• 한국항해항만학회지
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• 제42권3호
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• pp.177-186
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• 2018

보트의 초기설계단계에서 설계자는 주요치수 결정을 위해 많은 정보를 필요로 하며, 그러한 정보의 대부분은 해당 보트와 유사한 실적선 자료들을 많은 시간에 걸쳐 조사 및 분석함으로써 얻을 수 있다. 또한, 결정된 주요치수는 설계과정(기본/상세설계) 전반에 걸쳐 영향을 미치게 되고, 이는 결국 보트의 안정성과 성능으로 직결된다. 따라서 본 연구에서는 700여 척의 실적선 자료를 이용하여 보트 초기설계시스템(설계지원플랫폼)을 개발하고, 50피트급 고속보트를 대상으로 이를 활용하여 설계자가 초기설계단계에서도 주요치수를 편리하고 합리적으로 도출 및 결정할 수 있음을 확인하였다.

• 전자공학회논문지SC
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• 제48권5호
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• pp.7-12
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• 2011

본 논문에서는 자료패턴을 분류하기에 적합한 특징을 추출하는 방법인, 클래스가 부가된 커널 주성분분석(class-augmented kernel principal component analysis)를 새로이 제안하였다. 특징추출에 널리 이용되는 부분공간 기법 중, 최근 제안된 클래스가 부가된 주성분분석(class-augmented principal component analysis)은 패턴 분류를 위한 특징을 추출하기 위해 이용되는 선형분류분석(linear discriminant analysis)등에 비해 정확한 특징을 계산상의 문제 없이 추출할 수 있는 기법이다. 그러나, 추출되는 특징은 입력의 선형조합으로 제한되어 자료에 따라 적절한 특징을 추출하기 어려운 경우가 발생한다. 이를 해결하기 위하여 클래스가 부가된 주성분분석에 커널 트릭을 적용하여 비선형 특징을 추출할 수 있는 새로운 부분공간 기법으로 확장하고, 실험을 통하여 성능을 평가하였다.

• Journal of Ecology and Environment
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• 제38권2호
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• pp.145-156
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• 2015

This study was based on water quality data of the Lake Doam watershed, monitored from 2010 to 2013 at eight different sites with multiple physiochemical parameters. The dataset was divided into two sub-datasets, namely, non-rainy and rainy. Principal component analysis (PCA) and factor analysis (FA) techniques were applied to evaluate seasonal correlations of water quality parameters and extract the most significant parameters influencing stream water quality. The first five principal components identified by PCA techniques explained greater than 80% of the total variance for both datasets. PCA and FA results indicated that total nitrogen, nitrate nitrogen, total phosphorus, and dissolved inorganic phosphorus were the most significant parameters under the non-rainy condition. This indicates that organic and inorganic pollutants loads in the streams can be related to discharges from point sources (domestic discharges) and non-point sources (agriculture, forest) of pollution. During the rainy period, turbidity, suspended solids, nitrate nitrogen, and dissolved inorganic phosphorus were identified as the most significant parameters. Physical parameters, suspended solids, and turbidity, are related to soil erosion and runoff from the basin. Organic and inorganic pollutants during the rainy period can be linked to decayed matters, manure, and inorganic fertilizers used in farming. Thus, the results of this study suggest that principal component analysis techniques are useful for analysis and interpretation of data and identification of pollution factors, which are valuable for understanding seasonal variations in water quality for effective management.

• 대한토목학회논문집
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• 제8권2호
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• pp.99-107
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• 1988

과압밀점토(過壓密粘土)에 대한 일련의 입방형삼축시험(立方型三軸試驗)이 실시되었다. 삼축시험(三軸試驗)은 세 주응력(主應力)을 서로 독립적으로 제어시킬 수 있는 입방체형삼축시험기(立方體型三軸試驗機)를 사용하여 실시되었다. 점토공시체(粘土供試體)로는 현장(現場)에서 직접 채취된 자연시료(自然試料)를 삼축(三軸) chamber 내(內)에서 과압밀비(過壓密比)가 5가 되게 만든 입방체형공시체(立方體型供試體)가 사용되었으며 본연구결과(本硏究結果), 중간주응력(中間主應力)은 과압밀점토(過壓密粘土)의 응력변형률(應力變形率), 비배수강도(非排水强度), 유효강도(有效强度), 유효내부마찰각(有效內部摩擦角) 및 간극압(間隙壓)에 큰 영향을 미치고 있음이 구명(究明)되었다. 중간주응력(中間主應力)이 최소주응력(最小主應力)과 같지 않은 경우의 과압밀점토파괴강도(過壓密粘土破壞强度)는 Mohr-Coulomb 파괴규준(破壞規準)에 의하여 과소평가(過小評價)되나 Lade규준(規準)에 의하여는 대단히 양호하게 산정된다. 또한 과압밀점토(過壓密粘土)의 비배수강도(非排水强度)는 Tresca규준(規準)에 일치하지 않는다.

