• Journal of information and communication convergence engineering
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• v.15 no.1
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• pp.7-13
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• 2017

We consider a distributed estimation where many nodes remotely placed at known locations collect the measurements of the parameter of interest, quantize these measurements, and transmit the quantized data to a fusion node; this fusion node performs the parameter estimation. Noting that quantizers at nodes should operate in a non-regular framework where multiple codewords or quantization partitions can be mapped from a single measurement to improve the system performance, we propose a low-weight estimation algorithm that finds the most feasible combination of codewords. This combination is found by computing the weighted sum of the possible combinations whose weights are obtained by counting their occurrence in a learning process. Otherwise, tremendous complexity will be inevitable due to multiple codewords or partitions interpreted from non-regular quantized data. We conduct extensive experiments to demonstrate that the proposed algorithm provides a statistically significant performance gain with low complexity as compared to typical estimation techniques.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.444-449
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• 1996

The semiconductor, which is precision product, requires many inspection processes. The surface conditions of the semiconductor chip affect on the functions of the semiconductors. The defects of the chip surface are cracks or voids. As general inspection method requires many inspection procedure, the inspection system which searches immediately and precisely the defects of the semiconductor chip surface is required. We suggest the detection algorithm for inspecting the surface defects of the semiconductor surface. The proposed algorithm first regards the semiconductor surface as random texture and point spread function, and secondly presents the character of texture by linear estimation theorem. This paper assumes that the gray level of each pixel of an image is estimated from a weighted sum of gray levels of its neighbor pixels by linear estimation theorem. The weight coefficients are determined so that the mean square error is minimized. The obtained estimation window(two-dimensional estimation window) characterizes the surface texture of semiconductor and is used to discriminate the defects of semiconductor surface.

• Journal of the Korean Data and Information Science Society
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• v.12 no.2
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• pp.1-10
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• 2001

Neural networks we increasingly being seen as an addition to the statistics toolkit which should be considered alongside both classical and modern statistical methods. Neural networks are usually useful for classification and function estimation. In this paper we concentrate on function estimation using neural networks with weight decay factor The use of weight decay seems both to help the optimization process and to avoid overfitting. In this type of neural networks, the problem to decide the number of hidden nodes, weight decay parameter and iteration number of learning is very important. It is called the optimization of weight decay neural networks. In this paper we propose a automatic optimization based on genetic algorithms. Moreover, we compare the weight decay neural network automatically learned according to automatic optimization with ordinary neural network, projection pursuit regression and support vector machines.

• Journal of Forest and Environmental Science
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• v.33 no.4
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• pp.305-314
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• 2017

This study aimed to predict changes in forest area using a probability density function, in order to promote effective forest management in the area north of the civilian control line (known as the Minbuk area) in Korea. Time series analysis (2010 and 2016) of forest area using land cover maps and accessibility expressed by distance covariates (distance from buildings, roads, and civilian control line) was applied to a probability density function. In order to estimate the probability density function, mean and variance were calculated using three methods: area weight (AW), area rate weight (ARW), and sample area change rate weight (SRW). Forest area increases in regions with lower accessibility (i.e., greater distance) from buildings and roads, but no relationship with accessibility from the civilian control line was found. Estimation of forest area change using different distance covariates shows that SRW using distance from buildings provides the most accurate estimation, with around 0.98-fold difference from actual forest area change, and performs well in a Chi-Square test. Furthermore, estimation of forest area until 2028 using SRW and distance from buildings most closely replicates patterns of actual forest area changes, suggesting that estimation of future change could be possible using this method. The method allows investigation of the current status of land cover in the Minbuk area, as well as predictions of future changes in forest area that could be utilized in forest management planning and policymaking in the northern area.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.5
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• pp.404-414
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• 2013

In the conceptual design phase of jet fighters, the trade study is performed repeatedly for a selection of the baseline configuration. The automation of repeated trade study makes possible to select efficiently the baseline configuration. In this study, the performance analysis code was developed for the automation of trade study. The code was consists of the module of shape generation, the module of weight estimation, the module of mission performance analysis. 3D CAD Model can be generated by the module of shape generation and Weight can be estimated by using the empirical equation in the module of weight estimation. The module of mission performance analysis was able to calculate the mission performance about the arbitrary mission profile. In addition, the optimal mission performance can be calculated by using optimization method. By performing the validation, the code was confirmed to be able to apply to the conceptual design phase.

