• International conference on construction engineering and project management
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• 2022.06a
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• pp.136-144
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• 2022

Construction sites are characterized by dangerous situations and environments that cause fatal accidents. Potential risk detection needs to be improved by continuously monitoring site conditions. However, the current labor-intensive inspection practice has many limitations in monitoring dangerous conditions at construction sites. Computer vision technology that can quickly analyze and collect site conditions from images has been in the spotlight as a solution. Nonetheless, inspection results obtained via computer vision are still stored and managed in centralized systems vulnerable to tampering with information by the central node. Blockchain has been used as a reliable and efficient decentralized information management system. Despite its potential, only limited research has been conducted integrating computer vision and blockchain. Therefore, to solve the current safety management problems, the authors propose a framework for construction site inspection that integrates object detection and blockchain network, enabling efficient and reliable remote inspection. Object detection is applied to enable the automatic analysis of site safety conditions. As a result, the workload of safety managers can be reduced with inspection results stored and distributed reliably through the blockchain network. In addition, errors or forgery in the inspection process can be automatically prevented and verified through a smart contract. As site safety conditions are reliably shared with project participants, project participants can remotely inspect site conditions and make safety-related decisions in trust.

• Nuclear Engineering and Technology
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• v.52 no.9
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• pp.2009-2016
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• 2020

A nuclear power plant is a large complex system with tens of thousands of components. To ensure plant safety, the early and accurate diagnosis of abnormal situations is an important factor. To prevent misdiagnosis, operating procedures provide the anticipated symptoms of abnormal situations. While the more severe emergency situations total less than ten cases and can be diagnosed by dozens of key plant parameters, abnormal situations on the other hand include hundreds of cases and a multitude of parameters that should be considered for diagnosis. The tasks required of operators to select the appropriate operating procedure by monitoring large amounts of information within a limited amount of time can burden operators. This paper aims to develop a system that can, in a short time and with high accuracy, select the appropriate operating procedure and sub-procedure in an abnormal situation. Correspondingly, the proposed model has two levels of prediction to determine the procedure level and the detailed cause of an event. Simulations were conducted to evaluate the developed model, with results demonstrating high levels of performance. The model is expected to reduce the workload of operators in abnormal situations by providing the appropriate procedure to ultimately improve plant safety.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06b
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• pp.33-36
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• 2011

본 논문에서는 SMART(Self-Monitoring Analysis and Reporting Technology)를 기반으로 SSD(Solid State Drives) 저장 장치의 신뢰성을 분석할 수 있는 방법론과 도구를 제안한다. 방법론은 SSD를 구성하는 플래시 메모리의 결함 종류, 결함들을 효과적으로 모니터링 할 수 있는 SMART 속성과 임계값, 그리고 이를 기반으로 SSD의 신뢰성을 예측할 수 있는 모델로 구성된다. 이 방법론은 신뢰성 분석 도구로 구현 되었으며, 이 도구는 Workload generator, SMART monitor, Dependability analyzer, 그리고 GUI viewer로 구성된다. 실제 두 회사에서 생산한 6개의 SSD를 이용하여 실험한 결과, SMART를 기반으로 SSD의 고장 예측이 가능하며, 여러 속성들을 동시에 고려하였을 때 예측의 정확도가 높아짐을 발견하였다.

• Journal of the Korea Society of Computer and Information
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• v.22 no.7
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• pp.101-108
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• 2017

A wireless image sensor node collecting image data for environmental monitoring or surveillance requires a large amount of energy to transmit the huge amount of video data. Even though solar energy can be used to overcome the energy constraint, since the collected energy is also limited, an efficient energy management scheme for transmitting a large amount of video data is needed. In this paper, we propose a method to reduce the number of blackout nodes and increase the amount of gathered data by selecting an appropriate video coding method according to the energy condition of the node in a solar-powered wireless video sensor network. This scheme allocates the amount of energy that can be used over time in order to seamlessly collect data regardless of night or day, and selects a high compression coding method when the allocated energy is large and a low compression coding when the quota is low. Thereby, it reduces the blackout of the relay node and increases the amount of data obtained at the sink node by allowing the data to be transmitted continuously. Also, if the energy is lower than operating normaly, the frame rate is adjusted to prevent the energy exhaustion of nodes. Simulation results show that the proposed scheme suppresses the energy exhaustion of the relay node and collects more data than other schemes.

• Nuclear Engineering and Technology
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• v.46 no.4
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• pp.489-500
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• 2014

In this study, remote handling strategies for a large-scale argon cell facility were considered. The suggested strategies were evaluated by several types of field test. The teleoperation tasks were performed using a developed remote handling system, which enabled traveling over entire cell area using a bridge transport system. Each arm of the system had six DOFs (degrees of freedom), and the bridge transport system had four DOFs. However, despite the dexterous manipulators and redundant monitoring system, many operators, including professionals, experienced difficulties in operating the remote handling system. This was because of the lack of a strategy for handling the installed camera system, and the difficulty in recognizing the gripper pose, which might fall outside the FOV (field of vision) of the system during teleoperation. Hence, in this paper, several considerations for the remote handling tasks performed in the target facility were discussed, and the tasks were analyzed based on ergonomic factors such as the workload. Toward the development of a successful operation strategy, several ergonomic issues, such as active/passive view of the remote handling system, eye/hand alignment, and FOV were considered. Furthermore, using the method for classifying remote handling tasks, several unit tasks were defined and evaluated.

