• Proceedings of the Korean Institute of Industrial Safety Conference
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• 2000.11a
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• pp.64-67
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• 2000

옥내전선의 도체재료로 주로 동(CU)이 사용되고 있으며, 절연재료로는 염소(Cl)를 주성분으로 한 콤파운드가 사용되고 있다. 전선을 장시간 사용하게 되면 전기적, 열적, 기계적, 환경적 요인 등에 의해 열화가 진행되며, 도체 및 절연물의 열분해, 산화, 뒤틀림 등에 의한 특상저하로 전기설비 및 전기기기에 재해를 유발하게 된다.(중략)

• Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference
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• 2001.04a
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• pp.168-168
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• 2001

제지공정의 지절 현상은 많은 공정 변수들이 복합적으로 작용하여 발생하는 가장 큰 공정 트러블 중의 하나이다. 지절은 생산량 감소 뿐만 아니라 발생 후 공정의 복구 와 정리, 생산재가동 및 공정의 재안정화를 위해 많은 시간과 비용, 그리고 노력이 투 입되어야 하므로 공정의 효율과 생산성을 크게 저하시키는 요인이다. 그러나 지절 현상 의 복잡성 때문에 이에 대해 쉽게 접근하거나 해결하지 못하고 있는 것이 현실이지만 그 필요성은 더욱 더 증대되고 있다. 본 연구에서는 최근 들어 각종 산업분야에서 복잡 한 공정상의 결점 발견 및 진단에 효과적이라고 인정받고 있는 예측 분석기법인 인공 신경망(artificial neural network) 시율레이션과 일반적인 통계기법 중의 하나인 주성분 분석을 이용하여 제지 공정의 지절 현상의 검토 가능성을 타진하였다. 인공신경망이란 인간두뇌에서 일어나는 자극-반응-학습과정을 모사하여 현실세계에 존재하는 다양한 현상들의 업력벡터와 출력상태 간의 비선형 mapping올 컴퓨터 시율 레이션을 통하여 분석하고자 하는 기법으로, 여러 가지 현상들을 학습을 통해서 인식하 는 신경망 내의 신경단위들이 병렬처리에 의해 많은 양의 자료에 대한 추론이나 판단 을 신속하고 정확하게 해주는 특징이 있으며 실시간 패턴인식이나 분류 응용분야에도 매우 매력적으로 이용되고 있는 방법이다. 이러한 인공 신경망 기법 중에서도 본 연구 에서는 퍼셉트론의 한계점을 극복하기 위하여 입력총과 출력층에 한 개 이상의 은닉층 ( (hidden layer)을 사용하여 다층 네트워으로 구성하고, 모든 입력패턴에 대하여 발생하 는 오차함수를 최소화하는 방향으로 연결강도를 조정하는 back propagation 학습 알고 리즘을 사용하였다. 지절의 원인으로 추정 가능한 공정인자들을 변수로 하여 최적의 인 공신경망을 구축하기 위해 학습률과 모멘트 상수의 변화 및 은닉층의 수와 출력층의 뉴런 수를 조절하는 동의 작업을 거쳐 네트워크의 정확도가 높은 인공신경망을 설계하 였다. 또한 이러한 인공신경망과의 비교분석을 위해 동일한 공정 데이터들올 이용하여 보편적으로 사용하는 통계기법 중의 하나인 주성분회귀분석을 실시하였다. 주성분 분석은 여러 개의 반응변수에 대하여 얻어진 다변량 자료의 다차원적인 변 수들을 축소, 요약하는 차원의 단순화와 더불어 서로 상관되어있는 반응변수들 상호간 의 복잡한 구조를 분석하는 기법이다. 본 발표에서는 공정 자료를 활용하여 인공신경망 과 주성분분석을 통해 공정 트러블의 발생에 영향 하는 인자들을 보다 현실적으로 추 정하고, 그 대책을 모색함으로써 이를 최소화할 수 있는 방안을 소개하고자 한다.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2012.05a
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• pp.159-170
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• 2012

