• Journal of Korea Water Resources Association
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• v.42 no.11
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• pp.1017-1028
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• 2009

NSRPM (Neyman-Scott Rectangular Pulse Model) is one of the common model for generating future precipitation time series in stochastical hydrology. There are 5 parameters to compose the NSRPM model for generating precipitation time series. Generally parameter estimation using moment has some problems related with increased objective functions and shows different results in accordance with random variable generating models. In this study, direct parameter estimation method was proposed to cover with disadvantages of parameter estimation using moment. To apply the direct parameter estimation, generating stochastical data variance in accordance with numbers of precipitation events of NSRPM was done. Both kinds of methods were applied at the Cheongju gauge station data. Precipitation time series were generated using 4 different random variable generator, and compared with observed time series to check the accuracies. As a results, direct method showed more stable and better results.

• Journal of Nutrition and Health
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• v.26 no.9
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• pp.1033-1048
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• 1993

This study was designed to describe the effect of the protein quality at different intake level of protein on the protein metabolism in the whole body of growing pigs with a simulation model. Varying to the protein level in feeds, four simulations were conducted. The feed protein level, represented as proportions of digestible protein to the metabolic energy (DP/ME, g/MJ), were 6-8, 11-13, 17-19, and 23-25 DP/ME, respectively. Two protein quality and six weeks of growth time were used at each simulation. The objective function for the simulations was protein deposition in the whole body, which was calculated from the experimental results. The parameters in the simulation were determined by the parameter estimation technique. The results obtained from the simulation were as follows: The protein synthesis and breakdown rates(g/day) in the whole body was increased with the increase of protein quality only at lower or required level of protein intake. They showed a parallel behavior in the course of growth, irrespective of quality and level of feed protein intake. The simulated protein deposition and protein synthesis showed a linear relationship between them at different protein quality and level. The affinity parameter showed a linear relationship between them at different protein quality and level. The affinity parameter showed that arginine, tryptophan and isoleucine were more efficient in the stimulation ofbody protein synthesis. Lysine and phenylalanine+tyrosine were less efficient. The oxidation parameter showed that histidine, pheyalanine+tyrosine were less efficient. The oxidation parameter showed that histidine, phenyalanine+tyrosine, and methionine+cystine were oxidized in larger magnitude than lysine and threonine. The oxidation parameter of most amino acids increased with the increase of protein intake beyond the requirement level, but not any more at highest protein intake level. Finally it was found that the improvement of feed protein quality at the lower or required level of protein intake increase protein deposition through a parallel increase of protein synthesis and breakdown.

• Advances in Energy Research
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• v.8 no.2
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• pp.95-110
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• 2022

Wind energy can be utilized for the generation of electricity, due to significant wind potential at different parts of the world, some countries have already been generating of electricity through wind. Pakistan is still well behind and has not yet made any appreciable effort for the same. The objective of this work was to add some new strategies to calculate Weibull parameters and assess wind energy potential. A new approach calculates Weibull parameters; we also developed an alternate formula to calculate shape parameters instead of the gamma function. We obtained k (shape parameter) and c (scale parameter) for two-parameter Weibull distribution using five statistical methods for five different cities in Pakistan. Maximum likelihood method, Modified Maximum likelihood Method, Method of Moment, Energy Pattern Method, Empirical Method, and have been to calculate and differentiate the values of (shape parameter) k and (scale parameter) c. The performance of these five methods is estimated using the Goodness-of-Fit Test, including root mean square error, mean absolute bias error, mean absolute percentage error, and chi-square error. The daily 10-minute average values of wind speed data (obtained from energydata.info) of different cities of Pakistan for the year 2016 are used to estimate the Weibull parameters. The study finds that Hyderabad city has the largest wind potential than Karachi, Quetta, Lahore, and Peshawar. Hyderabad and Karachi are two possible sites where wind turbines can produce reasonable electricity.

• Journal of the Korean Society for Railway
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• v.13 no.2
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• pp.222-228
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• 2010

In this paper, we propose a optimization approach for the Electric Locomotive Overhaul Maintenance Facility (ELOMF), which aims at the simulation optimization so as to meet the design specification. In simulation design, we consider the critical path and sensitivity analysis of the critical (dependent) factors and the design (independent) parameters for the parameter selection and reduction of the metamodel. Therefore, we construct the multi-objective non-linear programming. The objective function is normalized for the generalization of design parameter while the constraints are composed of the simulation-based regression metamodel for the critical factors and design factor's domain. Then the effective solution procedure based on the pareto optimal solution set is proposed. This approach provides a comprehensive approach for the optimization of Train Overhaul Maintenance Facility(TOMF)'s design parameters using the simulation and metamoels.

• Journal of Korean Society on Water Environment
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• v.25 no.3
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• pp.432-440
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• 2009

The effect of selecting hydrologic item for calculating objective function on calibration of stream flow was evaluated by Hydrologic Simulation Porgram-Fortran (HSPF) linked with Model Independent Parameter Optimizer (PEST). Daily and monthly stream flow and flow duration were used to calculate objective function. Automated calibration focused on monthly stream was proper to analyze seasonal or yearly water budget but not proper to predict daily stream flow or percent chance flow exceeded. Calibration result focused on flow duration is proper to predict precent chance flow exceeded but not proper to analyze water budget or predict peak flow. These results indicate that hydrologic item calculated for objective function on calibration procedure could influence calibration results and watershed modeler should select carefully hydrologic item for the purpose of model application. Current, the criteria of stream flow of Korean TMDL is generated based on percent chance flow exceeded, so flow duration should be included to calculate objective function on calibration procedure for the estimation of criteria of stream flow using hydrologic model.

