• Structural Monitoring and Maintenance
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• 제9권2호
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• pp.179-200
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• 2022

This paper proposes a data-driven methodology for online early damage identification under changing environmental conditions. The proposed method relies on two data analysis methods: feature-based method and hybrid principal component analysis (PCA) and kernel PCA to separate damage from environmental influences. First, spectral sub-band features, namely, spectral sub-band centroids (SSCs) and log spectral sub-band energies (LSSEs), are proposed as damage-sensitive features to extract damage information from measured structural responses. Second, hybrid modeling by integrating PCA and kernel PCA is performed on the spectral sub-band feature matrix for data normalization to extract both linear and nonlinear features for nonlinear procedure monitoring. After feature normalization, suppressing environmental effects, the control charts (Hotelling T² and SPE statistics) is implemented to novelty detection and distinguish damage in structures. The hybrid PCA-KPCA technique is compared to KPCA by applying support vector machine (SVM) to evaluate the effectiveness of its performance in detecting damage. The proposed method is verified through numerical and full-scale studies (a Bridge Health Monitoring (BHM) Benchmark Problem and a cable-stayed bridge in China). The results demonstrate that the proposed method can detect the structural damage accurately and reduce false alarms by suppressing the effects and interference of environmental variations.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1994년도 추계학술대회
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• pp.169-171
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• 1994

This paper is to find out more reliable analyzing method of heart rate variability. Heart rate variability analysis is to evaluate cardiovascular stability and also have used as an indicator of autonomic nervous system activity. In this study, time domain analysis, spectral analysis and state space analysis method are applied to analyze heart rate variability. Because of nonlinear characteristics of heart rate, we need not only spectral analysis, but also state space analysis. Fractal dimension of spectral estimation is useful indicator of autonomic nervous activity.

• 한국소음진동공학회논문집
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• 제20권10호
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• pp.940-945
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• 2010

Noise reduction of vacuum cleaner is important, according as get into standard that estimate quality of product. To reduce noise of vacuum cleaner, we need analysis of correct noise source and contribution grasping about Identified noise sources' output noise. Because noise sources' correlation exists in vacuum cleaner that is small and complicated system, analysis is not easy. In this case, we need to apply Multi-dimensional spectral analysis(MDSA) method that can remove correlation between noise sources and grasp pure contribution degree of noise sources. In this study, we take transfer path analysis between output noise and noise that measured in inside/outside of vacuum cleaner.

• Journal of applied mathematics & informatics
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• 제22권1_2호
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• pp.209-222
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• 2006

Estimation of the spectral measure, covariance and spectral density functions of a strictly stationary r-vector valued time series is considered, under the assumption that some of the observations are missed. The modified periodograms are calculated using data window. The asymptotic normality is studied.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2010년 춘계학술발표회 논문집
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• pp.11-13
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• 2010

Combined with the indeterminate boundaries of spatial objects, n:m correspondences makes an object-based matching be a complex problem. In this study, we model the boundary of a polygon object with fuzzy model and describe their overlapping relations as a weighted bipartite graph. Then corresponding pairs including 1:0, 1:1, 1:n and n:m relations are identified using a spectral singular value decomposition.

• 대한약학회:학술대회논문집
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• 대한약학회 2002년도 Proceedings of the Convention of the Pharmaceutical Society of Korea Vol.2
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• pp.402.2-402.2
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• 2002

An algorithm for finding the best regression models has been developed using NIR spectral data. In cases of regression analysis for quantitation with NIR spectral data, it is very critical to find essential features from the spectral data. This task was accessed in two ways. The first one was to use all-possible combinations of varibles (wavelengths). Correlation coefficients at each spectral points were calculated to get initial set of variables and all of the possible combinations of variable sets were tested with SEC. SEP and/or $R^2$. (omitted)

• East Asian mathematical journal
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• 제37권3호
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• pp.295-305
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• 2021

In this paper, we analyze the efficiency of a domain decomposition method for the two-dimensional telegraph equations. We formulate the theoretical spectral radius of the iteration matrix generated by the domain decomposition method, because the rate of convergence of an iterative algorithm depends on the spectral radius of the iteration matrix. The theoretical spectral radius is confirmed by the experimental one using MATLAB. Speedup and operation ratio of the domain decomposition method are also compared as the two measurements of the efficiency of the method. Numerical results support the high efficiency of the domain decomposition method.

