• Journal of Aerospace System Engineering
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• v.17 no.4
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• pp.67-74
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• 2023

Recently, Urban Aircraft Mobility (UAM) has been attracting attention as a transportation system of the future, and small drones also play a role in various industries. The failure of various types of aviation systems can lead to crashes, which can result in significant property damage or loss of life. In the defense industry, where aviation systems are widely used, the failure of aviation systems can lead to mission failure. Therefore, this study proposes an anomaly detection model using deep learning technology to detect anomalies in aviation systems to improve the reliability of development and production, and prevent accidents during operation. As training and evaluating data sets, current data from aviation systems in an extremely low-temperature environment was utilized, and a deep learning network was implemented using the convolutional neural network, which is a deep learning technique that is commonly used for image recognition. In an extremely low-temperature environment, various types of failure occurred in the system's internal sensors and components, and singular points in current data were observed. As a result of training and evaluating the model using current data in the case of system failure and normal, it was confirmed that the abnormality was detected with a recall of 98 % or more.

• The Journal of Society for e-Business Studies
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• v.27 no.2
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• pp.65-77
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• 2022

Due to the recent development in electronic financial services, transactions of electronic prepayment are rapidly growing, leading to growing fraud attempts. This paper proposes a methodology that can effectively detect fraud transactions in electronic prepayment by machine learning algorithms, including support vector machines, decision trees, and artificial neural networks. Actual transaction data of electronic prepayment services were collected and preprocessed to extract the most relevant variables from raw data. Two different approaches were explored in the paper. One is a transaction-based approach, and the other is a user ID-based approach. For the transaction-based approach, the first model is primarily based on raw data features, while the second model uses extra features in addition to the first model. The user ID-based approach also used feature engineering to extract and transform the most relevant features. Overall, the user ID-based approach showed a better performance than the transaction-based approach, where the artificial neural networks showed the best performance. The proposed method could be used to reduce the damage caused by financial accidents by detecting and blocking fraud attempts.

• Korean Journal of Remote Sensing
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• v.39 no.3
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• pp.311-323
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• 2023

Oil spill accidents can cause various environmental issues, so it is important to quickly assess the extent and changes in the area and location of the spilled oil. In the case of oil spill detection using satellite imagery, it is possible to detect a wide range of oil spill areas by utilizing the information collected from various sensors equipped on the satellite. Previous studies have analyzed the reflectance of oil at specific wavelengths and have developed an oil spill index using bands within the specific wavelength ranges. When analyzing multiple images before and after an oil spill for monitoring purposes, a significant amount of time and computing resources are consumed due to the large volume of data. By utilizing Google Earth Engine, which allows for the analysis of large volumes of satellite imagery through a web browser, it is possible to efficiently detect oil spills. In this study, we evaluated the applicability of four types of oil spill indices in the area of various land cover using Sentinel-2 MultiSpectral Instrument data and the cloud-based Google Earth Engine platform. We assessed the separability of oil spill areas by comparing the index values for different land covers. The results of this study demonstrated the efficient utilization of Google Earth Engine in oil spill detection research and indicated that the use of oil spill index B ((B3+B4)/B2) and oil spill index C (R: B3/B2, G: (B3+B4)/B2, B: (B6+B7)/B5) can contribute to effective oil spill monitoring in other regions with complex land covers.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.2
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• pp.188-196
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• 2023

Among marine accidents caused by bad weather, visibility restrictions caused by sea fog occurrence cause accidents such as ship strand and ship bottom damage, and at the same time involve casualties caused by accidents, which continue to occur every year. In addition, low visibility at sea is emerging as a social problem such as causing considerable inconvenience to islanders in using transportation as passenger ships are collectively delayed and controlled even if there are local differences between regions. Moreover, such measures are becoming more problematic as they cannot objectively quantify them due to regional deviations or different criteria for judging observations from person to person. Currently, the VTS of each port controls the operation of the ship if the visibility distance is less than 1km, and in this case, there is a limit to the evaluation of objective data collection to the extent that the visibility of sea fog depends on the visibility meter or visual observation. The government is building a marine weather signal sign and sea fog observation networks for sea fog detection and prediction as part of solving these obstacles to marine traffic safety, but the system for observing locally occurring sea fog is in a very insufficient practical situation. Accordingly, this paper examines domestic and foreign policy trends to solve social problems caused by low visibility at sea and provides basic data on the need for government support to ensure maritime traffic safety due to sea fog by factually investigating and analyzing social problems. Also, this aims to establish a more stable maritime traffic operation system by blocking marine safety risks that may ultimately arise from sea fog in advance.

