• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.70-72
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• 2007

In this study, electromagnetic fields emitted from the various environment in the hospital were measured. Measurement spot was patients' head. To monitor how much magnetic fields are emitting from operation room, monitoring device was attached to 19 anesthesiologist and monitoring lasted 8 hours. We also took a measurement from various medical devices. Devices include ESWL, PET, MRI, CT, Gamma knife, X-ray, Angiogram, Echocardiogram, Upper GI and Linear Accelerator. Electromagnetic fields were measured from 10 spots from each of 5 patient waiting room. As a results, there were no places showing risk of high exposure. All the measurement values were below the reference levels for general public exposure to time varying electric and magnetic fields which is issued by ICNIRP.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.446-454
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• 2023

The impact of climate change on agriculture is substantial, especially as global warming is projected to lead to varying temperature and humidity patterns in the future. These changes pose a higher risk for both crops and livestock, exposing them to environmental stressors under altered climatic conditions. Specifically, as temperatures are expected to rise, the risk of heat stress is assessable through the Temperature-Humidity Index (THI), derived from temperature and relative humidity data. This study involved the comparison of THI collected from 10 Korea Meteorological Administration ASOS stations spanning a 60-year period from 1961 to 2020. Moreover, high-resolution temperature and humidity distribution data from 1981 to 2020 were employed to generate high-resolution TH I distributions, analyzing temporal changes. Additionally, the number of days characterized by heat stress, derived from TH I, was compared over different time periods. Generally, TH I showed an upward trend over the past, albeit with varying rates across different locations. As TH I increased, the frequency of heat stress days also rose, indicating potential future cost increases in the livestock industry due to heat-related challenges. The findings emphasize the feasibility of evaluating heat stress risk in livestock using THI and underscore the need for research analyzing THI under future climate change scenarios.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.326-329
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• 2004

In this paper, we show a new form of blood pressure controller combined PI control with $H_{\infty}$ loop-shaping. Hypertensive patients or post-operative patients need to maintain normally blood pressure. Exact regulation of blood pressure is needed for maintaining variable blood pressure of preventing complications. The regulation of blood pressure is achieved by injecting drugs, and usually sodium nitroprusside is used as those kinds of drugs. It is necessary to control the infusion rate sodium-nitroprusside carefully to achieve the desired blood pressure. It has been known that regulation of blood pressure by automatic controller is more effective than regulation of blood pressure by human operators. The control of blood pressure has many constraints and uncertainties. Most of biological system has the time-varying variables and the side effects such as increased risk of sepsis and organ failure. To solve such a problem, we design a new robust PI controller using $H_{\infty}$ loop-shaping to decrease noise effects that come out from human body and errors for time delay. The system with designed controller shows more stable control of mean blood pressure and more robust performance for uncertainties. Validation methods for the control performance are confirmed to computer simulations.

• Geotechnical Engineering
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• v.9 no.3
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• pp.67-76
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• 1993

Korea being composed of a number of mountains has been damaged and destroyed in lives and properties by the occurrence of many landslides during the wet seasons. Therefore, it is necessary to study the forecast system and risk analysis for the occurrence of landslides : the rise of groundwater levels due to rainfall is the main cause of landslides. In this paper, the autoregressive models are used to predict the grondwater levls using cases of both time invariant and time -varing autoregressive coefficients. In the former case, AR(1), AR(2), and AR(3) models are selected and their single-valued parameters are estimated to fit them to the observed groundwater level series. In the latter case, modified AR(1) and typical AR(2) models are used as process model and a discrete Kalman Filtering technique is utilized to estimate the parameters which are themselves a function of time. The results show that the real time forecast system using the time-varying autoregressive coefficinets as well as time -invariant AR model is good to predict the groundwater level in hillside slopes and we might get better result if we use the time-hourly rainfall intensity as well as the observed groundwater level.

• The Korean Journal of Financial Management
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• v.26 no.3
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• pp.199-226
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• 2009

We examine the intertemporal relation between risk and return in the Korean stock market and foreign exchange market based on the two factor ICAPM framework. The standard GARCH model and the GJR(1993) model are employed to estimate conditional variances of the stock returns and foreign exchange rates. The covariance between the rates of stock returns and changes in the exchange rates are estimated by the constant conditional correlation model of Bollerslev(1990) and the dynamic conditional correlation model of Engle(2002). The multivariate GARCH in mean model and quasi-maximum likelihood estimation method, consequently, are applied to investigate riskreturn relation jointly. We find that the estimated coefficient of relative risk aversion is negative and statistically significant in the post-financial crisis sample period in the Korean stock market. We also show that the expected stock returns are negatively related to the dynamic covariance with foreign exchange rates. Both estimated parameters of conditional variance and covariance in the foreign exchange market, however, are not statistically significant. The GJR model is better than the standard GARCH model to estimate the conditional variances. In addition, the dynamic conditional correlation model has higher explanatory power than the constant correlation model. The empirical results of this study suggest following two points to investors and risk managers in hedging and diversifying strategies for their portfolios in the Korean stock market: first, the variability of foreign exchange rates should be considered, and second, time-varying correlation between stock returns and changes in foreign exchange rates supposed to be considered.

