• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.3
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• pp.133-139
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• 2023

This paper proposes a two-stage Water Shield Automation System (WSAS) to predict the possibility of river overflow and vehicle flooding due to sudden rainfall. The WSAS uses a two-stage Deep Neural Network (DNN) model. First, a river overflow prediction module is designed with LSTM to decide whether the river is flooded by predicting the river's water level rise. Second, a vehicle flooding prediction module predicts flooding of underground parking lots by detecting flooded tires with YOLOv5 from CCTV images. Finally, the WSAS automatically installs the water barrier whenever the river overflow and vehicle flooding events happen in the underground parking lots. The only constraint to implementing is that collecting training data for flooded vehicle tires is challenging. This paper exploits the Image C&S data augmentation technique to synthesize flooded tire images. Experimental results validate the superiority of WSAS by showing that the river overflow prediction module can reduce RMSE by three times compared with the previous method, and the vehicle flooding detection module can increase mAP by 20% compared with the naive detection method, respectively.

• Bulletin of the Korean Chemical Society
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• v.23 no.12
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• pp.1719-1723
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• 2002

1,5-diphenylcarbazone was immobilized on sodium dodecyl sulfate coated alumina. The alumina particle was effectively used for collection of mercury(II) and methylmercury cations at sub-ppb level. The adsorbed mercury was eluted with l mol $L^{-1}$ of hydrobromic acid solution. The mercury(II) was then directly measured by cold vapor atomic absorption spectrometry utilizing tin (II) chloride where as the total mercury was determined after the oxidation of methylmercury into the inorganic mercury. The methylmercury concentration was calculated by the difference between the value of total mercury and mercury (II). Mercury (II) and methylmercury cations were completely recovered from water with a preconcentration factor of 100 (for 1 L solution.) Relative standard deviation at Hg L ${\mu}gL^{-1}$ level 1.7%(n=8) and the limit of detection was 0.11 ${\mu}gL^{-1}$. The procedure was applied to spring water, well water and seawater and accuracy was assessed through recovery experiments.

• Journal of the Korean Society of Radiology
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• v.5 no.1
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• pp.5-10
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• 2011

Based on basic concept of detection limit, sample measurement time & background measurement time was considered, and MDA values according to background measurement time and sample measurement time in land samples(river soil, surface soil, drinking water, underground water, surface water, pine leaf, mugwort) analysis among environmental samples were compared. Seeing the water sample analysis result, it was shown that most of the samples were not detected, and most of the samples in land specimen analysis showed to be below the detection limit of "Ministry of Education, Science and Technology Announcement Je-2008-28-ho", but $^{137}Cs$ which is one of artificial radioactive nuclide was detected in some samples. It can be traced back to 1950s and 1960s when nuclear tests were carried out in atmosphere and catastrophic Chernobyl atomic power station accident that caused fallouts in the sky, and this is common level of detection that can be observed worldwide. Seeing the result that the $^{134}Cs$(which is a isotope of $^{137}Cs$, and it has relatively short half life) was not detected in all samples, it can be considered it doesn't affect to the operation of atomic power station.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.21 no.4
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• pp.541-546
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• 2012

This study investigates the detection system of oil pollution level using single optical fiber sensor. This study focus on sensing of oil pollution by moisture and iron powder which are representatives of oil pollution factor. In addition, It is placed that the water and iron powder as an oil pollution factor in the oil tank which is the oil circulation in. The oil pollution detection system was measured by the changing of intensity of light and sensing gap. The result of this experimentation not only confirmed the contamination by moisture volume in the oil tank from the section 190ppm to 540ppm, but also monitored the contamination by iron volume from the section 1200ppm to 3500ppm. This study confirmed effectiveness of this detection system using optical fiber sensor. There is expectations of measuring another section by various optical fiber sensor.

• Biomedical Science Letters
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• v.16 no.1
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• pp.10-18
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• 2010

The present study was set to develop comprehensive system for assessing the safety of drinking water using PCR-reverse blot hybridization assay (REBA). The REBA developed in this study can detect waterborne pathogens such as Shigella spp., Salmonella spp., Citrobacter spp., Enterobacter spp., Klebsiella spp., Yersinia spp., Mycobacterium spp., Listeria spp. at the genus level, and Escherichia coli, Citrobacter freundii, Klebsiella pneumoniae, Pseudomonas aeruginosa, Yersinia enterocolitica, Y. pseudotuberculosis, Mycobacterium avium complex, M. marinum, Enterococcus faecalis, and Staphylococcus aureus at the species level, and E. coli O157:H7 at the strain level.

