• 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.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.6
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• pp.821-826
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• 2013

When the values of design variables change, mode switching can often occur. If the mode of interest is not tracked, the frequencies and modes for design optimization may be miscalculated owing to modes that differ from the intended ones. Thus, mode tracking must be employed to identify the frequencies and modes of interest whenever the values of design variables change during optimization. Furthermore, reliability-based design optimization (RBDO) must be performed for design problems with design variables containing uncertainty. In this research, we perform RBDO considering the mode tracking of a compressive coil spring, i.e., a component of the joint spring that supports a compressor, with design variables containing uncertainty by using only kriging metamodels based on multiple responses approach (MRA) without existing mode tracking methods. The reliability analyses for RBDO are employed using kriging metamodel-based Monte Carlo simulation.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.2
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• pp.663-669
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• 2014

Background: With recent progress in health science administration, a huge amount of data has been collected from thousands of subjects. Statistical and computational techniques are very necessary to understand such data and to make valid scientific conclusions. The purpose of this paper was to develop a statistical probability model and to predict future survival times for male breast cancer patients who were diagnosed in the USA during 1973-2009. Materials and Methods: A random sample of 500 male patients was selected from the Surveillance Epidemiology and End Results (SEER) database. The survival times for the male patients were used to derive the statistical probability model. To measure the goodness of fit tests, the model building criterions: Akaike Information Criteria (AIC), Bayesian Information Criteria (BIC), and Deviance Information Criteria (DIC) were employed. A novel Bayesian method was used to derive the posterior density function for the parameters and the predictive inference for future survival times from the exponentiated Weibull model, assuming that the observed breast cancer survival data follow such type of model. The Markov chain Monte Carlo method was used to determine the inference for the parameters. Results: The summary results of certain demographic and socio-economic variables are reported. It was found that the exponentiated Weibull model fits the male survival data. Statistical inferences of the posterior parameters are presented. Mean predictive survival times, 95% predictive intervals, predictive skewness and kurtosis were obtained. Conclusions: The findings will hopefully be useful in treatment planning, healthcare resource allocation, and may motivate future research on breast cancer related survival issues.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.3C
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• pp.329-340
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• 2009

This paper proposes a novel code tracking scheme to track the fine code synchronization for BOC(pn,n) modulated spreading signals. The correlation function of BOC(pn,n) modulated spreading signals has been several peaks. In this paper, we observe that the correlation function in the advanced offset region remains almost unchanged, due to the multipath signals being received later than a line-of-sight signal. Based on this observation, we propose a novel code tracking scheme which is called the advanced region correlation (ARC) method for BOC(n,n) modulated spreading signals. And, we compare with the code tracking accuracy between the conventional and proposed methods in the static multipath and land mobile satellite system channels through the Monte-Carlo simulation. Then, base on the proposed scheme, we propose the generalized-ARC (ARC) scheme for BOC(pn, n) modulated spreading signals.

• Tunnel and Underground Space
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• v.25 no.2
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• pp.210-219
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• 2015

This paper describes a new quantitative process for evaluating the roughness of discontinuity, which is suggested as a qualitative criteria in RMR or Q-system. For this purpose, the Delphi method which is one of the surveying methods was introduced. The selected panels were asked to evaluate the roughness of discontinuities on the Web which was hosted by authors in advance. A total of 3 surveys were performed using JRCs suggested by Barton and Choubey as well as Ai generated by the Monte Carlo simulations. After each survey, the results were provided to all panels for comparing their decisions to others. As surveys proceeded, better consensus and convergence were achieved. With a good agreement of panels on roughness classification, the quantitative criteria for roughness of discontinuity in RMR and Q-system was established in this study.

• The Korean Journal of Applied Statistics
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• v.22 no.3
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• pp.443-461
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• 2009

In order to overcome the lack of Korean credit rating migration data, we consider an empirical Bayes procedure to estimate credit rating migration matrices. We derive the posterior probabilities of Korean credit rating transitions by utilizing the Moody's rating migration data and the credit rating assignments from Korean rating agency as prior information and likelihood, respectively. Metrics based upon the average transition probability are developed to characterize the migration matrices and compare our Bayesian migration matrices with some given matrices. Time series data for the metrics show that our Bayesian matrices are stable, while the matrices based on Korean data have large variation in time. The bootstrap tests demonstrate that the results from the three estimation methods are significantly different and the Bayesian matrices are more affected by Korean data than the Moody's data. Finally, Monte Carlo simulations for computing the values of a portfolio and its credit VaRs are performed to compare these migration matrices.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.9
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• pp.906-915
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• 2009

