• Asian-Australasian Journal of Animal Sciences
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• 제12권7호
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• pp.1015-1018
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• 1999

Single trait mixed models have been dominantly utilized for genetic evaluation of the reproductive traits in swine. However employing multiple trait approach may lead to more accurate genetic evaluations. For 5 litter size and litter weight traits of Danish Landrace, genetic parameters were estimated with a multiple trait mixed model. The heritability estimates were 0.02, 0.03, 0.03, 0.05, and 0.07, respectively for litter size at birth, litter size born alive, litter weight at birth, litter size at weaning, and litter weight at weaning. Negative genetic correlations were all positive. The litter weight at birth showed genetic antagonism with litter size born alive (-0.65) and litter size at weaning (-0.31), but positive with litter size at birth (0.47) and litter weight at weaning (0.31). The estimates of environmental correlations were larger than their corresponding genetic correlation estimates except for those between litter weight at birth and the other four traits. This study recommends simultaneous selection for two or more traits with multivariate mixed models in order to improve overall economic response.

• 산업공학
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• 제18권4호
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• pp.444-453
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• 2005

The purpose of the Gage R&R study is to determine whether a measurement system is adequate for monitoring a process. If the measurement system variation is small relative to the process variation, then the measurement system is deemed "adequate". The sources of variation associated with the measurement system are compared using an analysis of variance (ANOVA) model, in general. A typical ANOVA model used in a standard Gage R&R study is the two-factor random effect model. Then, the ANOVA partitions the total variation into three categories: repeatability, reproducibility, part variation. However, if the process variation possesses the between group variation, within group variation, and within part variation, these variations can cause the measurement system evaluation to provide misleading results. That is, in the standard Gage R&R study these variations affect the estimate of repeatability, reproducibility, or both. This paper presents a four-factor nested factorial ANOVA model which explicitly considers these variations for the Gage R&R study. The variance component estimators are derived by setting the EMS equations equal to the corresponding mean square from the ANOVA table and solving. And the proposed model is compared with the standard Gage R&R model.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회/대한산업공학회 2005년도 춘계공동학술대회 발표논문
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• pp.975-982
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• 2005

The purpose of the Gage R&R study is to determine whether a measurement system is adequate for monitoring a process. If the measurement system variation is small relative to the process variation, then the measurement system is deemed 'adequate'. The sources of variation associated with the measurement system are compared using an analysis of variance (ANOVA) model, in general. A typical ANOVA model used in a standard Gage R&R study is the two-factor random effect model. Then, the ANOVA partitions the total variation into three categories: repeatability, reproducibility, part variation. However, if the process variation possesses the between group variation, within group variation, and within-part variation, these variations can cause the measurement system evaluation to provide misleading results. That is, in the standard Gage R&R study these variations affect the estimate of repeatability, reproducibility, or both. This paper presents a four-factor nested factorial ANOVA model which explicitly considers these variations for the Gage R&R study. The variance component estimates are derived by setting the EMS equations equal to the corresponding mean square from the ANOVA table and solving. And the proposed model is compared with the standard Gage R&R model.

• 조명전기설비학회논문지
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• 제24권8호
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• pp.55-61
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• 2010

본 논문은 클래스 내와 클래스 간의 분산정보를 이용한 주파수 성분의 선택적 추출기법과 PCA-ELM 기반의 유도전동기 고장진단 시스템을 제안한다. 제안된 방법은 취득된 전류신호를 DFT에 의해 주파수 영역으로 변환한 후 분산정보를 이용하여 고장상태별로 차별성이 큰 순서대로 주파수 성분을 추출한다. 다음 단계로 선택된 주파수 성분에 대해서 PCA를 이용하여 고장상태별 특징들을 추출한다. 마지막 단계는 학습속도가 매우 우수한 ELM분류기에 의해 유도전동기의 상태를 진단하게 된다. 다양한 부하에 대하여 몇몇의 전기적 고장과 기계적 고장 하에서 획득한 데이터를 이용하여 제안된 방법의 타당성을 검증한다.

• 한국물환경학회지
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• 제35권1호
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• pp.19-27
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• 2019

The purpose of this study is to evaluate the water quality and phytoplankton community in Bukhan River which account for 44.4 % of the total inflow into Lake Paldang, using multivariate statistical techniques (i.e., correlation analysis, principal component analysis (PCA)/factor analysis (FA)). Water samples were collected from March to November 2015 and the following parameters measured; water temperature, pH, DO, EC, SS, BOD, Chl-a, COD, TN, $NO_3-N$, $NH_3-N$, TP, DTP, $PO_4-P$, and phytoplankton community. The water quality of the main stream and the tributaries were not significantly different apart from the relatively high concentration of BOD, COD and nutrients recorded in MH. The highest cell density of Stephanodiscus hantzschii and Merismopedia glauca dominated phytoplankton was observed in PD. Based on the correlation analysis, total phytoplankton and cyanophyceae were highly correlated with BOD, COD and nutrients. PCA/FA resulted in four main factors accounting for 82.240 % of the total variance in the water quality dataset. The group of component 1 (TN, DTN, DO, $NO_3-N$, water temperature) and component 2 ($PO_4-P$, T-P, DTP, SS) were classified as nutrient element factor whereas component 3 (Chl-a, COD, BOD, $NH_3-N$, pH) was related to organic substances. Hence, the identification of the main potential environmental pollution factors in Bukhan River will help policy makers make better and more informed decisions on how to improve the water quality.

