• YAKHAK HOEJI
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• v.52 no.6
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• pp.419-425
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• 2008

A qualitative and quantitative analytical method was developed for detection of methamphetamine (MA) and its main metabolite amphetamine (AM) in oral fluid. Oral fluids of eleven drug abusers were provided by Police, specimens were collected by stimulation with a cotton swab treated with 20 mg of citric acid ($Salivette^{(R)}$; Sarstedt, USA). As the preliminary test, oral fluid samples were screened for amphetamines by Fluorescence Polarization Immunoassay (TDxFLx, Abbott Co.). Extraction for MA was performed using solid-phase extraction (SPE) by $RapidTrace^{TM}$ (Zymark, USA) with mixed mode cation exchange cartridge, CLEAN $SCREEN^{(R)}$ (130 mg/3 ml, UCT) after dilution with phosphate buffer. Samples were evaporated and derivatized by pentafluoropropionic acid anhydride (PFPA). Quantitation of MA and AM was performed by gas chromatography-mass spectrometry (GC-MS) using selective ion monitoring (SIM), the quantitation ions were m/z 204 (MA), 208 (MA-$D_5$), 190 (AM) and 194 (AM-$D_5$). The selectivity, linearity of calibration, limit of detection (LOD) and quantification (LOQ) within- and between day precision, accuracy and recoveries were examined as parts of the method validation. All oral fluid samples gave positive results to immunoassay for MA (cut-off level, 50 ng/ml as d-amphetamine). Concentrations of MA and AM by GC-MS in eleven samples were ranged 104.2${\sim}$4603.3 ng/ml and 32.4${\sim}$268.6 ng/ml, respectively. Extracted calibration curves of MA and AM were linear over the two concentration range of 1${\sim}$100 and 50${\sim}$1000 ng/ml with correlation coefficient of above 0.999. LOQ of MA and AM was 1 and 3 ng/ml, respectively. The intraand inter-day run precisions (CV) for MA and AM were less than 10%, and the accuracies (bias) for MA and AM were also less than 10% at the two different concentrations 5 and 100 ng/ml at low calibration range, 50 and 1000 ng/ml at high calibration range. The absolute recoveries of MA and AM at low and high calibration ranges were more than 82% and 75%, respectively. In this study the qualitative and quantitative analytical method of MA in oral fluid was established. Oral fluid testing may detect drug use in past hours because of its shorter detection window than urine, and be useful in post-accident situations. So oral fluids will be most useful for testing drug abuse in the driving under the influence of drug (DUID) as the alternative specimens of urine.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.7 s.349
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• pp.72-83
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• 2006

It is not a practical solution that the DDoS attacks or worm propagations are protected and responded within a domain itself because it clogs access of legitimate users to share communication lines beyond the boundary a domain. Especially, the DDoS attacks with spoofed source address or with bogus packets that the destination addresses are changed randomly but has the valid source address does not allow us to identify access of legitimate users. We propose a scheme of distributed network security management to protect access of legitimate users from the DDoS attacks exploiting randomly spoofed source IP addresses and sending the bogus packets. We assume that Internet is divided into multiple domains and there exists one or more domain security manager in each domain, which is responsible for identifying hosts within the domain. The domain security manager forwards information regarding identified suspicious attack flows to neighboring managers and then verifies the attack upon receiving return messages from the neighboring managers. Through the experiment on a test-bed, the proposed scheme was verified to be able to maintain high detection accuracy and to enhance the. normal packet survival rate.

• Journal of Digital Convergence
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• v.18 no.4
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• pp.201-209
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• 2020

In this paper, we perform a case study of children's emotional care program that analyzes the emotional status through the drawings of children based on web system. In order to overcome spatial and temporal environment constraints, we have developed based on web system that performs to support the whole process from the request of analysis of children 's drawings to the feedback of the final result step by step. The online platform is designed to conduct observations for the purpose of primary screening using a smartphone, and then proceed to the offline secondary care linkage process based on the results. Then according to the results of the analysis, children and parents who need deep examination are figured out and professional institutions are linked to them for help. Parental stress had been analyzed to improve the accuracy of the test and to figure out the cause of the problem. The study was conducted on 2,532 children and their parents between the ages of 3 and 5 years attending a day care center. As a result, 564 children and 223 parents were figured out to be in need of secondary institutional care, and 311 parents were educated and counseled from the professional institutions.