• 한국지역사회생활과학회지
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• 제20권3호
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• pp.437-448
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• 2009

The purpose of this study was to examine the effect of individual and interpersonal variables on early childhood teachers' efficacy of problem behavior guidance. Individual variables consisted of teachers' socio-demographic characteristics, experience of training course on problem behavior guidance and warm-hearted attitude. Interpersonal variables consisted of intimacy with colleagues, support from the principal of a kindergarten, parental partnerships. Subjects were 122 early childhood teachers in Busan. Major findings were as follows. There were significant differences in teachers' efficacy of problem behavior guidance with respect to teachers' age, teaching experience, position, marriage status, experience of training course on problem behavior guidance, warm-hearted attitude, intimacy with colleagues, and support from the principal of a kindergarten. In other words, a higher level of teachers' efficacy of problem behavior guidance was shown in the teachers who were older, highly experienced, or in higher positions. In addition, teachers who were married, had completed a training course on problem behavior guidance, had a higher warm-hearted attitude, had a intimacy with colleagues, or had a support from the principal of a kindergarten were found to have higher efficacy of problem behavior guidance. As results of examining relative effects of individual and interpersonal variables on efficacy of problem behavior guidance, the influential variables are teaching experience, warm-hearted attitude, support from the principal of a kindergarten, and position in that order.

• 환경위생공학
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• 제9권2호
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• pp.8-23
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• 1994

During the period from Mar., 1991 to Feb., 1992 66 tSP samples were collected by Hi volume air sampler at 1 sampling site in Seoul and the amount of concentration of 21 components(SO$_{4}$$^{2-}$, NO$_{3}$$^{-}$, NH$_{4}$$^{+}$, Cl$^{-}$, Al, Ba, Ca, Cd, Cr, Cu, Fe, It Mg, Mn, Na, Ni, Pt Si, Ti, Zn, Zr ) were measured. And monthly and seasonal variation were surveyed and the principal component analysis( PCA ) were carried out with respect to these amount of pollutants, minimum of visibility and radiation on a horizontal surface. The total amount of soluble ion in water was high in order o(SO$_{4}$$^{2-}$> NO$_{3}$$^{-}$> N%'>Cl$^{-}$ and metal ion was high in order of Na> Ca>Si> Fe> Al> K> Mg> Zn> Pb> Cu>Ti> Mn > Ba> Cr> Zr> Ni> Cd. There was Seasonal variation in concentration for SO$_{4}$$^{2-}$, NH$_{4}$$^{+}$, Cl$^{-}$, Na, Al, Ca, Bt Mg, Fe and Si. It was assumed that the components of the highest concentration on April were depend on yellow sand and the frequency of wind velocity and direction. As the results of PCA, the amount of pollution components was able to characterized with two principal components(Z$_{1}$, Z$_{2}$ ). The first principal components Z$_{1}$ was considered to be a factor indicating the pollutants originated from natural generation and The second principal components Z$_{2}$ was considered to be a factor indicating the pollutants originated from human work. The monthly concentration of pollutants in ISP, minimum of visibility and radiation on a horizontal surface was possible to evaluate by the use of these two principal components Z$_{1}$ and Z$_{2}$ .

