• Korean Journal of Clinical Pharmacy
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• v.26 no.4
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• pp.312-317
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• 2016

Objective: Midazolam is mainly metabolized by cytochrome P450 (CYP) 3A. Inhibition or induction of CYP3A can affect the pharmacological activity of midazolam. The aims of this study were to develop a population pharmacokinetic (PK) model and evaluate the effect of CYP3A-mediated interactions among ketoconazole, rifampicin, and midazolam. Methods: Three-treatment, three-period, crossover study was conducted in 24 healthy male subjects. Each subject received 1 mg midazolam (control), 1 mg midazolam after pretreatment with 400 mg ketoconazole once daily for 4 days (CYP3A inhibition phase), and 2.5 mg midazolam after pretreatment with 600 mg rifampicin once daily for 10 days (CYP3A induction phase). The population PK analysis was performed using a nonlinear mixed effect model ($NONMEM^{(R)}$ 7.2) based on plasma midazolam concentrations. The PK model was developed, and the first-order conditional estimation with interaction was applied for the model run. A three-compartment model with first-order elimination described the PK. The influence of ketoconazole and rifampicin, CYP3A5 genotype, and demographic characteristics on PK parameters was examined. Goodness-of-fit (GOF) diagnostics and visual predictive checks, as well as bootstrap were used to evaluate the adequacy of the model fit and predictions. Results: Twenty-four subjects contributed to 900 midazolam concentrations. The final parameter estimates (% relative standard error, RSE) were as follows; clearance (CL), 31.8 L/h (6.0%); inter-compartmental clearance (Q) 2, 36.4 L/h (9.7%); Q3, 7.37 L/h (12.0%), volume of distribution (V) 1, 70.7 L (3.6%), V2, 32.9 L (8.8%); and V3, 44.4 L (6.7%). The midazolam CL decreased and increased to 32.5 and 199.9% in the inhibition and induction phases, respectively, compared to that in control phase. Conclusion: A PK model for midazolam co-treatment with ketoconazole and rifampicin was developed using data of healthy volunteers, and the subject's CYP3A status influenced the midazolam PK parameters. Therefore, a population PK model with enzyme-mediated drug interactions may be useful for quantitatively predicting PK alterations.

• Journal of the Semiconductor & Display Technology
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• v.10 no.1
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• pp.43-49
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• 2011

In this study, the dynamic characteristics of an air spring connected with an external chamber through a flexible tube are examined. The uncoupled dynamic parameters of the air spring are identified through experiments, followed by the suggestion of a model-based approach to obtain the remaining coupled dynamic parameters using the various frequency response functions derived in PART I paper [1]. To improve or control the damping characteristics of the air spring, this vibration isolation air spring system is physically established in laboratory scale. And we attempt to identify various parameters used to describe to air spring system by both theoretically [1] and experimentally, which is performed in this report. The damping parameter of the tube system is identified through experiments on the system incorporated with the air cylinder, and a nonlinear regression procedure is employed to find solutions. The resulting value is used to expect the frequency response function of dynamic pressure in the top chamber (air spring) with respect to that in the bottom chamber (external chamber). Comparison with the experimental data supports the validity of the present estimation procedures. Also, the dynamic mechanism of the damping effects particularly in a low frequency range is investigated through this experimental endeavor.

• Smart Structures and Systems
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• v.31 no.2
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• pp.131-140
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• 2023

As well-known, the extended Kalman filter (EKF) is a powerful tool for parameter identification with limited measurements. However, traditional EKF is not applicable when the external excitation is unknown. By using least-squares estimation (LSE) for force identification, an EKF with unknown input (EKF-UI) approach was recently proposed by the authors. In this approach, to ensure the influence matrix be of full column rank, the sensors have to be deployed at all the degrees-of-freedom (DOFs) corresponding to the unknown excitation, saying collocated measurements are required. However, it is not easy to guarantee that the sensors can be installed at all these locations. To circumvent this limitation, based on the idea of first-order-holder discretization (FOHD), an improved EKF with unknown input (IEKF-UI) approach is proposed in this study for the simultaneous identification of structural parameters and unknown excitation. By using projection matrix, an improved observation equation is obtained. Few displacement measurements are fused into the observation equation to avoid the so-called low-frequency drift. To avoid the ill-conditioning problem for force identification without collocated measurements, the idea of FOHD is employed. The recursive solution of the structural states and unknown loads is then analytically derived. The effectiveness of the proposed approach is validated via several numerical examples. Results show that the proposed approach is capable of satisfactorily identifying the parameters of linear and nonlinear structures and the unknown excitation applied to them.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.4
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• pp.283-293
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• 2024

