• Asian-Australasian Journal of Animal Sciences
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• v.10 no.5
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• pp.510-513
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• 1997

This study examined the effects of ignoring inbreeding depression on (co)variance components for weaning weight through the use of Monte Carlo simulation. Weaning weight is of particular interest as a trait for which additive direct and maternal genetic components exist and there then is the potential for a direct-maternal genetic covariance. Ignoring inbreeding depression in the analytical model (.8 kg reduction of phenotypic value per 1% inbreeding) led to biased estimates of all genetic (co) variance components, all estimates being larger than the true values of the parameters. In particular, a negative bias in the direct-maternal genetic covariance was observed in analyses that ignored inbreeding depression. A small spurious sire-by-year interaction variance was also observed.

• Journal of Korean Institute of Industrial Engineers
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• v.29 no.2
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• pp.179-189
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• 2003

Gate poly-silicon critical dimension is a prime characteristic of a metal-oxide-semiconductor field effect transistor. It is important to achieve the uniformity of gate poly-silicon critical dimension in order that a semiconductor device has acceptable electrical test characteristics as well as a semiconductor wafer fabrication process has a competitive net-die-per-wafer yield. However, on gate poly-silicon critical dimension, the complexity associated with a semiconductor wafer fabrication process entails hierarchical variance components according to run-to-run, wafer-to-wafer and even die-to-die production unit changes. Specifically, estimates of the hierarchical variance components are required not only for disclosing dominant sources of the variation but also for testing the wafer-level uniformity. In this paper, two experimental designs, a two-stage nested design and a randomized complete block design are considered in order to estimate the hierarchical variance components. Since gate poly-silicon critical dimensions are collected from fixed die positions within wafers, a factor representing die positions can be regarded as fixed in linear statistical models for the designs. In this context, the two-stage nested design also checks the wafer-level uniformity taking all sampled runs into account. In more detail, using variance estimates derived from randomized complete block designs, Duncan's multiple range test examines the wafer-level uniformity for each run. Consequently, a framework presented in this study could provide guidelines to practitioners on estimating the hierarchical variance components and testing the wafer-level uniformity in parallel for any characteristics concerned in semiconductor wafer fabrication processes. Statistical analysis is illustrated for an experimental dataset from a real pilot semiconductor wafer fabrication process.

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.9
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• pp.1407-1414
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• 2018

Objective: The aim of this study was to estimate (co) variance components and genetic parameters for categorical carcass traits using Bayesian inference via mixed linear and threshold animal models in Anglonubian goats. Methods: Data were obtained from Anglonubian goats reared in the Brazilian Mid-North region. The traits in study were body condition score, marbling in the rib eye, ribeye area, fat thickness of the sternum, hip height, leg perimeter, and body weight. The numerator relationship matrix contained information from 793 animals. The single- and two-trait analyses were performed to estimate (co) variance components and genetic parameters via linear and threshold animal models. For estimation of genetic parameters, chains with 2 and 4 million cycles were tested. An 1,000,000-cycle initial burn-in was considered with values taken every 250 cycles, in a total of 4,000 samples. Convergence was monitored by Geweke criteria and Monte Carlo error chain. Results: Threshold model best fits categorical data since it is more efficient to detect genetic variability. In two-trait analysis the contribution of the increase in information and the correlations between traits contributed to increase the estimated values for (co) variance components and heritability, in comparison to single-trait analysis. Heritability estimates for the study traits were from low to moderate magnitude. Conclusion: Direct selection of the continuous distribution of traits such as thickness sternal fat and hip height allows obtaining the indirect selection for marbling of ribeye.

• Asian-Australasian Journal of Animal Sciences
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• v.28 no.8
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• pp.1090-1094
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• 2015

The aim of the study was to select traits that may constitute a prospective criterion for breeding value prediction of young horses. The results of 1,232 starts of 894 four-, five-, six-, and seven-year-old horses, obtained during jumping championships for young horses which had not been evaluated in, alternative to championships, training centres were analyed. Nine traits were chosen of those recorded: ranking in the championship, elimination (y/n), conformation, rating of style on day one, two, and three, and penalty points on day one, two, and three of a championship. (Co)variance components were estimated via the Gibbs sampling procedure and adequate (co)variance component ratios were calculated. Statistical classifications were trait dependent but all fitted random additive genetic and permanent environment effects. It was found that such characteristics as penalty points and jumping style are potential indicators of jumping ability, and the genetic variability of the traits was within the range of 14% to 27%. Given the low genetic correlations between the conformation and other results achieved on the parkour, the relevance of assessment of conformation in four-years-old horses has been questioned.

• Asian-Australasian Journal of Animal Sciences
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• v.29 no.12
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• pp.1682-1687
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• 2016

The objective of this study was to estimate the genetic parameters of milk protein yields in Iranian Holstein dairy cattle. A total of 1,112,082 test-day milk protein yield records of 167,269 first lactation Holstein cows, calved from 1990 to 2010, were analyzed. Estimates of the variance components, heritability, and genetic correlations for milk protein yields were obtained using a random regression test-day model. Milking times, herd, age of recording, year, and month of recording were included as fixed effects in the model. Additive genetic and permanent environmental random effects for the lactation curve were taken into account by applying orthogonal Legendre polynomials of the fourth order in the model. The lowest and highest additive genetic variances were estimated at the beginning and end of lactation, respectively. Permanent environmental variance was higher at both extremes. Residual variance was lowest at the middle of the lactation and contrarily, heritability increased during this period. Maximum heritability was found during the 12th lactation stage ($0.213{\pm}0.007$). Genetic, permanent, and phenotypic correlations among test-days decreased as the interval between consecutive test-days increased. A relatively large data set was used in this study; therefore, the estimated (co)variance components for random regression coefficients could be used for national genetic evaluation of dairy cattle in Iran.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3585-3601
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• 2016

