• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.1025-1032
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• 2018

Snow Cover is a form of precipitation that is defined by snow on the surface and is the single largest component of the cryosphere that plays an important role in maintaining the energy balance between the earth's surface and the atmosphere. It affects the regulation of the Earth's surface temperature. However, since snow cover is mainly distributed in area where human access is difficult, snow cover detection using satellites is actively performed, and snow cover detection in forest area is an important process as well as distinguishing between cloud and snow. In this study, we applied the Normalized Difference Snow Index (NDSI) and the Normalized Difference Vegetation Index (NDVI) to the geostationary satellites for the snow detection of forest area in existing polar orbit satellites. On the rest of the forest area, the snow cover detection using $R_{1.61{\mu}m}$ anomaly technique and NDSI was performed. As a result of the indirect validation using the snow cover data and the Visible Infrared Imaging Radiometer (VIIRS) snow cover data, the probability of detection (POD) was 99.95 % and the False Alarm Ratio (FAR) was 16.63 %. We also performed qualitative validation using the Himawari-8 Advanced Himawari Imager (AHI) RGB image. The result showed that the areas detected by the VIIRS Snow Cover miss pixel are mixed with the area detected by the research false pixel.

• Korean Journal of Remote Sensing
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• v.35 no.2
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• pp.229-239
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• 2019

All vegetation colonies have layered structure. This layer is called 'forest vertical structure.' Nowadays it is considered as an important indicator to estimate forest's vital condition, diversity and environmental effect of forest. So forest vertical structure should be surveyed. However, vertical structure is a kind of inner structure, so forest surveys are generally conducted through field surveys, a traditional forest inventory method which costs plenty of time and budget. Therefore, in this study, we propose a useful method to classify the vertical structure of forests using remote sensing aerial photographs and machine learning capable of mass data mining in order to reduce time and budget for forest vertical structure investigation. We classified it as SVM (Support Vector Machine) using RGB airborne photos and LiDAR (Light Detection and Ranging) DSM (Digital Surface Model) DTM (Digital Terrain Model). Accuracy based on pixel count is 66.22% when compared to field survey results. It is concluded that classification accuracy of layer classification is relatively high for single-layer and multi-layer classification, but it was concluded that it is difficult in multi-layer classification. The results of this study are expected to further develop the field of machine learning research on vegetation structure by collecting various vegetation data and image data in the future.

• Korean Journal of Remote Sensing
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• v.35 no.2
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• pp.203-215
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• 2019

As hyperspectral sensors that can be mounted on drones are developed, it is possible to acquire hyperspectral imagery with high spatial and spectral resolution. Although the importance of atmospheric correction has been reduced since imagery of drones were acquired at a low altitude,studies on the conversion process from raw data to spectral reflectance should be done for studies such as estimating the concentration of surface materials using hyperspectral imagery. In this study, a vicarious radiometric calibration and an atmospheric correction algorithm based on atmospheric radiation transfer model were applied to hyperspectral data of drone and the results were compared and analyzed. The vicarious calibration method was applied to an empirical line calibration using the spectral reflectance of a tarp made of uniform material. The atmospheric correction algorithm used ATCOR-4 based Modran-5 that was widely used for the atmospheric correction of aerial hyperspectral imagery. As a result of analyzing the RMSE of the difference between the reference reflectance and the correction, the vicarious calibration using the tarp in a single period of hyperspectral image was the most accurate, but the atmospheric correction was possible according to the application purpose of using hyperspectral imagery. If the correction process of normalized spectral reflectance is carried out through the additional vicarious calibration for imagery from multiple periods in the future, accurate analysis using hyperspectral drone imagery will be possible.

• The korean journal of orthodontics
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• v.51 no.6
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• pp.366-374
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• 2021

Objective: This study investigated the impact of a single piezocision in the maxillary alveolar process on the speed of tooth movement. The null hypothesis was that the speed of tooth movement will be equal with and without piezocision. Methods: All maxillary molars on one side were moved against the combined incisors in 10 ten-week-old male Wistar rats. Under general anesthesia, a force of 25 cN was applied on either side using a Sentalloy closed coil spring. After placing the orthodontic appliance, vertical corticision was performed using a piezotome under local anesthesia, 2 mm mesial from the mesial root of the first molar on a randomly selected side; the other side served as the control. At the beginning of the treatment, and 2 and 4 weeks later, skull micro-computed tomography was performed. After image reconstruction, the distance between the mesial root of the first molar and the incisive canal, and the length of the mesial root of the first maxillary molar were measured. Moreover, the root resorption score was determined as described by Lu et al. Results: Significantly higher speed of tooth movement was observed on the corticision side; thus, the null hypothesis was rejected. The loss of root length and root resorption score were significantly more pronounced after piezocision than before. A strong correlation was observed between the speed of tooth movement and root resorption on the surgical side, but the control side only showed a weak correlation. Conclusions: Piezocision accelerates orthodontic tooth movement and causes increased root resorption.

