• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1273-1283
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• 2022

Recently, forest fires have frequently occurred due to climate change, leading to human and property damage every year. The forest fire monitoring technique using remote sensing can obtain quick and large-scale information of fire-damaged areas. In this study, the Gangneung and Donghae forest fires that occurred in March 2022 were analyzed using the spectral band of Sentinel-2, the normalized difference vegetation index (NDVI), and the normalized difference water index (NDWI) to classify the affected areas of forest fires. The U-net based convolutional neural networks (CNNs) model was simulated for the fire-damaged areas. The accuracy of forest fire classification in Donghae and Gangneung classification was high at 97.3% (f₁=0.486, IoU=0.946). The same model used in Donghae and Gangneung was applied to Uljin and Samcheok areas to get rid of the possibility of overfitting often happen in machine learning. As a result, the portion of overlap with the forest fire damage area reported by the National Institute of Forest Science (NIFoS) was 74.4%, confirming a high level of accuracy even considering the uncertainty of the model. This study suggests that it is possible to quantitatively evaluate the classification of forest fire-damaged area using a spectral band and indices similar to that of the Compact Advanced Satellite 500 (CAS500-4) in the Sentinel-2.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.728-737
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• 2021

In the meantime, broadcasting CG has gone through the process of dismantling, changing, and distorting, while broadcasting CG in broadcasting programs utilizes the expanded background of 'temporality' and 'formality'. This is to create an audiovisual language that appeals to human synesthesia by expressing the meaning to be conveyed in three dimensions. Broadcast CG goes beyond simple instructional and informational broadcast graphic operation, and increases the pure aesthetic value and sensibility of the video considering readability and formativeness, and through this, the audiovisual information perfection of the broadcast program is derived and acts as a very important factor. Therefore, this paper examines the results of broadcast CG production and utilization methods at existing local broadcasters, and identifies the limitations of local broadcasters' CG production and utilization through case analysis for each broadcast program type. We want to derive a model that is a compromise line. In addition, I would like to suggest a plan that can be applied more actively and practically to local broadcasting programs. In order to solve this problem, this study first examines "Analysis of cases of use of broadcasting CG production in broadcasting programs" and then "more efficient broadcasting CG production techniques by identifying problems in broadcasting CG production methods and utilization of local broadcasters" and how to actively use it". In addition, the results of this study are expected to contribute to the establishment of a new role and practical broadcast CG production model for broadcast graphic designers in charge of broadcast CG production and the technical perspective of broadcast program production by local broadcasters.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.571-585
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• 2022

As the threat of natural disasters such as droughts, floods, forest fires, and landslides increases due to climate change, social demand for high-resolution soil moisture retrieval, such as Synthetic Aperture Radar (SAR), is also increasing. However, the domestic environment has a high proportion of mountainous topography, making it challenging to retrieve soil moisture from SAR data. This study evaluated the usability of Sentinel-1 SAR, which is applied with the Artificial Neural Network (ANN) technique, to retrieve soil moisture. It was confirmed that the backscattering coefficient obtained from Sentinel-1 significantly correlated with soil moisture behavior, and the possibility of stand-alone use to correct vegetation effects without using auxiliary data observed from other satellites or observatories. However, there was a large difference in the characteristics of each site and topographic group. In particular, when the model learned on the mountain and at flat land cross-applied, the soil moisture could not be properly simulated. In addition, when the number of learning points was increased to solve this problem, the soil moisture retrieval model was smoothed. As a result, the overall correlation coefficient of all sites improved, but errors at individual sites gradually increased. Therefore, systematic research must be conducted in order to widely apply high-resolution SAR soil moisture data. It is expected that it can be effectively used in various fields if the scope of learning sites and application targets are specifically limited.

• Journal of Korea Entertainment Industry Association
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• v.14 no.6
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• pp.77-89
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• 2020

The film "Parasite" portrays Korea's history and its present in a space that clearly represents the real world's hierarchy as a vertical structure. It demonstrates the problems of an insurmountable reality and the elements of various conflicts occurring below the surface of Korean society through a complex mix of human emotions and relationships. The most realistic yet unrealistic characters cross boundaries between being victims and perpetrators, defamiliarizing ordinary scenes from everyday life through their small mistakes, strange obsessions, bizarre behavior, anxious psychology, and desperate struggles. This study analyzes the expression of the film "Parasite" through its characters with the belief that the film expresses director Bong Joon-ho's consistent cinematic philosophy of taking reality beyond the traditional rules of film genres. By doing so, Bong creates a feature of the expression that shifts genres as the characters' personalities amplify related behaviors, conflicts and questions, and that this is the core of the unique nuance and distinct humor of this film. In addition, the personalities of the characters interact with all the film's elements (cinematic techniques, space, props, etc.), evoking effects of various meanings, which are transmitted through the actors'images and acting. In this respect, the study analyzes how the actors were cast in order to realistically reproduce the characters of the actors, how their acting was harmonized with the film's elements, and its features as well as how they were expressed.

• Journal of Broadcast Engineering
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• v.27 no.6
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• pp.936-939
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• 2022

As air combat system technologies developed in recent years, the development of air defense systems is required. In the operating concept of the anti-aircraft defense system, selecting an appropriate armament for the target is one of the system's capabilities in efficiently responding to threats using limited anti-aircraft power. Much of the flying threat identification relies on the operator's visual identification. However, there are many limitations in visually discriminating a flying object maneuvering high speed from a distance. In addition, as the demand for unmanned and intelligent weapon systems on the modern battlefield increases, it is essential to develop a technology that automatically identifies and classifies the aircraft instead of the operator's visual identification. Although some examples of weapon system identification with deep learning-based models by collecting video data for tanks and warships have been presented, aerial vehicle identification is still lacking. Therefore, in this paper, we present a model for classifying fighters, helicopters, and drones using a convolutional neural network model and analyze the performance of the presented model.

