• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.370-375
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• 1998

Spectral reflectance signatures of upland crops at OSMI bands were collected and evaluated for the feasibility of crop discrimination knowledge-based on crop calendar. Effective bands and their ratio values for discriminating corn from two other legumes were defined with OSMI equivalent bands and their ratio values. June 22 among measurements dates was the best date for corn discrimination from two other legumes, peanut and soybean, because all OSMI equivalent bands and their ratio values in June 22 were highly significant for corn separability. Phenological growth stage of a silage corn (rs510) could be estimated as a function of spectral reflectance signatures in vegetative stage. Five growth stage prediction models were generated by the SAS procedures REG and STEPWISE with OSMI equivalent bands and their ratio values in vegetative stage.

• Communications for Statistical Applications and Methods
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• v.17 no.2
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• pp.223-229
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• 2010

We consider the asymptotic results of the variance ratio statistic when the underlying processes have moving average(MA) unit roots. This degenerate situation of zero spectral density near the origin cause the limit of the variance ratio to become zero. Its asymptotic behaviors are different from non-degenerating case, where the convergence rate of the variance ratio statistic is formally derived.

• Wind and Structures
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• v.16 no.6
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• pp.603-616
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• 2013

This study is aimed at formulating an empirical equation for the across-wind fluctuating moment and spectral density coefficient, which are needed to estimate the across-wind dynamic responses of tall buildings, as a function of the side ratios of buildings. In order to estimate an empirical formula, wind tunnel tests were conducted on aero-elastic models of the rectangular prisms with various aspect and side ratios in turbulent boundary layer flows. In this paper, criteria for the across-wind fluctuating moment and spectral density are briefly discussed and the results are analyzed mainly as a function of the side ratios of the buildings. Finally, empirical formulas for the across-wind fluctuating moment coefficient and spectral density coefficient according to variation of the aspect ratio are proposed.

• 전자공학회논문지 IE
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• v.49 no.2
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• pp.9-17
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• 2012

One of the problems on the application of the speech recognition system in the real world is the degradation of the performance by acoustical distortions. The most important source of acoustical distortion is the additive noise. This paper describes a spectral compensation technique based on a spectral peak enhancement scheme followed by an efficient noise subtraction scheme for noise robust speech recognition. The proposed methods emphasize the formant structure and compensate the spectral tilt of the speech spectrum while maintaining broad-bandwidth spectral components. The recognition experiments was conducted using noisy speech corrupted by white Gaussian noise, car noise, babble noise or subway noise. The new technique reduced the average error rate slightly under high SNR(Signal to Noise Ratio) environment, and significantly reduced the average error rate by 1/2 under low SNR(10 dB) environment when compared with the case of without spectral compensations.

• Journal of Information Processing Systems
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• v.15 no.4
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• pp.748-764
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• 2019

In order to deal with the filtering delay problem of least mean square adaptive filter noise reduction algorithm and music noise problem of spectral subtraction algorithm during the speech signal processing, we combine these two algorithms and propose one novel noise reduction method, showing a strong performance on par or even better than state of the art methods. We first use the least mean square algorithm to reduce the average intensity of noise, and then add spectral subtraction algorithm to reduce remaining noise again. Experiments prove that using the spectral subtraction again after the least mean square adaptive filter algorithm overcomes shortcomings which come from the former two algorithms. Also the novel method increases the signal-to-noise ratio of original speech data and improves the final noise reduction performance.

• Journal of the Korean Society of Radiology
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• v.14 no.5
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• pp.669-676
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• 2020

The purpose of this study was to analyze the changes in the values of Hounsfield Unit (HU) according to the changes in monoenergy (keV) and dilution ratio of the contrast agent, using the spectral CT. Spectral CT was used as the testing device, while 20 cc syringe phantom was used to set a total of six dilution ratios of the contrast agent: 8:2, 7:3, 6:4, 5:5, 4:6, and 3:7. Here, the non-ionic iodine solution (350 mg/ml) was used as a contrast agent. The syringe axial image was reconstructed by adjusting the obtained data on nine MonoE levels; 40 keV, 45 keV, 50 keV, 55 keV, 60 keV, 65 keV, 70 keV, 75 keV, and 80 keV. The HU values were measured at the three points of the reconstructed syringe axial image. The measurements were taken 1,620 times in total. In the analysis of the HU values according to the changes in keV and dilution ratio of the contrast agent, the highest and lowest HU values were obtained from dilution ratio 8:2 and dilution ratio 3:7, respectively, across every MonoE in the comparison of HU according to dilution ratio per MonoE (p<0.05), while the highest and lowest HU values were obtained from 40 keV and 80 keV, respectively, across all dilution ratios in the comparison of HU according to MonoE per dilution ratio (p<0.05). For the correlation per each parameter, a negative correlation of -15.014 ± 0.298 was found for HU per keV (R²=0.519) and a negative correlation of -61.372 ± 3.608 was found for HU per dilution ratio (R²=0.152) (p<0.05). To conclude, an increase in keV or dilution ratio of the contrast agent was shown to decrease the HU, and the findings in this study are anticipated to serve as the basic data in the research of HU-related parameters in Spectral CT.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.4
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• pp.125-135
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• 2009

