• Journal of Forest and Environmental Science
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• v.40 no.1
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• pp.15-23
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• 2024

This research aimed to assess the possibility of detecting forest degradation using time-series satellite imagery and three different deep learning-based change detection techniques. The dataset used for the deep learning models was composed of two sets, one based on surface reflectance (SR) spectral information from satellite imagery, combined with Texture Information (GLCM; Gray-Level Co-occurrence Matrix) and terrain information. The deep learning models employed for land cover change detection included image differencing using the Unet semantic segmentation model, multi-encoder Unet model, and multi-encoder Unet++ model. The study found that there was no significant difference in accuracy between the deep learning models for forest degradation detection. Both training and validation accuracies were approx-imately 89% and 92%, respectively. Among the three deep learning models, the multi-encoder Unet model showed the most efficient analysis time and comparable accuracy. Moreover, models that incorporated both texture and gradient information in addition to spectral information were found to have a higher classification accuracy compared to models that used only spectral information. Overall, the accuracy of forest degradation extraction was outstanding, achieving 98%.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1666-1671
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• 2003

Exact dynamic stiffness model for a uniform straight pipeline conveying unsteady fluid is formulated from a set of fully coupled pipe-dynamic equations of motion, in which the fluid pressure and velocity of internal flow as well as the transverse and axial displacements of the pipeline are all treated as dependent variables. The accuracy of the dynamic stiffness model formulated herein is first verified by comparing its solutions with those obtained by the conventional finite element model. The spectral element analysis based on the present dynamic stiffness model is then conducted to investigate the effects of fluid parameters on the dynamics and stability of an example pipeline problem.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2003.04a
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• pp.3-10
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• 2003

The use of frequency-dependent dynamic stiffness matrix (or spectral element matrix) in structural dynamics may provide very accurate solutions, while it reduces the number of degrees-of-freedom to improve the computational efficiency and cost problems. Thus, this paper develops a spectral element model for the thin plates moving with constant speed under uniform in-plane tension and gravity. The concept of Kantorovich method and the principle of virtual displacement is used in the frequency-domain to formulate the dynamic stiffness matrix. The present spectral element model is evaluated by comparing its solutions with the exact analytical solutions. The effects of moving speed, in-plane tension and gravity on the natural frequencies of the plate are numerically investigated.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.60-65
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• 2003

In this study, for estimating responses of a controlled structure and determining the maximum control force of velocity-dependent damping devices, three estimation models such as Fourier envelope convex model, probability model, and Newmark design spectrum are used. For this purpose, a procedure proposed by Gupta (1990) for estimating spectral velocity using pseudo-spectral velocity which is given by the estimation models is used and modified to consider the effects of increased damping ratio by the damping device. Time history results indicate that Newmark design spectrum gives the best estimation of maximum control force for over all period structures.

• 한국지구물리탐사학회:학술대회논문집
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• 2007.06a
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• pp.81-86
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• 2007

Spectral features of the seismic wave propagation from Odaesan Earthquake were evaluated based on the commonly treated random error between the observed data and the prediction values by the stochastic point-source ground-motion spectral model regarding the source, path and site effects. Radiation pattern of the error according to azimuth angle was found to be similar to the theoretical estimate. It was also observed that the spatial distribution of the errors was correlated with the geological map and the Q0 map which are indicatives of seismic boundaries.

• Current Optics and Photonics
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• v.1 no.4
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• pp.271-277
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• 2017

Based on the extended Huygens-Fresnel principle, the analytical propagation formulae for spectrally partially coherent Gaussian Schell-model pulsed (SPGSMP) beams propagating in turbulent atmosphere have been derived. The influences of the parameters for turbulent atmosphere and SPGSMP beams on the on-axis and off-axis spectral shift and degree of coherence for SPGSMP beams propagating in turbulent atmosphere have been analyzed, using numerical calculations. The obtained results have potential applications for SPGSMP beams in free-space optical communication and laser lidar.

