• Korean journal of communication and information
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• v.58
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• pp.31-54
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• 2012

This study explored possibilities and conditions of the SNS dromological paradigm and creative resistance in SNS era. For solve this theoretical questions, I analyzed authority of speed and material conditions. In order to attain this achieve, reviewed Virilio's theories which is criticizing speed, power and sense of artificial. And also studied Kittler's theories about material conditions, 'Information Machine'. Following those theoretical base, this study find social issues and advanced research's propensity for connecting SNS dromological paradigm. Furthermore, I designed depth interview to find SNS users think and experience. This study's significance of result is expanding cultural study filed in SNS approach and provided that exploratory sight.

• Korean Journal of Remote Sensing
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• v.36 no.5_2
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• pp.975-988
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• 2020

Change detection is the process of identifying changes by observing the multi-temporal images at different times, and it is an important technique in remote sensing using satellite images. Among the change detection methods, the unsupervised change detection technique has the advantage of extracting rapidly the change area as a binary image. However, it is difficult to understand the changing pattern of land cover in binary images. This study used grid points generated from seamless digital map to evaluate the satellite image change detection results. The land cover change results were extracted using multi-temporal KOMPSAT-3A (K3A) data taken by Gimje Free Trade Zone and change detection algorithm used Spectral Angle Mapper (SAM). Change detection results were presented as binary images using the methods Otsu, Kittler, Kapur, and Tsai among the automated threshold selection algorithms. To consider the seasonal change of vegetation in the change detection process, we used the threshold of Differenced Normalized Difference Vegetation Index (dNDVI) through the probability density function. The experimental results showed the accuracy of the Otsu and Kapur was the highest at 58.16%, and the accuracy improved to 85.47% when the seasonal effects were removed through dNDVI. The algorithm generated based on this research is considered to be an effective method for accuracy assessment and identifying changes pattern when applied to unsupervised change detection.

• Advances in nano research
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• v.2 no.1
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• pp.1-14
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• 2014

Dislocations are basic crystal defects and represent one-dimensional native nanostructures embedded in a perfect crystalline matrix. Their structure is predefined by crystal symmetry. Two-dimensional, self-organized arrays of such nanostructures are realized reproducibly using specific preparation conditions (semiconductor wafer direct bonding). This technique allows separating dislocations up to a few hundred nanometers which enables electrical measurements of only a few, or, in the ideal case, of an individual dislocation. Electrical properties of dislocations in silicon were measured using MOSFETs as test structures. It is shown that an increase of the drain current results for nMOSFETs which is caused by a high concentration of electrons on dislocations in p-type material. The number of electrons on a dislocation is estimated from device simulations. This leads to the conclusion that metallic-like conduction exists along dislocations in this material caused by a one-dimensional carrier confinement. On the other hand, measurements of pMOSFETs prepared in n-type silicon proved the dominant transport of holes along dislocations. The experimentally measured increase of the drain current, however, is here not only caused by an higher hole concentration on these defects but also by an increasing hole mobility along dislocations. All the data proved for the first time the ambipolar behavior of dislocations in silicon. Dislocations in p-type Si form efficient one-dimensional channels for electrons, while dislocations in n-type material cause one-dimensional channels for holes.

• Journal of Korea Water Resources Association
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• v.54 no.7
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• pp.535-544
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• 2021

Agricultural water occupies 48% of water demand, and management of agricultural reservoirs is essential for water resources management within agricultural basins. For more efficient use of agricultural water, monitoring the distribution of water resources in agricultural reservoirs and agricultural basins is required. Therefore, in this study, three threshold determination methods (i.e., fixed threshold, Otsu threshold, Kittler-Illingworth (KI) threshold) were compared to detect terrestrial water bodies using Sentinel-1 images for 3 years from 2018 to 2020. The purpose of this study was to evaluate methods for determining threshold values to more accurately estimate the reservoir area. In addition, by analyzing the relationship between the water surface and water storage at the Edong, Gosam, and Giheung reservoirs, water storage based on the SAR image was estimated and validated with observations. The thresholding method for detecting a waterbody was found to be the most accurate in the case of the KI threshold, and the water storage estimated by the KI threshold indicated a very high agreement (r = 0.9235, KGE' = 0.8691). Although the seasonal error characteristics were not observed, the problem of underestimation at high water levels may occur; the relationship between the water surface and the water storage could change rapidly. Therefore, it is necessary to understand the relationship between the water surface area and water storage through ground observation data for a more accurate estimation of water storage. If the use of SAR data through water resources satellites becomes possible in the future, based on the results of this study, it is judged that it will be beneficial for monitoring water storage and managing drought.

• Korean Journal of Remote Sensing
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• v.31 no.3
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• pp.227-244
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• 2015

Synthetic Aperture Radar is able to provide images of wide coverage in day, night, and all-weather conditions. Recently, as the SAR image resolution improves up to the sub-meter level, their applications are rapidly expanding accordingly. Especially there is a growing interest in the use of geographic information of high resolution SAR images and the change detection will be one of the most important technique for their applications. In this paper, an automatic threshold tracking and change detection algorithm is proposed applicable to high-resolution SAR images. To detect changes within SAR image, a reference image is generated using log-ratio operator and its amplitude distribution is estimated through K-S test. Assuming SAR image has a non-gaussian amplitude distribution, a generalized thresholding technique is applied using Kittler and Illingworth minimum-error estimation. Also, MoLC parametric estimation method is adopted to improve the algorithm performance on rough ground target. The implemented algorithm is tested and verified on the simulated SAR raw data. Then, it is applied to the spaceborne high-resolution SAR images taken by Cosmo-Skymed and KOMPSAT-5 and the performances are analyzed and compared.