• Structural Engineering and Mechanics
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• v.67 no.3
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• pp.301-310
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• 2018

In this paper, a multi-objective multiparameter optimization procedure is developed by combining rigorously developed metamodels with an evolutionary search algorithm-Genetic Algorithm (GA). Response surface methodology (RSM) is used for developing the metamodels to replace the tedious finite element analyses. A nine-node isoparametric plate bending element is used for conducting the finite element simulations. Highly accurate numerical data from an author compiled FORTRAN finite element program is first used by the RSM to develop second-order mathematical relations. Four material parameters-${\frac{E_1}{E_2}}$, ${\frac{G_{12}}{E_2}}$, ${\frac{G_{23}}{E_2}}$ and ${\upsilon}_{12}$ are considered as the independent variables while simultaneously maximizing fundamental frequency, ${\lambda}_1$ and frequency separation between the $1^{st}$ two natural modes, ${\lambda}_{21}$. The optimal material combination for maximizing ${\lambda}_1$ and ${\lambda}_{21}$ is predicted by using a multi-objective GA. A general sensitivity analysis is conducted to understand the effect of each parameter on the desired response parameters.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.21 no.6
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• pp.954-960
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• 2012

Nowadays, rapidly changing and unstable global economic environments request a lot of roles to engineers. In this situation, product should be designed to make more profit by cost down and to satisfy distinguished performance comparing to other competitive ones. In this research, the optimization design of the industrial robot casting will be done. The weight and deflection have to be reduced as objective functions and stress has to be constrained under some constant value. To reduce time cost, CCD (Central Composite Design) will be used to make experimental design. And RSM (Response Surface Methodology) will be taken to make regression model for objective functions and constraint function. Finally, optimization will be done with Genetic Algorithm. In this problem, the objective functions are multiple, so NSGA-II which is brilliant and efficient for such a problem will be used. For the solution quality check, the diversity between Pareto solutions will be also checked.

• Journal of the Korea institute for structural maintenance and inspection
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• v.12 no.4
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• pp.149-160
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• 2008

In this study, the research was carried out on how to identify the modal parameter by acquiring the output response of the structure only through the smart sensor system. The objective of this research is to verify the performance and the on-site adaptability of the smart sensor system that have been actively researched as the advanced measuring system so far. Smart Sensor System was developed so that the real-time dynamic measurement can be performed by means of MEMS-type accelerated sensor, 8 bit CPU, wireless MODEM. In the modal parameter identification test, random excitation was added to the cantilever beam, and then the response of the structure was obtained using the smart sensor system and the wire measurement system respectively. In analyzing the data, modal parameter was identified using NExT & ERA algorithm. Furthermore, the optimal measurement location was selected through EOT algorithm in order to obtain the qualified output response. Result of the test, it was possible to verify the on-site applicability of the smart sensor.

• Korean Journal of Clinical Pharmacy
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• v.23 no.2
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• pp.137-141
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• 2013

Purpose: This study compared the performance of new NONMEM estimation methods using a population analysis dataset collected from a clinical study that consisted of 40 individuals and 567 observations after a single oral dose of glimepiride. Method: The NONMEM 7.2 estimation methods tested were first-order conditional estimation with interaction (FOCEI), importance sampling (IMP), importance sampling assisted by mode a posteriori (IMPMAP), iterative two stage (ITS), stochastic approximation expectation-maximization (SAEM), and Markov chain Monte Carlo Bayesian (BAYES) using a two-compartment open model. Results: The parameters estimated by IMP, IMPMAP, ITS, SAEM, and BAYES were similar to those estimated using FOCEI, and the objective function value (OFV) for diagnosing the model criteria was significantly decreased in FOCEI, IMPMAP, SAEM, and BAYES in comparison with IMP. Parameter precision in terms of the estimated standard error was estimated precisely with FOCEI, IMP, IMPMAP, and BAYES. The run time for the model analysis was shortest with BAYES. Conclusion: In conclusion, the new estimation methods in NONMEM 7.2 performed similarly in terms of parameter estimation, but the results in terms of parameter precision and model run times using BAYES were most suitable for analyzing this dataset.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.1
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• pp.15-25
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• 2010

The objective of this study is to investigate the optimal arrangement of cameras used for the robot's vision control scheme. The used robot's vision control scheme involves two estimation models, which are the parameter estimation and robot's joint angle estimation models. In order to perform this study, robot's working region is divided into three work spaces such as left, central and right spaces. Also, cameras are positioned on circular arcs with radius of 1.5m, 2.0m and 2.5m. Seven cameras are placed on each circular arc. For the experiment, nine cases of camera arrangement are selected in each robot's work space, and each case uses three cameras. Six parameters are estimated for each camera using the developed parameter estimation model in order to show the suitability of the vision system model in nine cases of each robot's work space. Finally, the robot's joint angles are estimated using the joint angle estimation model according to the arrangement of cameras for robot's point-position control. Thus, the effect of camera arrangement used for the robot's vision control scheme is shown for robot's point-position control experimentally.