• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.12
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• pp.85-98
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• 1998

This paper proposes a new design method of neuro-FLC by the Lamarckian co-adaptation scheme that incorporates the backpropagation learning into the GA evolution in an attempt to find optimal design parameters (fuzzy rule base and membership functions) of application-specific FLC. The design parameters are determined by evolution and learning in a way that the evolution performs the global search and makes inter-FLC parameter adjustments in order to obtain both the optimal rule base having high covering value and small number of useful fuzzy rules and the optimal membership functions having small approximation error and good control performance while the learning performs the local search and makes intra-FLC parameter adjustments by interacting each FLC with its environment. The proposed co-adaptive design method produces better approximation ability because it includes the backpropagation learning in every generation of GA evolution, shows better control performance because the used COG defuzzifier computes the crisp value accurately, and requires small workspace because the optimization procedure of fuzzy rule base and membership functions is performed concurrently by an integrated fitness function on the same fuzzy partition. Simulation results show that the Lamarckian co-adapted FLC produces the most superior one among the differently generated FLCs in all aspects such as the number of fuzzy rules, the approximation ability, and the control performance.

• Journal of Life Science
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• v.20 no.10
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• pp.1433-1442
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• 2010

Parameters related to dissolved oxygen for the production of pullulan by Aureobasidium pullulans HP-2001 were optimized in 7 l and 100 l bioreactors. The optimal concentrations of glucose and yeast extract for the production of pullulan were 50.0 and 2.5 g/l, respectively, and its conversion rate from glucose was 37% at a flask scale. The optimal initial pH of the medium and temperature for cell growth were 7.5 and $30^{\circ}C$, whereas those for the production of pullulan were 6.0 and $25^{\circ}C$. The optimal agitation speed and aeration rate for cell growth were 600 rpm and 2.0 vvm in a 7 l bioreactor, whereas those for the production of pullulan were 500 rpm and 1.0 vvm. The production of pullulan with an optimized agitation speed of 500 rpm and aeration rate of 1.0 vvm was 18.13 g/l in a 7 l bioreactor. Maximal cell growth occurred without inner pressure, whereas the optimal inner pressure for the production of pullulan was 0.4 kgf/$cm^2$ in a 100 l bioreactor. The production of pullulan under optimized conditions in this study was 22.89 g/l in a 100 l bioreactor, which was 1.38 times higher than that without inner pressure.

• Tunnel and Underground Space
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• v.27 no.1
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• pp.12-25
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• 2017

In local underground mines heavily depending on the natural ventilation, ducted fan auxiliary ventilation system is strongly recommended instead of the total mine ventilation system requiring large capital and operating costs. Optimizing the installation of ducted fans in series in long large-opening mines is required to assure the economy and efficiency of the ventilation system. The two most critical design parameters for optimization are the wall separation distance and gap length between adjoining ducts. This study aims at deriving the optimal values for those two parameters concerning the economic and environmental aspects through the extensive CFD analysis, which minimizes pressure loss, leakage and entrainment of the contaminated air in the gap space. The ranges of the wall separation distance and gap length for study are selected by taking into consideration the existing recommendations and guidelines. The ultimate goal is to optimize the auxiliary ventilation system using ducted fans in series to provide a reliable and efficient solution to maintain clean and safe workplace environment in local long underground mines.

• Journal of Korean Society of Transportation
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• v.30 no.5
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• pp.71-82
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• 2012

Some previous studies adopted a method statistically based on the observed traffic volumes and travel times to estimate the parameters. Others tried to find an optimal set of parameters to minimize the gap between the observed and estimated traffic volumes using, for instance, a combined optimization model with a traffic assignment model. The latter is frequently used in a large-scale network that has a capability to find a set of optimal parameter values, but its appropriateness has never been demonstrated. Thus, we developed a methodology to estimate a set of parameter values of BPR(Bureau of Public Road) function using Harmony Search (HS) method. HS was developed in early 2000, and is a global search method proven to be superior to other global search methods (e.g. Genetic Algorithm or Tabu search). However, it has rarely been adopted in transportation research arena yet. The HS based transportation network calibration algorithm developed in this study is tested using a grid network, and its outcomes are compared to those from incremental method (Incre) and Golden Section (GS) method. It is found that the HS algorithm outperforms Incre and GS for copying the given observed link traffic counts, and it is also pointed out that the popular optimal network calibration techniques based on an objective function of traffic volume replication are lacking the capability to find appropriate free flow travel speed and ${\alpha}$ value.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.7
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• pp.694-704
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• 2011

