• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.773-784
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• 2019

With the recent development of 4th industrial revolution technology, BIM information systems are spreading to civil engineering fields as a link to this technology. Accordingly, the Land, Infrastructure and Transport Ministry is announcing a technical policy to introduce the BIM information system into the construction sector from 2020. Usually, SOC-related facilities are complex, making it difficult to implement BIM without a standards framework. To overcome these problems, it is urgent to develop a BIM standard classification system. In this study, the BIM property classification system was developed to link the previously developed object classification system by analyzing domestic and foreign prior studies and working standards. This includes property information of businesses, facilities, parts of facilities and components that correspond to the level of object composition in the road and river sectors. It also suggested ways to apply expansion to various SOC areas and to organize spatial information by facility. The results of this study were applied to road facilities to verify the possibility of information building. The development of the BIM Standards Classification System through this R&D will contribute to the development of construction IT by providing conditions for convenient modeling and information system.

• Journal of the Korea Computer Graphics Society
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• v.25 no.3
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• pp.11-20
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• 2019

In this study, a novel virtual reality (VR) experience environment is proposed for enabling walking adaptation of visually impaired people. The core of proposed VR environment is based on immersive walking interactions and deep learning based braille blocks recognition. To provide a realistic walking experience from the perspective of visually impaired people, a tracker-based walking process is designed for determining the walking state by detecting marching in place, and a controller-based VR white cane is developed that serves as the walking assistance tool for visually impaired people. Additionally, a learning model is developed for conducting comprehensive decision-making by recognizing and responding to braille blocks situated on roads that are followed during the course of directions provided by the VR white cane. Based on the same, a VR application comprising an outdoor urban environment is designed for analyzing the VR walking environment experience. An experimental survey and performance analysis were also conducted for the participants. Obtained results corroborate that the proposed VR walking environment provides a presence of high-level walking experience from the perspective of visually impaired people. Furthermore, the results verify that the proposed learning algorithm and process can recognize braille blocks situated on sidewalks and roadways with high accuracy.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2019.05a
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• pp.230-231
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• 2019

This study is a development on condition based maintenance(CBM) technology which is a core item of future autonomous ships. It is developing to design & installation of condition monitoring system and acquisition & processing of data from ongoing ships for fault prediction & prognosis of engine in operation. The ultimate goal of this study is to develop a predicts and decision support software for marine engine faults. To do this, the FMEA and fault tree analysis of the main engine should be accompanied by the analysis of classification of system, identification of the components, the type of faults, and the cause and phenomenon of the failure. Finally, the CBM system solution software could predict and diagnose the failure of main engine through integrated analysis for bid-data of ongoing ships and engineering knowledge. Through this study, it is possible to pro-actively cope with abnormal signals of engine and to manage efficiently, and as a result, expected that marine accident and ship operation loss during navigation will be prevented in advance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.464-466
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• 2019

Controllers used in nuclear power plants require high reliability. A controller including a Field Programmable Gate Array (FPGA) and a Complex Programmable Logic Device (referred to hereinafter as FPGA) has been applied to many Nuclear Power Plants (NPP) in the past, including the APR1400 (Advanced Power Reactor 1400), a Korean digital nuclear power plant. Initially, the FPGA was considered as a general IC (Integrated Circuit) and verified only by device verification and performance testing. In the 1990s, research on FPGA verification began, and until the FPGA became a chip, it was regarded as software and the software Verification and Validation (V&V) using IEEE 1012-2004 was implemented. Currently, IEC 62566, which is a European standard, has been applied for a lot of verification. This method has been evaluated as the most sensible method to date. This is because the method of verifying the characteristics of SoC (System on Chip), which has been a problem in the existing verification method, is sufficiently applied. However, IEC 62566 is a European standard that has not yet been adopted in the United States and maintains the application of IEEE 1012 for FPGA. IEEE 1012-2004 or IEC 62566 is a technical standard. In practice, various methods are applied to meet technical standards. In this paper, we describe the procedure and important points of verification method of Nuclear Safety Class FPGA applying SoC verification method.

• Journal of Internet of Things and Convergence
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• v.8 no.6
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• pp.49-54
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• 2022

Rapid changes in modern society after the COVID-19 have highlighted artificial intelligence talent as a major influencing factor in determining national competitiveness. Accordingly, the Ministry of Education planned a large-scale SW·AI camp education project to develop the digital capabilities of 4th to 6th grade elementary school students and middle and high school students who are in a vacuum in artificial intelligence education. Therefore, this study aims to develop a camp-type SW·AI education program for students in grades 4-6 of elementary school so that students in grades 4-6 of elementary school can acquire basic knowledge in artificial intelligence. For this, the meaning of SW·AI education in elementary school is defined and SW·AI contents to be dealt with in elementary school are: understanding of SW AI, 'principle and application of SW AI', and 'social impact of SW AI' was set. In addition, an attempt was made to link the set elements of elementary school SW AI education and learning with related subjects and units of textbooks currently used in elementary schools. As for the program used for education, entry, a software coding learning tool based on block coding, is designed to strengthen software programming basic competency, and all programs are designed to be operated centered on experience and experience-oriented participants in consideration of the developmental characteristics of elementary school students. In order for SW·AI education to be organized and operated as a member of the regular curriculum, it is suggested that research based on the analysis of regular curriculum contents and in-depth analysis of SW·AI education contents is necessary.

