• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.3
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• pp.239-247
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• 2022

Cities are becoming more complex due to rapid industrialization and population growth in modern times. In particular, urban areas are rapidly changing due to housing site development, reconstruction, and demolition. Thus accurate road information is necessary for various purposes, such as High Definition Map for autonomous car driving. In the case of the Republic of Korea, accurate spatial information can be generated by making a map through the existing map production process. However, targeting a large area is limited due to time and money. Road, one of the map elements, is a hub and essential means of transportation that provides many different resources for human civilization. Therefore, it is essential to update road information accurately and quickly. This study uses Semantic Segmentation algorithms Such as LinkNet, D-LinkNet, and NL-LinkNet to extract roads from drone images and then apply hyperparameter optimization to models with the highest performance. As a result, the LinkNet model using pre-trained ResNet-34 as the encoder achieved 85.125 mIoU. Subsequent studies should focus on comparing the results of this study with those of studies using state-of-the-art object detection algorithms or semi-supervised learning-based Semantic Segmentation techniques. The results of this study can be applied to improve the speed of the existing map update process.

• Journal of Korea Entertainment Industry Association
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• v.15 no.1
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• pp.143-152
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• 2021

The extremely isolated uninhabited island at the end of the West Sea in South Korea called "The Gyeokryeolbi Yeoldo" has recently begun to be managed by the government under the influence of public opinion demanding the island to be strictly protected. The island was created 70 million years ago by volcanic activities. So it is older than the birth history of Jeju Island, which is estimated to have been born about a million years ago. This study has focused on providing the basis for imagetelling and storytelling of the Gyeokryeolbi Yeoldo, known for its important value by exploring the cultural resources of the island. For the research, the ethnography including in-depth local interview and on-site investigation have been applied for 3 years from February 2018 to December 2020 in Taean, Chungnam Province, where the island is located. To analyze the cultural resources of this island, the resource classification model has been designed and used, which is modified from Valentine (2001) and Chi-ho Nam (2007). As a result, the "tangible cultural resources (TCR)" including various remains found on the island were mainly symbols of cultural bridge in the history of Korea-China exchange, and the spiritual land of life-saving. Also "intangible cultural resources (ICR)" extracted from the island were focused on the images of life protection, safety, bravery, and romance. Based on this study, the core concept of identity to be applied when refurbishing the island with a prominent cultural placeness( "sense of place") can be proposed as "a cultural ecological island centered on the Circular Yellow Sea that ruminates memories of love."

• Journal of Korea Entertainment Industry Association
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• v.14 no.8
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• pp.103-116
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• 2020

This paper starts with the recognition of the problem of the need for a link between text-centered acting and body-centered acting. This study is focused on Brecht's theory of acting to overcome loss of presence by repetition which have been discussed many times by not only actors, but also acting educators. Brecht's acting theory has already been mentioned by many researchers as an alternative to conventional actor training. However, not many studies have been conducted on practical applicable methods. The purpose of this study is to provide the basis for the actual practice of Brecht acting and possibility that his acting theory can serve as a link between text and body-centered acting theory. As a research method, we first conduct theoretical considerations on the concepts and limitations of text-centered representational acting and body-centered post-drama acting. Then distinguish between text and body-centered acting tools among Brecht's epic theatre, to summarize the terms and concepts he uses and to identify the existing effects he reaches while acting. Finally, this paper proposes an teaching model that transforms and develops Brecht's acting theory through the writer's teaching experience. However, there are limitations in generalizing its effectiveness because this study is based on the writer's experience. We hope that further research will help the diversity of acting education by developing in-depth insights on Brecht acting theory and various models of acting teaching methods.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1329-1341
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• 2022

