• Journal of information and communication convergence engineering
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• v.6 no.1
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• pp.19-23
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• 2008

The AQM (Active Queue Management) starts dropping packets earlier to notify traffic sources about the incipient stage of congestion. The AQM improves fairness between response flow (like TCP) and non-response flow (like UDP), and it can provide high throughput and link efficiency. In this paper, we suggest the QVARED (Queue Variation Adaptive RED) algorithm to respond to bursty traffic more actively. It is possible to provide more smoothness of average queue length and the maximum packet drop probability compared to RED and ARED (Adaptive RED). Therefore, it is highly adaptable to new congestion condition. Our simulation results show that the drop rate of QVARED is decreased by 80% and 40% compare to those of RED and ARED, respectively. This results in shorter end-to-end delay by decreasing the number of retransmitted packets. Also, the QVARED reduces a bias effect over 18% than that of drop-tail method; therefore packets are transmitted stably in the bursty traffic condition.

• Communications for Statistical Applications and Methods
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• v.19 no.5
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• pp.663-671
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• 2012

In the present study, a combined ratio cum regression estimator is proposed to estimate the population mean of the study variable in the presence of a non-response using an auxiliary variable under double sampling. The expressions of bias and mean squared error(MSE) based on the proposed estimator is derived under double (or two stage) sampling to the first degree of approximation. Some estimators are also derived from the proposed class by allocating the suitable values of constants used. A comparison of the proposed estimator with the usual unbiased estimator and other derived estimators is carried out. An empirical study is carried out to demonstrate the performance of the suggested estimator and of others; it is endow that the empirical results backing the theoretical study.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.69-71
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• 2014

MLCCs are used broadly in electronic industry like smart phone and TV. Although they are fabricated in small size and have high capacitance, there are acoustic noise problems to reduce comfort of user. Acoustic noise results from linear piezoelectricity and nonlinear electrostriction of $BaTiO_3$ in MLCC and there are some researches on MLCC vibration under AC electric field. When only AC electric field without DC bias is applied to MLCC, fundamental frequency response is affected by piezoelectricity and second-harmonic frequency response shows electrostrictive vibration. In this study we get vibration shape of MLCC under AC electric field for each frequency and analysis on the mechanism of MLCC vibration affected by piezoelectricity and electrostriction.

• Journal of the Korea Society for Simulation
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• v.9 no.4
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• pp.67-75
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• 2000

Often system analysts are interested in the estimation of percentile for system performance. For instance, in PERT network system, the percentile that the project. Typically the control variate method is used to reduce the variability of mean response using the correlation between the response and the control variates with a little additional cost during the course of simulation. In the same spirit, we apply this method to estimate the percentile of project completion time in PERT system, and evaluate the efficiency of the controlled estimator for its percentile.1 Simulation results indicate that the controlled estimators are more effective in reducing the variances of estimators than the simple estimators, however those tend to a little underestimate the percentiles for some critical values. We need more simulation experiments to examine such a kind of bias problem. We expect this research presents a step forward in the area of variance reduction techniques of stochastic simulation.

• Food Science and Biotechnology
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• v.15 no.5
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• pp.715-720
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• 2006

This study was performed to develop a predictive model for the growth kinetics of Listeria monocytogenes in tryptic soy broth (TSB) using a response surface model with a combination of potassium lactate (PL), temperature, and pH. The growth parameters, specific growth rate (SGR), and lag time (LT) were obtained by fitting the data into the Gompertz equation and showed high fitness with a correlation coefficient of $R^2{\geq}0.9192$. The polynomial model was identified as an appropriate secondary model for SGR and LT based on the coefficient of determination for the developed model ($R^2\;=\;0.97$ for SGR and $R^2\;=\;0.86$ for LT). The induced values that were calculated using the developed secondary model indicated that the growth kinetics of L. monocytogenes were dependent on storage temperature, pH, and PL. Finally, the predicted model was validated using statistical indicators, such as coefficient of determination, mean square error, bias factor, and accuracy factor. Validation of the model demonstrates that the overall prediction agreed well with the observed data. However, the model developed for SGR showed better predictive ability than the model developed for LT, which can be seen from its statistical validation indices, with the exception of the bias factor ($B_f$ was 0.6 for SGR and 0.97 for LT).

