• Asian Pacific Journal of Cancer Prevention
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• v.15 no.16
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• pp.6819-6822
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• 2014

Background: The aim of this study was to evaluate the accuracy of a new scoring system in Korean patients with hematuria at high risk of bladder cancer. Materials and Methods: A total of 319 consecutive patients presenting with painless hematuria without a history of bladder cancer were analyzed, from the period of August 2012 to February 2014. All patients underwent clinical examination, and 22 patients with incomplete data were excluded from the final validation data set. The scoring system included four clinical parameters: age (${\geq}50$ = 2 vs. <50 =1), gender (male = 2 vs. female = 1), history of smoking (smoker/ex-smoker = 4 vs. non-smoker = 2) and nature of the hematuria (gross = 6 vs. microscopic = 2). Results: The area under the receiver-operating characteristic curve (95% confidence interval) of the scoring system was 0.718 (0.655-0.777). The calibration plot demonstrated a slight underestimation of bladder cancer probability, but the model had reasonable calibration. Decision curve analysis revealed that the use of model was associated with net benefit gains over the treat-all strategy. The scoring system performed well across a wide range of threshold probabilities (15%-45%). Conclusions: The scoring system developed is a highly accurate predictive tool for patients with hematuria. Although further improvements are needed, utilization of this system may assist primary care physicians and other healthcare practitioners in determining a patient's risk of bladder cancer.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.28 no.8
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• pp.501-507
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• 2015

In this paper, EPR (ethylene propylene rubber) insulation material was accelerated degradation test at $121^{\circ}C$, $136^{\circ}C$, $151^{\circ}C$, and experiment the typical EAB (elongation at break) at mechanical characteristics analysis. It is shown that the failure-time at the point of 50% of the initial value of Elongation rate to obtain the activation energy. The failure-time was shown each 5,219 hr, 3,165 hr, and 668 hr at three temperatures. In order to derive the activation energy, Arrhenius methodology was applied. Also, we got the Arrhenius plot from three accelerated temperatures. The activation energy values got 0.98 eV from EAB test. The experimental data were evaluated for estimating the probability density, and the suitable distribution by using statistical program MINITAB. It is shown that EAB data by the acceleration thermal degradation is most suitable for the Weibull distribution.

• YAKHAK HOEJI
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• v.39 no.2
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• pp.103-112
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• 1995

Population pharmacokinetics for gentamicin were compared with 24 American patients (16 male and 8 female) and 16 Korean-American appendicitis patients(12 male and 4 female). Two to six blood specimens were collected from all patients at the following times: just before a regularly scheduled infusion and at 1/2 hour after the end of a 1/2 hour infusion. Nonparametric expected maximum(NPEM) algorithm for population modeling was used. The estimated parameters were the elimination rate constant(K), the slope of the relationship between K versus creatinine clearance(KS), the apparent volume of distribution(V), the slope of the relationship between V versus weight(VS), gentamicin clearance(CL) and the slope of the relationship between CL versus creatinine clearance and the VS(CS). The output includes a 3-dimensional plot of the joint probability density function(PDF), two marginal PDF, means, medians, modes, variance, skewness, kurtosis, and CV%. The mean K(KS) were 0.424$\pm$0.139(0.00429$\pm$0.00164) and 0.411$\pm$0.135 hr$^{-1}$ (0.00475$\pm$0.00180[hr.mL/min/1.73m$^{2}]^{-1}$) for American and Korean-American populations, respectively. The mean V(VS) were not different at 15.6$\pm$4.77(0.233$\pm$0.0526) and 15.1$\pm$3.84L(0.239$\pm$0.0492 L/kg) for American and Korean-American populations, respectively (P>0.2). The mean CL (CS) were 6.28$\pm$1.85(0.0634$\pm$0.0191) and 5.70$\pm$1.77 L/hr(0.0701$\pm$0.0215 L/kg[hr.mL/min/1.73m$^{2}$)] for American and Korean-American populations, respectively. There are no differences in gentamicin pharmacokinetics between American and Korean-American Appendicitis patients.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.79-82
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• 2012