In this paper, we present a design of a 5th order Chebyshev interdigital band-pass filter using inverter and susceptance slope parameter values obtained from EM simulated multi-port Y-parameters. The shifted length of the resonator is determined when the frequency of the transmission zero is separated far away from the center frequency. For the initial dimensions of the interdigital filter, the filter is decomposed into the individual resonators, and the dimensions are obtained using EM Simulation of the decomposed resonators. However, the interdigital filter with the dimensions determined from the EM simulation of the decomposed resonators shows slightly distorted response from the desired frequency response due to the coupling between non-adjacent resonators. To obtain a EM simulation dataset, EM simulation for this filter is carried out by parameter sweep with constant ratio for the initial values. In this dataset, it is determined the final values for the filter by optimization. The fabricated filter by PCB shows an upper-shift of center frequency of about 70 MHz, which was caused by permittivity changed and tolerance of fabrication.

• Geotechnical Engineering
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• v.10 no.1
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• pp.47-62
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• 1994

It has been well known that the rainfall-triggered rise of groundwater levels is one of the most important factors resulting the instability of the hillside slopes. Thus, the prediction of porewater pressure is an essential step in the evaluation of landslide hazard. This study involves the development and verification of numerical groundwater flow model for the prediction of groundwater flow fluctuations accounting for both of unsatu나toed flow and saturated flow on steep hillside slopes. The first part of this study is to develop a nomerical groundwater flow model. The numerical technique chosen for this study is the finitro element method in combination with the finite difference method. The finite element method is used to transform the space derivatives and the finite difference method is used to discretize the time domain. The second part of this study is to estimate the unknown model parameters used in the proposed numerical model. There were three parameters to be estimated from input -output record $K_e$, $\psi_e$, b. The Maximum -A-Posteriori(MAP) optimization method is utilized for this purpose, . The developed model is applied to a site in Korea where two debris avalanches of large scale and many landslides of small scale were occurred. The results of example analysis show that the numerical groundwater flow model has a capacity of predicting the fluctuation of groundwater levels due to rainfall reasonably well.

• Asian-Australasian Journal of Animal Sciences
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• v.10 no.5
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• pp.460-470
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• 1997

On an absolute straw diet, the effect of graded levels of green grass supplementation on intake, nutrient digestibility, rumen fermentation pattern and microbial N yield has been studied in cattle. Of the two trials conducted, 16 intact growing bulls of 304 kg weight and 32 months old, randomly allocated to four treatments in a completely randomized design in the 1st trial. While, in the, 2nd trial, four rumen cannulated local bulls of about 60 months old and 400 kg weight were used in a $4{\times}4$ Latin square design with four treatments in four periods. In both the trials, in addition to a mineral mixture, animals were supplemented with graded levels of naturally grown green grass of 0 kg (T1), 2 kg (T2), 4 kg (T3) or 6 kg (T4) to an ad libitum rice straw diet In the 1st trial, measurements were made on intake digestibility, growth rate, N balance and microbial N yield. While in the 2nd trial, in addition to the above parameters (except growth rate), rumen parameters were also studied. All levels of grass supplementation decreased the straw DM intake and increased the substitution rate. The rumen $NH_3-N$ concentration increased with the increase in grass level and ranges from 8-46 mg/l. The rumen pH and the rate and extent of DM degradability of straw were not affeceted by different rumen environments created by different levels of grass inclusion. At 48 h, straw DM degradability were 42, 44, 44 and 43% respectively for 0, 2, 4 and 6 kg grass supplementation daily. The whole gut digestibilities of DM, OM and ADF increased significantly (p < 0.05) only at 6 kg level daily. The microbial N yield was not affected by the levels of grass supplemented. The mean microbial N yield was 10 (SD 3.7) g/kg DOM apparently fermented in the rumen. The estimated minimum N loss and thus the maintenance requirement of tissue protein was 303 mg/kg $W^{0.75}/d$. All the animals lost live weight but 6 kg grass supplementation gave positive energy and N balances. Small amount of green grass supplementation is often recommended for optimization of rumen environment of a straw diet However, under the present experimental condition, no such beneficiary effect observed up to 6 kg (26% of DM intake) level of supplementation.

