• The Bulletin of The Korean Astronomical Society
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• v.43 no.2
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• pp.59.1-59.1
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• 2018

SNe light curves have been used to understand the expansion history of the universe, and a lot of efforts have gone into understanding the overall shape of the radioactively powered light curve. However, we still have little direct observational evidence for the theorized SN progenitor systems. Recent studies suggest that the light curve of a supernova shortly after its explosion (< 1 day) contains valuable information about its progenitor system and can be used to set a limit on the progenitor size, R*. In order to catch the early light curve of SNe explosion and understand SNe progenitors, we are performing a ~8hr interval monitoring survey of nearby galaxies (d < 50 Mpc) with 1-m class telescopes around the world. Through this survey, we expect to catch the very early precursor emission as faint as R=21 mag (~0.1 Rsun for the progenitor). In this poster, we outline this project, and provide updates on IMSNG projects during 2017/2018 seasons.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.123-138
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• 2023

The Fourth Industrial Revolution and sensor technology have led to increased utilization of sensor data. In our modern society, data complexity is rising, and the extraction of valuable information has become crucial with the rapid changes in information technology (IT). Recurrent neural networks (RNN) and long short-term memory (LSTM) models have shown remarkable performance in natural language processing (NLP) and time series prediction. Consequently, there is a strong expectation that models excelling in NLP will also excel in time series prediction. However, current research on Transformer models for time series prediction remains limited. Traditional RNN and LSTM models have demonstrated superior performance compared to Transformers in big data analysis. Nevertheless, with continuous advancements in Transformer models, such as GPT-2 (Generative Pre-trained Transformer 2) and ProphetNet, they have gained attention in the field of time series prediction. This study aims to evaluate the classification performance and interval prediction of remaining useful life (RUL) using an advanced Transformer model. The performance of each model will be utilized to establish a health index (HI) for cutting blades, enabling real-time monitoring of machine health. The results are expected to provide valuable insights for machine monitoring, evaluation, and management, confirming the effectiveness of advanced Transformer models in time series analysis when applied in industrial settings.

• Korean Journal of Radiology
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• v.24 no.8
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• pp.784-794
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• 2023

Objective: To determine whether dynamic susceptibility contrast-enhanced (DSC) perfusion magnetic resonance imaging (MRI) can be used to evaluate posterior cerebral circulation in pediatric patients with moyamoya disease (MMD) who underwent anterior revascularization. Materials and Methods: This study retrospectively included 73 patients with MMD who underwent DSC perfusion MRI (age, 12.2 ± 6.1 years) between January 2016 and December 2020, owing to recent-onset clinical symptoms during the follow-up period after completion of anterior revascularization. DSC perfusion images were analyzed using a dedicated software package (NordicICE; Nordic NeuroLab) for the middle cerebral artery (MCA), posterior cerebral artery (PCA), and posterior border zone between the two regions (PCA-MCA). Patients were divided into two groups; the PCA stenosis group included 30 patients with newly confirmed PCA involvement, while the no PCA stenosis group included 43 patients without PCA involvement. The relationship between DSC perfusion parameters and PCA stenosis, as well as the performance of the parameters in discriminating between groups, were analyzed. Results: In the PCA stenosis group, the mean follow-up duration was 5.3 years after anterior revascularization, and visual disturbances were a common symptom. Normalized cerebral blood volume was increased, and both the normalized time-topeak (nTTP) and mean transit time values were significantly delayed in the PCA stenosis group compared with those in the no PCA stenosis group in the PCA and PCA-MCA border zones. TTP_PCA (odds ratio [OR] = 6.745; 95% confidence interval [CI] = 2.665-17.074; P < 0.001) and CBV_PCA-MCA (OR = 1.567; 95% CI = 1.021-2.406; P = 0.040) were independently associated with PCA stenosis. TTP_PCA showed the highest receiver operating characteristic curve area in discriminating for PCA stenosis (0.895; 95% CI = 0.803-0.986). Conclusion: nTTP can be used to effectively diagnose PCA stenosis. Therefore, DSC perfusion MRI may be a valuable tool for monitoring PCA stenosis in patients with MMD.