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.1
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• pp.80-83
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• 2017

In this paper, the X-band reconfigurable frequency selective surface having flexible geometry was proposed. The proposed RFSS is composed of patterns of cross-shaped loop with inductive stub, which can control the frequency response for C-Band and X-band by ON/OFF state of PIN diode. To minimize the parasitic effect and to obtain the high level of isolation between the unit cell of FSS and the bias circuit, we designed the grid type bias line on bottom layer through via hole. The measured transmission characteristics show good agreement with the simulation results and good stability of frequency response for different incident angles and curvatures of surface.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.17 no.10
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• pp.1100-1106
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• 2004

In this paper, we intend to make fringe-field switching (FFS) mode cell by the ion beam (IB) alignment method on the a-C：H thin film, to analyze electro-optical characteristics in this cell. We studied on the suitable inorganic thin film for fringe-field switching (FFS) cell and the aligning capabilities of nematic liquid crystal (NLC) using the alignment material of a-C：H thin film as working gas at 30 W rf bias condition. A high pretilt angle of about 5 $^{\circ}C$ by ion beam (IB) exposure on the a-C：H thin film surface was measured. Consequently, the high pretilt angle and the good thermal stability of LC alignment by the IB alignment method on the a-C：H thin film surface as working gas at 30 W rf bias condition can be achieved. An excellent voltage-transmittance (V -T) and response time curve of the IE-aligned FFS-LCD was observed with oblique IB exposure on the a-C：H thin films. Also, AC V-T hysteresis characteristics of the IB-aligned FFS-LCD with IE exposure on the a-C：H thin films is almost the same as that of the rubbing-aligned FFS cell on a polyimide (PI) surface.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.203-203
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• 2016

The linkage between climate change and water security, i.e., the response of water resource to the future climate change, have been of great concern to both scientific community and policy makers. In this study, the impact of future climate on water resources in Yellow River Basin in North of China has been investigated using the Coupled Land surface and Hydrology Model System (CLHMS) and IPCC AR5 projected future climate change in the basin. Firstly, the performances of 14 IPCC AR5 models in reproducing the observed precipitation and temperature in China, especially in North of China, have been evaluated, and it's suggested most climate models do show systematic bias compared with the observation, however, CNRM-CM5、HadCM5 and IPSL-CM5 model are generally the best models among those 14 models. Taking the daily projection results from the CNRM-CM5, along with the bias-correction technique, the response of water resources in Yellow river basin to the future climate change in different emission scenarios have been investigated. All the simulation results indicate a reduction in water resources. The current situation of water shortage since 1980s will keep continue, the water resources reduction varies between 28 and 23% for RCP 2.6 and 4.5 scenarios. RCP 8.5 scenario simulation shows a decrease of water resources in the early and mid 21th century, but after 2080, with the increase of rainfall, the extreme flood events tends to increase.

• Survey Research
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• v.7 no.2
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• pp.53-69
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• 2006

Weights can be made and imposed in both sample design stage and analysis stage in a sample survey. While in design stage weights are related with sample data acquisition quantities such as sample selection probability and response rate, in analysis stage weights are connected with external quantities, for instance population quantities and some auxiliary information. The final weight is the product of all weights in both stage. In the present paper, we focus on the weight in analysis stage and investigate the effect of such weights imposed on the weighted mean when estimating the population mean. We consider a finite population with a pair of fixed survey value and weight in each unit, and suppose equal selection probability designs. Under the condition we derive the formulas of the bias as well as mean square error of the weighted mean and show that the weighted mean is biased and the direction and amount of the bias can be explained by the correlation between survey variate and weight: if the correlation coefficient is positive, then the weighted mein over-estimates the population mean, on the other hand, if negative, then under-estimates. Also the magnitude of bias is getting larger when the correlation coefficient is getting greater. In addition to theoretical derivation about the weighted mean, we conduct a simulation study to show quantities of the bias and mean square errors numerically. In the simulation, nine weights having correlation coefficient with survey variate from -0.2 to 0.6 are generated and four sample sizes from 100 to 400 are considered and then biases and mean square errors are calculated in each case. As a result, in the case or 400 sample size and 0.55 correlation coefficient, the amount or squared bias of the weighted mean occupies up to 82% among mean square error, which says the weighted mean might be biased very seriously in some cases.

• Journal of Korea Water Resources Association
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• v.54 no.12
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• pp.1317-1328
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• 2021

This study aims to provide a predictive model based on climate models for simulating continuous daily rainfall sequences by combining bias-correction and spatio-temporal downscaling approaches. For these purposes, this study proposes a combined modeling system by applying conditional Copula and Multisite Non-stationary Hidden Markov Model (MNHMM). The GloSea5 system releases the monthly rainfall prediction on the same day every week, however, there are noticeable differences in the updated prediction. It was confirmed that the monthly rainfall forecasts are effectively updated with the use of the Copula-based bias-correction approach. More specifically, the proposed bias-correction approach was validated for the period from 1991 to 2010 under the LOOCV scheme. Several rainfall statistics, such as rainfall amounts, consecutive rainfall frequency, consecutive zero rainfall frequency, and wet days, are well reproduced, which is expected to be highly effective as input data of the hydrological model. The difference in spatial coherence between the observed and simulated rainfall sequences over the entire weather stations was estimated in the range of -0.02~0.10, and the interdependence between rainfall stations in the watershed was effectively reproduced. Therefore, it is expected that the hydrological response of the watershed will be more realistically simulated when used as input data for the hydrological model.