• Imaging Science in Dentistry
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• v.51 no.2
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• pp.117-127
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• 2021

Purpose: The aim of this study was to evaluate the volumetric characteristics of mucous retention cysts(MRCs) in the maxillary sinus and to analyze potential associations of MRCs with dentoalveolar pathologies. Materials and Methods: Cone-beam computed tomography (CBCT) scans exhibiting bilateral maxillary sinuses that were acquired from January 2016 to February 2019 were initially screened. A total of 227 scans(454 sinuses) that fulfilled the inclusion criteria were included. The presence, location, and volumetric characteristics of the diagnosed MRCs were evaluated on CBCT images using the 3D-Slicer software platform. The presence of MRCs was correlated with potential influencing factors including age, sex, and dentoalveolar pathology. For MRCs located on the sinus floor, factors with a potential impact on the volume, surface, and diameter were analyzed. Results: An MRC was present in 130 (28.6%) of the 454 sinuses. Most MRCs were located on the sinus walls and floor. The mean MRC volume, surface, and diameter were 551.21±1368.04 mm³, 228.09±437.56 mm², and 9.63±5.40 mm, respectively. Significantly more sinuses with associated endodontically treated teeth/periapical lesions were diagnosed with an MRC located on the sinus floor. For MRCs located on the sinus floor, endodontic status exhibited a significant association with increased volume, surface, and diameter. Conclusion: Periapical lesions might be a contributing factor associated with the presence and volume of MRCs located on the sinus floor. The 3D-Slicer software platform was found to be a useful tool for clinicians to analyze the size of MRCs before surgical interventions such as sinus floor elevation procedures.

• Journal of Navigation and Port Research
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• v.46 no.3
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• pp.269-279
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• 2022

With the development of artificial intelligence, artificial intelligence is being introduced to automate systems throughout the industry. In the maritime industry, artificial intelligence is being applied step by step, through the paradigm of autonomous ships. In line with this trend, ABS and DNV have published guidelines for autonomous vessels. However, there is a possibility that the risk of artificial intelligence has not been sufficiently considered, as the classification guidelines describe the requirements from the perspective of ship operation and marine service. Thus in this study, using the standards established by the ISO/ IEC JTC1/SC42 artificial intelligence division, classification requirements are classified as the causes of risk, and a measure that can evaluate risks through the combination of risk causes and artificial intelligence metrics want to use. Through the combination of the risk causes of artificial intelligence proposed in this study and the characteristics to evaluate them, it is thought that it will be beneficial in defining and identifying the risks arising from the introduction of artificial intelligence into the marine system. It is expected that it will enable the creation of more detailed and specific safety requirements for autonomous ships.

• Tunnel and Underground Space
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• v.32 no.2
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• pp.120-130
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• 2022

In this study, the applicability of the microseismic monitoring system based on the underground mine communication system has been verified by operation test in the domestic underground mine. The microseismic data consists of wavelet data and meta-data for mine safety management, and both data should be transferred, stored, analyzed and managed with proper method according to the purpose and size of each data. In order to select the optimal communication system for the microseismic monitoring system considering the underground environment as well as properties of data, various types of communication system have been tested and compared during operation test after installing the optical cable communication system, 2.4 GHz and 900 MHz wireless communication system through the underground mine tunnel and overground area of the test site. The integrated microseismic monitoring software, which was developed to secure the stability of data management and ease of use, has been updated according to findings from operation test. Through the operation test of the microseismic monitoring system including the communication system and the monitoring software, the technical basis was established corresponding to various requirements of the domestic mine for adoption of the microseismic monitoring system.

• 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.

• Journal of Internet Computing and Services
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• v.23 no.4
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• pp.57-64
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• 2022

If the inside of a building collapses due to a disaster such as fire, collapse, or natural disaster, the physical security inside the building is likely to become ineffective. Here, physical security is needed to minimize the human casualties and physical damages in the collapsed building. Therefore, this paper proposes an algorithm to minimize the damage in a disaster situation by fusing existing research that detects obstacles and collapsed areas in the building and a deep learning-based object detection algorithm that minimizes human casualties. The existing research uses a single camera to determine whether the corridor environment in which the robot is currently located has collapsed and detects obstacles that interfere with the search and rescue operation. Here, objects inside the collapsed building have irregular shapes due to the debris or collapse of the building, and they are classified and detected as obstacles. We also propose a method to detect rescue requesters-the most important resource in the disaster situation-and minimize human casualties. To this end, we collected open-source disaster images and image data of disaster situations and calculated the accuracy of detecting rescue requesters in disaster situations through various deep learning-based object detection algorithms. In this study, as a result of analyzing the algorithms that detect rescue requesters in disaster situations, we have found that the YOLOv4 algorithm has an accuracy of 0.94, proving that it is most suitable for use in actual disaster situations. This paper will be helpful for performing efficient search and rescue in disaster situations and achieving a high level of physical security, even in collapsed buildings.