• Korean Journal of Construction Engineering and Management
• /
• v.5 no.2 s.18
• /
• pp.115-122
• /
• 2004

This study identifies various risk factors associated with activities of early construction stage, then establishes the Risk Breakdown Structure(RBS) by classifying the risks into the three groups; Common risks, risks for Earth works, and risks for Foundation works. The Common risks are identified and classified by considering various aspects of the early construction stage such as financial, political, constructional aspects, etc. The risks for Earth works and Foundation works are identified in detail by surveying technical specifications, relevant claim cases and interviewing with experts. These risks are classified based on the Wok Breakdown Structure(WBS) of the early construction stage. The WBS presented in this study classifies the works of early construction stage into four categories; excavation, sheeting works, foundation works, footing works. This study suggests a risk analysis method using fuzzy theory for construction projects. Construction risks are generally evaluated as vague linguistic value by subjective decision making. Fuzzy theory is a proper method to quantify vague conditions of construction activities. Therefore, this study utilizes fuzzy theory to analyse construction risks. The weight of risks is estimated by reflecting the interrelationship among risk factors from absolute weights obtained by fuzzy measure into the relative weights by Analytical Hierarchy Process(AHP). The interrelationship is estimated by Sugeno-fuzzy measure.

• East Asian mathematical journal
• /
• v.34 no.1
• /
• pp.1-16
• /
• 2018

We study an optimization problem for hyperbolic absolute risk aversion (HARA) utility function under two-factor Heston's stochastic volatility model. It is not possible to obtain an explicit solution because our financial market model is complicated. However, by using asymptotic analysis technique, we find the explicit forms of the approximations of the optimal value function and the optimal strategy for HARA utility function.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.1
• /
• pp.385-405
• /
• 2019

High Efficiency Video Coding (HEVC) enables significantly improved compression performance relative to existing standards. However, the advance also requires high computational complexity. To accelerate the intra prediction mode decision, a minimum risk Bayesian classification framework is introduced. The classifier selects a small number of candidate modes to be evaluated by a rate-distortion optimization process using the sum of absolute Hadamard transformed difference (SATD). Moreover, the proposed method provides a loss factor that is a good trade-off model between computational complexity and coding efficiency. Experimental results show that the proposed method achieves a 31.54% average reduction in the encoding run time with a negligible coding loss of 0.93% BD-rate relative to HEVC test model 16.6 for the Intra_Main common test condition.

• Journal of Korea Water Resources Association
• /
• v.52 no.12
• /
• pp.963-973
• /
• 2019

This study reviews a urban flooding risk criteria estimation model to predict risk criteria in areas where flood risk criteria are not precalculated by using watershed characteristic data and limit rainfall based on damage history. The risk criteria estimation model was designed using Support Vector Machine, one of the machine learning algorithms. The learning data consisted of regional limit rainfall and watershed characteristic. The learning data were applied to the SVM algorithm after normalization. We calculated the mean absolute error and standard deviation using Leave-One-Out and K-fold cross-validation algorithms and evaluated the performance of the model. In Leave-One-Out, models with small standard deviation were selected as the optimal model, and models with less folds were selected in the K-fold. The average accuracy of the selected models by rainfall duration is over 80%, suggesting that SVM can be used to estimate flooding risk criteria.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.32 no.5B
• /
• pp.267-272
• /
• 2012

To reduce the flood risk caused by unexpected heavy rainfall, many prediction methods for flood have been developed. A major constituent of flood prediction is an accurate rainfall estimation which is an input of hydrologic models. In this study, a regional-scale weather model which can provide relatively longer lead time for flood mitigation compared to the Nowcasting based on radar system will be introduced and applied to the Chongmi river basin located in central part of South Korea. The duration of application of a regional weather model is from July 11 to July 23 in 2006. The estimated rainfall amounts were compared with observations from rain gauges (Sangkeuk, Samjook, and Sulsung). For this rainfall event at Chongmi river basin, Thomson and Kain-Frisch Schemes for microphysics and cumulus parameterization, respectively, were selected as optimal physical conditions to present rainfall fall amount in terms of Mean Absolute Relative Errors (MARE>0.45).

• Journal of Korean Society on Water Environment
• /
• v.31 no.5
• /
• pp.543-555
• /
• 2015

The existing standard for soil erosion risk assessment has limitations in sustainable topsoil management since the fixed criteria are applied to determination of soil erosion risk areas regardless of land use types. It may not be necessary to apply soil erosion best management practices to agricultural areas with high potential of soil erosion because human or economic damage derived from soil erosion might be tiny in that region. Furthermore, the fixed criterion with absolute values can select too many hot spots of soil erosion to conduct efficient soil erosion management. Thus, objective of this study was to suggest the relative criteria using statistical analysis for efficient soil erosion management. In future, the relative indices for soil erosion prevention should be improved to provide a priority of soil erosion management considering economic damage from soil erosion or functional values of soil with quantitative soil erosion. Additional researches will be needed to reflect a regional characteristics and to consider various land use types and different criteria.

