• Asian-Australasian Journal of Animal Sciences
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• v.8 no.5
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• pp.499-503
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• 1995

The performance records of 410 Holstein Friesian crossbred cows belonging to seven genetic groups (Fl, 3/4, 1/4, 5/8, 3/8, triple cross and miscellaneous cross) maintained at Livestock Production Research Institute, Bahadurnagar, Okara were analyzed for various parameters of lifetime traits. For the analysis 2 data sets were made. Data set I included all the cows disposed off from the herd which have completed at least one lactation while for data set II performance traits for only first five lactations were considered. The data was analyzed by Mixed Model Least squares and Maximum Likelihood computer programme PC-I version. The least squares means ${\times}$ standard errors for data set I (periods are in days and milk yield is in litres) were $994.5{\pm}15.5$, $1,877.0{\pm}70.9$, $1,651.9{\pm}19.3$, $2,533.7{\pm}36.5$, $3,530.0{\pm}40.5$, $15,785.2{\pm}320.0$, $8.46{\pm}0.19$, $5.66{\pm}0.16$ and $3.79{\pm}0.08$, respectively for age at first calving (APC), Ist lactation milk yield (FLMY), productive life (PL), herd life (HL), total life (TL), lifetime milk yield (LTMY), milk yield per day of productive life (MY/PL), milk yield per day of herd life (MY/HL) and milk yield per day of total life (MY/TL). For data set II these values were $1,004.2{\pm}21.2$, $2,220.5{\pm}113.1$, $1,429.1{\pm}40.8$, $2,302.1{\pm}73.3$, $3,307.2{\pm}77.3$, $13,189.7{\pm}667.4$, $9.10{\pm}0.34$, $5.66{\pm}0.25$ and $4.02{\pm}0.18$ in the same order. For data set I the effect of year of first calving was significant for AFC, FLMY, PL, HL, LTMY and MY/PL. The season of Ist calving was significant only for MY/PL. The effect of genetic group was significant for AFC, FLMY, MY/PL and MY/TL while the effect of parity was significant for all the traits. For data set II the effect of year of Ist calving was significant only for AFC, FLMY and PL while the season of Ist calving was significant for FLMY and PL while the effect of genetic groups was significant for MY/HL only. The lifetime production performance is in general close to the various estimates reported in the literature.

• Korean Journal of Agricultural Science
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• v.40 no.4
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• pp.339-345
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• 2013

The objective of this study was to establish genetic evaluation systems with carcass data collected by 68 individual farms from 2007 to 2011 in Pyeongchang area of Kangwon province. All the possible of environment effects were corrected by analysis of variance (ANOVA) to estimate more accurate genetic parameters. Heritabilities and genetic correlations were estimated from carcass data collected from Hanwoo steers(n=10,441) born in Pyeongchang region from 2005 to 2008. Traits evaluated included carcass weight (CWT), eye muscle area (EMA), back fat thickness (BF) and marbling score (MS). As for the mean value and standard deviation for carcass traits, CWT, EMA, BF and MS were 424.5, 92, 13.7 and 5.7. Parameters were estimated using a multiple trait animal model and derivative-free restricted maximum likelihood procedures. Estimated heritabilities for CWT, EMA, BF and MS were 0.30, 0.21, 0.42 and 0.42, respectively. Genetic correlation of CWT with EMA, BF and MS were estimated to 0.24, 0.36 and 0.07, respectively. Genetic correlation of EMA with BF and MS was -0.27 and 0.61, respectively.

• Journal of Applied Reliability
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• v.15 no.2
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• pp.90-100
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• 2015

Reliability growth rate (or reliability growth curve slope) have the two cases of trend as a constant or changing one during the reliability growth testing. The changing case is very common situation. The reasons of reliability growth rate changing are that the failures to follow the NHPP (None-Homogeneous Poisson Process), and the solutions implemented during test to break out other problems or not to take out all of the root cause permanently. If the changing were big, the "Goodness of Fit (GOF)" of reliability growth curve to test data would be very low and then reduce the accuracy of assessing result with test data. In this research, we are using Duane model and AMSAA model for assessing test data and projecting the reliability level of complex and repairable system as like construction equipment and vehicle. In case of no changing in reliability growth rate, it is reasonable for reliability engineer to implement the original Duane model (1964) and Crow-AMSAA model (1975) for the assessment and projection activity. However, in case of reliability growth rate changing, it is necessary to find the method to increase the "GOF" of reliability growth curves to test data. To increase GOF of reliability growth curves, it is necessary to find the proper parameter calculation method of interesting reliability growth models that are applicable to the situation of reliability growth rate changing. Since the Duane and AMSAA models have a characteristic to get more strong influence from the initial test (or failure) data than the latest one, the both models have a limitation to contain the latest test data information that is more important and better to assess test data in view of accuracy, especially when the reliability growth rate changing. The main objective of this research is to find the parameter calculation method to reflect the latest test data in the case of reliability growth rate changing. According to my experience in vehicle and construction equipment developments over 18 years, over the 90% in the total development cases are with such changing during the developing test. The objective of this research was to develop the newly assessing method and the process for GOF level increasing in case of reliability growth rate changing that would contribute to achieve more accurate assessing and projecting result. We also developed the new evaluation method for GOF that are applicable to the both models as Duane and AMSAA, so it is possible to compare it between models and check the effectiveness of new parameter calculation methods in any interesting situation. These research results can reduce the decision error for development process and business control with the accurately assessing and projecting result.

