• Title/Summary/Keyword: 최소분산법

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Estimation of Variance Component and Environment Effects on Somatic Cell Scores by Parity in Dairy Cattle (젖소집단의 산차에 따른 체세포점수의 환경효과 및 분산성분 추정)

  • 조광현;나승환;서강석;김시동;박병호;이영창;박종대;손삼규;최재관
    • Journal of Animal Science and Technology
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    • v.48 no.1
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    • pp.39-48
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    • 2006
  • This study utilized test day of somatic cell score data of dairy cattle from 2000 to 2004. The number of data used were 124,635 of first parity, 134,308 of second parity, 77,862 of third parity, 41,787 of forth parity and 37,412 of fifth parity. The data was analyzed by least square mean method using GLM to estimate the effects of calving year, age, lactation stage, parity and season on somatic cell score. Variance component estimation using test day model was determined by using expectation maximization algorithm- restricted maximum likelihood (EM-REML) analysis method. In each parity, somatic cell score was low for younger group and was relatively high in older groups. Likewise, for lactation stage, the score was low in early-lactation and high in late-lactation in first parity and second parity. Nevertheless, for the third, fourth and fifth parity, however, high somatic cell score was observed in mid-lactation. Generally, the score was high in the peak. Although in fourth and fifth parity, the score was low in late-lactation. Environmental effect of season, somatic cell score was generally low from September to November for all parities. The score was high between June and August when the milk production is usually low. The heritability in each parity were 0.05, 0.09, 0.10, 0.05 and 0.05 for parity 1, 2, 3, 4, 5, respectively. Genetic variance value was estimated to be high in second, third and fifth parity in early-lactation and to be low in first and forth parity.

Efficient Correlation Channel Modeling for Transform Domain Wyner-Ziv Video Coding (Transform Domain Wyner-Ziv 비디오 부호를 위한 효과적인 상관 채널 모델링)

  • Oh, Ji-Eun;Jung, Chun-Sung;Kim, Dong-Yoon;Park, Hyun-Wook;Ha, Jeong-Seok
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.47 no.3
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    • pp.23-31
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    • 2010
  • The increasing demands on low-power, and low-complexity video encoder have been motivating extensive research activities on distributed video coding (DVC) in which the encoder compresses frames without utilizing inter-frame statistical correlation. In DVC encoder, contrary to the conventional video encoder, an error control code compresses the video frames by representing the frames in the form of syndrome bits. In the meantime, the DVC decoder generates side information which is modeled as a noisy version of the original video frames, and a decoder of the error-control code corrects the errors in the side information with the syndrome bits. The noisy observation, i.e., the side information can be understood as the output of a virtual channel corresponding to the orignal video frames, and the conditional probability of the virtual channel model is assumed to follow a Laplacian distribution. Thus, performance improvement of DVC systems depends on performances of the error-control code and the optimal reconstruction step in the DVC decoder. In turn, the performances of two constituent blocks are directly related to a better estimation of the parameter of the correlation channel. In this paper, we propose an algorithm to estimate the parameter of the correlation channel and also a low-complexity version of the proposed algorithm. In particular, the proposed algorithm minimizes squared-error of the Laplacian probability distribution and the empirical observations. Finally, we show that the conventional algorithm can be improved by adopting a confidential window. The proposed algorithm results in PSNR gain up to 1.8 dB and 1.1 dB on Mother and Foreman video sequences, respectively.

Site Characterization using Shear-Wave Velocities Inverted from Rayleigh-Wave Dispersion in Wonju, Korea (레일리파 분산을 역산하여 구한 횡파속도를 이용한 원주시의 부지특성)

  • Kim, Chungho;Ali, Abid;Kim, Ki Young
    • Geophysics and Geophysical Exploration
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    • v.17 no.1
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    • pp.11-20
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    • 2014
  • To reveal shear-wave velocities ($v_s$) and site characterization of Wonju, Korea, Rayleigh waves were recorded at 78 sites of lower altitude using 12 to 24 4.5-Hz vertical geophones for 20 days during the period of February to September 2013. Dispersion curves of the Rayleigh waves obtained by the extended spatial autocorrelation method were inverted using the damped least-squares method to derive $v_s$ models. From these 1-D models, the average $v_s$ to a depth of 30 m ($v_s30$), $v_s$ of weathered rocks, depths to these basement rocks, and average $v_s$ of the overburden layer were derived to be $16.3{\pm}0.7m$, $576{\pm}8m/s$, $290{\pm}7m/s$, and $418{\pm}13m/s$, respectively, in the 95% confidence range. To determine adequate proxies for $v_s30$, we computed correlation coefficients of $v_s30$ with topographic slope (r = 0.46) and elevation (r = 0.43). An empirical linear relationship is presented as a combination of individually estimated $v_s30$ with weighting factors of 0.45, 0.45, and 0.1 for topographic slope, elevation, and mapped lithology, respectively. Due to a weak correlation between $v_s30$ obtained from inversion of dispersion curves and the proxy-based estimation (r = 0.50), however, the relatively large error range should be considered for applications of this relationship.

