 보건의료 빅데이터를 활용하여 신체 정보와 혈액 내 지질 농도의 연관성을 다변량 분석하여 주요 요소들 사이의 영향력 정도를 비교 분석함으로써, 한국인의 이상지질혈증 예측모델 개발을 위한 근거를 제시하고자 한다. 3,312,971 명의 건강검진정보 자료를 통해서 신체 정보(나이, 신장, 체중, 허리둘레) 항목과 혈액검사(총콜레스테롤, 중성지방, HDL 콜레스테롤, LDL 콜레스테롤) 항목 간의 다차원적 선형상관관계를 도출하고, 항목 간의 영향력을 정준변량(canonical variate)으로 분석하였다. 그 결과 허리둘레가 크고 체중이 많이 나가면 중성지방이 높아지고 HDL 콜레스테롤 수치가 낮아지는 다차원적 상관관계를 도출하였다. 또한, 나이, 체중, 허리둘레, HDL 콜레스테롤 항목은 그 영향력 정도가 성별에 따라 유의미한 차이를 보였다. 특히, 나이에 따른 영향력의 정도는 체중, 허리둘레, HDL 콜레스테롤 항목이 40-50 전후 여성에게서 뚜렷한 변화를 보였다. 보건의료 빅데이터를 정준상관분석 기법을 적용하여 분석한 다차원적 상관관계는 비침습적인 방법으로 간편하게 측정 가능한 신체정보를 바탕으로 건강 상태를 평가할 수 있는 예측모델을 개발하는 데 활용될 수 있을 것이다.

• Journal of Ginseng Research
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• 제46권5호
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• pp.675-682
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• 2022

Background: Korean Red Ginseng (KRG) was reported to play an anti-inflammatory role, however, previous studies largely focused on the effects of KRG on priming step, the inflammation-preparing step, and the anti-inflammatory effect of KRG on triggering, the inflammation-activating step has been poorly understood. This study demonstrated anti-inflammatory role of KRG in caspase-11 non-canonical inflammasome activation in macrophages during triggering of inflammatory responses. Methods: Caspase-11 non-canonical inflammasome-activated J774A.1 macrophages were established by priming with Pam3CSK4 and triggering with lipopolysaccharide (LPS). Cell viability and pyroptosis were examined by MTT and lactate dehydrogenase (LDH) assays. Nitric oxide (NO)-inhibitory effect of KRG was assessed using a NO production assay. Expression and proteolytic cleavage of proteins were examined by Western blotting analysis. In vivo anti-inflammatory action of KRG was evaluated with the LPS-injected sepsis model in mice. Results: KRG reduced LPS-stimulated NO production in J774A.1 cells and suppressed pyroptosis and IL-1β secretion in caspase-11 non-canonical inflammasome-activated J774A.1 cells. Mechanistic studies demonstrated that KRG suppressed the direct interaction between LPS and caspase-11 and inhibited proteolytic processing of both caspase-11 and gasdermin D in caspase-11 non-canonical inflammasome-activated J774A.1 cells. Furthermore, KRG significantly ameliorated LPS-mediated lethal septic shock in mice. Conclusion: The results demonstrate a novel mechanism of KRG-mediated anti-inflammatory action that operates through targeting the caspase-11 non-canonical inflammasome at triggering step of macrophage-mediated inflammatory response.

• 한국축산식품학회지
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• 제38권4호
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• pp.794-805
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• 2018

To identify correlation between fresh meat and processed meat products, we performed canonical correlation analysis (CCA) to predict the relationship between pork supply and meat product production in Korea. Results of CCA showed a canonical correlation of 0.8576 in the first canonical pair (p<0.01). The production of meat products showed the highest correlation with pork import but the lowest correlation with the production of domestic pork. Although Korean consumer preferred meat products produced by fresh domestic pork, inexpensively imported pork with high share in meat products was supplied in the market. Therefore, securing domestically produced raw meat is important for expanding consumption of domestic meat products. Results of this study suggest that meat processor and pig producer can achieve the $6^{th}$ industrialization by combining the production of raw pork materials, meat processing, and sales service.

• 대한토목학회논문집
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• 제28권4D호
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• pp.569-577
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• 2008

본 연구의 목적은 위성영상으로부터 보다 정확한 토지정보를 취득하기 위해 다중시기데이터의 혼합과 특정 영상강조기법 및 영상분류알고리즘을 병합하여 적용하는 응용분류체계의 개발이다. 즉, 본 연구에서는 혼합된 다중시기데이터를 주성분분석한 후 정준상관분류기법을 적용하는 분류과정을 제안한다. 이 분류과정의 결과를 단일영상별 정준상관분류결과, 다중시기혼합영상의 정준상관분류결과, 시기별 주성분분석 후 정준상관분류결과와 비교한다. 사용된 위성영상은 1994년 7월 26일과 1996년 9월 1일에 취득된 Landsat 5 TM 영상이다. 정확도평가를 위한 지상실제데이터는 지형도 및 항공사진으로부터 취득되었으며, 연구대상영역 전체가 정확도평가 대상으로 사용되었다. 제안된 응용분류체계는 단일영상만을 사용하여 정준상관분류를 수행한 경우보다 분류정확도면에서 약 8.2% 상승되는 우수한 효과를 보여주었다. 특히, 복잡한 토지특성이 혼합되어 있는 도시역을 정확히 분류하는데 유효하였다. 결론적으로 Landsat TM 영상을 사용한 토지피복정보 추출시 분류정확도를 높이기 위해서, 다중시기영상을 사전에 주성분분석 후 정준상관분류기법을 적용하면 매우 효과적임을 확인하였다.