• 응용통계연구
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• 제22권3호
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• pp.531-539
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• 2009

로지스틱회귀분석은 고객관계관리를 위한 데이터마이닝 분야에서 많이 사용되는 기법인데, 이 분야의 모형설정 과정에서는 연관성이 매우 높은 설명변수들이 모형에 함께 포함되어 다중공선성의 문제를 유발하며, 더욱이 회귀자료에 이상점들이 포함되면 최우추정량은 심각한 결함을 갖게 된다. 두 가지 문제점을 동시에 해결하기 위하여 로버스트주성분로지스틱회귀를 적용할 수 있는데, 본 논문에서는 주성분의 선정기준을 결정하는 모형을 개발하고, 주성분모형에서의 추정치에 미치는 이상점의 영향을 축소하기 위한 로버스트추정법을 제안하였다. 제안된 추정법은 다중공선성과 이상점이 유발하는 문제들을 적절히 해결해 준다는 사실이 모의실험을 통하여 확인되었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권10호
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• pp.3989-4006
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• 2020

The intelligent agriculture monitoring is based on the perception and analysis of environmental data, which enables the monitoring of the production environment and the control of environmental regulation equipment. As the scale of the application continues to expand, a large amount of data will be generated from the perception layer and uploaded to the cloud service, which will bring challenges of insufficient bandwidth and processing capacity. A fog-based offline and real-time hybrid data analysis architecture was proposed in this paper, which combines offline and real-time analysis to enable real-time data processing on resource-constrained IoT devices. Furthermore, we propose a data process-ing algorithm based on the incremental principal component analysis, which can achieve data dimensionality reduction and update of principal components. We also introduce the concept of Squared Prediction Error (SPE) value and realize the abnormal detection of data through the combination of SPE value and data fusion algorithm. To ensure the accuracy and effectiveness of the algorithm, we design a regular-SPE hybrid model update strategy, which enables the principal component to be updated on demand when data anomalies are found. In addition, this strategy can significantly reduce resource consumption growth due to the data analysis architectures. Practical datasets-based simulations have confirmed that the proposed algorithm can perform data fusion and exception processing in real-time on resource-constrained devices; Our model update strategy can reduce the overall system resource consumption while ensuring the accuracy of the algorithm.

• 응용통계연구
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• 제33권1호
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• pp.61-74
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• 2020

심볼릭 자료 중 하나인 구간형 자료는 모든 관측값에서 단일 값이 아닌 구간을 값으로 취하며, 관측값 내에 변동이 존재한다는 특징을 갖는다. 주성분 분석은 자료의 분산을 최대로 설명하여 자료의 차원을 축소하는 방법이므로 구간형 자료의 주성분 분석은 관측값 간의 분산 뿐만 아니라 관측값 내의 분산 역시 설명하여야 한다. 본 논문에서는 구간형 자료의 세 가지 주성분 분석법을 소개하고자 한다. 또한 기존의 분위수 방법에서 균일분포를 사용하는 것이 아니라 구간의 중심점 부근이 좀 더 많은 정보를 가지고 있는 것으로 보고 절단정규분포를 사용하는 방법을 제안하였다. 모의실험과 OECD 관련 실제 통계 자료를 통하여 각 방법의 결과를 비교해 보았다. 마지막으로 분위수 방법의 경우 화살표 표현법을 통해 주성분 산점도를 그리고 분위수들의 위치와 분포를 확인하였다.

• 한국축산식품학회지
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• 제36권6호
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• pp.719-728
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• 2016

The aim of this study was to explore the volatile compounds of hind leg, foreleg, abdomen and Longissimus dorsi in both male and female Hyla rabbit meat by solid phase microextraction tandem with gas chromatography mass spectrometry, and to seek out the key odorants via calculating the odor activity value and principal component analysis. Cluster analysis is used to study the flavor pattern differences in four edible parts. Sixty three volatile compounds were detected, including 23 aldehydes, 4 alcohols, 5 ketones, 11 esters, 5 aromatics, 8 acids and 7 hydrocarbons. Among them, 6 aldehydes and 3 acids were identified as the potential key odorants according to the ratio of concentration and threshold. The contents of volatile compounds in male Hyla rabbit meat were significantly higher than those in female one (p<0.05). The results of principal component analysis showed that the first two principal component cumulative variance contributions reach 87.69%; Hexanal, octanal, 2-nonenal, 2-decenal and decanal were regard as the key odorants of Hyla rabbit meat by combining odor activity value and principal component analysis. Therefore volatile compounds of rabbit meat can be effectively characterized. Cluster analysis indicated that volatile chemical compounds of Longissimus dorsi were significantly different from other three parts, which provide reliable information for rabbit processing industry and for possible future sale.