• 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.

• 한국지하수토양환경학회지:지하수토양환경
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• 제27권6호
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• pp.22-36
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• 2022

Water resources in Jeju Island are dependent virtually entirely on groundwater. For groundwater resources, drought damage can cause environmental and economic losses because it progresses slowly and occurs for a long time in a large area. Therefore, this study quantitatively evaluated groundwater level fluctuations using principal component and cluster analyses for 42 monitoring wells in Jeju Island, and further identified the types of groundwater fluctuations caused by drought. As a result of principal component analysis for the monthly average groundwater level during 2005-2019 and the daily average groundwater level during the dry season, it was found that the first three principal components account for most of the variance 74.5-93.5% of the total data. In the cluster analysis using these three principal components, most of wells belong to Cluster 1, and seasonal characteristics have a significant impact on groundwater fluctuations. However, wells belonging to Cluster 2 with high factor loadings of components 2 and 3 affected by groundwater pumping, tide levels, and nearby surface water are mainly distributed on the west coast. Based on these results, it is expected that groundwater in the western area will be more vulnerable to saltwater intrusion and groundwater depletion caused by drought.

• 한국정보통신학회논문지
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• 제13권8호
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• pp.1679-1686
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• 2009

후각 정보의 실감성을 높일 수 있는 멀티미디어 통신 시스템에서 후각정보 전달을 위한 오더(odor) 센싱 시스템 및 관련 신호 처리 기술 개발은 차세대 멀티미디어 산업을 위한 핵심 과제로 떠오르고 있다. 오더 센싱 시스템의 성능 측정에 전통적으로 많이 사용된 방법은 주성분분석(PCA)이다. PCA는 분산에 기반한 도구로서 많은 경우 잘 동작한다. 그러나 오더 센싱 측정 데이터에 대해서는 의미 있는 값을 표시하는 것에 한계가 있다. 이 논문은 독립성분분석(ICA)을 사용하여 오더 센싱 데이터를 분석하는 방법을 설명한다. PCA와 ICA의 차이를 실질적인 측정데이터를 사용하여 비교하도록 한다. 실험을 통해 ICA가 개선된 변별력으로 센서의 경향 분석, 차원축소, 보다 적합한 데이터 표현 등에 있어 PCA보다 나은 결과를 도출함을 보인다.

• 한국조경학회지
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• 제13권2호
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• pp.37-70
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• 1985

The purpose of this study is to present objective basic data for environmental design by the quantitative analysis of visual quality emboded in physical environment. For this, as for the front garden of high schools, the spatial image was measured by the S.D. Scale Method, Factor Analysis was proceeded by the principal component analysis and the visual preference was investigated by the Paired Comparision Method. The scale values of plain and unpleasant road surface and external appearance of buildings, which are related to emotions of simpleness fell from straightness and stability, were found to be high. But, except for the road surface of Kyunggi High School, scale values of variables explaining the variation of the quality of materials, level of floor and rythm were generally low. For all green spaces, scale values of variables explaining the degree of pleasantness was found to be generally high. And, those explaining tidiness and characteristics of green spaces were not in the same tendency. But, the green spaces of Youngdong High school can be considered to the space with plenty of visual absorption uniqueness were high. As for the correlation between variables, variables for green spaces(12 and 26) and those for overall view of front garden( 1 and 4) revealed high positive correlation. Also, "order - disorder" and "convenient- incovenient" included in road surface variable can be regarded to have the same meaning since the correlation coefficient between them is very high, 0.7045. Image variables including road surface, external appearance of buildings, green spaces and overall view of front garden showed 91.21~61.08% of total variance. Thus, the remains can be considered to be the error valiance or specific variance. In Fctor I, II and III, main components explaining the road surface image of front gardens are order, hardness, texture, color, gradient and rythm. As for the external appearance of b wilding, variables of color, hardness, stability, peculiality and shape revealed high values of factor load. For all variables, communality was drastically high and ellen values and common variance were found to be very high in Factor I. As for the front gardens, variables explaining volume and peculiarity were found to be the main components of Factor I. In Factor II and III, variables of factor load were tidiness, pleasantness.

• 전자공학회논문지CI
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• 제46권2호
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• pp.19-26
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• 2009

본 논문은 PCA기반 얼굴인식 알고리즘에서 조명 변화에 따른 인식율의 변화 및 Cumulative Match Characteristic을 이용한 누적 식별 값 측정을 통해 알고리즘의 신뢰도를 확인하였다. 이를 위해 본 논문에서는 한 사람당 하나의 학습 영상만을 사용하는 경우뿐만 아니라 조명 조건이 다른 다중 학습 영상을 사용하여 실험하였고, 입력 영상 또한 다양한 조명 조건의 영상을 사용함으로서 학습 영상의 선택과 입력 영상의 조명 변화에 따른 알고리즘의 신뢰도에 관해 연구하였다. 실험 결과, 한사람 당 하나의 정면조명조건 학습 영상을 사용한 방식에 비하여 다중 학습 영상 사용 시 인식율은 떨어졌다. 그러나 학습 영상의 개수와 입력 영상의 조명 변화 범위에 관계없이 상위 유사도군에 들어가는 비율은 높은 양상을 보임으로서 조명 변화 환경에서 PCA 알고리즘의 인식 결과에 대한 신뢰도를 확인 할 수 있었다.