• Analytical Science and Technology
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• v.33 no.3
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• pp.151-158
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• 2020

Alcohol, which can easily be obtained in the same way as ordinary beverages, is harmful enough to cause death due to excessive drinking and chronic alcohol intake, so it is important to maintain a proper amount of drinking and healthy drinking habits. In addition, the incidence of behavioral disturbances and impaired judgments that can be caused by chronic alcohol drinking of more than adequate amounts of alcohol is also significant. Accordingly it is very useful for forensic science to check whether the person involved is drunken or is alcoholism state in various accidents. Currently, in Korea, alcohol consumption is determined by detecting the level of alcohol or alcohol metabolism 'ethyl glucuronide (EtG)' in blood or urine samples. However, analysis of alcohol or EtG in blood or urine can only provide information about the current state of alcohol consumption because of a narrow window of detection time. Therefore, it is important to analyze the EtG as a long-term direct alcohol metabolite bio-marker in human hair and to investigate relationship between alcohol consumption and EtG concentration for the evaluation of chronic ethanol consumption. In this study, we established an analytical method for the detection of EtG in Korean hair efficiently and validated selectivity, linearity, limits of detection (LOD), limits of quantification (LOQ), matrix effect, recovery, process efficiency, accuracy and precision using liquid chromatography tandem mass spectrometry (LC-MS/MS). In addition, the assay performance was evaluated in Korean social drinker's hair and the postmortem hair of a chronic alcoholism. The results of this study can be useful in monitoring the alcohol abuse of Korean in clinical cases and legal procedures related to custody and provide a useful tool to evaluate postmortem diagnosis of alcoholic ketoacidosis in forensics.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1773-1784
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• 2021

In order to minimize damage to oil spill accidents in the ocean, it is essential to collect a spilled area as soon as possible. Thus satellite-based remote sensing is a powerful source to detect oil spills in the ocean. With the recent rapid increase in the number of available satellites, it has become possible to generate a status report of marine oil spills soon after the accident. In this study, the oil spill area was calculated using various satellite images for the Symphony oil spill accident that occurred off the coast of Qingdao Port, China, on April 27, 2021. In particular, improving the accuracy of oil spill area determination was applied using high-resolution commercial satellite images with a spatial resolution of 2m. Sentinel-1, Sentinel-2, LANDSAT-8, GEO-KOMPSAT-2B (GOCI-II) and Skysat satellite images were collected from April 27 to May 13, but five images were available considering the weather conditions. The spilled oil had spread northeastward, bound for coastal region of China. This trend was confirmed in the Skysat image and also similar to the movement prediction of oil particles from the accident location. From this result, the look-alike patch observed in the north area from the Sentinel-1A (2021.05.01) image was discriminated as a false alarm. Through the survey period, the spilled oil area tends to increase linearly after the accident. This study showed that high-resolution optical satellites can be used to calculate more accurately the distribution area of spilled oil and contribute to establishing efficient response strategies for oil spill accidents.

• Journal of the Society of Disaster Information
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• v.14 no.1
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• pp.89-100
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• 2018

when the explosive wastes to be treated as designated wastes are brought into the wastes treatment plant by mistake and lead to an explosion in the wastes disposal process, many people and property damage are involved. Waste should be treated properly. As mentioned in this paper, ignition reac- tion tests of ignitable re-burning of explosives packing material waste (solid butadiene) confirmed that ignition was easily occurred, and that even small ignition sources were easily ignited and burned quickly and explosively. In particular, when explosives are loaded into incineration wastes in large quantities and mixed with organic compound wastes, such as fire and explosion accidents caused by explosives packing materials at waste disposal sites, flammable and oxidative gases are generated due to mutual oxidation and pyrolysis It is confirmed that there is a possibility that ignition sources such as spark ignite and instantaneously lead to explosion. It is hoped that this study will be a small reference for on - site detection in the field of fire, and it is expected that the fire - fighting agency will be recognized as a fire investigation agency and will contribute to the improvement of the credibility.