In this study, advanced unscented Kalman filter (UKF) and particle filter (PF) implementations are introduced and applied to perform system identification (SI) for sudden structural damage induced by seismic loading. These two methods are then compared to validate their applicability to SI tasks. For this validation, the Bouc- Wen model is used to simulate the nonlinear shear-building response, and an adaptive rule (i.e., an adaptive tracking method) is applied to the two filter methods to improve their tracking performance during sudden changes in system properties. When the original UKF and PF are applied to an earthquake scenario, both methods fail to estimate the damage initiation time and post-damage parameter values. After applying the adaptive tracking method, it is found for both methods that although the occurrence time is identified, the estimation of the damage state is still not accurate. To improve the accuracy, an adjusted adaptive tracking method is applied, and the two methods then derive accurate estimates. Finally, when considering the computation time, UKF is promoted as a better choice for practical applications, provided that a proper adaptive tracking method is implemented.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.2A
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• pp.119-130
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• 2009

Seismic fragility curves of a structure represent the probability of exceeding the prescribed structural damage state for a given various levels of ground motion intensity such as peak ground acceleration (PGA), spectral acceleration ($S_a$) and spectral displacement ($S_d$). So those are very essential to evaluate the structural seismic performance and seismic risk. The purpose of this paper is to develop seismic fragility curves for PSC box girder bridges. In order to construct numerical fragility curve of bridge structure using nonlinear time history analysis, a set of ground motions corresponding to design spectrum are artificially generated. Assuming a lognormal distribution, the fragility curve is estimated by using the methodology proposed by Shinozuka et al. PGA is simple and generally used parameter in fragility curve as ground motion intensity. However, the PGA has not good relationship with the inelastic structural behavior. So, $S_a$ and $S_d$ with more direct relationship for structural damage are used in fragility analysis as more useful intensity measures instead of PGA. The numerical fragility curves based on nonlinear time history analysis are compared with those obtained from simple method suggested in HAZUS program.

• Journal of the Korean GEO-environmental Society
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• v.19 no.12
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• pp.47-58
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• 2018

Duncan & Chang(1970) proposed the Duncan-Chang model that a linear relation of transformed stress-strain plots was reconstituted from a nonlinear relation of stress-strain curve of triaxial compression test using hyperbolic theory so as to estimate an initial tangent modulus and ultimate deviator stress for the soil specimen. Although the transformed stress-strain plots show a linear relationship theoretically, they actually show a nonlinearity at both low and high values of strain of the test. This phenomenon indicates that the stress-strain curve is not a complete form of a hyperbola. So, if linear regression analyses for the transformed stress-strain plot are performed over a full range of strain of a test, error in the estimation of their linear equations is unavoidable depending on ranges of strain with non-linearity. In order to reduce such an error, a modified regression analysis method is proposed in this study, in which linear regression analyses for transformed stress-strain plots are performed over the entire range of strain except the range the non-linearity is shown around starting and ending of the test, and then the initial tangent modulus and ultimate deviator stresses are calculated. Isotropically consolidated-drained triaxial compression tests were performed on compacted weathered soil with a modified Proctor density to obtain their model parameters. The modified regression analyses for transformed stress-strain plots were performed and analyzed results are compared with results estimated by 2 points method (Duncan et al., 1980). As a result of analyses, initial tangent moduli are about 4.0% higher and ultimate deviator stresses are about 2.9% lower than those values estimated by Duncan's 2 points method.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.3
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• pp.193-200
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• 2022

In this study, the finite-failure NHPP software reliability model was applied to the software development model based on the Weibull lifetime distribution (Goel-Okumoto, Rayleigh, Type-2 Gumbe), which is widely used in the software reliability field, and then the cost attributes were compared and evaluated. For this study, failure time data detected during normal operation of the software system were collected and used, the most-likelihood estimation (MLE) method was applied to the parameter estimation of the proposed model, and the calculation of the nonlinear equation was solved using the binary method. As a result, first, in the software development model, when the cost of testing per unit time and the cost of removing a single defect increased, the cost increased but the release time did not change, and when the cost of repairing failures detected during normal system operation increased, the cost increased and the release time was also delayed. Second, as a result of comprehensive comparative analysis of the proposed models, it was found that the Type-2 Gumble model was the most efficient model because the development cost was lower and the release time point was relatively faster than the Rayleigh model and the Goel-Okumoto basic model. Third, through this study, the development cost properties of the Weibull distribution model were newly evaluated, and the analyzed data is expected to be utilized as design data that enables software developers to explore the attributes of development cost and release time.

