• Korean Journal of Remote Sensing
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• v.35 no.5_1
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• pp.649-663
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• 2019

The 2018 United Nations Development Programme (UNDP) report announced that deforestation in North Korea is the most extreme situation and in terms of climate change, this deforestation is a global scale issue. To respond deforestation, various study and projects are conducted based on remote sensing, but access to public data in North Korea is limited, and objectivity is difficult to be guaranteed. In this study, the forest detection based on density estimation in statistic using Landsat imagery was conducted in Gangwon province which is the only administrative district divided into South and North. The forest spatial data of South Korea was used as data for the labeling of forest and Non-forest in the Normalized Difference Vegetation Index (NDVI), and a threshold (0.6658) for forest detection was set by Gaussian Probability Density Function (PDF) estimation by category. The results show that the forest area decreased until the 2000s in both Korea, but the area increased in 2010s. It is also confirmed that the reduction of forest area on the local scale is the same as the policy direction of urbanization and industrialization at that time. The Kappa value for validation was strong agreement (0.8) and moderate agreement (0.6), respectively. The detection based on the Gaussian PDF estimation is considered a method for complementing the statistical limitations of the existing detection method using satellite imagery. This study can be used as basic data for deforestation in North Korea and Based on the detection results, it is necessary to protect and restore forest resources.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.989-998
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• 2021

In the utilization of optical satellite imagery, which is greatly affected by clouds, periodic composite technique is a useful method to minimize the influence of clouds. Recently, a technique for selecting the optimal pixel that is least affected by the cloud and shadow during a certain period by directly inputting cloud and cloud shadow information during period compositing has been proposed. Accurate extraction of clouds and cloud shadowsis essential in order to derive optimal composite results. Also, in the case of an surface targets where spectral information is important, such as crops, the loss of spectral information should be minimized during cloud-free compositing. In thisstudy, clouds using two spectral indicators (Haze Optimized Tranformation and MeanVis) were used to derive a detection technique with low loss ofspectral information while maintaining high detection accuracy of clouds and cloud shadowsfor cabbage fieldsin the highlands of Gangwon-do. These detection results were compared and analyzed with cloud and cloud shadow information provided by Sentinel-2A/B. As a result of analyzing data from 2019 to 2021, cloud information from Sentinel-2A/B satellites showed detection accuracy with an F1 value of 0.91, but bright artifacts were falsely detected as clouds. On the other hand, the cloud detection result obtained by applying the threshold (=0.05) to the HOT showed relatively low detection accuracy (F1=0.72), but the loss ofspectral information was minimized due to the small number of false positives. In the case of cloud shadows, only minimal shadows were detected in the Sentinel-2A/B additional layer, but when a threshold (= 0.015) was applied to MeanVis, cloud shadowsthat could be distinguished from the topographically generated shadows could be detected. By inputting spectral indicators-based cloud and shadow information,stable monthly cloud-free composited vegetation index results were obtained, and in the future, high-accuracy cloud information of Sentinel-2A/B will be input to periodic cloud-free composite for comparison.

• The Transactions of the Korea Information Processing Society
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• v.2 no.6
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• pp.937-946
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• 1995

We proposed and efficient block segmentation and classification method for the document analysis using SGLDM(spatial gray level dependence matrix) and BP (back Propagation) neural network. Seven texture features are extracted directly from the SGLDM of each gray-level block image, and by using the nonlinear classifier of neural network BP, we can classify document blocks into 9 categories. The proposed method classifies the equation block, the table block and the flow chart block, which are mostly composed of the characters, out of the blocks that are conventionally classified as non-character blocks. By applying Sobel operator on the gray-level document image beforebinarization, we can reduce the effect of the background noises, and by using the additional horizontal-vertical smoothing as well as the vertical-horizontal smoothing of images, we can obtain an effective block segmentation that does not lead to the segmentation into small pieces. The result of experiment shows that a document can be segmented and classified into the character blocks of large fonts, small fonts, the character recognigible candidates of tables, flow charts, equations, and the non-character blocks of photos, figures, and graphs.