Hydrologic Regimes Analyses on Down Stream Effects of the Young Chun Dam by Indicators of Hydrologic Alterations (수문변화 지표법에 의한 영천댐이 하류하천에 미치는 유황변화 분석)

  • Park, Bong-Jin;Kim, Joon-Tae;Jang, Chang-Lae;Jung, Kwan-Sue
    • Journal of Korea Water Resources Association
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    • v.41 no.2
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    • pp.163-172
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    • 2008
  • Hydrologic regimes play a major role in determining the biotic composition, structure, and function of river ecosystem. In this study, hydrologic regimes were analyzed on down stream effects of the Young-Chun dam construction using the Indicators of Hydrologic Alterations(IHA). The analysis results were as follows ; (1) Monthly mean flows were decreased during drought and flood season on the pre and post dam, (2) Magnitude and Duration of Annual Exterm Conditions, annual minima 1-day means was $3.48m^3/sec$, $0.89m^3/sec$ and annual maxima 1-day mean was $833.1m^3/sec$, $672.1m^3/sec$ on the pre and post dam (3) Timing of Annual Exterm conditions, Julian date of the annual minima 1-day means was 180th(June) in the pre dam, 257th(September) in the post dam, Julian date of the annual maxima 1-day means was 209th(July) in the pre dam, 217th(August) in the post dam, (4) Frequency and Duration of High and Low Pulse, Low Puls counts and duration were 3 times and 23 days in the pre dam, High Pulse counts and duration were 4 times and 2 days in the pre dam. (5) Rate and Frequency of Water Condition Changes, rise rates was 39.27 %, 19.36 % and fall rates -15.85 %, -8.16 % in the pre and post dam, respectively (6) Coefficient of Variation, annual exteram water conditions were decreased from 0.9054 to 0.6314 and from 1.0440 to 0.9617, Timing of Annual Exterm conditions were incereased for minima flow from 0.269 to 0.282, for maxima form 0.069 to 0.153.

Nonlinear Characteristics of Non-Fuzzy Inference Systems Based on HCM Clustering Algorithm (HCM 클러스터링 알고리즘 기반 비퍼지 추론 시스템의 비선형 특성)

  • Park, Keon-Jun;Lee, Dong-Yoon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.13 no.11
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    • pp.5379-5388
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    • 2012
  • In fuzzy modeling for nonlinear process, the fuzzy rules are typically formed by selection of the input variables, the number of space division and membership functions. The Generation of fuzzy rules for nonlinear processes have the problem that the number of fuzzy rules exponentially increases. To solve this problem, complex nonlinear process can be modeled by generating the fuzzy rules by means of fuzzy division of input space. Therefore, in this paper, rules of non-fuzzy inference systems are generated by partitioning the input space in the scatter form using HCM clustering algorithm. The premise parameters of the rules are determined by membership matrix by means of HCM clustering algorithm. The consequence part of the rules is represented in the form of polynomial functions and the consequence parameters of each rule are identified by the standard least-squares method. And lastly, we evaluate the performance and the nonlinear characteristics using the data widely used in nonlinear process. Through this experiment, we showed that high-dimensional nonlinear systems can be modeled by a very small number of rules.

Analysis and parameter extraction of motion blurred image (움직임 열화 현상이 발생한 영상의 분석과 파라메터 추출)

  • 최지웅;최병철;강문기
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.24 no.10B
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    • pp.1953-1962
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    • 1999
  • While acquiring the image, the shaking of the image capturing equipment or the object seriously damages the image quality. This phenomenon, which degrades the clarity and the resolution of the image is called motion blur. In this paper, a newly defined function is introduced for finding the degree and the length of the motion blur. The domain of this function defined as Peak-trace domain. In The Peak-trace domain, the noise dominant region for calculating the noise variance and the signal dominant region for extracting the degree and the length of the motion blur are defined and analyzed. Using the information of the Peak-trace in the signal dominant region, we can find the direction of the motion regardless of the noise corruption. Weighted least mean square method helps extracting the Peak-trace more precisely. After getting the direction of the motion blur, we can find the length of the motion blur based on one dimensional Cepstrum. In the experiment, we could efficiently restore the degraded image using the information obtained by the proposed algorithm.

