• Journal of Korean Tunnelling and Underground Space Association
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• v.22 no.5
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• pp.515-528
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• 2020

Underground concrete structures are usually designed to be used for decades, but in recent years, many of them are nearing their original life expectancy. As a result, it is necessary to promptly inspect and repair the structure, since it can cause lost of fundamental functions and bring unexpected problems. Therefore, personnel-based inspections and repairs have been underway for maintenance of underground structures, but nowadays, objective inspection technologies have been actively developed through the fusion of deep learning and image process. In particular, various researches have been conducted on developing a concrete crack detection algorithm based on supervised learning. Most of these studies requires a large amount of image data, especially, label images. In order to secure those images, it takes a lot of time and labor in reality. To resolve this problem, we introduce a method to increase the accuracy of crack area detection, improved by 0.25% on average by applying adversarial learning in this paper. The adversarial learning consists of a segmentation neural network and a discriminator neural network, and it is an algorithm that improves recognition performance by generating a virtual label image in a competitive structure. In this study, an efficient deep neural network learning method was proposed using this method, and it is expected to be used for accurate crack detection in the future.

• Journal of Korea Spatial Information System Society
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• v.12 no.1
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• pp.57-65
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• 2010

In this study, disaster damage investigation system was developed using high resolution satellite images and GIS technique to afford effective damage investigation system for widely disaster damaged area. Study area was selected in Bonghwa, Gyungsangbukdo where high magnitude of damages from torrential rain has occurred at July in 2008. GIS DB was built using 1:5,000 topographic map, cadastral map, satellite image and aerial photo to apply for investigation algorithm. Disaster damage investigation system was developed using VB NET languages, ArcObject component and MS-SQL DBMS for effective management of damage informations. The system can finding damaged area comparing pre- and post-disaster images and drawing damaged area according to the damage item unit. Extracted object was saved in Shape file format and overlayed with background GIS DB for obtaining detail information of damaged area. Disaster damage investigation system using high resolution spatial images can extract damage information rapidly and highly reliably for widely disaster areas. This system can be expected to highly contributing to enhance the disaster prevention capabilities in national level field investigation supporting and establishing recovery plan etc. This system can be utilized at the plan of disaster prevention through digital damage information and linked in national disaster information management system. Further studies are needed to better improvement in system and cover for the linkage of damage information with digital disaster registry.

• The Journal of the Korea Contents Association
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• v.21 no.7
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• pp.45-58
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• 2021

This study aims to select representative performance art visualization projects that react to changes in the culture enjoyment methods and needs of contemporary performance art consumers for performance art culture value creation and vitalization that suit the Fourth Industry and a global age, verify new cultural value creation possibilities of performance projects, and look into important matters and keynotes of production processes. Focusing on the report 'NT Live-Digital broadcast of theatre Learning from the pilot season'(2011), a thorough analysis was conducted on the Royal National Theatre of England, a leading model of cinema broadcast performance visualization projects, including the purpose, production processes (copyright agreements, personnel compositions, filming and broadcasting), marketing methods, and audiences of its "NT Live" project and observations were made of production processes and cultural and artistic values that differ from existing performance art to examine administrative and financial keynotes for the sustainability of performance visualization projects. Through this, possibilities of source creations with artistic, cultural, and economic values that cinema broadcast (live performance broadcast) performance viewing methods have as a new form of performance art products can be verified. In addition, the development of various performance approaches that respond to the culture enjoyment methods and consumption patterns of audiences will result in the vitalization of performing arts visualization projects through the enhancement of popular appeal and the expansion of audience types of the performing arts field.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.85-91
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• 2020

Recently, video-taping equipment such as CCTV have been seeing more use for crime prevention and general safety concerns. Since these video-taping equipment operates all throughout the day, the need for security personnel is lessened, and naturally costs incurred from managing such manpower should also decrease. However, technology currently used predominantly lacks self-sufficiency when given the task of searching for a specific object in the recorded video such as a person, and has to be done manually; current security-based video equipment is insufficient in an environment where real-time information retrieval is required. In this paper, we propose a technology that uses the latest deep-learning technology and OpenCV library to quickly search for a specific person in a video; the search is based on the clothing information that is inputted by the user and transmits the result in real time. We implemented our system to automatically recognize specific human objects in real time by using the YOLO library, whilst deep learning technology is used to classify human clothes into top/bottom clothes. Colors are also detected through the OpenCV library which are then all combined to identify the requested object. The system presented in this paper not only accurately and quickly recognizes a person object with a specific clothing, but also has a potential extensibility that can be used for other types of object recognition in a video surveillance system for various purposes.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.2
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• pp.602-607
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• 2018

The destruction of forests requires continuous management due to the risk of disasters such as landslides and landslides. However, existing forest inspection methods are inefficient as they require a lot of manpower and time. Recently, drones are attracting attention as an effective way to construct and utilize spatial information. The size of the drone-related industrial market is rapidly increasing. In this study, we attempted to increase the efficiency of forest investigation utilizing drones. The study area was photographed through the use of drones, and ortho image and DSM were generated through data processing. Study results found that it was possible to calculate the area and the volume for the forest damaged area effectively by employing drones, and suggested the applicability of drones. In the future, it is expected that the method of analyzing the forested area using drones can save manpower and time compared to existing methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.11
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• pp.2181-2186
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• 2016