본 연구는 다음과 같은 분석결과를 제시한다. 먼저 우리나라 10개 산업의 기술생태지형을 결정하는 상호관계 K는 9개로 나타났다. 이러한 주성분요인분석결과는 K=N-1의 기술생태지형 구조를 가지고 있음을 보여준다. 둘째, Kauffman NK모형에 따른 우리나라 기술생태지형은 K=N-1인 경우로 다 극점을 존재하는 적응체계로 매우 울퉁불퉁한 기술생태지형을 가지고 있다고 볼 수 있다. 따라서 우리나라의 기술생태계경우에 기술 또는 산업의 수 N이 증가함에 따라서 국소 최적 점의 수는 매우 빠르게 증대할 수 있다. 이러한 매우 많은 국소 최적 점을 가진 기술생태지형에서 기술탐색과정은 전체 최적 기술조합 또는 기술개발에 효율적으로 도달하기 어려우며, 역시 기술생태지형은 매우 복잡한 진화 및 발전체계를 갖고 있음을 의미한다. 본 연구결과의 기술 정책적 시사점은 우리나라 산업간 그리고 기술간에 보다 상호연관성을 높임으로써, 기술생태지형을 완만하고 매끄럽게 조성할 필요성이 제기된다.

• Journal of Korean Society of Transportation
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• v.27 no.2
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• pp.117-131
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• 2009

When most drivers take to the freeway, they don't necessarily pay attention to the geometric design. They expect proper design by depending on their own senses and recognition. When they evaluate the features of traveling on the freeway, they can think differently than engineers. The design needs to predict the exact speed of the driver to satisfy the driver's expectation, safety, pleasure and so on. This study categorized the factors influencing the speed of six freeways considering geometric and operational features to make a prediction model of speed. The model used multiple regression with these factors and produced statically appropriate results. This study utilized the principle component analysis and the quantification II analysis based on the image data of the satisfaction of the traveling environment collected through individual interviews. As a result, this study found the factors of satisfaction in a traveling environment. It made a satisfaction model of the traveling environment on freeways considering the change of driver's actual recognition and societal recognition using structural equations and the quantification II theory. Through the model made in this study, This model can present not only qualitative factors like satisfaction of traveling environment on freeways, but also the quantitative elements like speed. What is important is the evaluation of features of traveling on freeways reflected in the recognition and traffic environment felt by drivers.

• The Korean Journal of Applied Statistics
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• v.21 no.4
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• pp.571-580
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• 2008

The logistic regression analysis is widely used in the area of customer relationship management and credit risk management. It is well known that the maximum likelihood estimation is not appropriate when multicollinearity exists among the regressors. Thus we propose the logistic principal components regression to deal with the multicollinearity problem. In particular, new method is suggested to select proper principal components. The selection method is based on the condition index instead of the eigenvalue. When a condition index is larger than the upper limit of cutoff value, principal component corresponding to the index is removed from the estimation. And hypothesis test is sequentially employed to eliminate the principal component when a condition index is between the upper limit and the lower limit. The limits are obtained by a linear model which is constructed on the basis of the conjoint analysis. The proposed method is evaluated by means of the variance of the estimates and the correct classification rate. The results indicate that the proposed method is superior to the existing method in terms of efficiency and goodness of fit.

• The Korean Journal of Applied Statistics
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• v.30 no.6
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• pp.889-899
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• 2017

Independent component analysis is a multivariate approach to separate mixed signals into original signals. It is the most widely used method of blind source separation technique. ICA uses linear transformations such as principal component analysis and factor analysis, but differs in that ICA requires statistical independence and non-Gaussian assumptions of original signals. PCA have a natural ordering based on cumulative proportion of explained variance; howerver, ICA algorithms cannot identify the unique optimal ordering of the components. It is meaningful to set order because major components can be used for further analysis such as clustering and low-dimensional graphs. In this paper, we compare the performance of several criteria to determine the order of the components. Kurtosis, absolute value of kurtosis, negentropy, Kolmogorov-Smirnov statistic and sum of squared coefficients are considered. The criteria are evaluated by their ability to classify known groups. Two types of data are analyzed for illustration.

• Economic and Environmental Geology
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• v.38 no.4 s.173
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• pp.435-450
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• 2005