The error rate performance of circularly distributed antenna system is studied over Nakagami-m fading channels, where a dual-channel receiver is employed for the quadrature phase shift keying signals detection. To mitigate the Co-Channel Interference (CCI) caused by the adjacent cells and to save the transmit power, this work presents remote antenna unit selection transmission based on the best channel quality and the maximized path-loss, respectively. The commonly used Gaussian and Q-function approximation method in which the CCI and the noise are assumed to be Gaussian distributed fails to depict the precise system performance according to the central limit theory. To this end, this work treats the CCI as a random variable with random variance. Since the in-phase and the quadrature components of the CCI are correlated over Nakagami-m fading channels, the dependency between the in-phase and the quadrature components is also considered for the error rate analysis. For the special case of Rayleigh fading in which the dependency between the in-phase and the quadrature components can be ignored, the closed-form error rate expressions are derived. Numerical results validate the accuracy of the theoretical analysis, and a comparison among different transmission schemes is also performed.

• Journal of the Korea Society of Computer and Information
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• v.23 no.1
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• pp.25-32
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• 2018

In this paper, we propose an edge detection algorithm for auto focus of infrared camera. We designed and implemented the edge detection of infrared image by using a spatial filter on FPGA. The infrared camera should be designed to minimize the image processing time and usage of hardware resource because these days surveillance systems should have the fast response and be low size, weight and power. we applied the $3{\times}3$ mask filter which has an advantage of minimizing the usage of memory and the propagation delay to process filtering. When we applied Laplacian filter to extract contour data from an image, not only edge components but also noise components of the image were extracted by the filter. These noise components make it difficult to determine the focus state. Also a bad pixel of infrared detector causes a problem in detecting the edge components. So we propose an adaptive edge detection filter that is a method to extract only edge components except noise components of an image by analyzing a variance of pixel data in $3{\times}3$ memory area. And we can detect the bad pixel and replace it with neighboring normal pixel value when we store a pixel in $3{\times}3$ memory area for filtering calculation. The experimental result proves that the proposed method is effective to implement the edge detection for auto focus in infrared camera.

• Korean Journal of Community Nutrition
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• v.20 no.1
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• pp.1-10
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• 2015

Objectives: This study was conducted to develop and validate Eating Behaviors Test form (EBT) for infants and young children, including eating behaviors of their parents and parental feeding practices. Methods: Draft version of EBT form was developed after a pretest on 83 mothers. It was consisted of 42 questions including 3 components; eating behavior of children, eating behavior of parents, and parental feeding practices. Using these questionnaires, the first survey was conducted on 320 infants and children, 1 to 6 year old, for exploratory factor analysis, and the second survey was collected on 731 infants and children for confirmatory factor analysis. Results: Exploratory factor analysis on 42 questions of EBT form resulted in 3 factor model for children's eating behavior, 3 factor model for parents' eating behavior, and 1 factor model for parental feeding practices. Three factors for children's eating behavior could be explained as follows; factor 1, pickiness (reliability ${\alpha}=0.89$; explanation of variance=27.79), factor 2, over activity (${\alpha}=0.80$, explanation of variance=16.51), and factor 3, irregularity (${\alpha}=0.59$, explanation of variance=10.01). Three factors for mother's eating behavior could be explained as follows; factor 1,irregularities (${\alpha}=0.73$, explanation of variance=21.73), factor 2, pickiness (${\alpha}=0.65$, explanation of variance= 20.16), and factor 3, permissiveness (${\alpha}=0.60$, explanation of variance=19.13). Confirmatory factor analysis confirmed an acceptance fit for these models. Internal consistencies for these factors were above 0.6. Conclusions: Our results indicated that EBT form is a valid tool to measure comprehensive eating and feeding behaviors for infants and young children.

• Asian-Australasian Journal of Animal Sciences
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• v.21 no.7
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• pp.923-927
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• 2008

The objective of this study was to compare random regression model and multiple trait animal model estimates of the (co) variance of total sperm cells over the active lifetime of AI boars. Data were provided by Smithfield Premium Genetics (Rose Hill, NC). Total number of records and animals for the random regression model were 19,629 and 1,736, respectively. Data for multiple trait animal model analyses were edited to include only records produced at 9, 12, 15, 18, 21, 24, and 27 months of age. For the multiple trait method estimates of genetic and residual variance for total sperm cells were heterogeneous among age classifications. When comparing multiple trait method to random regression, heritability estimates were similar except for total sperm cells at 24 months of age. The multiple trait method also resulted in higher estimates of heritability of total sperm cells at every age when compared to random regression results. Random regression analysis provided more detail with regard to changes of variance components with age. Random regression methods are the most appropriate to analyze semen traits as they are longitudinal data measured over the lifetime of boars.

• Journal of the Korean Society of Industry Convergence
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• v.10 no.4
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• pp.195-200
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• 2007

These days, various and complex threads are developed, so it is necessary to develop the cutting a thread sensors for checking a cut thread in severe environment and it is very important to evaluate the quality of the cutting a thread sensors. The analysis of variance(ANOVA) method is very useful method on the quality evaluation field. In this study, the quality is evaluated by one way layout ANOVA method with the surface roughness data. The experiment is carried out by 3 sensors and the result show that the sensors have the good quality in precision.