• Journal of Korean Society of Environmental Engineers
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• v.32 no.12
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• pp.1102-1110
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• 2010

Tidal mudflat is a reservoir for diverse microbial resources. Microbial diversity in tidal mudflat sediment can be easily influenced by various human activities. It is necessary to take representative samples to monitor microbial diversity in tidal mudflat sediments. In this study, we analyzed the microbial diversity and chemical characteristics of vegetation and non-vegetation tidal mudflat regions in the Kangwha tidal mudflat using geo-statistics and data-mining. According to the geo-statistical analysis, most correlation range values for the vegetation region were smaller than those for the non-vegetation region, which suggested that the shorter number and interval of sampling are required for the vegetation tidal mudflat environment due to its higher degree of chemical and biological complexity and heterogeneity. The data-mining analysis suggested that the organic content and nitrate were the major environmental factors influencing microbial diversity in the vegetation region while pH and sulfate were the major influencing factors in the non-vegetation region. Using the geo-statistical and data-mining integration approach, we proposed a guideline for determining the sampling interval and number to monitor microbial diversity in tidal mudflat.

• The Korean Journal of Pharmacology
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• v.31 no.2
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• pp.251-259
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• 1995

Pharmacokinetics and pharmacodynamics of metoprolol, a selective beta-l blocker, were examined for 360 minutes after intravenous bolus administration of metoprolol to 6 dogs. Plasma concentration and excreted amount in the urine metoprolol were measured by liquid chromatography with fluorescence detection. PR interval and heart rate were measured by ECG monitoring. Blood pressure was monitored through intraarterial catheter in femoral artery and cardiac output by thermodilution method using Swan-Ganz catheter. To analyze the effect site concentration-response relationship, plasma concentration and pharmacological effects were simultaneously fitted to a two pharmacokinetic compartment linked to pharmacodynamic model with NONLIN program. Results are as follows. 1) The plasma concentration of metoprolol after intrvenous injection decreased biexponentially. The terminal half-life estimated was $1.33{\pm}0.40$ hours and the volume of distribution at steady state (Vdss) and the total body clearance were $1.04{\pm}0.4\;L/kg,\;6.55{\pm}2.21\;L/hr$, respectively. The central compartment volume of distribution and peripheral compartment volume of distribution were $0.35{\pm}0.14L/kg\;and\;0.69{\pm}0.34L/kg$. The renal clearance and intercompartment clearance were $0.53{\pm}0.25\;L/min\;and\;0.35{\pm}0.19\;L/min$. 2) Simulated biophase concentration-response curve shows hyperbolic relationship and the estimated concentration-effect relationship was best explained by Emax model when the prolongation of PR interval and the reduction of the heart rate were used as pharmacodynamic parameters. Emax and EC50 were estimated to be $26.3{\pm}4.7\;msec\;and\;88.8{\pm}82.3\;g/ml$ for PR interval, and $48.7{\pm}18.8\;beats/min\;and\;113.5{\pm}78.7\;ng/ml$ for heart rate, respectively. 3) The changes of cardiac output-effect site concentration relationship was best fitted by a linear model and the slope of the relationship was $0.005{\pm}0.003$. Diastolic blood pressure-effect site concentration relationship was also explained by the linear model and the slope of the relationship was $0.038{\pm}0.034$.

• Journal of Radiation Protection and Research
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• v.38 no.2
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• pp.68-77
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• 2013

Derived Investigation levels(DILs) were calculated to protect the workers from the effects of both radiological hazard and chemical toxicity by uranium intake. Investigation Levels(ILs) of committed effective dose of 2 mSv $y^{-1}-6$ mSv $y^{-1}$ and uranium concentration of 0.3 ${\mu}g$ $g^{-1}$ in kidney, based on Korean Nuclaer Safety Act, Korean Occupational Safety and Health Act and current scientific studies of uranium intake were assumed. DILs of radiological hazard and chemical toxicity were then calculated based on the concentration of uranium in air of workplace, the lung monitoring and urine analysis, respectively. As a result, in case of the nuclear fuel fabrication plant where 3.5% enriched uranium is handled, derived investigation level(DIL) for the control of the concentration of uranium in the air of workplace assumed with 15-min acute inhalation was 0.6 mg $m^{-3}$ for all types of uranium. DILs for the control of the average concentration of uranium in air of workplace, assuming an 8-hour workday, were 15.21 ${\mu}g$ $m^{-3}$ of Type F uranium, 0.41-1.23 Bq $m^{-3}$ and 0.13-0.39 Bq $m^{-3}$ for Type M and Type S uranium, respectively. DILs for the lung monitoring assumed with a period of 6-month interval were 0.37-1.11 Bq and 0.39-1.17 Bq in acute and chronic inhalation for Type M, respectively and 0.30- 0.91 Bq and 0.19-0.57 Bq in acute and chronic inhalation for Type S, respectively. Since a detection limit of typical germanium detector for the measurement of 235U activity is 4 Bq, DILs calculated for the lung monitoring were not appropriate. DILs for urine analysis, for which an interval was assumed to be 1 month, were 14.57 ${\mu}g$ $L^{-1}$ based on chemical toxicity after acute inhalation. In addition, acute and chronic inhalation of Type M were calculated 2.85-8.58 ${\mu}g$ $L^{-1}$ and 1.09-3.27 ${\mu}g$ $L^{-1}$ based on the radiological hazard, respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.4C
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• pp.296-304
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• 2005

