• Proceedings of the KSME Conference
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• 2005.11a
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• pp.108.1-108.1
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• 2005

• Journal of Korea Water Resources Association
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• v.47 no.5
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• pp.435-446
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• 2014

Various drought indices developed from previous studies can not consider the inherent uncertainty of drought because they assess droughts using a pre-defined threshold. In this study, to consider inherent uncertainty embedded in monthly streamflow data, Hidden Markov Model (HMM) based drought index (HMDI) was proposed and then probabilistic assessment of hydrologic drought was performed using HMDI instead of using pre-defined threshold. Using monthly streamflow data (1966~2009) of Pyeongchang river and Upper Namhan river provided by Water Management Information System (WAMIS), applying the HMM after moving-averaging the data with 3, 6, 12 month windows, this study calculated the posterior probability of hidden state that becomes the HMDI. For verifying the method, this study compared the HMDI and Standardized Streamflow Index (SSI) which is one of drought indices using a pre-defined threshold. When using the SSI, only one value can be used as a criterion to determine the drought severity. However, the HMDI can classify the drought condition considering inherent uncertainty in observations and show the probability of each drought condition at a particular point in time. In addition, the comparison results based on actual drought events occurred near the basin indicated that the HMDI outperformed the SSI to represent the drought events.

• The Korean Journal of Coaching Psychology
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• v.4 no.1
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• pp.1-19
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• 2020

The study was intended to explore the relevance of the variables below, assuming that the intolerance of uncertainty and dichotomous thinking would represent sequential serialized effects in the relationship between perfectionistic self-presentation and social anxiety. The data of this study were collected on questionnaire survey of 252 adult men and women in Seoul using perfectionistic self-presentation scale, social interaction anxiety scale, social phobia scale, intolerance of uncertainty scale and dichotomous thinkingI-30R as index, which results are as follow. First, intolerance of uncertainty and dichotomous thinking showed perfect mediation effects on the relationship between perfectionistic self-presentation and social anxiety. Intolerance of uncertainty and dichotomous thinking were identified as contributing factors to the development and preservation of social anxiety by perfectionistic self-presenters. Second, in the relationship between perfectionistic self-presentation and dichotomous thinking, intolerance of uncertainty showed mediation effect. And in the relationship between intolerance of uncertainty and social anxiety, dichotomous thinking showed mediation effect. This suggested that if tolerance of uncertainty was deficient, it was likely to lead to dichotomous thinking. And a dichotomous thinking has prompted or accelerated negative cognitive biases resulting from intolerance of uncertainty, triggering and deepening social anxiety. Lastly, the limitations of this study and future research direction were suggested.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.2
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• pp.1-13
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• 2015

The Coupled Model Intercomparison Project Phase 5 (CMIP5), coordinated by the World Climate Research Programme in support of the Intergovernmental Panel on Climate Change (IPCC) AR5, is the most recent, provides projections of future climate change using various global climate models under four major greenhouse gas emission scenarios. There is a wide selection of climate models available to provide projections of future climate change. These provide for a wide range of possible outcomes when trying to inform managers about possible climate changes. Hence, future agrometeorological indicators estimation will be much impacted by which global climate model and climate change scenarios are used. Decision makers are increasingly expected to use climate information, but the uncertainties associated with global climate models pose substantial hurdles for agricultural resources planning. Although it is the most reasonable that quantifying of the future uncertainty using climate change scenarios, preliminary analysis using reasonable factors for selecting a subset for decision making are needed. In order to narrow the projections to a handful of models that could be used in a climate change impact study, we could provide effective information for selecting climate model and scenarios for climate change impact assessment using maximum/minimum temperature, precipitation, reference evapotranspiration, and moisture index of nine Representative Concentration Pathways (RCP) scenarios.

