• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.4
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• pp.1-13
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• 2007

We make image that accumulate two principal component after change picture to use GLCM(Gray Level Co-Occurrence Matrix)'s texture feature information. And then these images use preprocess to achieved corner detection and area detection. Experiment results, two principle component conversion accumulation images had most informations about six kind textures by Eigen value 94.6%. When compared with red tide area that uses sea color and red tide area of image that have all principle component, displayed the most superior result. Also, we creates Euclidian space using Euclidian distance measurement about red tide area and clear sea. We identify of red tide area by red tide area and clear sea about random sea area through Euclidian distance and spatial distribution.

• 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.

• Smart Structures and Systems
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• v.12 no.3_4
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• pp.327-344
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• 2013

Beam string structure (BSS) is introduced as a new type of hybrid prestressed string structures. The composition and mechanics features of BSS are discussed. The main principles of wavelet packet transform (WPT), principal component analysis (PCA) and support vector machine (SVM) have been reviewed. WPT is applied to the structural response signals, and feature vectors are obtained by feature extraction and PCA. The feature vectors are used for training and classification as the inputs of the support vector machine. The method is used to a single one-way arched beam string structure for damage detection. The cable prestress loss and web members damage experiment for a beam string structure is carried through. Different prestressing forces are applied on the cable to simulate cable prestress loss, the prestressing forces are calculated by the frequencies which are solved by Fourier transform or wavelet transform under impulse excitation. Test results verify this method is accurate and convenient. The damage cases of web members on the beam are tested to validate the efficiency of the method presented in this study. Wavelet packet decomposition is applied to the structural response signals under ambient vibration, feature vectors are obtained by feature extraction method. The feature vectors are used for training and classification as the inputs of the support vector machine. The structural damage position and degree can be identified and classified, and the test result is highly accurate especially combined with principle component analysis.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.57 no.1
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• pp.83-88
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• 2012

In order to get information on tocopherol content and composition in fifty-six soybean germplasms were evaluated by HPLC. From the principle component analysis, the first three components accounted for 71.6% of the total variance of tocopherol content in the germplasms. Principal component 1 showed significant correlations with all the morphological markers except 100-seed weight. Soybean germplasms were divided into three groups by the first two principal components. The highest content of ${\alpha}$-tocopherol was $38.6{\mu}g$ per g in Tanner, while that of ${\gamma}$-tocopherol was $195.6{\mu}g$ in PI 91073. In case of ${\delta}$-tocopherol, IT 105622 showed the highest value as $29.8{\mu}g$. The contents of tocopherol were gradually increased from the late August to late September, which was 10 days before maturity, in Alchankong and PI 96322. The tocopherol content was higher in seeds from the plants sown early than those sown late. Total tocopherol contents of PI 96188, Geomjeongkong 2, and Suwon 183 grown in Gimje were higher than those grown in Iksan, but the difference was not observed in PI 96322. These results suggest that the contents of tocopherol in soybean were affected not only by the genotypes but also by environment.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2008.06a
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• pp.63-63
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• 2008

Environmental monitoring sub-system has been developed using gas sensor module, Bluetooth module and PDA phone. The gas sensor module consists of $NO_2or$ CO gas sensor and signal processing chips. Gas sensor is composed of the micro-heater, sensing electrode and sensing material. Metal oxide nano-material was selectively deposited on a substrate with micro-heater and was integrated to the gas sensor module. The change in resistance of the metal oxide nano-material due to exposure of oxidizing or deoxidizing gases is utilized as the principle of this gas sensor operation mechanism. This variation detected in the gas sensor module was transferred to the PDA phone by way of Bluetooth module.

