• Current Optics and Photonics
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• v.8 no.2
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• pp.192-200
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• 2024

Wheat stripe rust, caused by Puccinia striiformis, has reduced winter wheat yield globally for ages. In this work, multi-spectral Mueller matrix imaging with 37 measurements using the method of double rotatable quarter-wave plates was used to investigate wheat stripe rust. Individual Mueller matrix measurements were performed on incident monochromatic light with nine bands in the range of 430 to 690 nm. As a result, it was found that the infected area absorbed linearly polarized light and was sensitive to circularly polarized light in the spectral domain. Both linear depolarization and linear diattenuation images distinguished between wheat stripe rust and healthy tissue. The responsiveness of stripe rust to polarized light reveals the potential of using polarization imaging to detect plant diseases. This further suggests that the multi-spectral Mueller matrix imaging system provides us with an alternative approach to agricultural disease detection.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.36 no.2
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• pp.70-79
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• 2024

In this study, we introduce a linear spectral method capable of simulating wave generation and transformation caused by a moving bottom in a 3-dimensional space. The governing equations are linear dynamic free-surface boundary conditions and linear kinematic free-surface boundary conditions, which are solved in Fourier space. Solved velocity potential and free-surface displacement should satisfy continuity equation and kinematic bottom boundary condition. For numerical analysis, a 4th order Runge-Kutta method was utilized to analyze the time integral. The results obtained in Fourier space can be converted into velocity potential and free-surface displacement in a real space using inverse Fourier transform. Regular waves generated by various types of moving bottoms were simulated with the linear spectral method. Additionally, obliquely generated regular waves using specified bottom movements were simulated. The results obtained from the spectral method were compared to analytical solutions, showing good agreement between the two.

• The Korean Journal of Applied Statistics
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• v.24 no.2
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• pp.217-225
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• 2011

In this paper, a seasonal variable selection method using the spectral analysis accompanied with seasonal linear model is suggested. The suggested method is applied to the prediction of intra-day call arrivals at a large North American commercial bank call center and a signi cant intra-month seasonal variable I detected. This newly detected seasonal factor is included in the seasonal linear model and is compared with the seasonal linear models without this variable to see whether the new variable helps to improve the forecasting performance. The seasonal linear model with the new variable outperformed the models without it in one-day-ahead forecasting.

• 한국공간정보시스템학회:학술대회논문집
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• 2005.11a
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• pp.35-39
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• 2005

선형혼합분광분석(LSU, Linear Spectral Unmixing) 모델은 위성 영상의 한 화소 값이 공간 내에 포함된 다양한 지표 대상물의 반사에너지가 혼합된 결과로 나타난다는 가정을 통해 화소이하(Sub-Pixel) 단위의 영상 분석을 수행하는 알고리즘의 한 형태이다. 분석의 결과는 한 화소에 존재하는 순수 대상물(Endmember)의 비율로 나타나며, 최소제곱법을 이용하여 결과를 도출하는 것이 일반적인 방법으로 알려져 있다. 하지만, 최소제곱법을 이용한 선형혼합분광분석모델은 기본적인 가정을 만족시키지 못하며, Endmember를 사용자가 임의로 지정해야 하기 때문에 영상 분석에 많은 어려움이 있다. 이런 단점을 극복하기 위해 무감독으로 추출된 Endmember를 이용한 제약선형분광혼합분석(Constrained Linear Spectral Unmixing) 모델을 본 연구를 통해 제안하고자 한다. 결과를 통해, 무감독 제약선형분광혼합분석 모델은 선형분광혼합분석 모델에 비해 각각의 Endmember에 대하여 제약조건을 만족하는 점유비율(Abundance) 정보를 제공하였으나, 비슷한 Endmember를 중복 추출할 수 있는 가능성도 지니고 있음을 확인할 수 있었다.

• ETRI Journal
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• v.31 no.4
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• pp.454-456
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• 2009

The maximum likelihood linear spectral transformation (ML-LST) using a numerical iteration method has been previously proposed for robust speech recognition. The numerical iteration method is not appropriate for real-time applications due to its computational complexity. In order to reduce the computational cost, the objective function of the ML-LST is approximated and a closed-form solution is proposed in this paper. It is shown experimentally that the proposed closed-form solution for the ML-LST can provide rapid speaker and environment adaptation for robust speech recognition.

• Journal of the Korean Society for Railway
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• v.9 no.1 s.32
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• pp.63-68
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• 2006

This paper proposes a fast Fourier transform(FFT)-based spectral analysis method(SAM) for the dynamic responses of the linear discrete dynamic models with non-proportional damping. The SAM was developed by using discrete Fourier transform(DFT)-theory. To verify the proposed SAM, a three-DOF system with non-proportional viscous damping is considered as an illustrative example. The present SAM is evaluated by comparing the dynamic responses obtained by SAM with those obtained by Runge-Kutta method.

• Korean Journal of Remote Sensing
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• v.23 no.6
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• pp.537-546
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• 2007

In hyperspectral remote sensing, linear spectral mixture model is a common procedure decomposing into the components of a mixed pixel and estimating the fraction of each end-member. Although linear spectral mixture model is frequently used in geology and mineral mapping because this model is simple and easy to apply, this model is not always valid in forest and urban area having rather complex structure. This study aims to analyze possible error for applying linear spectral mixture model. For the study, we measured laboratory spectra of mixture sample, having various materials, fractions, distributions. The accuracy of linear mixture model is low with the mixture sample having similar fraction because the multi-scattering between components is maximum. Additionally, this multi-scattering is related to the types, fraction, and distribution of components. Further analysis is necessary to quantify errors from linear spectral mixture model.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.717-721
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• 2008

This paper proposes an image system that can efficiently measure the spectral reflectance of a scene using RGB cameras and LED light sources. Multispectral imaging system is composed of LED controllers, LED clusters and RGB cameras. It captures full-spectral images at real-time. The system adopts a simple, empirical linear model to estimate the full spectral reflectance at each pixel. Since the model is linear, the reconstruction is efficient and stable. We estimated the spectral reflectance of various scenes using the system and showed the effectiveness of the proposed system.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.249-252
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• 2005

Microphytobenthos bloom from late January to early March in Korean tidal flats. KOMPSAT-2 will provide multi-spectral images with a spatial resolution of 4 m comparable with IKONOS. Using IKONOS and Landsat data, algal mat detection was tested in the Saemangeum area~ Micro-benthic diatoms are abundant and a major primary product in the tidal flats. A linear spectral unmixing (LSU) method was applied to the test data. LSU was effective to detect algal mat and the classified algal mat fraction well correlated with NDVI image. Fine grained upper tidal flats are generally known to be the best environment for algal mat. Algal mat thriving in coarse grained lower tidal flats as well as upper tidal flats were reported in this study. A high resolution multi-spectral sensor in KOMPSAT-2 will provide useful data for long-term monitoring of microphytobenthos in tidal flats.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.4 s.235
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• pp.578-583
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• 2005

This paper introduces a fast Fourier transform (FFT)-based spectral dynamic analysis method for the transient responses as well as the steady-state responses of the linear discrete systems subject to non-zero initial conditions. The forced vibration of a viscously damped three-DOF system is considered as the illustrative numerical example. The proposed spectral analysis method is evaluated by comparing its results with the exact analytical solutions and the numerical solutions obtained by the Runge-Kutta method.