• Journal of the Korean Geographical Society
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• v.40 no.1 s.106
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• pp.27-46
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• 2005

Land suitability assessment(LSA) is a useful method to assess land characteristics according to its physical, locational, and environmental characteristics, and then to classify it into several categories based on its usability and the necessity for conservation. Therefore, the credibility of this assessment result depends on the rationality of assessment method such as computation of suitability values and the criteria of ranking the land grade. This study focused on identifying problems in current LSA method by critically reviewing it, and aimed to suggest a suitable method for the assessment of land suitability. As a alternative method in this study, linear transformation method was used for scoring factors instead of critical values and the weight for each assessment factor. and all values of those factors were added to produce comprehensive suitability values. Those values were ordered and categorizied with suitability level based on the ratio of square measure. After comparing existing LSA method to the suggested alternative method, it is concluded that the alternative method was more suitable to assess the characteristics of lands than existing LSA method. This method was also suitable to represent the characteristics of various assessment factors. Field survey using satellite image clearly revealed the suitability of the alternative method compared to an existing method of land assessment. Furthermore, the alternative method of grading the land suitability improves the problem of using standardiZiation method and gives more flexibility, which makes this method very rational.

• The Korean Journal of Rheology
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• v.10 no.4
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• pp.185-194
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• 1998

Flow-induced voids during resin impregnation and poor fiber wetting give serious effects on the mechanical properties of composites in resin transfer molding process. In order to better understand the characteristics of resin flow and to investigate the mechanism of void formation, flow visualization experiment for the resin impregnation was carried out on plain weaving glass fiber mats using silicon oils with various viscosity values. The permeability and the capillary pressure for the fiber mats of different porosities were obtained by measuring the penetration length of the resin with time and with various injection pressure. At low porosity and low operating pressure, the capillary pressure played a significant role in impregnation process. Video-assisted microscopy was used in taking the magnified photograph of the flow front of the resin to investigate the effect of the capillary pressure on the void formation. The results showed that the voids were formed easily when the capillary pressure was relatively high. No voids were detected above the critical capillary number of 2.75$\times$$10^{-3}, and below the critical number the void content increased exponentially with decrease of the capillary number. The content of void formed was independent of the viscosity of the resin. For a given capillary number, the void content reduced with the lower porosity of the fiber mat.

• Journal of the Korea Concrete Institute
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• v.21 no.1
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• pp.13-20
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• 2009

The influence of steel fiber volume on the tension softening behavior in steel fiber-reinforced ultra high strength concrete was investigated. Three-point bending test (TPBT) with notched beams was performed and inverse analysis method by Uchida et al. was adopted to obtain the tension softening behaviors from the results of TPBT. It could be found that the intial stiffness was constant regardless of steel fiber volume, the increase of steel fiber volume fraction made the tensile strength higher, but all of the curves converged on an asymptote with a crack width. It was proposed the equation of softening curve expressed by combination of plastic behavior part and exponential descending behavior part considering the steel fiber volume fraction and $\omega_0$, which is corresponding to the maximum crack width of plastic area. Thereafter, the crack propagation analysis using finite element method with smeared crack model was also carried out and it was confirmed that the proposed equation had a good agreement with the experimental results.

• Journal of the Korean Chemical Society
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• v.48 no.2
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• pp.195-202
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• 2004