• 대한원격탐사학회지
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• 제33권4호
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• pp.411-422
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• 2017

This research aims to analyze spectral reflectance of intertidal zone and its changes under various environmental conditions. We sampled sand of Mongsanpo tidal flat, Korea, and measured its spectral reflectance by using a spectroradiometer under various water contents, compositions and granularity. We also simulated the reflectance of Landsat 7 ETM+ and compared it with an actual satellite data. Five locations were selected for sampling from the coastline towards the ocean. Grain size diminished stepwise from the coastline to ocean direction, while spectral reflectance differed with wavelength. Water contents lowered the overall reflectance especially at the water absorption bands. Spectral reflectance data were then converted into the simulated one by using Landsat 7 ETM+ spectral reflectance function to be compared with the actual Landsat 7 ETM+ images. It showed the decrease of the spectral reflectance due to the increase of moisture contents from seashore towards the ocean. It is shown that Landsat 7 ETM+ imagery can be efficient to extract moisture contents in the tidal flat while compositional analysis needs satellite sensors with much higher spectral resolution.

• 대한원격탐사학회지
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• 제28권1호
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• pp.39-54
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• 2012

본 연구의 목적은 KOMPSAT-2 위성영상에 가장 일반적으로 적용 가능한 영상융합기법을 제시하는 것이다. 가장 널리 사용되는 영상융합기법인 HPF, modified IHS, pan-sharpened, wavelet을 지역적, 계절적 특성이 서로 다른 4장의 KOMPSAT-2 위성영상에 적용하였고, 각각의 융합결과를 공간적, 분광적으로 비교분석하였다. 영상융합기법의 품질평가는 시각적 분석과 정량적 분석을 병행하여 수행하였으며, 정량적 분석에는 spatial ERGAS, spectral ERGAS, SAM, Q4가 사용되었다. 종합적인 분석결과를 고려할 때, pan-sharpened가 색상정보와 공간정보의 균형적인 보존 측면에서 다른 융합기법들에 비해, 상대적으로 우수한 결과를 나타냈다. modified-IHS의 경우, 공간정보는 잘 보존하였지만 다소 큰 색상 왜곡이 발생되었고, HPF와 wavelet은 색상 왜곡은 적었지만, 공간정보의 왜곡이 발생하였다.

• 대한원격탐사학회지
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• 제31권5호
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• pp.361-370
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• 2015

초분광영상을 이용한 변화탐지 기법으로는 Chronochrome(CC), Principal Component Analysis(PCA), 분광혼합분석(spectral unmixing) 등이 있다. 특히, 분광혼합분석을 이용한 변화탐지는 변화객체의 위치 정보뿐만 아니라 변화의 속성까지 분석할 수 있다는 점에서 매우 효과적이나, 분광혼합분석을 활용한 초분광영상의 변화탐지 연구는 여전히 초기단계에 머물러 있다. 본 연구에서는 분광혼합분석을 이용한 효과적인 변화탐지를 위하여 Iterative Error Analysis(IEA)와 Spectral Angle Mapper(SAM) 등을 활용하여 두 영상에서 변화지역을 설명할 수 있는 동일한 endmember를 결정하였으며, 점유비율의 차영상을 통하여 변화지역을 추출하였다. 제안기법의 적용성을 평가하기 위하여 임의의 변화지역을 포함한 Compact Airborne Spectrographic Imager(CASI) 및 Hyperion 모의영상에 대한 변화탐지를 수행하였다. 실험결과, 제안기법이 기존의 CC, PCA, N-FINDR를 이용한 분광혼합분석보다 효과적으로 변화지역을 추출할 수 있는 것으로 나타났다. 본 연구의 제안기법은 사전정보 없이 자동으로 동일한 endmember를 추출할 수 있는 장점을 갖기 때문에 다양한 피복물질로 구성된 영상의 변화탐지에 효과적으로 활용될 것이다.