• 한국농공학회논문집
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• 제61권6호
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• pp.93-101
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• 2019

This study aims to analyze the influences of applications of two different evapotranspiration (ET) estimation methods on the irrigation water requirements (IWR) for paddy rice and water supply reliability of agricultural reservoirs. The modified Penman (MP), traditional method, and the Penman-Monteith (PM), the new adopted method, were applied on 149 reservoirs located in Honam province for this study. The weather date was used from 1987 to 2016, and analysed the trends of temperature and rainfall during rice growing season between past and current 10 years respectively. The increased average temperature and rainfall were observed from the current 10 years compared to the past years. This phenomena impacts on the results of ET and IWR estimations with decreased IWR obtained from high rainfall regions and increased ET obtained high temperature regions. For the comparisons of application results of two ET approaches, the PM method showed lower ET and IWR, and hence more reliable storage capacity of the reservoirs respect to water supply to paddy fields. The results also showed that the influences of different ET methods applications on the water supply reliability of reservoirs are negligible for the cases of over 3.7 watershed ratio and 670 mm unit reservoir storage, while significant variations of the results obtain from the applications between two ET approaches for the opposite cases. Further studies are necessary to consider various field conditions for practical applications of the PM method estimating ET in the fields of paddy farming.

• Korean Journal of Hydrosciences
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• 제7권
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• pp.125-137
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• 1996

The subject of the paper is the selection of the number and location of raingauge stations among existing ones for the computation of mean areal precipitation and for use as input of real-time flow prediction models. The weighted average method developed by National Weather Service was used to compute MAP over the Boone River basin in Iowa with a 40 year daily data set. Two different searching methods were used to find local optimal solutions. An operational rainfall-runoff model was used to determine the optimal location and number of stations for flow prediction.

• Communications for Statistical Applications and Methods
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• 제9권3호
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• pp.715-723
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• 2002

This paper is to show a clustering application of a density estimation method that utilizes the Gaussian mixture model. We define "closeness measure" as a clustering criterion to see how close given two Gaussian components are. Closeness measure is defined as the ratio of log likelihood between two Gaussian components. According to simulations using artificial data, the clustering algorithm turned out to be very powerful in that it can correctly determine clusters in complex situations, and very flexible in that it can produce different sizes of clusters based on different threshold valuesold values

• 한국도로학회논문집
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• 제18권3호
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• pp.115-125
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• 2016

PURPOSES : This study proposes a methodology to collect data necessary for microlevel emission estimation, such as second-by-second speeds and road grades, and to accordingly estimate emissions. METHODS : To ease data collection for microlevel emission estimation, a vehicle equipped with speed- and location-recording instruments as well as equipment for measuring road geometry was used. As a case study, this vehicle and the proposed methodology were used on a 10-km-long highway in Yongin City, Korea. Emissions from the vehicle during driving were estimated in various microscale driving conditions. RESULTS : Differences in the estimated emission under different microscale driving conditions cannot be ignored. Compared with the estimations obtained when second-by-second data were not considered, CO and NOx emissions were more than threefold higher when considering second-by-second speed; similarly, CO and NOx emission estimations were higher by approximately 10% and 3%, respectively, when considering second-by-second road grade. CONCLUSIONS : The proposed method can estimate vehicle emissions under real-world driving conditions in such applications as road design and traffic policy assessments.

• Nuclear Engineering and Technology
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• 제54권9호
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• pp.3242-3249
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• 2022

As Kori unit 1 is undergoing the decommissioning process, estimating the disposal amount of waste from the decommissioned nuclear reactor has become one of the challenging issues. Since the waste disposal amount estimation depends on the packing of the waste, it is highly desirable to optimize the waste packing plan. In this study, we developed an efficient scheme for packing waste component segments. The scheme consists of 1) preparing three-dimensional models of segments, 2) orienting each segment in such a way to minimize the bounding box volume, and 3) applying hybrid genetic algorithm to pack the segments in the disposal containers. When the packing solution converges in the algorithm, it comes up with the number of containers used and the placement of segments in each container. The scheme was applied to Kori-1 reactor pressure vessel. The required number of containers calculated by the developed scheme was 24 compared to 42 that was the estimation of the prior packing plan, resulting in disposal volume savings by more than 40%. The developed method is flexible for applications to various packing problems with waste segments from different cutting options and different sizes of containers.

