• Environmental Engineering Research
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• v.25 no.3
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• pp.281-289
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• 2020

Environmental fate of ionizable organic pollutants such as perfluoroalkyl acids (PFAAs) are of increasing interest but has not been well understood because of uncertain values for parameters related with atmospheric interphase partitioning behavior. In the present study, not only the values for air-water partition coefficient (K_AW) and dissociation constant (pKa) of PFAAs were induced by adjusting to in situ measurements of air-water distribution coefficient between vapor phase and rainwater but also gas-particle partition coefficients were also estimated using three-phase partitioning model of ionizable organic pollutants, in situ measurements of PFAAs in aerosol and air vapor phase, and obtained parameter values. The pKa values of PFAAs we obtained were close to the minimum values suggested in literature except for perfluorooctane sulfonic acids, and COSMOtherm-modeled K_AW values were assessed to more appropriate among suggested values. When applying parameter values we obtained, it was predicted that air particle-associated fate and transport of PFAAs could be negligible and PFAAs could distribute ubiquitously along the transection from urban to rural region by pH-dependent phase transfer in air. Our study is expected to have some implications in prediction of the environmental redistribution of other ionizable organic compounds.

• Korean Journal of Acupuncture
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• v.27 no.2
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• pp.107-120
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• 2010

Objectives : The aim of this study is to measure pulse waveforms by applying 5-level graded pressure, and selecting optimum pulse waveforms. Also to proposing the possibility of using AW(Area of the 1/3 upper height of h1) rate in respect to AT(Total Area) for risk assessment of hypertension or arteriosclerosis is another aim of the study. Methods : Pulse waveforms of normotensive were measured by 5-level graded pressure. The pulse waveforms well reflecting properties of blood vessel(having the largest h1) were selected for optimum pulse waveforms. Various parameters(h-parameter, t-parameter, and others) of optimum pulse waveforms were analyzed. AIx(Augmentation index) was calculated by height-parameters to assess arterial stiffness. The area rate of the 1/3 upper height for h1 in respect to total area was analyzed according to aging. Results : According to aging 1. in height-parameter, h2 and h3 were increased but h5 was decreased. 2. In time-parameter, t2, t3, and t5 were getting short. 3. Area of systolic period was increased, and that of diastolic period decreased. 4. AIx rose by aging. 5. AW was significantly increased despite no changes in AT. Conclusions : By analyzing optimum pulse waveforms of 5-level graded pressure method, we could complement weakness of single graded pressure method. Also, possibility of applying the AW rate to risk assessment of hypertension or arteriosclerosis was confirmed in normotensive population which might not be assessed by AIx.

• Biomedical Science Letters
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• v.13 no.2
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• pp.83-89
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• 2007

Effects of alkaline reduced water (ARW) on the scavenging of reactive oxygen species (ROS) and diabetes were recently reported. However, no studies have yet been investigated on general drinking effects. In this study, we examined 100 patients hospitalized for senile disease treatment and recuperation. All examines received the ARW for 2 months. WBC level was decreased from $6.34\pm1.9(\times10^9/L)$ to $5.66\pm1.7(\times10^9/L)$. SGPT level was decreased from 27.47$\pm$14 Ut to 23.95$\pm$8.8 U/L. Cholesterol level was increased from 167.9$\pm$32 mg/dl to 176.21$\pm$42 mg/dl within normal range. However, the levels of potassium, adiponectin, SGOT and blood pressure showed no significant difference. The levels of growth hormone and homocysteine and mini-mental state examination also showed no significant difference. We suppose that the slight blood parameter trends indicate an improved physical condition induced by the ARW. Furthermore, we could found no harmful effect of the ARW in this study.

• Health Policy and Management
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• v.19 no.4
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• pp.98-120
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• 2009

The purpose of this study is to elicit preference for drug listing decision criteria and to estimate the ICER threshold in South Korea using the discrete choice experiment (DCE) method. To collect the data, a DCE survey was administered to a subject sample either educated in the principle concepts of pharmacoeconomics or were decision makers within that field. Subjects chose between alternative drug profiles differing in four attributes: ICER, uncertainty, budget impact and severity of disease. The orthogonal and balanced designs were determined through computer algorithm to take the optimal set of drug profiles. The survey employed 15 hypothetical choice sets. A random effect probit model was used to analyze the relative importance of attributes and the probabilities of a recommendation response. Parameter estimates from the models indicated that three attributes (ICER, Impact, Severity of disease) influenced respondents' choice significantly(p${\pm}$0.001). In addition, each parameter displayed an expected sign. The Lower the ICER, the higher the probability of choosing that alternative. Respondents also preferred low levels of uncertainty and smaller impact on health service budget. They were also more likely to choose drugs for serious diseases rather than mild or moderate ones. Uncertainty however is not statistically significant. The ICER threshold, at which the probability of a recommendation was 0.5, was 29,000,000 KW/QALY in expert group and 46,500,000 KW/QALY in industry group. We also found that those in our sample were willing to accept high ICER to get medication for severe diseases. This study demonstrates that the cost-effectiveness, budget impact and severity of disease are the main reimbursement decision criteria in South Korea, and that DCE can be a useful tool in analyzing the decision making process where a variety of factors are considered and prioritized.