• Journal of the Korean Society of Safety
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• v.30 no.1
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• pp.14-20
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• 2015

A Large Eddy Simulation(LES) was performed for the prediction of unsteady dispersion behavior of hydrogen fluoride (HF). The HF leakage accident occurred at the Gumi fourth industrial complex was numerically investigated using the Fire Dynamics Simulator (FDS) based on the LES. The accident area was modeled three-dimensionally and time-varying boundary conditions for wind were adopted in the simulation for considering the realistic accident conditions. The Message Passing Interface (MPI) parallel computation technique was used to reduce the computational time. As a result, it was found that the present LES simulation could predict the unsteady dispersion features of HF near the accident area effectively. The dispersion behaviors of the leaked HF was much affected by the unsteady wind direction. The LES could predict the time variation of the HF concentration reasonably and give an useful information for the risk analysis while the prediction with the time-averaging concept of HF concentration had a limitation for the amount of HF concentration at specific location point. It was identified that the LES is very useful to predict the dispersion characteristics of hazardous chemicals.

• Asia-Pacific Journal of Business
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• v.11 no.3
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• pp.243-260
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• 2020

Purpose - This paper aims to investigate the properties of crude oil based derivative security (DLS) focusing on step-down type for comprehensive understanding of its risk. Design/methodology/approach - Kernel estimation is conducted to figure out statistical feature of the process of oil price. We simulate oil price paths based on kernel estimation results and derive probabilities of hitting the barrier and early redemption. Findings - The amount of issuance for crude oil based DLS is relatively low when base prices are below $40 while it is high when base prices are around $60 or $100, which is not consistent with kernel estimation results showing that oil futures prices tend to revert toward $46.14 and the mean-reverting speed is faster as oil price is lower. The analysis based on simulated oil price paths reveals that probability of early redemption is below 50% for DLS with high base prices and the ratio of the probability of early redemption to the probability of hitting barrier is remarkably low compared to the case for DLS with low base prices, as the chance of early redemption is deferred. Research implications or Originality - Empirical results imply that the level of the base price is a crucial factor of the risk for DLS, thus introducing a time-varying knock-in barrier, which is similar to adjust the base price, merits consideration to enhance protection for DLS investors.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.4B
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• pp.389-397
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• 2010

This study introduced a Bayesian based frequency analysis in which the statistical trend analysis for hydrologic extreme series is incorporated. The proposed model employed Gumbel extreme distribution to characterize extreme events and a fully coupled bayesian frequency model was finally utilized to estimate design rainfalls in Seoul. Posterior distributions of the model parameters in both Gumbel distribution and trend analysis were updated through Markov Chain Monte Carlo Simulation mainly utilizing Gibbs sampler. This study proposed a way to make use of nonstationary frequency model for dynamic risk analysis, and showed an increase of hydrologic risk with time varying probability density functions. The proposed study showed advantage in assessing statistical significance of parameters associated with trend analysis through statistical inference utilizing derived posterior distributions.

• Annals of Hepato-Biliary-Pancreatic Surgery
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• v.27 no.2
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• pp.158-165
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• 2023

Backgrounds/Aims: Within two years of surgery, 70% of resected intrahepatic cholangiocarcinoma (iCCA) recur. Better biomarkers are needed to identify those at risk of "early recurrence" (ER). In this study, we defined ER and investigated whether preoperative neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic-inflammatory index were prognostic of both overall relapse and ER after curative hepatectomy for iCCA. Methods: A retrospective cohort of patients who underwent curative-intent hepatectomy for iCCA between 2005 and 2017 were created. The cut-off timepoint for the ER of iCCA was estimated using a piecewise linear regression model. Univariable analyses of recurrence were conducted for the overall, early, and late recurrence periods. For the early and late recurrence periods, multivariable Cox regression with time-varying regression coefficient analysis was used. Results: A total of 113 patients were included in this study. ER was defined as recurrence within 12 months of a curative resection. Among the included patients, 38.1% experienced ER. In the univariable model, a higher preoperative NLR (> 4.3) was significantly associated with an increased risk of recurrence overall and in the first 12 months after curative surgery. In the multivariable model, a higher NLR was associated with a higher recurrence rate overall and in the ER period (≤ 12 months), but not in the late recurrence period. Conclusions: Preoperative NLR was prognostic of both overall recurrence and ER after curative iCCA resection. NLR is easily obtained before and after surgery and should be integrated into ER prediction tools to guide preoperative treatments and intensify postoperative follow-up.

• The Korean Journal of Applied Statistics
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• v.24 no.2
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• pp.293-305
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• 2011

The volatility is one of most important parameters in the areas of pricing of financial derivatives an measuring risks arising from a sudden change of economic circumstance. We propose a Bayesian approach to estimate the volatility varying with time under a linear model with ARMA(p, q)-GARCH(r, s) errors. This Bayesian estimate of the volatility is compared with the ML estimate. We also present the probability of existence of the unit root in the GARCH model.