• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.5
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• pp.9-13
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• 2009

Modal parameters including resonant frequencies and mode shapes are heavily utililized in most damage identification throries for structural health monitoring. However, extracting modal parameters from dynamic responses needs postprocessing which inevitably involves errors in curve-fitting resonants as well as transforming the domain of responses. In this paper, the applicability of a damage identification method based on free vibration responses to the in-sevice responses is experimentally verified. The experiment is performed via applying periodic and nonperiodic moving loads to a simply supported beam and displacement responses are measured. The moving load is simulated using steel balls and a downhill device. The damage identification results show that the in-service response may be applicable to identifying damage in the beam.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.29 no.2
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• pp.55-66
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• 2021

ICAO recommended that airspace monitoring and periodic safety assessments in each Contracting State ensure the stability of the airspace, since reducing the aircraft lateral and vertical separation intervals would rather increase the risk of collision. The target level of safety of the AKARA-FUKUE Corridor at the southern end of Jeju was 247×10^-9. In simple comparison, this means that the risk of an aircraft collision in this area (international safety standards, 5.0×10^-9) is about 50 times higher. The scope of this study is to organize the concept of terms, analyze the air traffic volume, the current status of navigational safety facility usage fees, and investigations of an aircraft collision risk in Jeju southern air corridor. Analyzing government policies and overseas evaluations, revising some of the existing contents, presenting some of the additional contents of new routes, and changing the instrument procedure for Korean-Chinese routes, change of arrive/departure route between Incheon Airport and Shanghai Airport, reduce the risk of aircraft collisions. We hope to restore airspace sovereignty, contribute to policies for the government to take the lead in solving this problem, and expect stability and operational efficiency in air traffic.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.33 no.3
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• pp.375-383
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• 2023

Objectives: Coal-fired power plants feature diverse working conditions, including multi-layered employment structures and irregular work cycles due to outsourcing and non-standardized tasks. The current uniform occupational environment measurement systems have limitations in accurately assessing and evaluating these varied conditions. This study aims to propose alternative measurement and assessment strategies to supplement existing methods. Methods: Major domestic coal-fired power plants were selected as the study targets. To prepare for the study and establish strategies, work processes were identified and existing occupational environment measurement results were compared and analyzed. The study proceeded by employing three strategies: specific exposure groups (SEGs) measurement, continuous monitoring, and supplementary measurements, which were then compared and discussed. Results: Previous exposure index evaluations (5,268 cases) indicated that crystalline silica, a type of respirable particulate matter, had detection limits below the threshold (non-detectable) in 82.6% (4,349 cases) of instances. Exposures below 10% of the exposure limit were observed at a very low concentration of 96.1%. Similar exposure group measurements yielded results where detection limits were below the threshold in 38.2% of cases, and exposures below 10% of the limit were observed in 70.6%. Continuous monitoring indicated detection limits below the threshold in 12.6% of cases, and exposures below 10% of the limit were observed in 75.6%. Instances requiring active workplace management accounted for more than 30% of cases, with SEGs at 11.8% (four cases), showing a higher proportion compared to 3.0% (four cases) in continuous monitoring. For coal dust, exposures below 10% of the limit were highest in legal measurements at 90.2% (113 cases), followed by 74.0% (91 cases) in continuous monitoring, and 47.0% (16 cases) in SEGs. Instances exceeding 30% were most prevalent in SEGs at 14.7% (five cases), followed by legal measurements at 5.0% (eight cases), and continuous monitoring at 2.4% (three cases). When examining exposure levels through arithmetic means, crystalline silica was found to be 104.7% higher in SEGs at 0.0088 mg/m³ compared to 0.0043 mg/m³ in continuous monitoring. Coal dust measurements were highest in SEGs at 0.1247 mg/m³, followed by 0.1224 mg/m³ in legal measurements, and 0.0935 mg/m³ in continuous monitoring. Conclusions: Strategies involving SEGs measurement and continuous monitoring can enhance measurement reliability in environments with irregular work processes and frequent fluctuations in working conditions, as observed in coal-fired power plants. These strategies reduce the likelihood of omitting or underestimating processes and enhance measurement accuracy. In particular, a significant reduction in detection limits below the threshold for crystalline silica was observed. Supplementary measurements can identify worker exposure characteristics, uncover potential risks in blind spots of management, and provide a complementary method for legal measurements.

• Journal of Cadastre & Land InformatiX
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• v.52 no.1
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• pp.17-36
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• 2022

The purpose of this study is to diagnose problems in the regulation and management of Restricted Development Zone and to prepare a construction plan to convert it to a data-based monitoring system. Unlike other land-use zones, the Restricted Development Zone is a exceptional zone that prohibits all development activities other than the minimum maintenance and must be strictly controlled and managed by the local government. However, the current Restricted Development Zone management is distributed according to the conditions of each local government, and it is not possible to monitor changes in the entire Restricted Development Zone as shown in the survey results. In particular, in this study, by introducing an AI-based monitoring system, MOLIT sends the results of detecting changes across the country at regular time points(monthly and quarterly) to the local governments based on the same regulation standards, and the local governments can be trusted while inputting the regulation results into the system. To propose this methodology, first, a survey and interview were conducted with local government officials and experts. Second, we analyzed cases in which AI analysis was applied to local governments and proposed a plan to improve the efficiency of regulation work according to the introduction of the monitoring system. Third, a plan was prepared to establish a monitoring system based on the advancement of the management information system. This monitoring system can be expanded and applied to land that needs periodic regulation and management in the future, and this study tried to propose a methodology and policy for this.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.22 no.6
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• pp.63-76
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• 2019

