• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.525-528
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• 2004

최근 인터넷 및 무선 통신기술의 광범위한 보급으로 인해 현장 계측 데이터 등과 같은 중요 데이터를 인터넷을 통해 실시간으로 수신 가능케 하는 다양한 형태의 웹 기반 원격 모니터링 시스템이 설계되고 있다. 이러한 웹 모니터링 시스템은 기본적으로 짧은 주기마다 측정된 데이터를 원격의 서버로 전송하는 것이 바람직하나 과도한 통신비 문제로 인해 효율적인 시스템 운영이 어렵다는 문제점을 갖는다. 따라서 본 연구에서는 측정데이터의 변화를 효율적으로 검출할 수 있는 PCA(Principle Component Analysis) 기법과 데이터 압축에 탁월한 특성을 갖는 wavelet 기법을 융합한 새로운 형태의 웹 기반 원격모니터링용 데이터 전송기법을 제안하고 실제 데이터에 적용하여 봄으로써 제안된 기법의 유용성을 확인하고자 한다.

• Journal of Korean Society for Quality Management
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• v.13 no.1
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• pp.26-30
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• 1985

In the light of the properties of colloids, in the surface of disperse phase and dispersion, there exist specific characters such as adsorption or electric double layer, which seems to play important roles in determining the physiochemical properties in the dyeing system. Nylon, wool and silk, the typical amphoteric fibers were dyed with Acid dye and various combinations were prepared by combining pH, temperature and dye concentration, in order to generate flowing electric potential which were measured by microviolt meter and specific conductivity meter. The results were transformed to Zeta potential by Helmholtz-Smoluchowski formular and to surface electric charge density by Suzawa formular, surface dye amount, and effective surface area of fibers, and these data were statistically analysed by principle component analysis.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.05a
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• pp.285-288
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• 2003

기존의 침입탐지 시스템은 오용탐지모델이 널리 사용되고 있다. 이 모델은 낮은 오판율(False Alarm rates)을 가지고 있으나 새로운 공격에 대해 전문가시스템(Expert Systems)에 의한 규칙추가를 필요로 하고, 그 규칙과 완전히 매칭되는 시그너처만 공격으로 탐지하므로 변형된 공격을 탐지하지 못한다는 문제점을 가지고 있다. 본 논문에서는 이러한 문제점을 보완하기 위해 주성분분석(Principle Component Analysis ; 이하 PCA)과 시간지연신경망(Time Delay Neural Network ; 이하 TDNN)을 이용한 침입탐지 시스템을 제안한다. 패킷은 PCA를 이용하여 주성분을 결정하고 패킷이미지패턴으로 만든다. 이 연속된 패킷이미지패턴을 시간지연신경망의 학습패턴으로 사용한다.

• Proceedings of the Korea Multimedia Society Conference
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• 2003.05b
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• pp.314-317
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• 2003

기존의 침입탐지 시스템에서는 오용탐지모델이 널리 사용되고 있다. 이 모델은 낮은 오판율(False Alarm rates)을 가지고 있으나, 새로운 공격에 대해 전문가시스템(Expert Systems)에 의한 규칙추가를 필요로 한다. 그리고 그 규칙과 완전히 일치되는 시그너처만 공격으로 탐지하므로 변형된 공격을 탐지하지 못한다는 문제점을 가지고 있다 본 논문에서는 이러한 문제점을 보완하기 위해 주성분분석(Principle Component Analysis; 이하 PCA)과 서포트 벡터 머신(Support Vector Machines; 이하 SVM)을 이용한 침입탐지 시스템을 제안한다. 네트워크 상의 패킷은 PCA를 이용하여 결정된 주성분 공간에서 해석되고, 정상적인 흐름과 비정상적인 흐름에 대한 패킷이미지패턴으로 정규화 된다. 이러한 두 가지 클래스에 대한 SVM 분류기를 구현한다. 개발하는 침입탐지 시스템은 알려진 다양한 침입유형뿐만 아니라, 새로운 변종에 대해서도 분류기의 유연한 반응을 통하여 효과적으로 탐지할 수 있다.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.499-503
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• 2008

In this paper, a novel human activity recognition method is proposed which utilizes independent components of activity shape information from image sequences and Hidden Markov Model (HMM) for recognition. Activities are represented by feature vectors from Independent Component Analysis (ICA) on video images, and based on these features; recognition is achieved by trained HMMs of activities. Our recognition performance has been compared to the conventional method where Principle Component Analysis (PCA) is typically used to derive activity shape features. Our results show that superior recognition is achieved with our proposed method especially for activities (e.g., skipping) that cannot be easily recognized by the conventional method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.11a
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• pp.305-309
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• 2006

In this paper, a face recognition algorithm system using Principle Component Analysis is proposed. The algorithm recognized a person by comparing characteristics (features) of the face to those of known individuals which is a face database of Intelligence Control Laboratory(ICONL). Experiments were simulated in order to demonstrate the performance of this algorithm due to face recognition which presented for the classification of face and non-face and the classification of known and unknown.