• Korean Journal of Remote Sensing
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• v.35 no.5_1
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• pp.665-679
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• 2019

Mesoscale soil moisture measurement from the promising Cosmic-Ray Neutron Probe (CRNP) is expected to bridge the gap between large scale microwave remote sensing and point-based in-situ soil moisture observations. Traditional calibration based on $N_0$ method is used to convert neutron intensity measured at the CRNP to field scale soil moisture. However, the static calibration parameter $N_0$ used in traditional technique is insufficient to quantify long term soil moisture variation and easily influenced by different time-variant factors, contributing to the high uncertainties in CRNP soil moisture product. Consequently, in this study, we proposed a modified traditional calibration method, so-called Dynamic-$N_0$ method, which take into account the temporal variation of $N_0$ to improve the CRNP based soil moisture estimation. In particular, a nonlinear regression method has been developed to directly estimate the time series of $N_0$ data from the corrected neutron intensity. The $N_0$ time series were then reapplied to generate the soil moisture. We evaluated the performance of Dynamic-$N_0$ method for soil moisture estimation compared with the traditional one by using a weighted in-situ soil moisture product. The results indicated that Dynamic-$N_0$ method outperformed the traditional calibration technique, where correlation coefficient increased from 0.70 to 0.72 and RMSE and bias reduced from 0.036 to 0.026 and -0.006 to $-0.001m^3m^{-3}$. Superior performance of the Dynamic-$N_0$ calibration method revealed that the temporal variability of $N_0$ was caused by hydrogen pools surrounding the CRNP. Although several uncertainty sources contributed to the variation of $N_0$ were not fully identified, this proposed calibration method gave a new insight to improve field scale soil moisture estimation from the CRNP.

• The Korean Journal of Nuclear Medicine
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• v.37 no.5
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• pp.288-300
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• 2003

Purpose: To obtain regional blood flow and tissue-blood partition coefficient with time-activity curves from ${H_2}^{15}O$ PET, fitting of some parameters in the Kety model is conventionally accomplished by nonlinear least squares (NLS) analysis. However, NLS requires considerable compuation time then is impractical for pixel-by-pixel analysis to generate parametric images of these parameters. In this study, we investigated several fast parameter estimation methods for the parametric image generation and compared their statistical reliability and computational efficiency. Materials and Methods: These methods included linear least squres (LLS), linear weighted least squares (LWLS), linear generalized least squares (GLS), linear generalized weighted least squares (GWLS), weighted Integration (WI), and model-based clustering method (CAKS). ${H_2}^{15}O$ dynamic brain PET with Poisson noise component was simulated using numerical Zubal brain phantom. Error and bias in the estimation of rCBF and partition coefficient, and computation time in various noise environments was estimated and compared. In audition, parametric images from ${H_2}^{15}O$ dynamic brain PET data peformed on 16 healthy volunteers under various physiological conditions was compared to examine the utility of these methods for real human data. Results: These fast algorithms produced parametric images with similar image qualify and statistical reliability. When CAKS and LLS methods were used combinedly, computation time was significantly reduced and less than 30 seconds for $128{\times}128{\times}46$ images on Pentium III processor. Conclusion: Parametric images of rCBF and partition coefficient with good statistical properties can be generated with short computation time which is acceptable in clinical situation.

• Journal of Korean Society of Forest Science
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• v.86 no.2
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• pp.135-145
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• 1997

This study aimed at evaluating one curvilinear equation and nine non-linear equations for estimating stand growth characteristics(mean dbh, mean height and volume per ha) for the plantations of Pinus koraiensis and the natural stands of Quercus mongolica. The data were collected from 92 plots in Pines koraiensis stands and 83 plots in Quercus mongolica stands, and the site index of all the stands is 14. The curvilinear equation, $Y=at^be^{-c/t}$, used in preparing the yield tables was well fitted within the range of data, but was likely to give overestimates when extrapolating in old stage due to the tendency of linear increase. Among the non-linear equations, logistic equation and Sloboda equation gave overestimates in young stands and reached the asymptotic status early which means underestimates in old stage. Extrapolating in old stage, Hossfeld equation generally gave larger values than others due to its large estimates of parameter a, the maximum value. On the other hand, Bertalanffy equation gave underestimates in young and old stands and overestimates in middle-aged stands. The estimates with Korf equation was relatively low for Pinus koraiensis stands, and this tendency was more obvious in dbh growth of Quercus mongolica stands. Ueno-Ohzaki equation was liable to give over or underestimates depending on the value of parameter b when extrapolating in old stands. Considering the accuracy of estimates and the biological base of the growth equations, Gompertz equation, Chapman-Richards equation and Weibull equation were generally applicable for estimating the stand growth characteristics of both species in the whole range of stand ages including extrapolated range. To get more accurate and precise parameter estimates, more data, especially in old stands, should be required in further study.