Destroying the marine environment and marine ecosystem and causing marine accidents, marine debris is generated every year, and among them, submerged marine debris is difficult to identify and collect because it is on the seabed. Therefore, deep-learning-based semantic segmentation was experimented on waste fish nets and waste ropes using underwater images to identify efficient collection and distribution. For segmentation, a high-resolution network (HRNet), a state-of-the-art deep learning technique, was used, and the performance of each optimizer was compared. In the segmentation result fish net, F1 score=(86.46%, 86.20%, 85.29%), IoU=(76.15%, 75.74%, 74.36%), For the rope F1 score=(80.49%, 80.48%, 77.86%), IoU=(67.35%, 67.33%, 63.75%) in the order of adaptive moment estimation (Adam), Momentum, and stochastic gradient descent (SGD). Adam's results were the highest in both fish net and rope. Through the research results, the evaluation of segmentation performance for each optimizer and the possibility of segmentation of marine debris in the latest deep learning technique were confirmed. Accordingly, it is judged that by applying the latest deep learning technique to the identification of submerged marine debris through underwater images, it will be helpful in estimating the distribution of marine sedimentation debris through more accurate and efficient identification than identification through the naked eye.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1385-1394
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• 2022

This study was to analyze the change in albedo by level-2 land cover map for 20 years(2002-2021) using MODerate resolution Imaging Spectroradiometer (MODIS) data. Also, the difference from the MODIS data was analyzed using the 10-year (2012-2021) data of Visible Infrared Imaging Radiometer Suite (VIIRS). For the albedo data of MODIS and VIIRS, daily albedo data, MCD43A3 and VNP43IA, of 500 m spatial resolution of sinusoidal tile grid produced by Bidirectional Reflectance Distribution Function (BRDF) model were prepared for the South Korea range. Reprojection was performed using the code written based on Python 3.9, and the nearest neighbor was applied as the resampling method. White sky albedo and black sky albedo of shortwave were used for analysis. As a result of 20-year albedo analysis using MODIS data, the albedo tends to rise in all land use. Compared to the 2000s (2002-2011), the average albedo of the 2010s (2012-2021) showed the most significant increase of 0.0027 in the forest area, followed by the grass increase of 0.0024. As a result of comparing the albedo of VIIRS and MODIS, it was found that the albedo of VIIRS was larger from 0.001 to 0.1, which was considered to be due to differences in the surface reflectivity according to the time of image capture and sensor characteristics.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1069-1080
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• 2022

The tropospheric ozone is a pollutant that causes a great deal of damage to humans and ecosystems worldwide. In the event that ozone moves downwind from its source, a localized problem becomes a regional and global problem. To enhance ozone monitoring efficiency, geostationary satellites with continuous diurnal observations have been developed. The objective of this study is to derive the Tropospheric Ozone Movement Vector (TOMV) by employing continuous observations of tropospheric ozone from geostationary satellites for the first time in the world. In the absence of Geostationary Environmental Monitoring Satellite (GEMS) tropospheric ozone observation data, the GEOS-Chem model calculated values were used as synthetic data. Comparing TOMV with GEOS-Chem, the TOMV algorithm overestimated wind speed, but it correctly calculated wind direction represented by pollution movement. The ozone influx can also be calculated using the calculated ozone movement speed and direction multiplied by the observed ozone concentration. As an alternative to a backward trajectory method, this approach will provide better forecasting and analysis by monitoring tropospheric ozone inflow characteristics on a continuous basis. However, if the boundary of the ozone distribution is unclear, motion detection may not be accurate. In spite of this, the TOMV method may prove useful for monitoring and forecasting pollution based on geostationary environmental satellites in the future.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1633-1641
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• 2022

Urban population concentration and indiscriminate development are causing various environmental problems such as air pollution and heat island phenomena, and causing human resources to deteriorate the damage caused by natural disasters. Urban trees have been proposed as a solution to these urban problems, and actually play an important role, such as providing environmental improvement functions. Accordingly, quantitative measurement and analysis of individual trees in urban trees are required to understand the effect of trees on the urban environment. However, the complexity and diversity of urban trees have a problem of lowering the accuracy of single tree detection. Therefore, we conducted a study to effectively detect trees in Dongjak-gu using high-resolution aerial images that enable effective detection of tree objects and You Only Look Once Version 5 (YOLOv5), which showed excellent performance in object detection. Labeling guidelines for the construction of tree AI learning datasets were generated, and box annotation was performed on Dongjak-gu trees based on this. We tested various scale YOLOv5 models from the constructed dataset and adopted the optimal model to perform more efficient urban tree detection, resulting in significant results of mean Average Precision (mAP) 0.663.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.79-85
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• 2022