• Journal of the Korean Society of Safety
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• v.27 no.1
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• pp.76-85
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• 2012

This paper proposes a robust damper design technique for adjacent structures against model uncertainty. This approach introduces multi-objective optimization based system identification using measurement information which enables reasonable selection of the perturbation range in the robust design. Moreover, in order to improve the numerical efficiency in sampling the structural models required for the robust design of large structures, we define new objective functions which enable us to minimize the number of candidate models suitable to the purpose of the robust design. In addition, the performance index is newly employed to evaluate the robust performance of the sampled structural models, and the robust design has been performed according to the performance index. As a numerical example to demonstrate the efficiency of the proposed method, 5-story and 10-story two adjacent buildings are taken into account, and the existing and newly proposed robust design approaches are compared with each other. The results demonstrate that the proposed approach can guarantee more robust damper system only using small number of samples of the structural models because of using the measurement information which leads to improvement in the numerical efficiency, compared with the existing robust design methods.

• Korea Journal of Hospital Management
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• v.25 no.4
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• pp.1-12
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• 2020

During the COVID-19 pandemic, most of the western countries with advanced medical technology failed to contain coronavirus. This fact triggered our research question of what factors influence the clinical outcomes like infection rates and case mortality rates. This study aims to identify the determinants of COVID-19 related infection rates and case mortality rates. We considered three sets of independent variables: 1) socio-demographic characteristics; 2) cultural characteristics; 3) healthcare system characteristics. For the analysis, we created an international dataset from diverse sources like World Bank, Worldometers, Hofstede Insight, GHS index etc. The COVID-19 related statistics were retrieved from Aug. 1. Total cases are from 95 countries. We used hierarchical regression method to examine the linear relationship among variables. We found that obesity, uncertainty avoidance, hospital beds per 1,000 made a significant influence on the standardized COVID-19 infection rates. The countries with higher BMI score or higher uncertainty avoidance showed higher infection rates. The standardized COVID-19 infection rates were inversely related to hospital beds per 1,000. In the analysis on the standardized COVID-19 case mortality rates, we found that two cultural characteristics(e.g., individualism, uncertainty avoidance) showed statistically significant influence on the case mortality rates. The healthcare system characteristics did not show any statistically significant relationship with the case mortality rates. The cultural characteristics turn out to be significant factors influencing the clinical outcomes during COVID-19 pandemic. The results imply that the persuasive communication is important to trigger the public commitment to follow preventive measures. The strategy to keep the hospital surge capacity needs to be developed.

• Journal of Distribution Science
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• v.11 no.10
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• pp.73-79
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• 2013

Purpose - This study examines the impact of oil price volatility on economic activities in Korea. The new millennium has seen a deregulation in the crude oil market, which invited immense capital inflow into Korea. It has also raised oil price levels and volatility. Drawing on the recent theoretical literature that emphasizes the role of volatility, this paper attends to the asymmetric changes in economic growth in response to the oil price movement. This study further examines several key macroeconomic variables, such as interest rate, production, and inflation. We come to the conclusion that oil price volatility can, in some part, explain the structural changes. Research design, data, and methodology - We use two methodological frameworks in this study. First, in regards to the oil price uncertainty, we use an Exponential-GARCH (Exponential Generalized Autoregressive Conditional Heteroskedasticity: EGARCH) model estimate to elucidate the asymmetric effect of oil price shock on the conditional oil price volatility. Second, along with the estimation of the conditional volatility by the EGARCH model, we use the estimates in a VECM (Vector Error Correction Model). The study thus examines the dynamic impacts of oil price volatility on industrial production, price levels, and monetary policy responses. We also approximate the monetary policy function by the yield of monetary stabilization bond. The data collected for the study ranges from 1990: M1 to 2013: M7. In the VECM analysis section, the time span is split into two sub-periods; one from 1990 to 1999, and another from 2000 to 2013, due to the U.S. CFTC (Commodity Futures Trading Commission) deregulation on the crude oil futures that became effective in 2000. This paper intends to probe the relationship between oil price uncertainty and macroeconomic variables since the structural change in the oil market became effective. Results and Conclusions - The dynamic impulse response functions obtained from the VECM show a prolonged dampening effect of oil price volatility shock on the industrial production across all sub-periods. We also find that inflation measured by CPI rises by one standard deviation shock in response to oil price uncertainty, and lasts for the ensuing period. In addition, the impulse response functions allude that South Korea practices an expansionary monetary policy in response to oil price shocks, which stems from oil price uncertainty. Moreover, a comparison of the results of the dynamic impulse response functions from the two sub-periods suggests that the dynamic relationships have strengthened since 2000. Specifically, the results are most drastic in terms of industrial production; the impact of oil price volatility shocks has more than doubled from the year 2000 onwards. These results again indicate that the relationships between crude oil price uncertainty and Korean macroeconomic activities have been strengthened since the year2000, which resulted in a structural change in the crude oil market due to the deregulation of the crude oil futures.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.1
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• pp.63-73
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• 2010