Micellar catalysis is an essential part of theoretical and experimental curricular. The sodium dodecylsulfate (SDS) catalyzed reaction between glycine and potassium permanganate in acidic medium is an ideal kinetic experiment for the secondary and undergraduate physical chemistry laboratory, to show the effect of micellar catalysis on rate of the reaction. The reaction is conducted both with and without SDS to observe the rate enhancement in the presence of surfactant. To show surfactant catalysis a plot between k and [SDS] is plotted. As surfactant catalysis is observed even before the critical micelle concentration of SDS, this pre-micellar catalysis can be understood in the light of positive co-operativity. The value of positive cooperative index (n) has been found to be 2.37. Further, dependence of the reaction rate on substrate and oxidant concentrations is also discussed. The reaction follows pseudo-first-order kinetics. The overall reaction is second order, with first-order dependence on both glycine and permanganate concentrations. The theory of surfactant catalysis is also discussed. With the conditions specified in the experiment, total reaction times are in 3~4 hours lab session, thus allowing several data sets to be acquired in a single laboratory period. Preparation of solutions and procedure is also given in detail.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.18 no.6
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• pp.571-580
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• 1985

Based on the data collected by R/V "Shinkai Maru" of the Japan Marine Fishery Resources Research Center during the period from April 1978 to April 1979, seasonal migration of Merluccius hubbsi was studied using the catch per fishing effort (tons/30 min. haul) and gonad maturity index (gonad weight /body weight X $10^3$). Merlurccius hubbsi are found in the area between $36^{\circ}S\;and\;54^{\circ}S$ along the coast of Arzentine and are abundant especially above the 100 fathoms in northern offshore of $48^{\circ}S$. It was observed that critical maturity body lengths (spawning minimum body length) in terms of gonad maturity index are 40 cm and 30cm in female and male respectively, while spawning seasons are from December to January and from November to December for female and male respectively. It was assumed that while the group which distrbutes in the north ($36^{\circ}S{\sim}39^{\circ}S$) in spring moves down south to $42^{\circ}{\sim}46^{\circ}S$ for spawning in summer (from December to January), the group which does not move or a part of this group which comes back to the north spawn in the area north of $42^{\circ}S$ throughout the long period except winter time (from July to August). Southern group as well might move north and spawn after mixing together with northern group at $42^{\circ}{\sim}46^{\circ}S$ area around the period of December to January,

• Korean Journal of Food Science and Technology
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• v.17 no.2
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• pp.107-112
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• 1985

Viscometric properties of japonica(Olchal) and japonica${\times}$indica(Hankang and Suwon 317) waxy rice starches were investigated. Light transmittance of starch suspension increased from $50^{\circ}{\sim}55^{\circ}C$ and remained constant after $75^{\circ}C$. Swelling power was in the order of Hankang, Suwon 317 and Olchal. Amylograph data revealed that Hankang had the highest viscosity at all reference points. The apparent viscosity of 5% starch suspension indicated that the j${\times}$indica starches were completely gelatinized after 30 min cooking at $65^{\circ}C$ whereas japonica starch at $70^{\circ}C$. The apparent viscosity of gelatinized starch at $121^{\circ}C$(15 psig) was higher compared to that of gelatinized one at $95^{\circ}C$. Hankang was the most susceptable to alkali gelatinization followed by Suwon 317 and Olchal.

• Korean Journal of Remote Sensing
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• v.31 no.2
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• pp.149-160
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• 2015

A comparative study was conducted for alternative consecutive procedures of detection of cloud-contaminated pixels and gap-filling and smoothing of time-series data to produce high-quality gapless satellite vegetation index (i.e. Normalized Difference Vegetation Index, NDVI). Performances of five alternative methods for detecting cloud contaminations were tested with ground-observed cloudiness data. The data gap was filled with a simple linear interpolation and then, it was applied two alternative smoothing methods (i.e. Savitzky-Golay and Wavelet transform). Moderate resolution imaging spectroradiometer (MODIS) data were used in this study. Among the alternative cloud detection methods, a criterion of MODIS Band 3 reflectance over 10% showed best accuracy with an agreement rate of 85%, which was followed by criteria of MODIS Quality assessment (82%) and Band 3 reflectance over 20% (81%), respectively. In smoothing process, the Savitzky-Golay filter was better performed to retain original NDVI patterns than the wavelet transform. This study demonstrated an operational framework of gapdetection, filling, and smoothing to produce high-quality satellite vegetation index.