The purpose of the study is to analyze the hydrogeochemical characteristics by multivariate statistical method, to interpret the hydrogeochemical processes for the new variables calculated from principal components analysis (PCA), and to infer the groundwater flow and circulation mechanism by applying the geostatistical methods for each element and principal component. Chloride and nitrate are the most influencing components for groundwater quality, and the contents of $NO_3$ increased by the input of agricultural activities show the largest variation. The results of PCA, a multivariate statistical method, show that the first three principal components explain $73.9\%$ of the total variance. PC1 indicates the increase of dissolved ions, PC2 is related with the dissolution of carbonate minerals and nitrate contamination, and PC3 shows the effect of cation exchange process and silicate mineral dissolution. From the results of experimental semivariogram, the components of groundwater are divided into two groups: one group includes electrical conductivity (EC), Cl, Na, and $NO_3$, and the other includes $HCO_3,\;SiO_2,$ Ca, and Sr. The results for spatial distribution of groundwater components showed that EC, Cl, and Na increased with approaching the coastal line and nitrate has close relationship with the presence of agricultural land. These components are also correlated with the topographic features reflecting the groundwater recharge effect. The kriging analysis by using principal components shows that PC 1 has the different spatial distribution of Cl, Na, and EC, possibly due to the influence of pH, Ca, Sr, and $HCO_3$ for PC1. It was considered that the linear anomaly zone of PC2 in western area was caused by the dissolution of carbonate mineral. Consequently, the application of multivariate and geostatistical methods for groundwater in the study area is very useful for determining the quantitative analysis of water quality data and the characteristics of spatial distribution.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.2
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• pp.236-241
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• 2011

Soil microbial diversity was responsible for a strong effect on the chemical properties of orchard soils. This study evaluated a relationship between soil chemical properties and soil microbial diversities at 25 sites in orchard soils in Gyeongnam Province. The average nutrients in the orchard soils were 2.6 times for available phosphorous, 2.3 times for exchangeable potassium and 1.3 times for exchangeable calcium higher compared to recommend concentrations in the orchard soils. Contents of available phosphorous and organic matter in the inclined piedmont soils were higher than those in the other topographical soils (p<0.05). Populations of fungi and fluorescence Pseudomonas sp. in the silt loam soils were significantly higher than those in the sandy loam soils (p<0.05). In principal component analysis of chemical properties and microbial populations in the upland soils, our findings suggested that population of bacteria should be considered as potential factor responsible for the clear orchard soils differentiation. The soil organic matter was significantly negative correlation with population of bacteria whereas was positive correlation with population of fungi in orchard soils.

• Korean Journal of Construction Engineering and Management
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• v.19 no.6
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• pp.46-54
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• 2018

In the 21st century, the Earth has continued its efforts to reduce carbon emissions to overcome the crisis caused by climate change. The construction industry, which is a representative industry that produces large amounts of the environmental load during construction, should actively reduce the amount of the environmental load. From the planning stage of the construction facility, it is necessary to consider the environmental load such as route selection and structure type selection to reduce the environmental load. However, the environmental load can be estimated based on the input resource amount. However, in the planning stage, it is difficult to accurately calculate the environmental load due to lack of information on the construction amount. The purpose of this study is to select the environmental load factors for IPC girder bridges to be used in the environmental load estimation model in the planning stage. Specific information related to the environmental load was selected from a list of information available in the planning stage, reflecting the Life Cycle Assessment(LCA), correlation, principal components analysis and expert opinion. The list of selected planning stage information is 10 such as span length and bridge extension, and it is expected to be used as a basic data for the future development of environmental load estimation model.

• Journal of the Korean Society for Marine Environment & Energy
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• v.14 no.1
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• pp.1-10
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• 2011

To understand characteristics of the water quality on the coastal boundary on tidal flat, field observations between 2008 and 2009 were undertaken twice a month at five coastal areas (Muan bay, Tando bay, Hampyeong bay, Shinan Jido and Yeongkwang coastal areas). Yearly water temperature difference was large with the range between $1.3^{\circ}C$ and $31.1^{\circ}C$. Salinity was about 32 but was the lower less than 20 for the heavy rainfall season. DO was high in winter and low in summer according to the variation of water temperature. pH represented the variation similar to DO. Suspended solid was averagely high over 100 mg/l in Yeongkwang coastal area, especially. COD did not revealed large variation with the value of about 1 mg/l. DIN and DIP concentration were high when freshwater was highly input in summer. DIN concentration was low for winter and early spring but DIP concentration did not show the seasonal variation with the continuous increase from July 2009 to December 2009. Chlorophyll a appeared high for spring with approximately $10\;{\mu}g/l$ and was higher for summer in Yeongkwang coastal area than other sites. The results of principal component analysis conducted to compare the characteristics of water quality observed in study areas showed the distinguishable features as follows. The freshwater input fluctuation appeared as the first factor in Muan and Tando bays, and the change of water temperature was the first factor in Shinan Jido and Yeongkwang coastal areas. The influence mixed with the variation of freshwater outflow and the change of water temperature in Hampyeong bay was to be the first factor.