• Geosystem Engineering
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• v.21 no.5
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• pp.251-261
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• 2018

With the urbanization in recent years, the power line interference noise in electromagnetic signal is increasing day by day, and has gradually become an unavoidable component of noises in magnetotelluric signal detection. Therefore, a kind of power line interference noise elimination method based on independent component analysis in wavelet domain for magnetotelluric signal is put forward in this paper. The method first uses wavelet decomposition to change single-channel signal into multi-channel signal, and then takes advantage of blind source separation principle of independent component analysis to eliminate power line interference noise. There is no need to choose the layer number of wavelet decomposition and the wavelet base of wavelet decomposition according to the observed signal. On the treatment effect, it is better than the previous power line interference removal method based on independent component analysis. Through the de-noising processing to actual magnetotelluric measuring data, it is shown that this method makes both the apparent resistivity curve near 50 Hz and the phase curve near 50 Hz become smoother and steadier than before processing, i.e., it effectively eliminates the power line interference noise.

• Proceedings of the KSRS Conference
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• v.1
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• pp.236-238
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• 2006

An algorithm for detection of yellow sand aerosols has been developed with infrared bands from Moderate Resolution Imaging Spectroradiometer (MODIS) and Multi-functional Transport Satellite-1 Replacement (MTSAT-1R) data. The algorithm is the hybrid algorithm that has used two methods combined together. The first method used the differential absorption in brightness temperature difference between $11{\mu}m$ and $12{\mu}m$ (BTD1). The radiation at 11 ${\mu}m$ is absorbed more than at 12 ${\mu}m$ when yellow sand is loaded in the atmosphere, whereas it will be the other way around when cloud is present. The second method uses the brightness temperature difference between $3.7{\mu}m$ and $11{\mu}m$ (BTD2). The technique would be most sensitive to dust loading during the day when the BTD2 is enhanced by reflection of $3.7{\mu}m$ solar radiation. We have applied the three methods to MTSAT-1R for derivation of the yellow sand dust and in conjunction with the Principle Component Analysis (PCA), a form of eigenvector statistical analysis. As produced Principle Component Image (PCI) through the PCA is the correlation between BTD1 and BTD2, errors of about 10% that have a low correlation are eliminated for aerosol detection. For the region of aerosol detection, aerosol index (AI) is produced to the scale of BTD1 and BTD2 values over land and ocean respectively. AI shows better results for yellow sand detection in comparison with the results from individual method. The comparison between AI and OMI aerosol index (AI) shows remarkable good correlations during daytime and relatively good correlations over the land.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.35 no.3
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• pp.243-249
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• 1999

Specificity of catches has been analyzed to japanese tuna purse seine A principle component analysis was used to improve the efficiency of fishing and increase sustainable production and productivity of Korean tuna purse seine.The result are as follows;From the principal component analysis of the fish catches, the first principal component(Z1) to promote principal component score was skipjack Kastsuwonus Pelamis, LINNAEUS and yellowfin tuna Thunnus Albacares, BONNATERRE (Small : smaller than 10kg) and proportion was 86.8% of total. The second principal component(Z2) to increase principal component score was yellowfin tuna (Large : larger than 10kg) and proportion was 9.5%.On the other hand, fish operating that have caught skipjack and yellowfin tuna (Small and Larger) was not so much. Fish catches for one species raised volume of the catches while catches for multi-species decreased it since principal composition score for one species and both species together has been increased.Fish school could be divided into three groups of schools each of which was associated with drift objects, payaho and ship, school associated with shark, whale and porpoise and school of breezing, feeding and jumping from proportion of principal component analysis for fish catches of school types. However, the biological pattern is different among school associated with ship, payaho and school associated with drift objects for analysis eigen vector. School associated with ship, payaho and school associated with drifting object associated is judged as school which be assembled to vessel and drifted log temporary.

• Journal of Korean Society on Water Environment
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• v.30 no.2
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• pp.119-127
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• 2014

The objective of this study is to evaluate and analyze Sumjin River Basin water environment system. It was necessary to improve the water quality. The data were collected from 2010 January to 2012 December including Water Temperature, pH, DO, EC, $BOD_5$, COD, TOC, SS, T-N, T-P. The data were used to study were required to; Correlation Analysis; Principle Component Analysis; Factor Analysis. The results were as followed. According to correlation analysis on $BOD_5$ against COD, TOC it revealed that the each value of correlation coefficient were 0.715 and 0.719; this means the strength of the relationship is strong. The same analysis on T-P against $BOD_5$, COD, TOC, SS has revealed that the range of the correlation coefficient value fell between 0.482 and 0.608 which means strength of the relationship between them remained normal. Through correlation analysis, it has been found that all elements except T-N have high correlation. The results of principal component analysis to target the overall water quality was extracted to three main components. The cumulative contribution rate is 68.990%. In the case of seasonal water quality, Spring and Summer are extracted to each of four main components. The cumulative contribution rate is 81.515% and 73.550% respectively. Fall and Winter are extracted to each of three main components. The cumulative contribution rate is 65.072% and 72.721% respectively. There is no seasonality in the case of factor analysis. The first common factor is $BOD_5$, COD, TOC, SS, T-P, which were classified. Totally speaking, Sumjin River Basin water system gets highly affected by the nutrient salts, organic matter and suspended solid at the same time.