• Communications for Statistical Applications and Methods
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• v.16 no.6
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• pp.1055-1066
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• 2009

Many articles have considered a hybrid censoring scheme, which is a mixture of Type-I and Type-II censoring schemes. We introduce a double hybrid censoring scheme and derive some approximate maximum likelihood estimators(AMLEs) of the scale parameter for the half logistic distribution under the proposed double hybrid censored samples. The scale parameter is estimated by approximate maximum likelihood estimation method using two different Taylor series expansion types. We also obtain the maximum likelihood estimator(MLE) and the least square estimator(LSE) of the scale parameter under the proposed double hybrid censored samples. We compare the proposed estimators in the sense of the mean squared error. The simulation procedure is repeated 10,000 times for the sample size n = 20(10)40 and various censored samples. The performances of the AMLEs and MLE are very similar in all aspects but the MLE and LSE have not a closed-form expression, some numerical method must be employed.

• Journal of the Korean Data and Information Science Society
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• v.21 no.2
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• pp.345-354
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• 2010

The Gamma Distribution is widely used in Engineering and Industrial applications. Estimation of parameters is revisited in the two-parameter Gamma distribution. The parameters are estimated by minimizing the likelihood ratios. A comparative study between the method of moments, the maximum likelihood method, the method of product spacings, and minimization of three different likelihood ratios is performed using simulation. For the scale parameter, the maximum likelihood estimate performs better and for the shape parameter, the product spacings estimate performs better. Among the three likelihood ratio statistics considered, the Anderson-Darling statistic has inferior performance compared to the Cramer-von-Misses statistic and the Kolmogorov-Smirnov statistic.

• Communications for Statistical Applications and Methods
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• v.27 no.6
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• pp.625-639
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• 2020

The gamma distribution is a flexible right-skewed distribution widely used in many areas, and it is of great interest to estimate the probability of a random variable exceeding a specified value in survival and reliability analysis. Therefore, the study develops a fixed-accuracy confidence interval for P(X > c) when X follows a gamma distribution, Γ(α, β), and c is a preassigned positive constant through: 1) a purely sequential procedure with known shape parameter α and unknown rate parameter β; and 2) a nonparametric purely sequential procedure with both shape and rate parameters unknown. Both procedures enjoy appealing asymptotic first-order efficiency and asymptotic consistency properties. Extensive simulations validate the theoretical findings. Three real-life data examples from health studies and steel manufacturing study are discussed to illustrate the practical applicability of both procedures.

• Journal of Convergence for Information Technology
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• v.9 no.8
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• pp.20-26
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• 2019

In this study, the optimal shape parameter condition is presented after analyzing the attributes of the software reliability model according to the change of the shape parameter of Loma life distribution with infinite fault NHPP. In order to analyze the software failure phenomena, the parametric estimation method was applied to the Maximum Likelihood Estimation method, and the nonlinear equation was applied to the bisection method. As a result, it was found that when the attributes according to the change of the shape parameter are compared, the smaller the shape parameter is, the better the prediction ability of the true value, and reliability attributes are efficient. Through this study, it is expected that software developers can increase reliability by preliminarily grasping the type of software failure based on shape parameter, and can be used as basic information to improve the software reliability attributes.

• Smart Structures and Systems
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• v.23 no.4
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• pp.359-371
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• 2019

As part of a structural health monitoring system, the relative geometric relationship between a ship and bridge has been recognized as important for bridge authorities and ship owners to avoid ship-bridge collision. This study proposes a novel computer vision method for the real-time geometric parameter identification of moving ships based on a single shot multibox detector (SSD) by using transfer learning techniques and monocular vision. The identification framework consists of ship detection (coarse scale) and geometric parameter calculation (fine scale) modules. For the ship detection, the SSD, which is a deep learning algorithm, was employed and fine-tuned by ship image samples downloaded from the Internet to obtain the rectangle regions of interest in the coarse scale. Subsequently, for the geometric parameter calculation, an accurate ship contour is created using morphological operations within the saturation channel in hue, saturation, and value color space. Furthermore, a local coordinate system was constructed using projective geometry transformation to calculate the geometric parameters of ships, such as width, length, height, localization, and velocity. The application of the proposed method to in situ video images, obtained from cameras set on the girder of the Wuhan Yangtze River Bridge above the shipping channel, confirmed the efficiency, accuracy, and effectiveness of the proposed method.

• Smart Structures and Systems
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• v.26 no.6
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• pp.735-751
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• 2020

Identification of structure parameters is crucial in Structural Health Monitoring (SHM) context for activities such as model validation, damage assessment and signal processing of structure response. In this paper, guided waves generated by piezoelectric transducers are used for in-situ and non-destructive structural parameter estimation based on Bayesian approach. As Bayesian approach needs iterative process, which is computationally expensive, this paper proposes a method in which an analytical model is selected and developed in order to decrease computational time and complexity of modeling. An experimental set-up is implemented to estimate three target elastic and geometrical parameters: Young's modulus, Poisson ratio and thickness of aluminum and steel plates. Experimental and simulated data are combined in a Bayesian framework for parameter identification. A significant accuracy is achieved regarding estimation of target parameters with maximum error of 8, 11 and 17 percent respectively. Moreover, the limitation of analytical model concerning boundary reflections is addressed and managed experimentally. Pulse excitation is selected as it can excite the structure in a wide frequency range contrary to conventional tone burst excitation. The results show that the proposed non-destructive method can be used in service for estimation of material and geometrical properties of structure in industrial applications.