Recently, the drone industry rapidly rises to the surface as the new market leading the future, and it seems that the hot UAV drone market shows the similar trend to that of the smartphone. It is expected that the individual application of the drone is quickly diffused as the smartphone roles of camera and game player with the communication medium. For example, the drone is developed mainly as war weapons, but now it is getting close to our real life as the toy or tool for the aerial photography. In this paper, we studied the education for how to bring the aging population to the drone industry. Previously, the controlling skill and taking aerial photography seemed to have nothing to do with citizen seniors. However, we develop the education for try to show any positive relationship between those, in this paper, thus creating more job opportunities for them.

• Korean Journal of Remote Sensing
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• v.24 no.2
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• pp.153-164
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• 2008

According to the economic growth, many highways are constructed for increasing need of better life style. Especially roads and roadside facilities are used for accident prevention and offering mobility for drivers. For these purpose, roads and roadside facilities should be well maintained and managed. Now, many roads and roadside facilities are constructed in many areas. Because of traditional surveying method requires much time and surveying efforts, we designed and developed mobile mapping system for highway maintenance and management purpose using multi sensors. We tested our mobile mapping system and data management process. Using developed database, road managers can easily check the information of facility conditions, positions, and attributes. We are expecting low cost and efficient road maintenance process by using our system.

• Journal of radiological science and technology
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• v.45 no.3
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• pp.213-223
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• 2022

Although the number of computed tomography(CT) is increasing every year, it is insufficient to establish appropriate workload calculation standards of radiologic technologist to provide optimal medical services to patients, such as patient safety management and infection management. The purpose of this study is to present guidelines for calculating the appropriate workload of radiologic technologist by analyzing the work flow of CT procedures and the time required for CT examination in major hospitals. As for the study subjects and methods, the appropriate process for each step of CT examination was investigated to systematically present the process and time required for the actual examination, and the CT procedure time of 104,105 adult patients and 465 pediatric patients under the age of 6 were analyzed. For the time required, data according to the use of contrast medium, procedure type, and adult/child were collected and compared. The test time of CT examination using contrast medium took about 13 minutes when one radiologic technologist worked and about 9 minutes when two radiologic technologists worked. The time required for the procedures were statistically significant depending on the presence or absence of contrast medium, multi-phase procedure, and patient age (considering pediatric patients). As a result, in order to thoroughly perform patient safety and infection management, the appropriate workload increased by about 40% when there were two radiologic technologists. The limit workload was an average of 32 people per day with one radiologic technologist per 15 minutes, and 48 people per day with two radiologic technologist per 10 minutes. This is a marginal workload, and in the case of procedures that require more time to acquire radiographic images, the interval between reservations should be widened.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.8
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• pp.1-8
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• 2020

Air ducts installed for ventilation inside buildings accumulate contaminants during their service life. Robots are installed to clean the air duct at low cost, but they are still not fully automated and depend on manpower. In this study, an intersection detection algorithm for autonomous driving was applied to an air duct cleaning robot. Autonomous driving of the robot was achieved by calculating the distance and angle between the extracted point and the center point through the intersection detection algorithm from the camera image mounted on the robot. The training data consisted of CAD images of the duct interior as well as the cross-point coordinates and angles between the two boundary lines. The deep learning-based CNN model was applied as a detection algorithm. For training, the cross-point coordinates were obtained from CAD images. The accuracy was determined based on the differences in the actual and predicted areas and distances. A cleaning robot prototype was designed, consisting of a frame, a Raspberry Pi computer, a control unit and a drive unit. The algorithm was validated by video imagery of the robot in operation. The algorithm can be applied to vehicles operating in similar environments.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.29-35
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• 2022

This paper proposes a fuel cell education framework installed on a Metaverse environment, which is to reduce the burden of education costs and improve the effect of education or learning. This Meta-Fuel cell platform utilizes the Unity 3D Web and enables not only theoretical education but also hands-on training. The platform was designed and developed to accommodate a variety of unit education contents, such as ppt documents, videos, etc. The platform, therdore, integrates ppt and video demonstrations for theoretical education, as well as software content "STACK-Up" for hands-on training. Theoretical education section provides specialized liberal arts knowledge on hydrogen, including renewable energy, hydrogen economy, and fuel cells. The software "STACK-Up" provides a hands-on practice on assembling the stack parts. Stack is the very core component of fuel cells. The Meta-Fuelcell platform improves the limitations of face-to-face education. It provides educators with the opportunities of non-face-to-face education without restrictions such as educational place, time, and occupancy. On the other hand, learners can choose educational themes, order, etc. It provides educators and learners with interesting experiences to be active in the metaverse space. This platform is being applied experimentally to a education project which is to develop advanced manpower in the fuel cell industry. Its improvement is in progress.