• Journal of the Korean Society of Marine Environment & Safety
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• v.21 no.3
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• pp.259-265
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• 2015

It is clearly understood that e-navigation is beneficial to prevent collision and grounding of ships. The purpose of this study is to define and present a future ship operation system under the e-navigation environment in order to provide clear direction for the design of Korean e-navigation system. The future ship operation system consists of shipboard navigational system, shore supporting system and maritime communication system. To achieve the objectives of this study, the ship operation system was discussed separately into SOLAS ships and non-SOLAS ships in this study. In SOLAS ships, mariners become a system manager, choosing system presets, interpreting system output, and monitoring vessel response. In small ships and fishing vessels, mariners may enjoy their navigation by using the automatic tracking of ship's position on the portable electronic chart display. The improved bridge design, integrated and harmonized navigational system and single window reporting will reduce significantly the administrative and physical workload of mariners. Mariners can concentrate their attention more on navigational duty under the e-navigation environment. To build an effective Korean e-navigation system, the essential navigational functions and e-navigation services for small ships and fishing vessels must be identified and developed taking into account user needs.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.17 no.2
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• pp.62-67
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• 2009

LOSA is a flight safety program that analyses human errors in normal operations. Trained pilot observers monitor the normal flights at the observer seat. LOSA is a proactive non jeopardy data collection tool using threat and error management(TEM) as a framework. With the analysis of crew behaviors through LOSA with The LOSA collaborative(TLC), the airlines can identify the behaviors of the crew during normal operations. The major objective of LOSA is to measure how the crew manage threats, errors and undesired aircraft deviations in the cockpit on day to day operations. The airlines are able to set up effective TEM training with practical six generation Crew recourse management(CRM) with data of error from LOSA instead of theoretical CRM courses. The Airlines can use TEM as an integral part of a Safety Management System(SMS) and uses monitoring and cross-checking skills in the flight operations to manage threats and errors effectively when we know the errors we make in the cockpit on daily operation. The result of LOSA indicates that the error detection rate should be enhanced since around the half of the errors went undetected. The areas which should be focused for enhancing the error detection are monitor, cross-check, the management of workload, automation and taxiway/ runway to manage errors effectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4572-4586
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• 2019

Mobile Edge Computing (MEC) and Information-Centric Networking (ICN) are essential network architectures for the future Internet. The advantages of MEC and ICN such as computation and storage capabilities at the edge of the network, in-network caching and named-data communication paradigm can greatly improve the quality of video streaming applications. However, the packet loss in wireless network environments still affects the video streaming performance and the existing loss recovery approaches in ICN does not exploit the capabilities of MEC. This paper proposes a Deep Learning based Loss Recovery Mechanism (DL-LRM) for video streaming over MEC based ICN. Different with existing approaches, the Forward Error Correction (FEC) packets are generated at the edge of the network, which dramatically reduces the workload of core network and backhaul. By monitoring network states, our proposed DL-LRM controls the FEC request rate by deep reinforcement learning algorithm. Considering the characteristics of video streaming and MEC, in this paper we develop content caching detection and fast retransmission algorithm to effectively utilize resources of MEC. Experimental results demonstrate that the DL-LRM is able to adaptively adjust and control the FEC request rate and achieve better video quality than the existing approaches.

• East Asian Journal of Business Economics (EAJBE)
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• v.10 no.4
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• pp.29-38
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• 2022

Purpose - The present research aims to assess the meaningful association between the extension of sports leisure culture and the spread of wearable devices. The research will discuss the current utilization of wearable devices in sports leisure and the present and future application of wearable devices in sports perspectives. Research design, Data, and methodology - We have investigated and conducted the qualitative content analysis (QCA) to obtain the adequate textual dataset in the current literature and conducted an in-depth analysis of the incorporation of cloud computing in the leisure sports industry by focusing on the development of wearable technologies. Result - From the QCA, it is evident that there is a meaningful connection between the extension of sports leisure culture and the spread of wearable devices, figuring out four kinds of associations as follows: (1) Monitoring the Impact of Sporting Activities, (2) Benefits of Sensor Technology, (3) Reducing Sedentary Behaviors, and (4) Measuring Workload done in Sport Leisure. Conclusion - The present research concludes that wearable devices positively influence individuals to participate in sports and leisure activities. Various technologies are very effective in motivating individuals to adopt sports leisure culture mainly because there is a certain degree of satisfaction that individuals gain in seeing the level of physical activities.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.3D
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• pp.457-468
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• 2011

Recently, the non-vibration mass excavation method is used on sewage pipes and road construction sites in Jeju. However, a construction cost estimation based on the unit quantity does not provide a proper unit price. In this study, a comparison of the productivity of the standard quantity-per-unit costing method and the one of the work crew combination method was made based on the site monitoring of the non-vibration mass excavation method that is used in construction sites near Jeju. For this, data of 35 sites were collected: a regression equation was derived from the 30 data, and verification was carried out through the remaining 5 data. The analysis concluded that a day's workload is $16.43m^3$. In addition, a combination of the equipment considering the site conditions and the amount of labor, which varies with the number of work crew was obtained in order to estimate the construction cost of the work crew combination method. The construction cost was calculated based on the one-day workload ($16.43m^3$) derived from the regression analysis. The cost then was analyzed and compared with the standard quantity-per-unit costing method.