최근 지진해일 발생으로 인한 막대한 피해로 인해 지진해일 방재에 대한 중요성이 높아지고 있다. 지진해일 방재연구는 주로 실제 발생하였던 역사지진해일과 발생가능성이 높은 가상의 지진해일에 대해 해당지역의 재해정보도를 제작하여, 지진해일 발생 시 인명 및 재산피해를 최소화 하는 것에 초점이 맞추어져 있다. 따라서 이번 연구에서는 이러한 재해정보도의 효율성을 높이기 위해 지진해일 발생 시 인명피해가 발생할 가능성이 높은 위험지역을 선정하였다. 지진해일 위험지역을 선정하기 위해 가상의 지진해일을 수치모의 하였으며, 지진해일 발생 시 인명피해가 발생할 수 있는 지진해일 범람 높이를 선정하여 선정한 기준 높이 이상의 범람이 발생할 확률을 계산하였다. 지진해일 수치모의는 지진해일 전파모의와 범람모의 과정으로 이루어진다. 지진해일 전파모형은 선형 Boussinesq 방정식을 지배방정식으로 사용하며, 지진해일 범람모형은 비선형 천수방정식을 지배방정식으로 사용하였다. 수치모의를 통해 주문진항에서의 가상의 지진해일에 대한 범람영역 및 범람 높이를 얻었다. 수치모의를 통해 얻어진 범람 데이터를 이용해 기준 높이 이상의 범람 발생 확률을 계산하였다. 확률 계산을 위해선 해당 데이터의 확률분포를 결정하여야 하기 때문에, 적합도 검정을 수행하였다. 이번 연구에서는 여러 가지 적합도 검정 기법 중 하나인 확률도시 상관계수 검정(Probability Plot Correlation Coefficient Test)을 사용하였으며, 범람 데이터의 확률분포로 Normal, Log-normal, Exponential, Gumbel 분포를 가정하여 검정을 수행하였다. 각 지점별로 확률도시 상관계수 검정을 수행하여, 해당 지점의 확률분포를 결정하였고, 각 지점별로 해당하는 확률분포의 누적확률분포 함수를 이용해 기준 높이 이상의 범람이 발생할 확률을 계산하였다. 얻어진 확률을 지도상에 도시하여 기준 높이 이상의 범람 발생 확률이 높은 지점을 주문진항에서의 지진해일에 대한 인명피해 발생 가능성이 높은 위험지역으로 선정하였다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.6
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• pp.800-806
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• 2018

Software efficiency is the probability of failure free use in operating environments, and is the most fundamental factor affecting software system stability. The malfunction of the computer system used in the information technology field may cause a significant loss in the related industry. Therefore, in this study, we analyze the attributes of software reliability models that depend on various hazard functions based on finite fault NHPP model with software failure time data. The hazard function pattern of proposed model is constant for the Goel-Okumoto model, and the Minimax and Rayleigh models follow the incremental pattern, but the hazard function increase value of the Minimax model is smaller than that of the Rayleigh model and the Goel-Okumoto model. Also, the Minimax model was relatively efficient because the true value error of the mean value function m(t) and the mean square error (MSE) of the Minimax model were smaller than those of the Rayleigh and Goel-Okumoto models. The results of this study are expected to be useful for software developers as basic information about the hazard function.

• Journal of Home Health Care Nursing
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• v.30 no.1
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• pp.48-58
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• 2023

Purpose: The purpose of this study was to construct a nomogram for predicting difficulty in peripheral intravenous cannulation (DPIVC) for adult inpatients. Methods: This study conducted a secondary analysis of data from the intravenous cannulation cohort by intravenous specialist nurses at a tertiary hospital in Seoul. Overall, 504 patients were included; of these, 166 (32.9%) patients with failed cannulation in the first intravenous cannulation attempt were included in the case group, while the remaining 338 patients were included in the control group. The nomogram was built with the identified risk factors using a multiple logistic regression analysis. The model performance was analyzed using the Hosmer-Lemeshow test, area under the curve (AUC), and calibration plot. Results: Five factors, including vein diameter, vein visibility, chronic kidney disease, diabetes, and chemotherapy, were risk factors of DPIVC. The nomogram showed good discrimination with an AUC of 0.81 (95% confidence interval: 0.80-0.82) by the sample data and 0.79 (95% confidence interval: 0.74-0.84) by bootstrapping validation. The Hosmer-Lemeshow goodness-of-fit test showed a p-value of 0.694, and the calibration curve of the nomogram showed high coherence between the predicted and actual probabilities of DPIVC. Conclusion: This nomogram can be used in clinical practice by nurses to predict DPIVC probability. Future studies are required, including those on factors possibly affecting intravenous cannulation.