• Journal of the Korean Physical Society
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• v.73 no.10
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• pp.1584-1588
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• 2018

During hyperthermia therapy, cancer cells are heated to a temperature in the range of $40{\sim}45^{\circ}C$ for a defined time period to damage these cells while keeping healthy tissues at safe temperatures. Prior to hyperthermia therapy, the amount of heat energy transferred to the cancer cells must be predicted. Among various non-invasive methods, the thermal prediction method using the specific absorption rate (SAR) is the most widely used method. The existing methods predict the thermal distribution by using a single constant for the mass density in one organ through assignment. However, because the SAR and the bio heat equation (BHE) vary with the mass density, the mass density of each organ must be accurately considered. In this study, the mass density distribution was calculated using the relationship between the Hounsfield unit and the mass density of tissues in preceding research. The SAR distribution was found using a quasi-static approximation to Maxwell's equation and was used to calculate the potential distribution and the energy distributions for capacitive RF heating. The thermal distribution during exposure to RF waves was determined by solving the BHE with consideration given to the considering contributions of heat conduction and external heating. Compared with reference data for the mass density, our results was within 1%. When the reconstructed temperature distribution was compared to the measured temperature distribution, the difference was within 3%. In this study, the density distribution and the thermal distribution were reconstructed for the agar phantom. Based on these data, we developed an algorithm that could be applied to patients.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.47 no.2
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• pp.163-170
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• 2021

This study was conducted to create a technology to remove acne bacteria with human-friendly materials. First, the Cutibacterium acnes (C. acnes) were adsorbed to the mica disc to grow, and then the biofilm was checked through an atomic microscope to see if the biofilm had grown. Based on the topographic image, the shape changed round, the size was 17% longer on average, and the phase value of the resonance frequency separating materials was observed as a single value, the biofilm grown by covering the extracellular polymeric substrate (EPS). As a result of processing 50 mM of amino acids in the matured biofilm, the concentration of C. acnes decreased when valine, serine, arginine and leucine were treated. Scanning with nanoindentation and AFM contact modes confirmed that the hardness of biofilms treated with Valine (Val) increased. This indicates that an AFM tip measured cell which may have more solidity than that of EPS. The experiment of fluorescent tagged to EPS displays an existence of EPS at the condition of 10 mM Val, but an inhibition of growth of EPS at the 50 mM Val. Number of C. acnes was also reduced above 10 mM of Val. Weak adhesion of biofilm generated from an inhibition of EPS formation seems to induce decrease of C. acnes. Accordingly, we elucidated that Val has an efficiency which eliminates C. acnes by approach of an inhibition of EPS.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.33 no.6
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• pp.246-256
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• 2021

Various development projects occurring on the coast cause an imbalance of surface sediments, causing coastal disasters or irreversible coastal erosion. Coastal erosion caused by the influence of various port structures built through coastal development can be directly identified by evaluating changes in the sediment budget, longshore sediment, and cross-shore sediment. In other words, it will be possible to evaluate the causality between coastal development and coastal erosion by classifying regions due to single cause and regions due to multiple causes according to the changes in the sediment classified into the three types mentioned above. In this study, the cause of long-term and continuous erosion was analyzed based on the analysis results of the coastal development history and the Coastal Erosion Monitoring targeting the coast of Gangwon-do and Gyeongsangbuk-do on the east coast. In addition, in order to evaluate the degree of erosion caused by the construction of artificial coastal structures, the concept of erosion impact assessment was established, three methods were proposed for the impact assessment. The erosion impact of Hajeo port was assessed using the results of satellite image analysis presented in the Coastal Erosion Monitoring Report, it was assessed that the development of Hajeo port had an impact of 93.4% on erosion, and that of the coastal road construction had an impact of 6.6%.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.5
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• pp.333-338
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• 2022

The single jet of decane/methylcyclohexane mixed fuel that is surrogate for kerosene was injected into supercritical environment and visualized using shadowgraph technique. The injection pressure drop of the fuel jet of T_r = 0.484 was kept constant at 0.5 MPa and the experiment was conducted above the critical point of the mixed fuel, and the reduced temperatures of the chamber was changed from 1.00 to 1.23, and the reduced pressures was 1.00 and 1.38. As an index for reducing the density of jets sprayed into the supercritical environment, the brightness intensity of the post-processed jet image was observed with the internal temperature and pressure of the chamber. It was confirmed that the decrease in the brightness intensity of the jet when the temperature inside the chamber increased, and when the pressure inside the chamber was higher at the same temperature, the decrease in the brightness intensity of the jet was delayed. When the pressure inside the chamber is high, it is thought that the change in brightness intensity is delayed due to the increase in the pseudo-critical temperature of the fuel and the increase in the temperature required to reduce the density of the fuel jet.

• Journal of Broadcast Engineering
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• v.27 no.3
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• pp.378-390
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• 2022

With the recent development of deep composite multiplication neural network learning, deep learning techniques applied to single-image super-resolution have shown good results, and the strong expression ability of deep networks has enabled complex nonlinear mapping between low-resolution and high-resolution images. However, there are limitations in applying it to real-time or low-power devices with increasing parameters and computational amounts due to excessive use of composite multiplication neural networks. This paper uses blocks that extract hierarchical characteristics little by little using information distillation and suggests the Recursive Distillation Super Resolution Network (RDSRN), a lightweight network that improves performance by making more accurate high frequency components through high frequency residual purification blocks. It was confirmed that the proposed network restores images of similar quality compared to RDN, restores images 3.5 times faster with about 32 times fewer parameters and about 10 times less computation, and produces 0.16 dB better performance with about 2.2 times less parameters and 1.8 times faster processing time than the existing lightweight network CARN.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.185-191
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• 2022

In this study, we propose a novel super-resolution neural network based on U-Net, residual neural network, and sub-pixel convolution. To prevent the loss of detailed information due to the max pooling of U-Net, we propose down-sampling and connection using sub-pixel convolution. This uses all pixels in the filter, unlike the max pooling that creates a new feature map with only the max value in the filter. As a 2×2 size filter passes, it creates a feature map consisting only of pixels in the upper left, upper right, lower left, and lower right. This makes it half the size and quadruple the number of feature maps. And we propose two methods to reduce the computation. The first uses sub-pixel convolution, which has no computation, and has better performance, instead of up-convolution. The second uses a layer that adds two feature maps instead of the connection layer of the U-Net. Experiments with a banchmark dataset show better PSNR values on all scale and benchmark datasets except for set5 data on scale 2, and well represent local area patterns.