ATCoP(Abnormal traffic controller based on prediction) is presented to securely support reliable Internet service and to guarantee network survivability, which is deployed in Internet access point. ATCoP is a method to control abnormal traffic that is entering into the network When unknown attack generates excessive traffic, service survivability is guaranteed by giving the priority to normal traffic than abnormal traffic, that is reserving some channels for normal traffic. If the reserved channel number increases, abnormal traffic has lower quality service by ATCoP system and then its service survivability becomes worse. As an analytic result, the proposed scheme maintains the blocking probability of normal traffic on the predefined level in the specific interval of input traffic.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.9
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• pp.1941-1946
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• 2009

Wireless sensor networks do the monitoring and collecting information in the environment instead of human. Sensor networks are consisted of small sensor nodes with very limited hardware resource and very low network bandwidth. The wireless communication environment causes lots of communication errors so that the sensor network requires error correction technique to increase the reliability of network. The performance of error correction technique could be increased by the researches about the error pattern of CRC. In the paper, we did the performance evaluation - transmission interval, distance between sensor nodes, racket size, and RF power - that affects to the success ratio of data transmission in the indoor environment. we propose the performance metrics of system configuration based on the analysis of performance evaluation.

• Environmental Analysis Health and Toxicology
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• v.31
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• pp.18.1-18.8
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• 2016

Objectives This study aimed to evaluate the risk factors associated with depression and suicidal ideation in a rural population. Methods A survey was conducted with 543 farmers from Chungcheongnam-do Province using the Center for Epidemiologic Studies Depression Scale (CES-D) for depression, Lubben Social Network Scale (LSNS) for social support, Swedish Q16 for neurotoxicity symptoms and a survey tool for farmer's syndrome. Results After adjusting for socioeconomic factors using logistic regression analysis, poor self-rated health, low social support and neurotoxicity were positively associated with the risk of depression (odds ratio [OR], 15.96; 95% confidence interval [CI], 3.11 to 81.97; OR, 3.14; 95% CI, 1.26 to 7.82; and OR, 3.68; 95% CI, 1.08 to 12.57, respectively). The risk of suicidal ideation significantly increased with low social support, neurotoxicity and farmer's syndrome (OR, 2.28; 95% CI, 1.18 to 4.40; OR, 6.17; 95% CI, 2.85 to 13.34; and OR, 3.70; 95% CI, 1.51 to 9.07, respectively). Conclusions Given the overall results of this study, there is a need to establish programs which can improve the health and social relationships of farmers. Also, when farmers have neurological symptoms from pesticide exposure and characteristic symptoms of farmer's syndrome, a monitoring system for depression and suicide must be made available.

• Proceedings of the Korean Fiber Society Conference
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• 2003.10a
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• pp.45-46
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• 2003

A process control system has been developed for measurement and characterization of the nanofiber web qualities. The nano-fiber information system (NAFIS) developed consists of a measurement device and an analysis algorithm, which are a microscope-laser sensor fusion system and a process information system, respectively. It has been found that NAFIS is so successful in detecting irregularities of pore and diameter that the resulting product has been quitely under control even at the high production rate. Pore distribution, fiber diameter and mass uniformity have been readily measured and analyzed by integrating the non-contact measurement technology and the random function-based time domain signal/image processing algorithm. Qualifies of the nano-fiber webs have been revealed in a way that the statistical parameters for the characteristics above are calculated and stored in a certain interval along with the time-specific information. Quality matrix, scale of homogeneity is easily obtained through the easy-to-use GUI information. Finally, ANFIS has been evaluated both for the real-time measurement and analysis, and for the process monitoring.