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A Robust Design of Response Surface Methods (반응표면방법론에서의 강건한 실험계획)

  • 임용빈;오만숙
    • The Korean Journal of Applied Statistics
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    • v.15 no.2
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    • pp.395-403
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    • 2002
  • In the third phase of the response surface methods, the first-order model is assumed and the curvature of the response surface is checked with a fractional factorial design augmented by centre runs. We further assume that a true model is a quadratic polynomial. To choose an optimal design, Box and Draper(1959) suggested the use of an average mean squared error (AMSE), an average of MSE of y(x) over the region of interest R. The AMSE can be partitioned into the average prediction variance (APV) and average squared bias (ASB). Since AMSE is a function of design moments, region moments and a standardized vector of parameters, it is not possible to select the design that minimizes AMSE. As a practical alternative, Box and Draper(1959) proposed minimum bias design which minimize ASB and showed that factorial design points are shrunk toward the origin for a minimum bias design. In this paper we propose a robust AMSE design which maximizes the minimum efficiency of the design with respect to a standardized vector of parameters.

Study on the Synthesis of Polycarbosilane as a SiC Precursor and its Comparative Property (탄화규소의 전구체로서 Polycarbosilane의 합성 및 물성 비교 연구)

  • Moon, Kyo-Tae;Min, Dong-Soo;Lim, Heun-Soung;Kim, Dong-Pyo
    • Applied Chemistry for Engineering
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    • v.9 no.2
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    • pp.159-164
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    • 1998
  • Polycarbosilane(PCS) as a SiC precursor was synthesized from the rearrangement reaction of polydimethysilane(PDMS) in an autoclave, which prepared by dehalocoupling reaction of dichlorodimethylsilane. After fractional precipitation into three fractions in n-hexane-methanol mixture, they were characterized by FT-IR, NMR, GPC, TGA/DSC and XRD, and compared with the commercial product. We found that the molecular weight distributions of the PCS depended on the reaction pressures, temperatures and the reaction times, and affected thermal property and ceramic yield of the polymer. The monodispersed PCS containing less amount of oligomers and nonsoluble products was prepared by reaction of PDMS at $420^{\circ}C$ for 10 hrs, and it also gave the greatest amount of medium molecular weight($M_n=4,000$) fraction.

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Analysis of Two-Dimensional Fluorescence Spectra in Biotechnological Processes by Artificial Neural Networks I - Classification of Fluorescence Spectra using Self-Organizing Maps - (인공신경망에 의한 생물공정에서 2차원 형광스펙트럼의 분석 I - 자기조직화망에 의한 형광스펙트럼의 분류 -)

  • Lee Kum-Il;Yim Yong-Sik;Kim Chun-Kwang;Lee Seung-Hyun;Chung Sang-Wook;Rhee Jong Il
    • KSBB Journal
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    • v.20 no.4
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    • pp.291-298
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    • 2005
  • Two-dimensional (2D) spectrofluorometer is often used to monitor various fermentation processes. The change in fluorescence intensities resulting from various combinations of excitation and emission wavelengths is investigated by using a spectra subtraction technique. But it has a limited capacity to classify the entire fluorescence spectra gathered during fermentations and to extract some useful information from the data. This study shows that the self-organizing map (SOM) is a useful and interpretative method for classification of the entire gamut of fluorescence spectral data and selection of some combinations of excitation and emission wavelengths, which have useful fluorometric information. Some results such as normalized weights and variances indicate that the SOM network is capable of interpreting the fermentation processes of S. cerevisiae and recombinant E. coli monitored by a 2D spectrofluorometer.

Busan Housing Market Dynamics Analysis with ESDA using MATLAB Application (공간적탐색기법을 이용한 부산 주택시장 다이나믹스 분석)

  • Chung, Kyoun-Sup
    • The Journal of the Korea Contents Association
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    • v.12 no.2
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    • pp.461-471
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    • 2012
  • The purpose of this paper is to visualize the housing market dynamics with ESDA (Exploratory Spatial Data Analysis) using MATLAB toolbox, in terms of the modeling housing market dynamics in the Busan Metropolitan City. The data are used the real housing price transaction records in Busan from the first quarter of 2006 to the second quarter of 2009. Hedonic house price model, which is not reflecting spatial autocorrelation, has been a powerful tool in understanding housing market dynamics in urban housing economics. This study considers spatial autocorrelation in order to improve the traditional hedonic model which is based on OLS(Ordinary Least Squares) method. The study is, also, investigated the comparison in terms of $R^2$, Sigma Square(${\sigma}^2$), Likelihood(LR) among spatial econometrics models such as SAR(Spatial Autoregressive Models), SEM(Spatial Errors Models), and SAC(General Spatial Models). The major finding of the study is that the SAR, SEM, SAC are far better than the traditional OLS model, considering the various indicators. In addition, the SEM and the SAC are superior to the SAR.