• Radiation Oncology Journal
• /
• v.35 no.1
• /
• pp.78-89
• /
• 2017

Purpose: To determine the optimal radiotherapy technique for gastric mucosa-associated lymphoid tissue lymphoma (MALToma), we compared the dosimetric parameters and the risk of solid secondary cancer from scattered doses among anterior-posterior/ posterior-anterior parallel-opposed fields (AP/PA), anterior, posterior, right, and left lateral fields (4_field), 3-dimensional conformal radiotherapy (3D-CRT) using noncoplanar beams, and intensity-modulated radiotherapy composed of 7 coplanar beams (IMRT_co) and 7 coplanar and noncoplanar beams (IMRT_non). Materials and Methods: We retrospectively generated 5 planning techniques for 5 patients with gastric MALToma. Homogeneity index (HI), conformity index (CI), and mean doses of the kidney and liver were calculated from the dose-volume histograms. Applied the Biological Effects of Ionizing Radiation VII report to scattered doses, the lifetime attributable risk (LAR) was calculated to estimate the risk of solid secondary cancer. Results: The best value of CI was obtained with IMRT, although the HI varied among patients. The mean kidney dose was the highest with AP/PA, followed by 4_field, 3D-CRT, IMRT_co, and IMRT_non. On the other hand, the mean liver dose was the highest with 4_field and the lowest with AP/PA. Compared with 4_field, the LAR for 3D-CRT decreased except the lungs, and the LAR for IMRT_co and IMRT_non increased except the lungs. However, the absolute differences were much lower than <1%. Conclusion: Tailored RT techniques seem to be beneficial because it could achieve adjacent organ sparing with very small and clinically irrelevant increase of secondary solid cancer risk compared to the conventional techniques.

• KDI Journal of Economic Policy
• /
• v.32 no.3
• /
• pp.71-99
• /
• 2010

The concept of CoVaR introduced by Adrian and Brunnermeier (2009) is a useful tool to measure the risk spillover effect. It can capture the risk contribution of each institution to overall systemic risk. While Adrian and Brunnermeier rely on the quantile regression method in the estimation of CoVaR, we propose a new estimation method using parametric distribution functions such as bivariate normal and $S_U$-normal distribution functions. Based on our estimates of CoVaR for Korean banking industry, we investigate the practical usefulness of CoVaR for a systemic risk measure, and compare the estimation performance of each model. Empirical results show that bank makes a positive contribution to system risk. We also find that quantile regression and normal distribution models tend to considerably underestimate the CoVaR (in absolute value) compared to $S_U$-normal distribution model, and this underestimation becomes serious when the crisis in a financial system is assumed.

• Korean Journal of Clinical Pharmacy
• /
• v.33 no.3
• /
• pp.168-177
• /
• 2023

Background & Objectives: Fixed-dose combinations (FDCs) offer advantages in adherence and cost-effectiveness compared to free combinations (FCs), but they can also complicate the prescribing process, potentially leading to therapeutic duplication (TD). This study aimed to identify the prescribing patterns of FDCs for dyslipidemia and investigate their associated risk of TD. Methods: This was a retrospective cohort study involving drugs that included statins, using Health Insurance Review & Assessment Service-National Patient Sample (HIRA-NPS) data from 2018. The unit of analysis was a prescription claim. The primary outcome was TD. The risk ratio of TD was calculated and adjusted for patient, prescriber, and the number of cardiovascular drugs prescribed using a multivariable Poisson model. Results: Our study included 252,797 FDC prescriptions and 515,666 FC prescriptions. Of the FDC group, 46.52% were male patients and 56.21% were aged 41 to 65. Ezetimibe was included in 71.61% of the FDC group, but only 0.25% of the FC group. TD occurred in 0.18% of the FDC group, and the adjusted risk ratio of TD in FDC prescriptions compared to FC was 6. 44 (95% CI 5. 30-7. 82). Conclusions: Prescribing FDCs for dyslipidemia was associated with a higher risk of TD compared to free combinations. Despite the relatively low absolute prevalence of TD, the findings underline the necessity for strategies to mitigate this risk when prescribing FDCs for dyslipidemia. Our study suggests the potential utility of Clinical Decision Support Systems and standardizing nomenclature in reducing medication errors, providing valuable insights for clinical practice and future research.

• The Korean Journal of Applied Statistics
• /
• v.29 no.7
• /
• pp.1231-1246
• /
• 2016

Cause-specific hazard model (Prentice et al., 1978) and subdistribution hazard model (Fine and Gray, 1999) are mostly used for the right censored survival data with competing risks. Some other models for survival data with competing risks have been subsequently introduced; however, those models have not been popularly used because the models cannot provide reliable statistical estimation methods or those are overly difficult to compute. We introduce simple and reliable competing risk regression models which have been recently proposed as well as compare their methodologies. We show how to use SAS and R for the data with competing risks. In addition, we analyze survival data with two competing risks using five different models.