This paper presents the optimal design method of an overlapped ultrasonic sensor ring for reduced positional uncertainty, and its application to the obstacle detection with improved resolution. Basically, it is assumed that a set of ultrasonic sensors are installed to form a circle at regular intervals with their beams overlapped. First, exploiting the overlapped beam pattern, the positional uncertainty inherent to an ultrasonic sensor is shown to be significantly reduced. Second, for an ideal ultrasonic sensor ring of zero radius, the effective beam width is defined to represent the positional uncertainty, and the optimal number of ultrasonic sensors required for minimal effective beam width is obtained. Third, for an actual ultrasonic sensor ring of nonzero radius, the design index is defined to represent the degree of positional uncertainty, and an optimal design of an overlapped ultrasonic sensor ring consisting of commercial ultrasonic sensors with low directivity is given. Fourth, given measured distances from ultrasonic sensors, the geometric method is described to compute the obstacle position with reference to the center of a mobile robot. Finally, through experiments using our overlapped ultrasonic sensor ring prototype, the validity and performance of the proposed method is demonstrated.

• Structural Engineering and Mechanics
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• v.56 no.5
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• pp.707-726
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• 2015

There is a growing trend of considering uncertainty in optimization process since last few decades. In this regard, Robust Design Optimization (RDO) scheme has gained increasing momentum because of its virtue of improving performance of structure by minimizing the variation of performance and ensuring necessary safety and feasibility of constraint under uncertainty. In the present study, RDO of reinforced concrete folded plate and shell structure has been carried out incorporating uncertainty in the relevant parameters by Monte Carlo Simulation. Folded plate and shell structures are among the new generation popular structures often used in aesthetically appealing constructions. However, RDO study of such important structures is observed to be scarce. The optimization problem is formulated as cost minimization problem subjected to the force and displacements constraints considering dead, live and wind load. Then, the RDO is framed by simultaneously optimizing the expected value and the variation of the performance function using weighted sum approach. The robustness in constraint is ensured by adding suitable penalty term and through a target reliability index. The RDO problem is solved by Sequential Quadratic Programming. Subsequently, the results of the RDO are compared with conventional deterministic design approach. The parametric study implies that robust designs can be achieved by sacrificing only small increment in initial cost, but at the same time, considerable quality and guarantee of the structural behaviour can be ensured by the RDO solutions.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.11
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• pp.75-82
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• 2004

A metrological atomic force microscope (M-AFM) was developed fur the length measurements of nanometer range, through the modification of a commercial AFM. To eliminate nonlinearity and crosstalk of the PZT tube scanner of the commercial AFM, a two-axis flexure hinge scanner employing built-in capacitive sensors is used for X-Y motion instead of PZT tube scanner. Then two-dimensional displacement of the scanner is measured using two-axis heterodyne laser interferometer to ensure the meter-traceability. Through the measurements of several specimens, we could verify the elimination of nonlinearity and crosstalk. The uncertainty of length measurements was estimated according to the Guide to the Expression of Uncertainty in Measurement. Among several sources of uncertainty, the primary one is the drift of laser interferometer output, which occurs mainly from the variation of refractive index of air and the thermal stability. The Abbe error, which is proportional to the measured length, is another primary uncertainty source coming from the parasitic motion of the scanner. The expanded uncertainty (k =2) of length measurements using the M-AFM is √(4.26)$^2$+(2.84${\times}$10$^{-4}$ ${\times}$L)$^2$(nm), where f is the measured length in nm. We also measured the pitch of one-dimensional grating and compared the results with those obtained by optical diffractometry. The relative difference between these results is less than 0.01 %.