• International Journal of Naval Architecture and Ocean Engineering
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• 제7권6호
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• pp.964-978
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• 2015

Numerous experiments with a scaled pilot facility were carried out to compare the relative bulk transfer performance of three special devices for applications to drilling systems. The pipe diameter for bulk transportation was 3 in., which corresponds to around half of the actual system dimensions. Two different pressures, 3 and 4 bar, were considered to check the relative performance under different pressure conditions at a bulk storage tank. And to make a practical estimation method of the bulk transfer rate at the early design stages of the bulk handling system, a series of experiments were conducted for real scaled bulk handing systems of two drilling vessels. The pressure drops at each pipe element as well as the bulk transfer rates were measured under different operating conditions. Using the measured results, the friction factor for each pipe element was calculated and a procedure for transfer rate estimation was developed. Compared to the measured transfer rate results for other drilling vessels, the estimated transfer rates were within a maximum 15% error bound.

• Communications for Statistical Applications and Methods
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• 제24권4호
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• pp.397-419
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• 2017

A four-parameter extended fatigue lifetime model called the odd Birnbaum-Saunders geometric distribution is proposed. This model extends the odd Birnbaum-Saunders and Birnbaum-Saunders distributions. We derive some properties of the new distribution that include expressions for the ordinary moments and generating and quantile functions. The method of maximum likelihood and a Bayesian approach are adopted to estimate the model parameters; in addition, various simulations are performed for different parameter settings and sample sizes. We propose two new models with a cure rate called the odd Birnbaum-Saunders mixture and odd Birnbaum-Saunders geometric models by assuming that the number of competing causes for the event of interest has a geometric distribution. The applicability of the new models are illustrated by means of ethylene data and melanoma data with cure fraction.

• Communications for Statistical Applications and Methods
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• 제10권3호
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• pp.859-871
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• 2003

In this paper we introduce some adaptive M-estimators using selector statistics to estimate the slope of regression model under the symmetric and continuous underlying error distributions. This selector statistics is based on the residuals after the preliminary fit L$_1$ (least absolute estimator) and the idea of Hogg(1983) and Hogg et. al. (1988) who used averages of some order statistics to discriminate underlying symmetric distributions in the location model. If we use L$_1$ as a preliminary fit to get residuals, we find the asymptotic distribution of sample quantiles of residual are slightly different from that of sample quantiles in the location model. If we use the functions of sample quantiles of residuals as selector statistics, we find the suitable quantile points of residual based on maximizing the asymptotic distance index to discriminate distributions under consideration. In Monte Carlo study, this adaptive M-estimation method using selector statistics works pretty good in wide range of underlying error distributions.

• 한국멀티미디어학회논문지
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• 제20권8호
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• pp.1406-1420
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• 2017

Artificial neural networks (ANNs) play an important role in the fields of function approximation, prediction, and classification. ANN performance is critically dependent on the input parameters, including the number of neurons in each layer, and the optimal values of weights and biases assigned to each neuron. In this study, we apply the particle swarm optimization method, a popular optimization algorithm for determining the optimal values of weights and biases for every neuron in different layers of the ANN. Several regression models, including general linear regression, Fourier regression, smoothing spline, and polynomial regression, are conducted to evaluate the proposed method's prediction power compared to multiple linear regression (MLR) methods. In addition, residual analysis is conducted to evaluate the optimized ANN accuracy for both training and test datasets. The experimental results demonstrate that the proposed method can effectively determine optimal values for neuron weights and biases, and high accuracy results are obtained for prediction applications. Evaluations of the proposed method reveal that it can be used for prediction and estimation purposes, with a high accuracy ratio, and the designed model provides a reliable technique for optimization. The simulation results show that the optimized ANN exhibits superior performance to MLR for prediction purposes.

• 제어로봇시스템학회논문지
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• 제13권3호
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• pp.224-229
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• 2007

This paper presents a camera calibration method using several images for three dimensional measurement applications such as stereo systems, mobile robots, and visual inspection systems in factories. Conventional calibration methods that use single image suffer from errors related to reference point extraction in image, lens distortion, and numerical analysis of nonlinear optimization. The camera parameter values obtained from images of same camera is not same even though we use same calibration method. The camera parameters that are obtained from several images of different view for a calibration target is usaully not same with large error values and we can not assume a special probabilistic distribution when we estimate the parameter values. In this paper, the median value of camera parameters from several images is used to improve estimation of the camera values in an iterative step with nonlinear optimization. The proposed method is proved by experiments using real images.