• Computers and Concrete
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• v.33 no.1
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• pp.55-75
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• 2024

The present study introduces an optimum performance soft computing model for predicting the compressive strength of high-performance concrete (HPC) by comparing models based on conventional (kernel-based, covariance function-based, and tree-based), advanced machine (least square support vector machine-LSSVM and minimax probability machine regressor-MPMR), and deep (artificial neural network-ANN) learning approaches using a common database for the first time. A compressive strength database, having results of 1030 concrete samples, has been compiled from the literature and preprocessed. For the purpose of training, testing, and validation of soft computing models, 803, 101, and 101 data points have been selected arbitrarily from preprocessed data points, i.e., 1005. Thirteen performance metrics, including three new metrics, i.e., a20-index, index of agreement, and index of scatter, have been implemented for each model. The performance comparison reveals that the SVM (kernel-based), ET (tree-based), MPMR (advanced), and ANN (deep) models have achieved higher performance in predicting the compressive strength of HPC. From the overall analysis of performance, accuracy, Taylor plot, accuracy metric, regression error characteristics curve, Anderson-Darling, Wilcoxon, Uncertainty, and reliability, it has been observed that model CS4 based on the ensemble tree has been recognized as an optimum performance model with higher performance, i.e., a correlation coefficient of 0.9352, root mean square error of 5.76 MPa, and mean absolute error of 4.1069 MPa. The present study also reveals that multicollinearity affects the prediction accuracy of Gaussian process regression, decision tree, multilinear regression, and adaptive boosting regressor models, novel research in compressive strength prediction of HPC. The cosine sensitivity analysis reveals that the prediction of compressive strength of HPC is highly affected by cement content, fine aggregate, coarse aggregate, and water content.

• Journal of the Korean Society of Food Science and Nutrition
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• v.38 no.2
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• pp.235-243
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• 2009

This study was performed to find the optimum ratio of ingredients in the Chinese radish jam. The experiment was designed according to the RSM (response surface methodology), which included 18 experimental points with 4 replicates for three independent variables (sugar $45{\sim}70%$, pectin $0.5{\sim}2.0.%$, citric acid $0.2{\sim}0.5%$). The compositional and functional properties of the prepared products were measured, and these values were applied to the mathematical models. By use of F-test, sweetness, color values (L, a, b), and firmness were expressed by a linear model, while the sensory characteristics (color, smell, taste, texture and overall acceptance) were by a quadratic model. In the numeric optimization, the optimal ingredient amounts were 53.7% sugar, 1.0% pectin, and 0.3% citric acid. And in the graphical optimization, 53.9% sugar, 1.0% pectin, and 0.3% citric acid; these data were equivalent to 0.6985 desirability, indicating that the values were almost equivalent to the numerical optimization points. The above results demonstrate the feasibility of Chinese radish jam, and therefore, the commercialization of a Chinese radish jam marketed as a functional food is deemed possible.

• Resources Recycling
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• v.27 no.1
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• pp.84-91
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• 2018

In this study, a novel soft information based most probable classification scheme is proposed for sorting recyclable metal alloys with laser induced breakdown spectroscopy (LIBS). Regression analysis with LIBS captured spectrums for estimating concentrations of common elements can be efficient for classifying unknown arbitrary metal alloys, even when that particular alloy is not included for training. Therefore, partial least square regression (PLSR) is employed in the proposed scheme, where spectrums of the certified reference materials (CRMs) are used for training. With the PLSR model, the concentrations of the test spectrum are estimated independently and are compared to those of CRMs for finding out the most probable class. Then, joint soft information can be obtained by assuming multi-variate normal (MVN) distribution, which enables to account the probability measure or a prior information and improves classification performance. For evaluating the proposed schemes, MVN soft information is evaluated based on PLSR of LIBS captured spectrums of 9 metal CRMs, and tested for classifying unknown metal alloys. Furthermore, the likelihood is evaluated with the radar chart to effectively visualize and search the most probable class among the candidates. By the leave-one-out cross validation tests, the proposed scheme is not only showing improved classification accuracies but also helpful for adaptive post-processing to correct the mis-classifications.

• Journal of Navigation and Port Research
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• v.31 no.1 s.117
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• pp.1-6
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• 2007

The evaluation of safety of simulated maneuvers is frequently analysed by so called goal-line or point of interest in Korea. For the purpose of warning the risk in the proximity measure composed of only the goal-line analysis, this paper utilized Korea Institute of Maritime and Fisheries Technology(KIMFT) which houses a real-time, full-mission shiphandling simulator to examine the goal-line and in-length analyses in the outbound channel of Kwangyang port as an example. It used a 15,000 TEU container ship as a model under environmental conditions of the northwestly 26-knot wind and 2.2-knot ebb current. The result of two analyses showed the probability invading the channel boundary obtained by the goal-line analysis is a little greater than that of the in-length analysis. Therefore it was acknowledged that the proximity measure by the goal-line analysis alone may be followed by some risk. In addition, this paper was to suggest the closest distance to channel boundary from the ship's edge as one of proximity measures, instead of using the ship's deviation from the centerline of channel.