• Journal of Korean Society on Water Environment
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• v.30 no.3
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• pp.329-339
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• 2014

This study aims to estimate chlorophyll-a concentration in rivers using multi-spectral RapidEye imagery and Spectral Mixture Analysis (SMA) and assess the applicability of SMA for multi-temporal imagery analysis. Comparison between images (acquired on Oct. and Nov., 2013) predicted and ground reference chlorophyll-a concentration showed significant performance statistically with determination coefficients of 0.49 and 0.51, respectively. Two band (Red-RE) model for the October and November 2013 RapidEye images showed low performance with coefficient of determinations ($R^2$) of 0.26 and 0.16, respectively. Also Three band (Red-RE-NIR) model showed different performance with $R^2$ of 0.016 and 0.304, respectively. SMA derived Chlorophyll-a concentrations showed relatively higher accuracy than band ratio models based values. SMA was the most appropriate method to calculate Chlorophyll-a concentration using images which were acquired on period of low Chlorophyll-a concentrations. The results of SMA for multi-temporal imagery showed low performance because of the spatio-temporal variation of each end members. This approach provides the potential of providing a cost effective method of monitoring river water quality and management using multi-spectral imagery. In addition, the calculated Chlorophyll-a concentrations using multi-spectral RapidEye imagery can be applied to water quality modeling, enhancing the predicting accuracy.

• Speech Sciences
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• v.11 no.3
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• pp.131-142
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• 2004

Speaker identification system basically functions by comparing spectral energy of an individual production model with that of an input signal. This study aimed to develop a new speaker identification system from two parameters from the spectral energy of numeric sounds: difference sum and correlation coefficient. A narrow-band spectrogram yielded more stable spectral energy across time than a wide-band one. In this paper, we collected empirical data from four male speakers and tested the speaker identification system. The subjects produced 18 combinations of three-digit numeric. sounds !en times each. Five productions of each three-digit number were statistically averaged to make a model for each speaker. Then, the remaining five productions were tested on the system. Results showed that when the threshold for the absolute difference sum was set to 1200, all the speakers could not pass the system while everybody could pass if set to 2800. The minimum correlation coefficient to allow all to pass was 0.82 while the coefficient of 0.95 rejected all. Thus, both threshold levels can be adjusted to the need of speaker identification system, which is desirable for further study.

• Journal of The Korean Astronomical Society
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• v.38 no.4
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• pp.445-462
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• 2005

In a companion paper, we have presented so-called Spatio-Spectral Maximum Entropy Method (SSMEM) particularly designed for Fourier-Transform imaging over a wide spectral range. The SSMEM allows simultaneous acquisition of both spectral and spatial information and we consider it most suitable for imaging spectroscopy of solar microwave emission. In this paper, we run the SSMEM for a realistic model of solar microwave radiation and a model array resembling the Owens Valley Solar Array in order to identify and resolve possible issues in the application of the SSMEM to solar microwave imaging spectroscopy. We mainly concern ourselves with issues as to how the frequency dependent noise in the data and frequency-dependent variations of source size and background flux will affect the result of imaging spectroscopy under the SSMEM. We also test the capability of the SSMEM against other conventional techniques, CLEAN and MEM.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.24 no.4
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• pp.533-542
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• 2000

Analytical experiments to determine the line-of-sight temperature distribution is conducted by using spectral radiation intensities. For this study, fourteen narrow bands of $25cm^{-1}$ interval in $CO_2\;4.3{\mu}m$ band ($2,050cm^{-1}$ to $2375cm^{-1}$) are selected. The applied system is a one-dimensional gas slab filled with 100% $CO_2$ gas at 1 atm. Two types of temperature profile are tested; parabolic and boundary layer types. Three kinds of radiation calculation are used in the iteration procedure for the temperature inversion; LBL(Line by Line), SNB(Statistical Narrow Band) and WNB(WSGGM. based Narrow Band) models. The LBL solution shows perfect agreement while some error of temperature prediction is caused by radiation modeling error when using SNB and WNB models. The inversion result shows that the WNB model may be used more accurately in spectral remote sensing techniques than the traditional SNB model.