Anomaly detection is a method to detect and block abnormal data flows in general users' data sets. The previously known method is a method of detecting and defending an attack based on a signature using the signature of an already known attack. This has the advantage of a low false positive rate, but the problem is that it is very vulnerable to a zero-day vulnerability attack or a modified attack. However, in the case of anomaly detection, there is a disadvantage that the false positive rate is high, but it has the advantage of being able to identify, detect, and block zero-day vulnerability attacks or modified attacks, so related studies are being actively conducted. In this study, we want to deal with these anomaly detection mechanisms, and we propose a new mechanism that performs both anomaly detection and classification while supplementing the high false positive rate mentioned above. In this study, the experiment was conducted with five configurations considering the characteristics of various algorithms. As a result, the model showing the best accuracy was proposed as the result of this study. After detecting an attack by applying the Extra Tree and Three-layer ANN at the same time, the attack type is classified using the Extra Tree for the classified attack data. In this study, verification was performed on the NSL-KDD data set, and the accuracy was 99.8%, 99.1%, 98.9%, 98.7%, and 97.9% for Normal, Dos, Probe, U2R, and R2L, respectively. This configuration showed superior performance compared to other models.

• Journal of Biomedical Engineering Research
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• v.43 no.5
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• pp.308-318
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• 2022

The purpose of this study is to evaluate the biomechanical properties of fractured adjacent soft tissue during closed reduction after forearm fracture using the finite element method. To accomplish this, a finite element (FE) model of the forearm including soft tissue was constructed, and the material properties reported in previous studies were implemented. Based on this, nine finite element models with different fracture types and fracture positions, which are the main parameters, were subjected to finite element analysis under the same load and boundary conditions. The load condition simulated the traction of increasing the fracture site spacing from 0.4 mm to 1.6 mm at intervals of 0.4 mm at the distal end of the radioulnar bone. Through the finite element analysis, the fracture type, fracture location, and displacement were compared and analyzed for the fracture site spacing of the fractured portion and the maximum equivalent stress of the soft tissues adjacent to the fracture(interosseous membrane, muscle, fat, and skin). The results of this study are as follows. The effect of the major parameters on the fracture site spacing of the fractured part is negligible. Also, from the displacement of 1.2 mm, the maximum equivalent stress of the interosseous membrane and muscle adjacent to the fractured bone exceeds the ultimate tensile strength of the material. In addition, it was confirmed that the maximum equivalent stresses of soft tissues(fat, skin) were different in size but similar in trend. As a result, this study was able to numerically confirm the damage to the adjacent soft tissue due to the fracture site spacing during closed reduction of forearm fracture.

• The Journal of the Korea Contents Association
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• v.22 no.10
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• pp.225-238
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• 2022

The purpose of this study is to explore the performance characteristics and laws of the symbol mark design of representative regional history museums in China, as well as the preferences of Chinese audiences for the symbol marks of different types of Chinese regional history museums. First, the performance theme, performance type, and type performance tendency of symbol mark modeling of the regional history museums among the top 100 museums in China are analyzed. Second, design laws based on the interrelationship of performance theme types and design performance types are explored. Finally, the questionnaire survey is carried out to explore preference from the aspects of attention, readability, closeness, originality, aesthetics and comprehensiveness. According to the results, the theme of regional history is the most in terms of themes. As for the modeling performance types, the concrete type and the visualization of Chinese character are the most. According to the content characteristics of different performance types, the following model characteristics are formed: expressing the theme of regional history, architecture, and regional natural ecological environment through the concrete type, expressing the concept through the abstract type, and expressing the concept and implying some building features through the geometric abstract figure. The three forms of the literal type, the concrete type expressing architecture, regional history, and regional natural ecological environment theme content, and the abstract type expressing concept are combined with each other, and expressed through the visualization of character, the mixture of abstract and literal type, the mixture of concrete and abstract type, and the mixture of concrete and abstract literal type in the mixture type. According to the survey results, Chinese audiences have higher preference for the concrete type in the symbol mark performance type and the regional historical theme in the performance content.