• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.448-451
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• 2002

This study will offer multi-feature recognition instead of an using mono-feature to improve the accuracy of recognition. Each Feature can be found by following ways. For a face, the feature is calculated by the principal component analysis with wavelet multiresolution. For a lip, a filter is used to find out on equation to calculate the edges of the lips first. Then the other feature is calculated by the distance ratio of facial parameters. We've sorted backpropagation neural network and experimented with the inputs used above and then based on the experimental results we discuss the advantage and efficiency.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.9
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• pp.4342-4348
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• 2013

The present study was intended to reveal the relationships between serum lipid levels and various factors of obesity and blood pressure. The study subjects were 1,838 adult women measured at a mass health screening during the period from January through December, 2011. TC, TG, HDL-C, LDL-C, SBP, DBP, degree of obesity, body fat rate were measured and the relation between these obesity and blood pressure measurements to serum lipid levels were studied. As a results, TC, TG, LDL-C, body fat rate and degree of obesity increased linearly with advancing age. TC, TG and LDL-C increased linearly with increasing blood pressure, and these values were higher in hypertension group than that of normal group. TC, TG and SBP increased linearly with increasing degree of obesity, and these values were higher in obesity group than that of normal group. HDL-C decreased linearly with increasing degree of obesity, and these values were lower in obesity group than that of normal group. TC, TG, HDL-C, degree of obesity, body fat rate was positive correlation with each others, but these values negatively correlated to HDL-C. Principal component analysis, showed that subjects could be divided into the group having the hypertensive group(1st principal component), the obesity group(2nd principal component), the hyperlipidemia group(3rd principal component), and HDL-C(4th principal component). In multiple regression analysis, age, TC, TG and body fat rate were affected to HDL-C. Above results suggest that higher the degree of obesity and blood pressure, the higher the serum lipid levels.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.17-17
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• 2023

국내의 부지특성 및 감시 관련 규정은 원자력 안전위원회 고시 제2021-16호 제4조(세부지침)와 원자력 안전위원회 고시 제2021-17호 제16조에 의거하고, 국외는 국제원자력기구(IAEA: International Atomic Energy Agency)에서 안전기준을 제시하고 있다(IAEA, 2011). 따라서 국내 중·저준위 방사성폐기물 처분시설은 2006년부터 광역 지질을 포함한 부지 지질/지형, 기상, 수문, 수리지질, 인문사회 등을 망라한 조사를 시행하여 부지 현황에 대한 분석 및 안정성 평가를 수행한다. 부지감시의 수문·지구화학 분야에서는 현장 수질 측정 6항목과 실내 분석 26항목을 감시하고 있으나, 본 연구는 이 중 9개 항목(EC, Na, K, Ca, Mg, SiO₂, Cl, SO₄, HCO₃)을 선정하여 분석하였다. 연구 목적은 물시료 분석자료의 주성분-다중선형회귀-군집 분석과 Piper Diagram 분석결과로부터 해수와 담수(지하수)와의 특성분석 및 해수 영향을 분석하는 것이다. 현장 부지내 지하수 7개 관정(GM-1, 2, 4, 5, 6, 7, 8)과 해수 2개 지점(Sea-1, 2)을 대상으로 통계학적 주성분 분석결과, 대부분의 지하수는2개~4개의 요인으로 구분되고, 해수와의 유사성을 해석하기 위해 확인한 관정은 GM-5, GM-6, GM-1 지점으로 분류되었다. 상기와 같이 해수의 영향을 확인하기 위해 해수 2개 지점과 동일한 군집으로 분류되는 지하수는 GM-5 관정으로 확인되었고, 해안선에서 가까운 GM-5 관정과 같이 유사한 거리에 분포한 지하수 GM-1, 2, 4 관정은 2개 혹은 3개의 최적 군집으로 분류하였을 때도 GM-5와는 다른 특성을 보여주었다. 이는 해안과 인접하더라도 수질은 다른 지질학적 특성(지형, 기상, 단열대 등)에 따라 영향받았음을 지시한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37B no.9
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• pp.837-848
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• 2012

This study has conducted the economic effects of R&D investment in the IT industry using multi-regression analysis with three independent variables; capital stock, labor input and R&D stock. In this study, the IT industry has been categorized into three sub-industries; broadcasting communication appliances, information appliances and electronic components industry. Our analysis has found that auto-correlation shows considerable levels whereas figures of t-value and R-square show significant levels among all the IT sub-industries. Meanwhile, the values of R&D stock in the information appliances industry and that of labor input coefficients in the electronic components industry were minus, thus multi-collinearity was suspected. We have solved the problems regarding auto-correlation and multi-collinearity through Cochrane-Orcutt estimation and principal components analysis. This paper has derived the implications that R&D investment in the broadcasting communication industry is much more influential than any other IT sub-industry.