• The Journal of the Convergence on Culture Technology
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• v.6 no.4
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• pp.789-795
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• 2020

Many deaths have been reported due to the worldwide pandemic of COVID-19. In order to prevent the further spread of COVID-19, it is necessary to quickly and accurately read images of suspected patients and take appropriate measures. To this end, this paper introduces a deep learning-based COVID-19 chest X-ray reading technique that can assist in image reading by providing medical staff whether a patient is infected. First of all, in order to learn the reading model, a sufficient dataset must be secured, but the currently provided COVID-19 open dataset does not have enough image data to ensure the accuracy of learning. Therefore, we solved the image data number imbalance problem that degrades AI learning performance by using a Stacked Generative Adversarial Network(StackGAN++). Next, the DenseNet-based classification model was trained using the augmented data set to develop the reading model. This classification model is a model for binary classification of normal chest X-ray and COVID-19 chest X-ray, and the performance of the model was evaluated using part of the actual image data as test data. Finally, the reliability of the model was secured by presenting the basis for judging the presence or absence of disease in the input image using Grad-CAM, one of the explainable artificial intelligence called XAI.

• Journal of the Korean Society of Propulsion Engineers
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• v.4 no.3
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• pp.64-73
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• 2000

The joint parts was composed of inner AL(aluminum) ring, FRP wedge and motor case which was manufactured by filament wound method. Where the motor case consists of helical and hoop layer. The finite element analysis was performed for the design variable of joint parts to improve the performance of motor case. Where the adhesive layer was modeled to elasto-perfect plastic material and the contact condition of AL ring and wedge was modeled by using the contact surface element of ABAQUS. And the sliding distance of AL ring and the hoop strain of composite case were compared to hydro-static test results to verify the accuracy of analysis results. When wedge and AL ring was perfect bonding, though the hoop strain of joint part was reduced, the maximum shear stress was occurred at the adhesive layer. Thus the adhesive layer had failed due to the high shear stress before the failure was occurred at the case. And as another design method, when wedge and AL ring was contact condition, the shear stress on adhesive layer was decreased. But the hoop stress of joint part increased due to the sliding behavior of AL ring. Finally, the fail was occurred at the composite case of joint part. The improved joint method reinforced by hoop layer to the joint parts under contact condition for wedge and Al. ring reduced the joint part's hoop strain by constraint the sliding behavior of AL ring.

• Korean Journal of Optics and Photonics
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• v.4 no.1
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• pp.15-21
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• 1993

This paper describes the design and development of a KrF excimer laser stepper and discusses the detailed system parameters and characterization data obtained from the performance test. We have developed a deep UV step-and-repeat system, operating at 248 nm, by retrofitting a commercial modules such as KrF excimer laser, precision wafer stage and fused silica illumination and 5X projection optics of numerical aperture 0.42. What we have developed, to the basic structure, are wafer alignment optics, reticle alignment system, autofocusing/leveling mechanisms and environment chamber. Finally, all these subsystem were integrated under the control of microprocessor-based controllers and computer. The wafer alignment system comprises the OFF-AXIS and the TTL alignment. The OFF-AXIS alignment system was realized with two kinds of optics. One is the magnification system with the image processing technique and the other is He-Ne laser diffraction type system using the alignment grating on the wafer. 'The TTL alignment system employs a dual beam inteferometric method, which takes advantages of higher diffraction efficiency compared with other TTL type alignment systems. As the results, alignment accuracy for OFF-AXIS and TTL alignment system were obtained within 0.1 $\mu\textrm{m}$/ 3 $\sigma$ for the various substrate on the wafers. The wafer focusing and leveling system is modified version of the conventional systems using position sensitive detectors (PSD). This type of detection method showed focusing and leveling accuracies of about $\pm$ 0.1 $\mu\textrm{m}$ and $\pm$ 0.5 arcsec, respectively. From the CD measurement, we obtained 0.4 $\mu\textrm{m}$ resolution features over the full field with routine use, and 0.3 $\mu\textrm{m}$ resolution was attainable under more strict conditions.

