• Journal of Korean Society for Atmospheric Environment
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• v.25 no.4
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• pp.304-315
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• 2009

Numerical simulations were carried out to understand the effect of Sea Surface Temperature (SST) spatial distribution on regional circulation. A three-dimensional non-hydrostatic atmospheric model RAMS, version 6.0, was applied to examine the impact of SST forcing on regional circulation. New Generation Sea Surface Temperature (NGSST) data were implemented to RAMS to compare the results of modeling with default SST data. Several numerical experiments have been undertaken to evaluate the effect of SST for initialization. First was the case with NGSST data (Case NG), second was the case with RAMS monthly data (Case RM) and third was the case with seasonally averaged RAMS monthly data (Case RS). Case NG showed accurate spatial distributions of SST but, the results of RM and RS were $3{\sim}4^{\circ}C$ lower than buoy observation data. By analyzing practical sea surface conditions, large difference in horizontal temperature and wind field for each run were revealed. Case RM and Case RS showed similar horizontal and vertical distributions of temperature and wind field but, Case NG estimated the intensity of sea breeze weakly and land breeze strongly. These differences were due to the difference of the temperature gradient caused by different spatial distributions of SST. Diurnal variations of temperature and wind speed for Case NG indicated great agreement with the observation data and statistics such as root mean squared error, index of agreement, regression were also better than Case RM and Case RS.

• Progress in Medical Physics
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• v.27 no.3
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• pp.117-124
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• 2016

Intrafractional motion of patients, such as respiratory motion during radiation treatment, is an important issue in image-guided radiotherapy. The accuracy of the radiation treatment decreases as the motion range increases. We developed a control system for a robotic patient immobilization system that enables to reduce the range of tumor motion by compensating the tumor motion. Fusion technology, combining robotics and mechatronics, was developed and applied in this study. First, a small-sized prototype was established for use with an industrial miniature robot. The patient immobilization system consisted of an optical tracking system, a robotic couch, a robot controller, and a control program for managing the system components. A multi speed and position control mechanism with three degrees of freedom was designed. The parameters for operating the control system, such as the coordinate transformation parameters and calibration parameters, were measured and evaluated for a prototype device. After developing the control system using the prototype device, a feasibility test on a full-scale patient immobilization system was performed, using a large industrial robot and couch. The performances of both the prototype device and the realistic device were evaluated using a respiratory motion phantom, for several patterns of respiratory motion. For all patterns of motion, the root mean squared error of the corresponding detected motion trajectories were reduced by more than 40%. The proposed system improves the accuracy of the radiation dose delivered to the target and reduces the unwanted irradiation of normal tissue.

• Environmental Engineering Research
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• v.25 no.4
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• pp.479-487
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• 2020

Current assumptions are used in the formulation of pseudo-first (PFO) and second-order (PSO) models to describe the kinetic data of filtration based on ideal operating conditions. This paper presents a new model developed with pseudo n^th order and based on real assumption. A comparison was performed between PFO, PSO and the new model to highlight their performance and the optimisation of the pseudo-order equation, using MATLAB software. Adsorption characteristic of bovine serum albumin adsorption on the track-etched membrane are used as a medium based on protein filtration data were extracted from the literature for different concentrations to demonstrate the comparison between PFO/PSO and the new model. The pseudo first and second-order kinetic models were applied to test the experimental data and they did not provide reasonable values. The results show that the predicted values are consistent with experimental values giving a good correlation coefficient R² = 0.997 and a minimum root mean squared error RMSE = 0.0171. Indeed, the experimental results follow the new model and the optimal pseudo equation order n = 1.115, the most suitable curves for the new model. As a result, we used different experimental adsorption data from the literature to examine and check the applicability and validity of the model.

• Journal of the Korea Organic Resources Recycling Association
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• v.21 no.2
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• pp.88-96
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• 2013

The objective of this research was to evaluate the suitability of sigmoidal and firstorder kinetic equations for simulating the methane production from solid wastes. The sigmoidal kinetic equations used were modified Gompertz and Logistic equations. Statistical criteria used to evaluate equation performance were analysis of goodness-of-fit (Residual sum of squares, Root mean squared error and Akaike's Information Criterion). Akaike's Information Criterion (AIC) was employed to compare goodness-of-fit of equations with same and different numbers of parameters. RSS and RMSE were decreased for first-order kinetic equation with lag-phase time, compared to the first-order kinetic equation without lag-phase time. However, first-order kinetic equations had relatively higher AIC than the sigmoidal kinetic equations. It seemed that the sigmoidal kinetic equations had better goodness-of-fit than the first-order kinetic equations in order to simulate the methane production.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.10A
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• pp.935-942
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• 2006

The performance of ROF systems can be severely degraded due to nonlinear effects in the channel. Also, Orthogonal Frequency Division Multiplex(OFDM), as a standard for broadband wireless and mobile internet networks, is being proposed for deployment with ROF systems to facilitate the total performance of a system. In this paper, at first, the performance of the OFDM-based RoF system with a Mach-Zehnder(MZ) modulator distortion effects has been analyzed at 5.8GHz. Evaluation of mean-squared error of the proposed OFDM-RoF system was carried out to compare with the conventional single carrier system based RoF link after the modulator distortion case and also for fixed signal to noise ratio(SNR) of 20dB using undistorted OFDM signal. Nominal and offset baising pre-distortion techniques are applied in proposed system to linearize the OFDM-RoF link. Finally, a comparison between the aforementioned pre-distortion techniques applied showed important observation in terms of distortion-free dynamic range and SNR to choose offset pre-distortion technique for our proposed system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.12C
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• pp.764-773
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• 2011