• Journal of Physiology & Pathology in Korean Medicine
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• v.33 no.3
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• pp.163-168
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• 2019

In order to enhance the 8 principle pattern diagnosis rate comparing with diagnostic method by self-report questionnaire on cold/heat pattern in the clinical practice, a new diagnostic method using form-color-pulse-symptom (FCPS) system is proposed. FCPS system is composed of outputs of cold/heat pattern through the calculation process of contribution degree to the cold, heat pattern and qi, blood, yin, yang deficiency patterns, based on analysis of 16 mechanisms of disease calculated by diagnostic system of oriental medicine (DSOM) first. And second component is an output of differentiated 8 principle patterns in detail through binding and calculating process with digital informations of pulse, color, form, constitution obtained by computerized measurement system. Putting together above two processes consecutively, cold-heat complex or true/false cold/heat patterns and personalized characters of cold/heat patterns of each patient can be subdivided through a computation method of determining each pattern. In conclusion, 8 principle pattern identification can be performed more accurately using FCPS system than existent self report questionnaire method. These hypothetic proposal is needed to be proven by clinical trial for the future and then the accurate numbers used in each calculational function should be revised properly.

• Journal of Korea Game Society
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• v.11 no.1
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• pp.139-146
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• 2011

We propose a photomosaic method using PCA(Principal Component Analysis), which uses PCA results to find the most similar candidate fast and correctly. When two images are projected onto a certain principal component, if their coefficients are similar, they are also likely to be similar. Thus our photomosaic method using PCA can take care of both colors and shapes of images. Our method using coefficient comparison is faster than the one using all color comparison and more correct than the one using average comparison. Our hardware accelerated photomosaic algorithm can handle video images in real-time.

• Journal of the Korean Society for Nondestructive Testing
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• v.24 no.6
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• pp.590-596
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• 2004

Neural network-based signal classification systems are increasingly used in the analysis of large volumes of data obtained in NDE applications. Ultrasonic inspection methods on the other hand are commonly used in the nondestructive evaluation of welds to detect flaws. An important characteristic of ultrasonic inspection is the ability to identify the type of discontinuity that gives rise to a peculiar signal. Standard techniques rely on differences in individual A-scans to classify the signals. This paper proposes an ultrasonic signal classification technique based on the information tying in the neighboring signals. The approach is based on a 2-dimensional Fourier transform and the principal component analysis to generate a reduced dimensional feature vector for classification. Results of applying the technique to data obtained from the inspection of actual steel welds are presented.

• Communications for Statistical Applications and Methods
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• v.24 no.2
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• pp.143-154
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• 2017

A variable selection method based on probabilistic principal component analysis (PCA) using penalized likelihood method is proposed. The proposed method is a two-step variable reduction method. The first step is based on the probabilistic principal component idea to identify principle components. The penalty function is used to identify important variables in each component. We then build a model on the original data space instead of building on the rotated data space through latent variables (principal components) because the proposed method achieves the goal of dimension reduction through identifying important observed variables. Consequently, the proposed method is of more practical use. The proposed estimators perform as the oracle procedure and are root-n consistent with a proper choice of regularization parameters. The proposed method can be successfully applied to high-dimensional PCA problems with a relatively large portion of irrelevant variables included in the data set. It is straightforward to extend our likelihood method in handling problems with missing observations using EM algorithms. Further, it could be effectively applied in cases where some data vectors exhibit one or more missing values at random.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.5
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• pp.33-40
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• 2004

In this paper, we constructs face database by using wavelet comparison, and compare face recognition rate by using principle component analysis (Principal Component Analysis : PCA) algorithm. General face recognition method constructs database, and do face recognition by using normalized size. Proposed method changes image of normalized size (92${\times}$112) to 1 step, 2 step, 3 steps to wavelet compression and construct database. Input image did compression by wavelet and a face recognition experiment by PCA algorithm. As well as method that is proposed through an experiment reduces existing face image's information, the processing speed improved. Also, original image of proposed method showed recognition rate about 99.05%, 1 step 99.05%, 2 step 98.93%, 3 steps 98.54%, and showed that is possible to do face recognition constructing face database of large quantity.