• Geophysics and Geophysical Exploration
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• v.21 no.1
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• pp.15-25
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• 2018

Seismic inversion is a high-resolution tool to delineate the subsurface structures which may contain oil or gas. On the other hand, marine controlled-source electromagnetic (mCSEM) inversion can be a direct tool to indicate hydrocarbon. Thus, the joint inversion using both EM and seismic data together not only reduces the uncertainties but also takes advantage of both data simultaneously. In this paper, we have developed a simultaneous joint inversion approach for the direct estimation of reservoir petrophysical parameters, by linking electromagnetic and seismic data through rock physics model. A cross-gradient constraint is used to enhance the resolution of the inversion image and the maximum likelihood principle is applied to the relative weighting factor which controls the balance between two disparate data. By applying the developed algorithm to the synthetic model simulating the simplified gas field, we could confirm that the high-resolution images of petrophysical parameters can be obtained. However, from the other test using the synthetic model simulating an anticline reservoir, we noticed that the joint inversion produced different images depending on the model constraint used. Therefore, we modified the algorithm which has different model weighting matrix depending on the type of model parameters. Smoothness constraint and Marquardt-Levenberg constraint were applied to the water-saturation and porosity, respectively. When the improved algorithm is applied to the anticline model again, reliable porosity and water-saturation of reservoir were obtained. The inversion results indicate that the developed joint inversion algorithm can be contributed to the calculation of the accurate oil and gas reserves directly.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1995.04a
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• pp.213-216
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• 1995

공사장의 건설기계 소음은 저주파 에너지를 많이 가지고 있기 때문에, 일단 소음이 발생되면 그 전파가 멀리까지 감쇄없이 진행하는 물리적 특징을 가지고 있으며 현실적으로 흡음재처리를 통한 소음방지효과는 저조한 실정이다. 특히, 선진국에서는 건설기계 등의 엄격한 소음 인증제도 실시로 인해 국내 일부 건설장비 생산제품이 외국에서 요구하는 소음규제치를 초과하기 때문에 저소음, 저진동 건설기계 설계 기술의 발전이 없으면, 향후 수출여건이 점차 어려워지고 있다. 이와같은 주변여건의 변화로 인해 건설기계를 생산하는 입체에서는 공사장 소음과 같은 저주파 에너지에 의해 지배 받는 소음문제를 효과적으로 저감시키기 위한 건설기계의 저소음, 저진동 설계의 필요성을 심각하게 인식하고 있는 실정이다. 건설기계중, 소음이 문제시되는 기계로는 지반정지공사, 기초공사, 콘크리트공사, 포장공사, 파괴 및 해체공사와 기타등 6가지가 있다. 이중에서 환경연구원의 연구결과에 따르면, 항타기, 브레이커 및 착암기가 높은 소음도를 나타내고 있다. 가장 높은 소음을 배출하고 있는 항타기는 기초 공사에 쓰이는 것으로써 지반 천공후 H빔을 싣는 디젤 항타기의 경우, 소음도가 107dBA를 보여주고 있다. 이 값은 기계로부터 7m 떨어진 거리에서 측정된 값이다. 또, 파괴 및 해제공사에 쓰이는 브레이커는 98dBA의 소음도를 보여주고 있다. 착암기는 작용원리에 따라 91-96dBA의 소음을 배출하고 있다. 본 연구에서는 건설기계중 소음이 높아 문제시 되고 있는 유압 브레이커의 저소음 설계기술개발에 관한 내용이다. 저소음 브레이커의 개발을 위해 소음에너지의 전달경로를 검토하고, 현실성있는 소음방지 대책을 제시하였다. 연구결과, 브레이커의 설계개량을 통해, 10dB의 소음저감효과를 볼 수 있어 만족스러운 결과를 도출할 수 있었다.타를 처리하기에는 부적절한 방법임이 널리 알려진 사실이다[3]. 최근에 Ben Mrad와 Fassois[4]는 신호에 잡음이 존재하여도 이를 잘 처리할 수 있는 확률적(stochastic) 방법을 개발하여 기존의 결정적 방법들과 그 결과를 비교하였다. 그러나, 개발된 방법은 응답 신호에 백색잡음(white noise)이 섞이는 특수한 경우에만 사용할 수 있게 만들어져서 이 방법의 실질적인 적용에는 어려움이 있다. 본 연구에서는 기존의 방법들의 단점을 극복할 수 있는 새로운 회귀적 모우드 변수 규명 방법을 개발하였다. 이는 Fassois와 Lee가 ARMAX모델의 계수를 효율적으로 추정하기 위하여 개발한 뱉치방법인 Suboptimum Maximum Likelihood 방법[5]를 기초로 하여 개발하였다. 개발된 방법의 장점은 응답 신호에 유색잡음이 존재하여도 모우드 변수들을 항상 정확하게 구할 수 있으며, 또한 알고리즘의 안정성이 보장된 것이다.. 여기서는 실험실 수준의 평 판모델을 제작하고 실제 현장에서 이루어질 수 있는 진동제어 구조물에 대 한 동적실험 및 FRS를 수행하는 과정과 동일하게 따름으로써 실제 발생할 수 있는 오차나 error를 실험실내의 차원에서 파악하여 진동원을 있는 구조 물에 대한 진동제어기술을 보유하고자 한다. 이용한 해마의 부피측정은 해마경화증 환자의 진단에 있어 육안적인 MR 진단이 어려운 제한된 경우에만 실제적 도움을 줄 수 있는 보조적인 방법으로 생각된다.ofile whereas relaxivity at high field is not affected by τS. On the other hand, the change in τV does not affect low field profile but strongly in fluences on both inflection