• Korean Journal of Remote Sensing
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• v.38 no.3
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• pp.311-326
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• 2022

The Compact Advanced Satellite 500-4 (CAS500-4) is under development to efficiently manage and monitor forests in Korea and is scheduled to launch in 2025. The National Institute of Forest Science is developing 36 types of forestry applications to utilize the CAS500-4 efficiently. The products derived using the remote sensing method require validation with ground reference data, and the quality monitoring results for the products must be continuously reported. Due to it being the first time developing the national forestry satellite, there is no official calibration and validation site for forestry products in Korea. Accordingly, the author designed a calibration and validation site for the forestry products following international standards. In addition, to install calibration and validation sites nationwide, the authors selected appropriate sensors and evaluated the applicability of the sensors. As a result, the difference between the ground observation data and the Sentinel-2 image was observed to be within ±5%, confirming that the sensor could be used for nationwide expansion.

• Journal of Bio-Environment Control
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• v.31 no.3
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• pp.255-260
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• 2022

This study aimed to develop a service model that uses a deep learning algorithm for detecting diseases and pests in strawberries through image data. In addition, the pest detection performance of deep learning models was further improved by proposing segmented image data sets specialized in disease and pest symptoms. The CNN-based YOLO deep learning model was selected to enhance the existing R-CNN-based model's slow learning speed and inference speed. A general image data set and a proposed segmented image dataset was prepared to train the pest and disease detection model. When the deep learning model was trained with the general training data set, the pest detection rate was 81.35%, and the pest detection reliability was 73.35%. On the other hand, when the deep learning model was trained with the segmented image dataset, the pest detection rate increased to 91.93%, and detection reliability was increased to 83.41%. This study concludes with the possibility of improving the performance of the deep learning model by using a segmented image dataset instead of a general image dataset.

• Journal of the Korean Society of Radiology
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• v.16 no.1
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• pp.15-23
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• 2022

3D printing technology is being used in various fields such as medicine and biotechnology, and materials containing metal powder are being commercialized through recent material development. Therefore, this study intends to analyze the photon spectrum during added filtration using 3D printing material during diagnostic X-ray examination through simulation. Among the Monte Carlo techniques, MCNPX (ver. 2.5.0) was used. First, the appropriateness of the photon spectrum generated in the simulation was evaluated through SRS-78 and SpekCalc, which are X-ray spectrum generation programs in the diagnostic field. Second, photon spectrum the same thickness of Al and Cu filters were obtained for characterization of 3D printing materials containing metal powder. In addition, the total photon fluence and average energy according to changes in tube voltage were compared and analyzed. As a result, it was analyzed that PLA-Al required about 1.2 ~ 1.4 times the thickness of the existing Al filter, and PLA-Cu required about 1.4 ~ 1.7 times the thickness of the Cu filter to show the same degree of filtration. Based on this study in the future, it is judged that it can be utilized as basic data for manufacturing 3D printing additional filters in medical fields.

• Journal of Aerospace System Engineering
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• v.16 no.5
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• pp.1-7
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• 2022

Recently, satellites equipped with high-performance electronics have required higher power consumption because of the advancement of satellite missions. For this reason, the size of the solar panel is gradually increasing to meet the required power budget. Increasing the size and weight of the solar panel is one of the factors that induce the elastic vibration of the flexible solar panel during the highly agile maneuvering of the satellite or the mode of vibration coupling to the satellite or the mode of vibration coupling to the micro-jitter from the on-board appendages. Previously, an additional damper system was applied to reduce the elastic vibration of the solar panel, but the increase in size and mass of system was inevitable. In this study, to overcome the abovementioned limitations, we proposed a high -damping yoke structure consisting of a superplastic SMA(Shape Memory Alloy) laminating a thin FR4 layer with viscoelastic tape on both sides. Therefore, this advantage contributes to system simplicity by reducing vibrations with small volume and mass without additional system. The effectiveness of the proposed superelastic SMA multilayer solar panel yoke was validated through free vibration testing and temperature testing using a solar panel dummy.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.4
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• pp.274-284
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• 2022

To use kenaf (Hibiscus cannabinus L.) as a fiber and livestock feed, a high-yielding variety needs to be identified. For this, accurate phenotyping of plant height is required for this breeding purpose due to the strong relationship between plant height and yield. Plant height can be estimated using RGB images from unmanned aerial vehicles (UAV-RGB) and photogrammetry based on Structure from Motion (SfM) algorithms. In kenaf, accurate measurement of height is limited because kenaf stems have high flexibility and its height is easily affected by wind, growing up to 3 ~ 4 m. Therefore, we aimed to identify a method suitable for the accurate estimation of plant height of kenaf and investigate the feasibility of using the UAV-RGB-derived plant height map. Height estimation derived from UAV-RGB was improved using multi-point calibration against the five different wooden structures with known heights (30, 60, 90, 120, and 150 cm). Using the proposed method, we analyzed the variation in temporal height of 23 kenaf cultivars. Our results demontrated that the actual and estimated heights were reliably comparable with the coefficient of determination (R²) of 0.80 and a slope of 0.94. This method enabled the effective identification of cultivars with significantly different heights at each growth stages.