UAVs are unmanned, autonomous or remotely piloted aircraft. As UAVs become smaller, lighter and more economical, their applications continue to expand. Researches on UAVs in the field of remote sensing show development methods and purposes similar to those on satellite images, and they are widely used in studies such as 3D image composition and monitoring. In the field of environmental impact assessment(EIA), satellite information and data are mainly used. However, only low-resolution images covering long distances and large-scale data allowing for rough examination are being provided, so their uses are seriously limited. Therefore, in this paper, we construct spatial information of forest area by using unmanned aerial vehicle and seek efficient utilization and policy improvement in the field of environmental impact assessment. As a result, high-resolution images and data from UAVs can be used to identify the location status of SEIA, EIA, and small scale EIA project plans and to evaluate detailed environmental impact analysis. In addition, when provided together with infographics about Post-environmental impact investigation, it was confirmed that the possibility of periodic spatial information construction and evaluation can be used throughout the entire project contents and project post-process.In order to provide sophisticated infographics for the EIA, drone photography and GCP surveying methods were derived.The results of this study will be used as a basis for improving high-resolution monitoring and environmental impact assessment in the forest sector.

• Nuclear Engineering and Technology
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• v.42 no.2
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• pp.219-230
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• 2010

In nuclear power plants (NPPs), periodic sensor calibrations are required to assure that sensors are operating correctly. By checking the sensor's operating status at every fuel outage, faulty sensors may remain undetected for periods of up to 24 months. Moreover, typically, only a few faulty sensors are found to be calibrated. For the safe operation of NPP and the reduction of unnecessary calibration, on-line instrument calibration monitoring is needed. In this study, principal component-based auto-associative support vector regression (PCSVR) using response surface methodology (RSM) is proposed for the sensor signal validation of NPPs. This paper describes the design of a PCSVR-based sensor validation system for a power generation system. RSM is employed to determine the optimal values of SVR hyperparameters and is compared to the genetic algorithm (GA). The proposed PCSVR model is confirmed with the actual plant data of Kori Nuclear Power Plant Unit 3 and is compared with the Auto-Associative support vector regression (AASVR) and the auto-associative neural network (AANN) model. The auto-sensitivity of AASVR is improved by around six times by using a PCA, resulting in good detection of sensor drift. Compared to AANN, accuracy and cross-sensitivity are better while the auto-sensitivity is almost the same. Meanwhile, the proposed RSM for the optimization of the PCSVR algorithm performs even better in terms of accuracy, auto-sensitivity, and averaged maximum error, except in averaged RMS error, and this method is much more time efficient compared to the conventional GA method.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.10
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• pp.941-948
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• 2016

In this paper, we efficiently simulated for collecting the data from the fixed sensor and mobile sensor of patients using the LEACH-Mobile method. The LEACH-Mobile method is the protocol to increase the mobility by adding the mobile node to the existed LEACH(:Low Energy Adaptive Clustering Hierarchy) protocol. It improves the mobility of The LEACH-Mobile in the LEACH, however it consumes more energy than the existed LEACH. There is reason why we use the LEACH-Mobile that the monitoring system is generally done by the CCTV and an periodic checkup by nurses. However the number of nurse is a few in the most of hospital. It can happen the accidents of the patients in out of the CCTV when the nurse can not see the monitoring system in the hospital. Therefore it is simulated to continuously gather the data of the position and sensors in the five situation of moving the patients in the hospital, it gets the result that the management of the mobile patients is more efficient.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.5
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• pp.1151-1160
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• 2016

A TrustZone-based rootkit detecting solution using a secure timer ensures the integrity of monitoring system, because ARM TrustZone technology provides isolated environments from a monitored OS against intercepting and modifying invoke commands. However, it is vulnerable to transient attack due to periodic monitoring. Also, Address Translation Redirection Attack (ATRA) cannot be detected, because the monitoring is operated by using the physical address of memory. To ameliorate this problem, we propose a snoop-based kernel introspection system. The proposed system can monitor a kernel memory in real-time by using a snooper, and detect memory-bound ATRA by introspecting kernel pages every context switch of processes. Experimental results show that the proposed system successfully protects the kernel memory without incurring any significant performance penalty in run-time.

• Journal of Korean Society of Steel Construction
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• v.23 no.2
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• pp.159-167
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• 2011

Steel structure construction is currently increasing on account of the many merits of steel structures. Due to numerous environmental factors, many cracks and extensive corrosion occur in steel structures, which cause the deterioration of the performance and life cycle of such structures. Maintenance of steel structures is thus strongly demanded, for safety control. The inspection methods that are currently being used, however, are very limited and can detect only local defects in steel structures. They also take much time to use and incur high maintenance costs. Moreover, such methods cannot be applied to huge steel structures, which men find unapproachable. They also require much time due to the need for periodic checks, and may lead to cost loss. Therefore, the development of a monitoring system that can detect defects in whole structures and can reduce the repair and strengthening costs at an early stage is very much needed. In this study, the generation and propagation of cracks were monitored via the electric-potential-drop method (EPDM).

• Journal of Cadastre & Land InformatiX
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• v.53 no.1
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• pp.107-121
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• 2023

In order to acquire a wide range of land that changes in real time and quickly and accurately grasp it, we plan to utilize the recently released high-resolution S.Korea's satellite image data and artificial intelligence (AI). Compared to existing satellite images, the spectral and periodic resolutions of S.Korea's satellite are higher, making them a more suitable data source for periodically monitoring changes in land. Therefore, this study aims to acquire S.Korea's satellite, select 8 types of objects to detect land changes, construct data sets for them, and apply AI models to analyze them. In order to confirm the optimal model and variable conditions for detecting 8 types of objects of various types, several experiments are performed and AI-based image analysis is technically reviewed.