• Asian-Australasian Journal of Animal Sciences
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• v.29 no.9
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• pp.1222-1228
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• 2016

The objective of this research was to estimate genetic parameters and trends for length of productive life (LPL), lifetime number of piglets born alive (LBA), lifetime number of piglets weaned (LPW), lifetime litter birth weight (LBW), and lifetime litter weaning weight (LWW) in a commercial swine farm in Northern Thailand. Data were gathered during a 24-year period from July 1989 to August 2013. A total of 3,109 phenotypic records from 2,271 Landrace (L) and 838 Yorkshire sows (Y) were analyzed. Variance and covariance components, heritabilities and correlations were estimated using an Average Information Restricted Maximum Likelihood (AIREML) procedure. The 5-trait animal model contained the fixed effects of first farrowing year-season, breed group, and age at first farrowing. Random effects were sow and residual. Estimates of heritabilities were medium for all five traits ($0.17{\pm}0.04$ for LPL and LBA to $0.20{\pm}0.04$ for LPW). Genetic correlations among these traits were high, positive, and favorable (p<0.05), ranging from $0.93{\pm}0.02$ (LPL-LWW) to $0.99{\pm}0.02$ (LPL-LPW). Sow genetic trends were non-significant for LPL and all lifetime production traits. Sire genetic trends were negative and significant for LPL ($-2.54{\pm}0.65d/yr$; p = 0.0007), LBA ($-0.12{\pm}0.04piglets/yr$; p = 0.0073), LPW ($-0.14{\pm}0.04piglets/yr$; p = 0.0037), LBW ($-0.13{\pm}0.06kg/yr$; p = 0.0487), and LWW ($-0.69{\pm}0.31kg/yr$; p = 0.0365). Dam genetic trends were positive, small and significant for all traits ($1.04{\pm}0.42d/yr$ for LPL, p = 0.0217; $0.16{\pm}0.03piglets/yr$ for LBA, p<0.0001; $0.12{\pm}0.03piglets/yr$ for LPW, p = 0.0002; $0.29{\pm}0.04kg/yr$ for LBW, p<0.0001 and $1.23{\pm}0.19kg/yr$ for LWW, p<0.0001). Thus, the selection program in this commercial herd managed to improve both LPL and lifetime productive traits in sires and dams. It was ineffective to improve LPL and lifetime productive traits in sows.

• Asian-Australasian Journal of Animal Sciences
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• v.22 no.4
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• pp.459-464
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• 2009