• Geophysics and Geophysical Exploration
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• v.18 no.2
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• pp.64-73
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• 2015

Recently, hydraulic fracturing is used in various fields and microseismic monitoring is one of the best methods for judging where hydraulic fractures exist and how they are developing. When locating microseismic events using single vertical well data, distances from the vertical array and depths from the surface are generally decided using time differences between compressional (P) wave and shear (S) wave arrivals and azimuths are calculated using P wave hodogram analysis. However, in field data, it is sometimes hard to acquire P wave data which has smaller amplitude than S wave because microseismic data often have very low signal to noise (S/N) ratio. To overcome this problem, in this study, we developed a grid search algorithm which can find event location using all combinations of arrival times recorded at receivers. In addition, we introduced and analyzed the method which calculates azimuths using S wave. The tests of synthetic data show the inversion method using all combinations of arrival times and receivers can locate events without considering the origin time even using only single phase. In addition, the method can locate events with higher accuracy and has lower sensitivity on first arrival picking errors than conventional method. The method which calculates azimuths using S wave can provide reliable results when the dip between event and receiver is relatively small. However, this method shows the limitation when dip is greater than about $20^{\circ}$ in our model test.

• Journal of Cadastre & Land InformatiX
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• v.50 no.1
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• pp.87-105
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• 2020

The government is trying to secure reliability by raising the accuracy, objectivity, and transparency of the official price by promoting the reliability improvement plan of the official price and increasing the realization rate, but the Realization rate of Publicly Notified Individual Land Price is showing a big difference because the current market price is not fully reflected in the official price. Therefore, this study collected the actual transaction price reported to the RTMS in Wansan-gu, Jeonju, Jeollabuk-do and the individual official price of the KRAS and calculated the realization rate of publicly notified individual Land Price. SPSS 25.0 program was used for the empirical analysis of this study. The Dependent Variable was the realization rate of publicly notified individual Land Price, and Independent Variables, was six land characteristics items were selected, one-way ANOVA was conducted and post-test was conducted by Scheffe method. As a result of the analysis, average difference in realization rate of publicly notified individual Land Price was found in Residential areas, Commercial areas, and Farmland, Public land and Residential and commercia, Residential and Forest. Especially, it was found that the price of commercial area is higher than that of residential area and green area, and the price is less reflected in individual official land price.

• Food Science and Preservation
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• v.10 no.2
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• pp.125-130
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• 2003

This study was carried out to investigate the thermo-physical properties and design Freezing time prediction model from data of freezing test of Kimchi. Density of Kimchi were measured as 1001.9 ${\pm}$0.03 kg/㎥ at unfrozen state, 987.0 ${\pm}$0.07 kg/㎥ at frozen state and volume of the Kimchi expanded 4.67% at -l5$^{\circ}C$. Initial freezing point of Kimchi and seasoning were -4.0$^{\circ}C$ and -2.5$^{\circ}C$, respectively. Freezing ratio of Kimchi were estimated more than 50％ at -5.0$^{\circ}C$, more than 75% at -l0$^{\circ}C$ and approximately 90% at -25$^{\circ}C$. To obtain equation for freezing time prediction of Kimchi, freezing time(Y) was regressed against the reciprocal( $X_3$) of difference of initial freezing point and freezing medium temperature, reciprocal( $X_4$) of surface heat transfer coefficient, the initial temperature( $X_1$) and thickness( $X_2$) of samples. As results of the multiple regression analysis, equations were obtained as follows. Y$_{kimchi}$=3.856 $X_1$+13982.8 $X_2$+8305.166 $X_3$+ 3559.181 $X_4$-639.189( $R^2$=0.9632). These equations shown better results than previous models, and the accuracy of its was very high as average absolute difference of about 10% in the difference between the fitted and experimental results.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.2
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• pp.289-297
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• 2009

In the paper, we propose the methodology to extract training dataset automatically for supervised classification of road networks. For the preprocessing, we co-register the airborne photos, LIDAR data and large-scale digital maps and then, create orthophotos and intensity images. By overlaying the large-scale digital maps onto generated images, we can extract the initial training dataset for the supervised classification of road networks. However, the initial training information is distorted because there are errors propagated from registration process and, also, there are generally various objects in the road networks such as asphalt, road marks, vegetation, cars and so on. As such, to generate the training information only for the road surface, we apply the Expectation Maximization technique and finally, extract the training dataset of the road surface. For the accuracy test, we compare the training dataset with manually extracted ones. Through the statistical tests, we can identify that the developed method is valid.