• The Korean Journal of Applied Statistics
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• v.30 no.6
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• pp.993-1004
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• 2017

A stratified sampling method is generally used with a sample selected using the same sample weight in each stratum in order to improve the accuracy of the sampling survey estimation. However, the weight should be adjusted to reflect the response rate if the response rate is affected by the value of the variable of interest. It may be also more effective to adjust the weights by subdividing the stratum rather than using the same weight if the variable of interest has a linear relationship with the continuous auxiliary variables. In this study, we propose a method to increase the accuracy of estimation using an informative sampling design technique when the response rate is an exponential function of the variable of interest and the variable of interest has a linear relationship with the auxiliary variable. Simulation results show the superiority of the proposed method.

• Journal of Advanced Navigation Technology
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• v.27 no.1
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• pp.77-95
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• 2023

In this study, the conceptual design of a tilt + stopped rotor type electric vertical take-off and landing (eVTOL) aircraft was performed using design iteration. Based on Hyundai Motor's S-A1, the mission profile was defined using the concept of urban air mobility (UAM), and configuration design and aerodynamic analysis were performed using OpenVSP and XFLR5 software. After estimating the required power for the designed eVTOL, the required performance of the battery and the maximum take-off weight (MTOW) were calculated. . It was iteratively calculated using Microsoft Excel and Visual Basic Application, and a new electric motor weight estimation formula was derived. Also, the sensitivity analyses of each design variables of an eVTOL was performed using the automated program.

• Journal of the Korea Society of Computer and Information
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• v.10 no.2 s.34
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• pp.21-30
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• 2005

In general, the robust estimation method is well known for a good statistical estimator that is insensitive to small departures from the idealized assumptions for which the estimation is optimized. While there are many existing robust estimation techniques that have been proposed in the literature, two main techniques used in computer vision are M-estimators and least-median of squares (LMS). Among these. we utilized the M-estimators since they are known to provide an optimal estimation of affine motion parameters. The M-estimators have higher statistical efficiency but tolerate much lower percentages of outliers unless properly initialized. To resolve these problems, we proposed an adaptive M-estimators algorithm that effectively separates outliers from non-outliers and estimate affine model parameters, using a continuous sigmoid weight function. The experimental results show the superiority of our method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.7
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• pp.2420-2435
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• 2010

This study presented estimation framework that consider website pattern and user use purpose for website estimation improvement. Also, analyzed and evaluated existing website using estimation framework. In this study, divided by general user and company user and analyzed relative importance between each estimation factors in estimation framework and secured reliability of website estimation model because applies AHP method and presented key factors to website construction, operation, administration. Through this study, projected necessity of weight calculation between estimation area by site type to website estimation field researchers and differentiate contents offered that follow in user type(individual, company) to website planners and operators, projected guideline that can provide more efficient and strategic service.

• Asian-Australasian Journal of Animal Sciences
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• v.24 no.8
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• pp.1041-1047
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• 2011

Data on 2,365 Mecheri sheep (1,201 males and 1,164 females), maintained at the Mecheri Sheep Research Station, Pottaneri, India, and recorded between 1979 and 2006, were analysed to study the growth related traits and their genetic control. The body weights at different ages (i.e. at birth, weaning (3 months), 6, 9 and 12 months) were recorded and collected from the birth and growth registers maintained in the farm. The average weights of Mecheri sheep at birth, and at 12 months of age were $2.24{\pm}0.01$ and $16.81{\pm}0.15$ kg respectively. The pre- and post-weaning average daily weight gains were $63.84{\pm}0.75$ and $29.52{\pm}0.43$ g respectively. Study revealed a significant difference with the period of lambing on body weight, weight gain and efficiency in weight gain at different stages of growth. Males were heavier and had a higher weight gain than females at almost all stages of growth and the differences tended to increase with age. The direct heritability estimates increased from birth to six months of age and then decreased. The direct heritabilities of all body weights at different stages of growth were low to moderate in magnitude and the values at birth, weaning, six, nine and 12 months of age were 0.08, 0.17, 0.21, 0.13 and 0.10 respectively. For the estimation of heritability at birth and three months body weights, the direct additive genetic and maternal additive genetic effects have to be taken into account and for the estimation of six months weight, the direct additive genetic and maternal permanent environmental effects have to be included in the model. The estimates of heritability, phenotypic and genetic correlations among the different body weights indicated that the selection for improving the body weights at different traits should be done on the basis of three or six months weight because of higher heritability estimates and having higher genetic correlations with other traits.