• Proceedings of the KSRS Conference
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• 2006.03a
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• pp.279-282
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• 2006

분광혼합은 위성영상에서 공간해상도의 한계로 인해 다른 분광 속성을 가진 물질들이 하나의 픽셀 내에 존재하게 될 때 발생하게 된다. 이러한 문제를 해결하고자 분광분리 알고리즘을 통해 픽셀의 순수한 영역만을 선정하여 정확도 높은 탐지가 가능하도록 하는 분광혼합분석(Spectral Mixture Analysis, 이하 SMA)을 고해상도 영상에 적용하였다. 본 연구는 산림의 훼손이 심각한 강원도 정선군 임계지역의 QuickBird 다중분광 위성영상을 이용하였다. 주성분분석(Principal Component Analysis, 이하 PCA)으로 생성된 결과 영상의 1, 2, 3번 밴드를 추출한 후에 밴드간의 Scatter plots 내에서 끝지점에 위치하는 Endmember를 3개(나지, 산림, 초지) 선정하였다. 선정된 Endmember를 토대로 작성된 fraction 영상을 이용하여 강원도 임계지역의 산림훼손으로 초지와 나지로 변화된 지역을 탐지하여 보았다.

• Journal of the Korea Convergence Society
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• v.10 no.12
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• pp.271-280
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• 2019

Smart factory, a critical part of digital transformation, enables data-driven decision making using monitoring, analysis and prediction. Predictive maintenance is a key element of smart factory and the need is increasing. The purpose of this study is to analyze the degradation characteristics of a galvanizing kettle for the steel plating process and to predict the remaining useful life(RUL) for predictive maintenance. Correlation analysis, multiple regression, principal component regression were used for analyzing factors of the process. To identify the trend of degradation, a proposed rolling window was used. It was observed the degradation trend was dependent on environmental temperature as well as production factors. It is expected that the proposed method in this study will be an example to identify the trend of degradation of the facility and enable more consistent predictive maintenance.

• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.123-130
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• 2022

Recently, studies on the detection and classification of Android malware based on API Call sequence have been actively carried out. However, API Call sequence based malware classification has serious limitations such as excessive time and resource consumption in terms of malware analysis and learning model construction due to the vast amount of data and high-dimensional characteristic of features. In this study, we analyzed various classification models such as LightGBM, Random Forest, and k-Nearest Neighbors after significantly reducing the dimension of features using PCA(Principal Component Analysis) for CICAndMal2020 dataset containing vast API Call information. The experimental result shows that PCA significantly reduces the dimension of features while maintaining the characteristics of the original data and achieves efficient malware classification performance. Both binary classification and multi-class classification achieve higher levels of accuracy than previous studies, even if the data characteristics were reduced to less than 1% of the total size.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.1
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• pp.25-31
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• 2003

There are a lot of factors influencing on the automobile fuel economy such as average speed, average acceleration, acceleration sum per kilometer, and so on. In this study, various driving data were recorded during road tests. The accumulated road test mileage in Seoul metropolitan area is around 1,300 kilometers. The data were analyzed by multivariate statistical techniques including correlation analysis, principal component analysis, and multiple linear regression analysis. The analyzed results show that the average trip time per kilometer is one of the most important factors to fuel consumption and the increase of the average speed is desirable for reducing emissions and fuel consumption.

• Journal of Plant Biology
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• v.35 no.1
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• pp.61-67
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• 1992

Principal component analysis of the morphological characters was applied to ordinate and examine morphological variation of Enteromorpha linza due to differences in environmental factors. As results, the samples from exposed populations to wave action were characterized by having longer stipe and maximum length, and narrower maximum width than samples from sheltered populations. The results of multiple comparision in each character among populations provided further support for the hypothesized existence of exposed, moderate, and sheltered morphotypes.otypes.

• Journal of Broadcast Engineering
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• v.20 no.4
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• pp.521-532
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• 2015

This paper presents a piecewise image denoising with multi-scale block region detector based on quadtree structure for effective image restoration. Proposed piecewise image denoising method suggests multi-scale block region detector (MBRD) by dividing whole pixels of a noisy image into three parts, with regional characteristics: strong variation region, weak variation region, and flat region. These regions are classified according to total pixels variation between multi-scale blocks and are applied principal component analysis with local pixel grouping, bilateral filtering, and structure-preserving image decomposition operator called relative total variation. The performance of proposed method is evaluated by Experimental results. we can observe that region detection results generated by the detector seems to be well classified along the characteristics of regions. In addition, the piecewise image denoising provides the positive gain with regard to PSNR performance. In the visual evaluation, details and edges are preserved efficiently over the each region; therefore, the proposed method effectively reduces the noise and it proves that it improves the performance of denoising by the restoration process according to the region characteristics.