• Nuclear Engineering and Technology
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• v.48 no.2
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• pp.419-433
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• 2016

One of the important severe accident management measures in the Light Water Reactors is water injection to the reactor core. The related phenomena are investigated by performing experiments and computer simulations. One of the most widely known is the QUENCH test-program. A number of analyses on QUENCH tests have also been performed by different computer codes for code validation and improvements. Unfortunately, any deterministic computer simulation is not free from the uncertainties. To receive the realistic calculation results, the best estimate computer codes should be used for the calculation with combination of uncertainty and sensitivity analysis of calculation results. In this article, the QUENCH-03 and QUENCH-06 experiments are modelled using ASTEC and RELAP/SCDAPSIM codes. For the uncertainty and sensitivity analysis, SUSA3.5 and SUNSET tools were used. The article demonstrates that applying the best estimate approach, it is possible to develop basic QUENCH input deck and to develop the two sets of input parameters, covering maximal and minimal ranges of uncertainties. These allow simulating different (but with the same nature) tests, receiving calculation results with the evaluated range of uncertainties.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.4
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• pp.346-354
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• 2020

Nowadays, it is required to apply low observable technology to weapon systems in operation or under development. Radar Cross Section(RCS) is a measure of the scattered power in an given direction when a target is illuminated by an incident wave and used as a parameter to estimate the low observable performance of weapon system. RCS of a target can be calculated by various numerical methods. However, measurement is also needed to estimate RCS of a complex target because it is difficult to estimate theoretically. To acquire reliable measurement results, an analysis of measurement uncertainty is essential. In this paper, error components and uncertainties of near-field RCS measurement system which was constructed in ASTEC(Aerospace System Test & Evaluation Center) were analyzed based on the IEEE recommended practice for radar cross-section test procedures(IEEE Std. 1502-2007) which describes the uncertainty of RCS measurement and unique error components of this near-field measurement system were also identified.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.7 no.5
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• pp.94-99
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• 2004

This study was carried out to find out what is the optimum conditions for RAPD of Zelkova serata. We changes the factors what affect to PCR band patterns, as a result, we established the optimum conditions as follows; template DNA 100mg, Primer 0.25uM, dNTP 100mM, Taq polymerase 1.0u, and total reaction volume was filled up to 10uL with distilled water. As the amount of primers went higher, PCR reaction rates were lowered. This reason was cause by exhaustion of primers during initial reaction. The amount of dNTP didn't showed noticable differtations between the range, but the optimum amount was 100mM for efficiency. Taq polymerase 1.0 unit was the best in the range. As the concentration of polymerase were increased, many non-specific bands were appeared, In primer selection, most Openron Random Primers are amplified in this experiment. The primers GC contents were 60, and set A, B, C, D, E, X were tested. Thermal cycler(ASTEC PC808, Japan) condition was, $95^{\circ}C$, 5min, initial denaturation, $94^{\circ}C$, 20sec, denaturation, $37^{\circ}C$, 40sec, annealing, $72^{\circ}C$, 1min, extention, 45cycle repeated and final extention $72^{\circ}C$10min.

• Analytical Science and Technology
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• v.32 no.5
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• pp.163-172
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• 2019

Methamphetamine (MA) is currently the most abused illicit drug in Korea and its major metabolite is amphetamine (AP). As MA exist as two enantiomers with the different pharmacological properties, it is necessary to determine their respective amounts in a sample. Thus a chiral stationary phase liquid chromatography-tandem mass spectrometric (LC-MS/MS) method was developed for identification and quantification of d-MA, l-MA, d-AP, and l-AP in human urine. Urine sample ($200{\mu}L$) was diluted with pure water and purified using solid-phase extraction (SPE) cartridge. A $5-{\mu}L$ aliquot of SPE treated sample solution was injected into LC-MS/MS system. Chiral separation was carried out on the Astec Chirobiotic V2 column with an isocratic elution for each enantiomer. Identification and quantification of enantiomeric MA and AP was performed using multiple reaction monitoring (MRM) detection mode. Linear regression with a $1/x^2$ as the weighting factor was applied to generate a calibration curve. The linear ranges were 25-1000 ng/mL for all compounds. The intra- and inter-day precisions were within 3.6 %, while the intra- and inter-day accuracies ranged from -5.4 % to 11.8 %. The limits of detection were 2.5 ng/mL (d-MA), 3.5 ng/mL (l-MA), 7.5 ng/mL (d-AP), and 7.5 ng/mL (l-AP). Method validation parameters such as selectivity, matrix effect, and stability were evaluated and met acceptance criteria. The applicability of the method was tested by the analysis of genuine forensic urine samples from drug abusers. d-MA is the most common compound found in urine and mainly used by abusers.

• Resources Recycling
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• v.30 no.4
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• pp.3-10
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• 2021

The field of recycling for waste electronic components, which is the typical example of an urban mine, requires the development of useful sorting techniques. In this study, a sorter based on image identification by deep learning was developed to select electronic components into four groups. They were recovered from waste printed circuit boards and should be separated to depend on the difference after treatment. The sorter consists of a workstation with GPU, camera, belt conveyor, air compressor. A small piece (less than 3.5 cm) of electronic components on the belt conveyor (belt speed: 6 cm/s) was taken and learned as teaching data. The accuracy of the image identification was 96% as kinds and 99% as groups. The optimum condition of sorting was determined by evaluating accuracies of image identification and recovery rates by blowdown when changing the operating condition such as belt speed and blowdown time of compressed air. Under the optimum condition, the accuracy of image classification in groups was 98.7%. The sorting rate was more than 70%.

• Clinical and Experimental Pediatrics
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• v.51 no.10
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• pp.1071-1076
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• 2008

Purpose : Respiratory syncytial virus (RSV) is the most frequent cause of lower respiratory infections in infants and young children. Early detection allows quarantining of infected inpatients to prevent nosocomial transmission and to choose a treatment. To achieve rapid reporting, to facilitate prompt antiviral therapy, and to avoid unnecessary use of antibiotics, an easy, rapid diagnostic method for RSV is needed. We evaluated a lateral flow immunochromatography (RSV Respi-Strip test) and EIA (Enzyme immuno assay) compared to RT-PCR. Methods : From April 2007 to March 2008, 112 consecutive respiratory specimens (nasopharyngeal aspirates, throat swabs, tracheal aspirates, sputum) from patients who were suffering from the clinical signs and symptoms of respiratory tract infection were enrolled in Busan. A total of 112 patients were tested with RSV Respi-Strip (Corio-BioConcept, Belgium), EIA, and RT-PCR at the same time. Results : Of the 112 specimens tested, the number of children who showed positive results at RT-PCR and Respi-Strip were 45 and 42, respectively. The Respi-Strip rapid antigen test had a sensitivity of 88% and a specificity of 94%. The positive and negative predictive values were 90% and 92%, respectively. The agreement was 83%. Conclusion : In our study, the rapid antigen test had as much sensitivity as any method for detection of RSV. The test has many advantages such as easy performance, simple interpretation, and rapid results. If the rapid antigen test is widely applied in the clinical setting, the may be useful for diagnostic and epidemiological studies of RSV infection.