• Journal of Korea Water Resources Association
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• v.41 no.8
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• pp.807-823
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• 2008

This paper presents a technique for estimating discharge rating curve parameters. In typical practical applications, the original non-linear rating curve is transformed into a simple linear regression model by log-transforming the measurement without examining the effect of log transformation. The model of pseudo-likelihood estimation is developed in this study to deal with heteroscedasticity of residuals in the original non-linear model. The parameters of rating curves and variance functions of errors are simultaneously estimated by the pseudo-likelihood estimation(P-LE) method. Simulated annealing, a global optimization technique, is adapted to minimize the log likelihood of the weighted residuals. The P-LE model was then applied to a hypothetical site where stage-discharge data were generated by incorporating various errors. Results of the P-LE model show reduced error values and narrower confidence intervals than those of the common log-transform linear least squares(LT-LR) model. Also, the limit of water levels for segmentation of discharge rating curve is estimated in the process of P-LE using the Heaviside function. Finally, model performance of the conventional log-transformed linear regression and the developed model, P-LE are computed and compared. After statistical simulation, the developed method is then applied to the real data sets from 5 gauge stations in the Geum River basin. It can be suggested that this developed strategy is applied to real sites to successfully determine weights taking into account error distributions from the observed discharge data.

• Journal of Wetlands Research
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• v.14 no.4
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• pp.519-535
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• 2012

In order to establish a rainfall-runoff model, calibration of hydrological parameters for the model is very important. Especially, Curve Number(CN), estimated by NRCS method, is a main factor to apply unit hydrograph theory to calculation of peak discharge. For using NRCS method, it is needed selecting AMC because CN is strongly connected with that. In this study, we focus our concern on finding a applicable standard for selecting AMC for CN. For this, three dams which are Boryeong, Habchon, Namgang are selected as target basins to use observed data including rainfall and dam inflow. As a result of this research, it is found that CN must be included as a calibrated parameter to calculate effective rainfall for the rainfall-runoff model. Also, it is preferred to use PWRMSE of HEC-HMS program as a objective function for optimizing hydrological parameters. From the analyzing result of variation of AMC for peak discharge, it is recommended to apply AMC-III to estimation of CN for calculating effective rainfall of design hydrograph.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.2
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• pp.91-99
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• 2014

The common-rail injectors are the most critical component of the CRDI diesel engines that dominantly affect engine performances through high pressure injection with exact control. Thus, from now on the advanced combustion technologies for common-rail diesel injection engine require high performance fuel injectors. Accordingly, the previous studies on the numerical and experimental analysis of the diesel injector have focused on a optimum geometry to induce proper injection rate. In this study, computational predictions of performance of the diesel injector have been performed to evaluate internal flow characteristics for various needle lift and the spray pattern at the nozzle exit. To our knowledge, three-dimensional computational fluid dynamics (CFD) model of the internal flow passage of an entire injector duct including injection and return routes has never been studied. In this study, major design parameters concerning internal routes in the injector are optimized by using a CFD analysis and Response Surface Method (RSM). The computational prediction of the internal flow characteristics of the common-rail diesel injector was carried out by using STAR-CCM+7.06 code. In this work, computations were carried out under the assumption that the internal flow passage is a steady-state condition at the maximum needle lift. The design parameters are optimized by using the L16 orthogonal array and polynomial regression, local-approximation characteristics of RSM. Meanwhile, the optimum values are confirmed to be valid in 95% confidence and 5% significance level through analysis of variance (ANOVA). In addition, optimal design and prototype design were confirmed by calculating the injection quantities, resulting in the improvement of the injection performance by more than 54%.