Owing to its fast computing capability for fusing images, the FIHS(Fast Intensity Hue Saturation) fusion is widely used for fusion purposes. However, the FIHS fusion also distorts color in the same way such as the IHS(Intensity Hue Saturation) fusion technique. In this paper, a FIHS fusion technique(FIHS-BR) which reduces color distortion by using the ratio of each spectral band and an adaptive FIHS fusion(FIHS-SABR) using spatial information and the ratio of each spectral band are proposed. The proposed FIHS-BR fusion reduces color distortion by adding different spatial detail improvement values for each spectral band. The spatial detail improvement values are derived from the ratio of spectral band. And the proposed FIHS-SABR fusion reduces more color distortion by readjusting the spatial detail improvement values for each spectral band according to the ratio of the spectral bands. The spatial detail improvement values are derived adaptively from the characteristics of spatial information of the local image. To evaluate the performance of the proposed FIHS-BR fusion and FIHS-SABR fusion, a computer simulation is performed for IKONOS remote sensing image. Results from the experiments show that the proposed methods have less color distortion for the forest regions which reveal severe color distortion in the traditional FIHS fusion. From the evaluation results of the characteristics of spectral information for fused image, we show that the proposed methods have best results.

• Korean Journal of Remote Sensing
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• v.36 no.1
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• pp.55-65
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• 2020

Image classification needs the spectral similarity comparison between spectral features of each pixel and the representative spectral features of each class. The spectral similarity is obtained by computing the spectral feature vector distance between the pixel and the class. Each spectral feature contributes differently in the image classification depending on the class separability of the spectral feature, which is computed using a suitable vector distance measure such as the Bhattacharyya distance. We propose a method to determine the weight value of each spectral feature in the computation of feature vector distance for the similarity measurement. The weight value is determined by the ratio between each feature separability value to the total separability values of all the spectral features. We created ten spectral features consisting of seven bands of Landsat-8 OLI image and three indices, NDVI, NDWI and NDBI. For three experimental test sites, we obtained the overall accuracies between 95.0% and 97.5% and the kappa coefficients between 90.43% and 94.47%.

• Economic and Environmental Geology
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• v.36 no.3
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• pp.201-212
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• 2003

Recently, the ability of earthquake detection in the Kyungsang Basin of southeastern Korean Peninsula is greatly improved since seismic stations including seismic network of KIGAM(Korea Institute of Geoscience and Mineral Resources) have been significantly increased. However, a large number of signals from explosions are recorded because of frequent medium to large chemical explosions. The discrimination between natural earthquakes and explosions in the Basin has become an important issue. High frequency local records from 43 earthquakes and 43 explosions with comparable magnitude are selected to establish a reliable discrimination technique in the Basin. Several discrimination techniques in spectral domain using spectral amplitude ratios among Pg, Sg, and Lg waves are widely examined with tile selected data. Among them the Pg/Lg spectral ratio method is appeared to be a good discrimination technique to improve the discrimination power. Multivariate discriminant analysis is also applied to the Pg/Lg spectral ratios. The discrimination power of the Pg/Lg ratios for distance corrected three component record compared to uncorrected vertical component one shows distinct improvement. In the frequency band 4 to 14 Hz, Pg/Lg spectral ratio for distance corrected three component record provides discrimination power with a total misclassification probability of only 0.89%.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.322-324
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• 2003

Leaf C:N ratio is a new factor in the field of biochemical inversion with hyperspectral data. Effects of common-used spectral transformations including log(R), log(1/R), 1/R, etc. from 400nm to 2490nm on its inversion are compared. Results show that their effects on statistical modeling are not apparent. Continuum removal is used on original reflectance in the range of 2030nm to 2220nm, in which exists an apparent absorption peak due to cellulose, lignin, protein, etc. The effect is distinctive and tends to improve the precision of C:N ratio inversion. Further, it is a robust and physically based transformation.