• Korean Journal of Remote Sensing
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• v.24 no.5
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• pp.445-452
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• 2008

Preliminary results are reported on ship detection using coherence images computed from cross-correlating images of multi-look-processed dual-polarization data (HH and HV) of ENVISAT ASAR. The traditional techniques of ship detection by radars such as CFAR (Constant False Alarm Rate) rely on the amplitude data, and therefore the detection tends to become difficult when the amplitudes of ships images are at similar level as the mean amplitude of surrounding sea clutter. The proposed method utilizes the property that the multi-look images of ships are correlated with each other. Because the inter-look images of sea surface are covered by uncorrelated speckle, cross-correlation of multi-look images yields the different degrees of coherence between the images and water. In this paper, the polarimetric information of ships, land and intertidal zone are first compared based on the cross-correlation between HH and HV images, In the next step, we examine the technique when the dual-polarization data are split into two multi-look images, It was shown that the inter-look cross-correlation method could be applicable in the performance improvement of small ship detection and the land masking, It was also found that a simple combination of coherence images from each co-polarised (HH) inter-look and cross-polarised (HV) inter-look data can provide much higher target-detection possibilities.

• Proceedings of the Korean Geotechical Society Conference
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• 2005.03a
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• pp.1211-1218
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• 2005

Temperature variation according to space and time on the inner parts of engineering constructions(e.g.: dam, slope) can be a basic information for diagnosing their safety problem. In general, as constructions become superannuated, structural deformation(e.g.: cracks, defects) could be occurred by various factors. Seepage or leakage of water through these cracks or defects in old dams will directly cause temperature anomaly. Groundwater level also can be easily observed by abrupt change of temperature on the level. This study shows that the position of seepage or leakage in dam body can be detected by multi-channel temperature monitoring using thermal line sensor. For this, diverse temperature monitoring experiments for a leakage physical model were performed in the laboratory. In field application of an old dam, temperature variations for water depth and for inner parts of boreholes located at downstream slope were measured. Temperature monitoring results for a long time at the bottom of downstream slope of the dam showed the possibility that temperature monitoring can provide the synthetic information about flowing path and quantity of seepage of leakage in dam body.

• Journal of the Korean Society of Radiology
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• v.13 no.6
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• pp.847-856
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• 2019

The various environmental issues arose with the development of today's economy. naturally, people were increased interest in environment and the importance of research on drinking water and contamination are emerging especially. A number of country areas, uranium and ²²²Rn in ground water have been detected to people using as drinking water. So this study evaluated the way for more accurate measurements than when measuring ²²²Rn concentrations in the ground water containing. the experiment was performed using the low-level liquid scintillation counter with an alpha, beta analysis easy PSA function of pulse. the scintillator as the preparation of the ground water samples are mixed, the measure value detection is lowered over prepare period and expiration date. Energy spectrum was also moved to a lower side channel. As a long time to buy the scintillator and over time after opening, it was confirmed that detection is lowered. if the purpose is to use a different scintillator can see the energy through the channel change.

• Journal of Magnetics
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• v.22 no.1
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• pp.34-42
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• 2017

Material defects in the Steam Generator Tubes (SGT) of sodium cooled fast breeder reactor (PFBR) can lead to leakage of water into sodium. The water and sodium reaction will lead to major accidents. Therefore, the examination of steam generator tubes for the early detection of defects is an important requirement for safety and economic considerations. In this work, the Magnetic Flux Leakage (MFL) based Non Destructive Testing (NDT) technique is used to perform the defect detection process. The rectangular notch defects on the outer surface of steam generator tubes are modeled using COMSOL multiphysics 4.3a software. The obtained MFL images are de-noised to improve the integrity of flaw related information. Grey Level Co-occurrence Matrix (GLCM) features are extracted from MFL images and taken as input parameter to train the neural network. A comparative study on characterization have been carried out using feed-forward back propagation (FFBP) and cascade-forward back propagation (CFBP) algorithms. The results of both algorithms are evaluated with Mean Square Error (MSE) as a prediction performance measure. The average percentage error for length, depth and width are also computed. The result shows that the feed-forward back propagation network model performs better in characterizing the defects.

• Nuclear Engineering and Technology
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• v.53 no.1
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• pp.253-257
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• 2021

This work demonstrates the use of baromembrane method based on reverse osmosis (RO) process. The method is realized on mobile complex, which allows to concentrate and determine ultra-low activity of radionuclides in water cooling ponds of Russian nuclear fuel cycle enterprises. The existence level of radionuclide background creates difficult conditions for identification the contribution of liquid discharges enterprise, as standard monitoring methods have a very high detection level for radionuclides. Traditional methods for determining the background radionuclides concentrations require the selection of at least 500 liters (l) of water, followed by their evaporation to form a dry residue. This procedure with RO membranes requires at least 5 days. It is possible to reduce the time and energy spent on evaporation of hundreds of water liters by pre-concentrating radionuclides in a smaller sample volume with baromembrane method. This approach allows preliminary concentration of water samples from 500 l volume till 20 l volume during several hours. This approach is universal for the concentration of dissolved salts of any heavy metals, other organic compounds and allows the preparation of water countable samples in much shorter time compared to the traditional evaporation method.