• Korean Journal of Environmental Biology
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• v.29 no.4
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• pp.373-378
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• 2011

Our aim was to investigate the genotoxicity of ambient air in the Krak$\acute{o}$w area after Fukushima Nuclear Power Plant (NPP) accident and compare with results from Chernobyl fallout. For the detection of ambient air genotoxicity the technique for screening gene mutation frequency in somatic cells of the $Tradescantia$ stamen hairs ($Trad$-SH assay) was used. Since 11th of March 2011 (Fukushima NPP accident), several pots containing at least 15 shoots of bioindicating plants were exposed to ambient air at 2 sites in the Krak$\acute{o}$w surrounding area, one in the city center, and about 100 pots in a control site (in the glasshouse of the Institute of Nuclear Physics) Continuous screening of mutations was performed. Progenies of 371,090 cells exposed were analyzed. Mutation frequency obtained in the first 10 days has shown a mean control level (GMF*100=$0.06{\pm}0.01$). At scoring period related to influence of a potential Fukushima fallout, a significant increase of gene mutation frequencies above the control level was observed at each site in the range, 0.10~0.33 depending on the location, (mean value for all sites GMF*100=$0.19{\pm}0.05$) that was associated with a strong expression of toxic effects. In the reported studies following the Chernobyl NPP accident monitoring $in$ $situ$ of the ambient air genotoxicity was performed in the period since April $29^{th}$ till June $3^{rd}$ 1986 also with Trad-SH bioindicator. In general, mutation frequency increases due to Chernobyl fallout(GMF*100=$0.43{\pm}0.02$) were corresponding to fluctuation of radioactivity in the air reported from physical measures, and to published reports about increase in chromosome aberration levels. Although, recent data obtained from monitoring of the ambient air quality in the Krak$\acute{o}$w and surroundings are lower when compared to results reported after Chernobyl NPP accident, though results express a significant increase above the control level and also are corresponding with increased air radioactivity reported from physical measurements. Statistically significant in comparison to control increase in gene mutation rates and more prolonged than that after Chernobyl fallout increase of GMF was observed during the period following the Fukushima NPP failure.

• Journal of the Korean Institute of Gas
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• v.21 no.5
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• pp.95-103
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• 2017

A lot of hazardous materials have been used for product processing and utility plant. Many accidents including toxic release, fire and explosions occur in the ammonia related facility and plant. Various safety and environment management program including PSM, SMS, ORA etc. are being implemented for risk management and accident prevention in the production industry. Also much study and research have been carried about risk assessment of accident scenario in the academic and research area. In this paper, firstly risk level was assessed by using a typically used KORA program and LOPA PFD method for the selected ammonia unloading and storage facility. And then risk reduction measures for the risk assessed facility were studied in 3 aspects and some measures were proposed. Those Risk Reduction measures are including a leak detection and emergency isolation, water spray, dilution tank, dike and trench, scattering protection in hardware impovement aspect, and a applicable risk criteria, conditional modifier for existing LOPA PFD, alternative supporting modeling program in risk estimation methodology aspect, and last RBPS(Risk Based Process Safety) program, re-doing of process hazard analysis, management system compliance audit in managerial activity aspect.

• Journal of the Korean Society for Nondestructive Testing
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• v.14 no.2
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• pp.122-131
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• 1994

Journal bearings in the rotating machineries are vulnerable to the contamination or the insufficient supply of lubricating oil, which is likely to be the cause of unexpected shutdown or malfunction of these systems. Various destructive and nondestructive testing methods had been used for the reduction of maintenance cost and the operational safety problems due to the accidents related to bearing damages. In this experimental approach, acoustic emission monitoring is employed to the detection of incipient failure caused by intervention of foreign particles most probable in the journal bearing systems. Experimental schedules for the intervention of foreign particles was composed to be more quantitative and systematic than last study in consideration of minimum oil film thickness and particle size. The experiment was conducted under such designed conditions as inserting alumina particles to the lubrication layer in the simulated journal bearing system. Several parameters such as AE rms level, waveform, AE energy distribution and other AE event parameters are used for analysis and characterization of damage source. The results showed that the history of damage was well correlated with the changes of AE rms level and the type of damage source signal can be verified using other informations such as waveform, distributions of AE parameters etc.