Data and pedigree information for Lori-Bakhtiari sheep used in this study were 6,239 records of lamb mortality from 246 sires and 1,721 dams, collected from 1989 through 2007 from a Lori-Bakhtiari flock at Shooli station in Shahrekord. The traits investigated were cumulative lamb mortality from birth up to 7 days, up to 14 days, up to 21 days, and up to 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 and 12 months of age. The models included fixed factors that had significant effects and random direct genetic, maternal genetic and maternal permanent environmental effects. Variance components were estimated using the restricted maximum likelihood procedure applying three animal models with and without maternal and common environmental effects. The overall mean of cumulative lamb mortality rate was 22.95% from birth to 1 year of age, while the overall mortality rate up to 3 and from 3 to 6 months of age was 6.14% and 12.76%, respectively. The mortality rate after 6 months of age declined as the lambs grew older. The age of dam had no important effect on lamb mortality. The type of birth was more important during the preweaning period than at later ages, and lamb mortality rate was higher in twins. The year of birth, month of birth and sex of lamb significantly (p${\leq}$0.01) affected the cumulative lamb mortality rate at all ages. The least square mean of mortality during the final one-third of the lambing period was higher than the first and middle onethird of the lambing period. Male lambs were found to be at a higher risk of mortality than females. Birth weight of the lamb had a highly significant (p${\leq}$0.01) effect on lamb mortality at all ages as a quadratic regression. Direct and maternal heritability estimates of lamb mortality ranged from 0.01 to 0.13 and 0.01 to 0.05, respectively. Direct heritability increased with age of lamb, while maternal effects (genetic and common environmental) were important in the preweaning period. These results indicate that lamb mortality can be reduced first through farm management practices and secondly by genetic selection. Both animal and maternal effects should be considered in breeding programmes for reducing lamb mortality at preweaning.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.10
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• pp.1558-1565
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• 2020

Objective: The objective of this study was to characterize the number of loci affecting growth traits and the distribution of single nucleotide polymorphism (SNP) effects on growth traits, and to understand the genetic architecture for growth traits in Hanwoo (Korean cattle) using genome-wide association study (GWAS), genomic partitioning, and hierarchical Bayesian mixture models. Methods: GWAS: A single-marker regression-based mixed model was used to test the association between SNPs and causal variants. A genotype relationship matrix was fitted as a random effect in this linear mixed model to correct the genetic structure of a sire family. Genomic restricted maximum likelihood and BayesR: A priori information included setting the fixed additive genetic variance to a pre-specified value; the first mixture component was set to zero, the second to 0.0001×σ²_g, the third 0.001×σ²_g, and the fourth to 0.01×σ²_g. BayesR fixed a priori information was not more than 1% of the genetic variance for each of the SNPs affecting the mixed distribution. Results: The GWAS revealed common genomic regions of 2 Mb on bovine chromosome 14 (BTA14) and 3 had a moderate effect that may contain causal variants for body weight at 6, 12, 18, and 24 months. This genomic region explained approximately 10% of the variance against total additive genetic variance and body weight heritability at 12, 18, and 24 months. BayesR identified the exact genomic region containing causal SNPs on BTA14, 3, and 22. However, the genetic variance explained by each chromosome or SNP was estimated to be very small compared to the total additive genetic variance. Causal SNPs for growth trait on BTA14 explained only 0.04% to 0.5% of the genetic variance Conclusion: Segregating mutations have a moderate effect on BTA14, 3, and 19; many other loci with small effects on growth traits at different ages were also identified.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.3 no.2
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• pp.127-135
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• 1983

A new approach is developed to analyze the reliability of the earth retaining wall using the concept of probability of failure, instead of conventional factor of safety. Many uncertainties, which are included in the conventional stability analysis, can be excluded by using the stochastic approach. And the reliability, more consistent with the reality, can be obtained by the simulation. The strength parameters of soil properties are assumed to be random variables to follow a generalized beta distribution. The interval [A, B] of the random variables could be determined using the maximum likelihood estimation. The pseudo-random values corresponding to the proposed beta distribution are generated using the rejection method. The probability of failure defined as follows, is obtained by using the Monte Carlo Method. $$P_f=\frac{M}{N}$$ where, $P_f$ : Probability of failure N : Total number of trials M : Total number of failure out of N A computer program is developed for the computation procedure mentioned above. Finally, a numerical example is solved using the developed program.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.4 no.3
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• pp.75-83
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• 1984

The probability of failure is used to analyze the reliability of three dimensional slope failure, instead of conventional factor of safety. The strength parameters are assumed to be normal variated and beta variated. These are interval estimated under the specified confidence level and maximum likelihood estimation. The pseudonormal and beta random variables are generated using the uniform probability transformation method according to central limit theorem and rejection method. By means of a Monte-Carlo Simulation, the probability of failure is defined as; $P_f=M/N$ N: Total number of trials M: Total number of failures Some of the conclusions derived. from the case study include; 1. Three dimensional factors of safety are generally much higher than 2-D factors of safety. However situations appear to exist where the 3-D factor of safety can be lower than the 2-D factor of safety. 2. The $F_3/F_2$ ratio appears to be quite sensitive to c and ${\phi}$ and to the shape of the 3-D shear surface and the slope but not to be to the unit weight of soil. 3. From the two models (normal, beta) considered for the distribution of the factor of safety, the beta distribution generally provides lager than normal distribution. 4. Results obtained using the beta and normal models are presented in a nomgraph relating slope height and slop angle to probability of failure.