Despite enormous performance gain with multi-antenna transmission in the single cell environment, its gain diminishes out in the multi-cell environment due to interference. It is also very hard to solve the efficient downlink beamforming with low complexity in multi-cell environment. First, this paper shows that the asymptotically sum rate optimal downlink beamformings at low and high SNR are maximum ratio transmit (MRT) and zero forcing (ZF) beamforming in the multi-cell system, respectively. Secondly, exploiting the asymptotically optimal downlink beamforming, we develop simple two types of near optimal downlink beamforming schemes having the form of minimum mean squared error (MMSE) beamforming obtained from the dual uplink problem. For each type, three different subclasses are also considered depending on the computational complexity. The simulation results show that the proposed near optimum algorithms provide the trade-off between the complexity and the performance.

• Atmosphere
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• v.16 no.2
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• pp.125-139
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• 2006

Precipitation forecasts from MM5 have been verified for the period 1989-2001 over Yeongdong region to show a tendency of model forecast. We select 57 events which are related with the heavy snowfall in Yeongdong region. They are classified into three precipitation types; mountain type, cold-coastal type, and warm type. The threat score (TS), the probability of detection (POD), and the false-alarm rate (FAR) are computed for categorical verification and the mean squared error (MSE) is also computed for scalar accuracy measures. In the case of POD, warm, mountain, and cold-coastal precipitation type are 0.71, 0.69, and 0.55 in turn, respectively. In aspect of quantitative verification, mountain and cold-coastal type are relatively well matched between forecasts and observations, while for warm type MM5 tends to overestimate precipitation. There are 12 events for the POD below 0.2, mountain, cold-coastal, warm type are 2, 7, 3 events, respectively. Most of their precipitation are distributed over the East Sea nearby Yeongdong region. These events are also shown when there are no or very weak easterlies in the lower troposphere. Even in the case that we use high resolution sea surface temperature (about 18 km) for the boundary condition, there are not much changes in the wind direction to compare that with low resolution sea surface temperature (about 100 km).

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.253-259
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• 2017

Recent development in science and technology has modernized the weapon system of ROKN (Republic Of Korea Navy). Although the cost of purchasing, operating and maintaining the cutting-edge weapon systems has been increased significantly, the national defense expenditure is under a tight budget constraint. In order to maintain the availability of ships with low cost, we need accurate demand forecasts for spare parts. We attempted to find consumption pattern using data mining techniques. First we gathered a large amount of component consumption data through the DELIIS (Defense Logistics Intergrated Information System). Through data collection, we obtained 42 variables such as annual consumption quantity, ASL selection quantity, order-relase ratio. The objective variable is the quantity of spare parts purchased in f-year and MSE (Mean squared error) is used as the predictive power measure. To construct an optimal demand forecasting model, regression tree model, randomforest model, neural network model, and linear regression model were used as data mining techniques. The open software R was used for model construction. The results show that randomforest model is the best value of MSE. The important variables utilized in all models are consumption quantity, ASL selection quantity and order-release rate. The data related to the demand forecast of spare parts in the DELIIS was collected and the demand for the spare parts was estimated by using the data mining technique. Our approach shows improved performance in demand forecasting with higher accuracy then previous work. Also data mining can be used to identify variables that are related to demand forecasting.

• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.993-1000
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• 2016

Semi-supervised learning makes it easy to use an unlabeled data in the supervised learning such as classification. Applying the semi-supervised learning on the regression analysis, we propose two methods for a better regression function estimation. The proposed methods have been assumed different marginal densities of independent variables and different smoothing parameters in unlabeled and labeled data. We shows that the overfitted pilot estimator should be used to achieve the fastest convergence rate and unlabeled data may help to improve the convergence rate with well estimated smoothing parameters. We also find the conditions of smoothing parameters to achieve optimal convergence rate.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.1
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• pp.205-213
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• 2011

The Long Term Evolution (LTE) system is designed to provide a high quality data service for fast moving mobile users. It is based on the Orthogonal Frequency Division Multiplexing (OFDM) and relies its channel estimation on the training samples which are systematically built within the transmitting data. Either a preamble or a lattice type is used for the distribution of training samples and the latter suits better for the multipath fading channel environment whose channel frequency response (CFR) fluctuates rapidly with time. In the lattice-type structure, the estimation of the CFR makes use of the least squares estimate (LSE) for each pilot samples, followed by an interpolation both in time-and in frequency-domain to fill up the channel estimates for subcarriers corresponding to data samples. All interpolation schemes should rely on the pilot estimates only, and thus, their performances are bounded by the quality of pilot estimates. However, the additive noise give rise to high fluctuation on the pilot estimates, especially in a communication environment with low signal-to-noise ratio. These high fluctuations could be monitored in the alternating high values of the first forward differences (FFD) between pilot estimates. In this paper, we analyzed statistically those FFD values and propose a postprocessing algorithm to suppress high fluctuations in the noisy pilot estimates. The proposed method is based on a localized adaptive moving-average filtering. The performance of the proposed technique is verified on a multipath environment suggested on a 3GPP LTE specification. It is shown that the mean-squared error (MSE) between the actual CFR and pilot estimates could be reduced up to 68% from the noisy pilot estimates.