• Smart Structures and Systems
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• 제17권6호
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• pp.1031-1053
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• 2016

The health conditions of in-service civil infrastructures can be evaluated by employing structural health monitoring technology. A reliable health evaluation result depends heavily on the quality of the data collected from the structural monitoring sensor network. Hence, the problem of sensor fault diagnosis has gained considerable attention in recent years. In this paper, an innovative sensor fault diagnosis method that focuses on fault detection and isolation stages has been proposed. The dynamic or auto-regressive characteristic is firstly utilized to build a multivariable statistical model that measures the correlations of the currently collected structural responses and the future possible ones in combination with the canonical correlation analysis. Two different fault detection statistics are then defined based on the above multivariable statistical model for deciding whether a fault or failure occurred in the sensor network. After that, two corresponding fault isolation indices are deduced through the contribution analysis methodology to identify the faulty sensor. Case studies, using a benchmark structure developed for bridge health monitoring, are considered in the research and demonstrate the superiority of the new proposed sensor fault diagnosis method over the traditional principal component analysis-based and the dynamic principal component analysis-based methods.

• 응용통계연구
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• 제28권1호
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• pp.49-60
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• 2015

군생태학에서 종, 장소 그리고 환경변수의 관계를 시각적으로 보기 위해 대응분석, 정준대응분석 등 다양한 서열화방법들을 사용한다. Ter Braak (1986), Jackson 등 (1991), Parmer (1993) 등은 고유값 및 거리그래프를 이용하여 서열화방법들을 비교하고 있는데, 이 방법들은 조사된 데이터에 근거하고 있기 때문에, 모집단과 행렬도의 관계를 보여주지는 못한다. 따라서, 본 논문에서는 행렬도에 모집단 정보의 표현정도를 측정하는 방법을 소개하고, 이를 활용하여 서열화방법들을 객관적으로 비교하였다. 비교결과, 정준대응분석은 대응분석과 유사한 정분류율을 유지하면서도 환경정보를 이차원 공간에 표현할 수 있는 장점을 지닌 분석임을 확인하였다.

• 한국작물학회지
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• 제45권4호
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• pp.267-271
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• 2000

A total of 1,830 soybean collections were grown in the field and characterized for 10 morphological traits to determine the diversity and relationship within and among geographical regions. Phenotypic variation was found within all regions for most characters. The Shannon-Weaver diversity index ranged from 0.49 to 0.62 across regions, and 0.09 to 1.00 across characters. Canonical discriminant analysis and clustering of the canonical means delineated 3 regional clusters: (ⅰ) Kyunggi, Chungchong, Kangwon, Chulla, and Kyungsang; (ⅱ) Heilongjiang; and (ⅲ) Jilin, Manchuria, central China, south China, Others (China), Hokkaido, Honshu, and Others (Japan).

• 경영과학
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• 제28권2호
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• pp.93-103
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• 2011

This paper has aimed to identify marketing variables which affect physicians' prescription of drug. Based on a literature review this paper derives the three factors (indirect commercial source, direct commercial source, academic information source) of information sources that physicians rely on for medicines, the three factors (research supporting activity, marketing supporting activity, medicine information supporting activity) of promotion activities physicians prefer, and the four factors (indirect quality of medicine, direct quality of medicine, experience of using medicine, price and design of medicine) of prescription criteria physicians use. Then it investigates using canonical correlation analysis whether or not physicians' prescriptions are affected by the information sources, the promotion activities, and the type of physicians. From the canonical correlation analysis this paper derives the meaningful three canonical functions of prescription for drugs. The first function explains the prescription which is insensitive to marketing activities, the second function does the prescription which is sensitive to them, and the final function does the prescription which is not affected by them.

• Industrial Engineering and Management Systems
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• 제11권2호
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• pp.134-141
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• 2012

It is difficult to find an appropriate ordering policy for a many types of items. One of the reasons for this difficulty is that each item has a different demand trend. We will classify items by shipment trend and then decide the ordering policy for each item category. In this study, we indicate that categorizing items from their statistical characteristics leads to an ordering policy suitable for that category. We analyze the ordering policy and shipment trend and propose a new method for selecting the ordering policy which is based on finding the strongest relation between the classification of the items and the ordering policy. In our numerical experiment, from actual shipment data of about 5,000 items over the past year, we calculated many statistics that represent the trend of each item. Next, we applied the canonical correlation analysis between the evaluations of ordering policies and the various statistics. Furthermore, we applied the cluster analysis on the statistics concerning the performance of ordering policies. Finally, we separate items into several categories and show that the appropriate ordering policies are different for each category.

• 품질경영학회지
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• 제8권1호
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• pp.8-15
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• 1980

There are many methods of pattern recognition. In this paper we assume that the responses of independent m groups are described by p-variate normal random variables with distinct mean vectors and a common covariance matrix. Under the assumption we give pattern recognition of m groups by means of canonical discrininant analysis and it's computer program. An example is presented.