To study the plume effects in the vacuum area, the Direct Simulation Monte Carlo(DSMC) method is usually adopted because the plume field usually contains the entire range of flow regime from the near-continuum in the vicinity of nozzle exit through transitional state to free molecular at far field region from the nozzle. The objective of this study is to investigate the behaviors of a small monopropellant thruster plume in the vacuum area numerically using DSMC method. To deduce accurate results efficiently, the preconditioned scheme is introduced to calculate continuum flow fields inside thruster to predict nozzle exit properties used for inlet conditions of DSMC method. By combining these two methods, the vacuum flow characteristics of plume such as strong nonequilibrium near nozzle exit, large back flow area, etc, can be investigated.

• Communications for Statistical Applications and Methods
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• v.16 no.1
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• pp.115-125
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• 2009

Simultaneous equation models, which are widely used in business and economic areas, generally consist of endogenous variables determined within models and exogenous variables externally determined and in the simultaneous equations model framework there are rank and order conditions for the model identification and the existence of unique solutions. By contrast, their estimating results have less efficiencies and furthermore do not exist, since the most estimating procedures are performed under the assumptions for rank and order conditions. We propose the new statistical test for sufficiency of the rank condition under the order condition, and show the asymptotic properties for the test. The Monte Carlo simulation studies are achieved in order to evaluate its power and to suggest the baseline for satisfying the rank conditions.

• Proceedings of the Korean Vacuum Society Conference
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• 2011.08a
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• pp.312-312
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• 2011

In SiH4/H2 discharge for growth process of hydrogenated amorphous silicon (a-Si:H), silane polymers, produced by SiH2 + Sin-1H2n ${\rightarrow}$ SinH2n+2, have no reactivity on the film-growing surface. However, under the SiH2 rich condition, high silane reactive species (HSRS) can be produced by electron collision to silane polymers. HSRS, having relatively strong reactivity on the surface, can react with dangling bond and form Si-H2 networks which have a close correlation with photo-induced degradation of a-Si:H thin film solar cell [1]. To find contributions of suggested several external plasma conditions (pressure, frequency and ratio of mixture gas) [2,3] to suppressing productions of HSRS, some plasma characteristics are studied by numerical methods. For this study, a zero-dimensional global model for SiH4/H2 discharge and a one-dimensional particle-in-cell Monte-Carlo-collision model (PIC-MCC) for pure SiH4 discharge have been developed. Densities of important reactive species of SiH4/H2 discharge are observed by means of the global model, dealing 30 species and 136 reactions, and electron energy probability functions (EEPFs) of pure SiH4 discharge are obtained from the PIC-MCC model, containing 5 charged species and 15 reactions. Using global model, SiH2/SiH3 values were calculated when pressure and driving frequency vary from 0.1 Torr to 10 Torr, from 13.56 MHz to 60 MHz respectively and when the portion of hydrogen changes. Due to the limitation of global model, frequency effects can be explained by PIC-MCC model. Through PIC-MCC model for pure SiH4, EEPFs are obtained in the specific range responsible for forming SiH2 and SiH3: from 8.75 eV to 9.47 eV [4]. Through densities of reactive species and EEPFs, polymerization reactions and production of HSRS are discussed.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.4 no.2
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• pp.13-19
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• 2008

In order to predict a remaining life of a plant, it is necessary to select the components that are critical to the plant life. The remaining life of those components shall be evaluated by considering the aging effect of materials used as well as numerous factors. However, when evaluating reliability of nuclear structural components, some problems are quite formidable because of lack of information such as operating history, material property change and uncertainty in damage models. Accordingly, if structural integrity and safety are evaluated by the deterministic fracture mechanics approach, it is expected that the results obtained are too conservative to perform a rational evaluation of plant life. The probabilistic fracture mechanics approaches are regarded as appropriate methods to rationally evaluate the plant life since they can consider various uncertainties such as sizes and shapes of cracks and degradation of material strength due to the aging effects. The objective of this study is to evaluate the structural integrity for a reactor pressure vessel under the small break loss of coolant accident by applying the deterministic and probabilistic fracture mechanics. The deterministic fracture mechanics analysis was performed using the three dimensional finite element model. The probabilistic integrity analysis was based on the Monte Carlo simulation. The selected random variables are the neutron fluence on the vessel inside surface, the content of copper, nickel, and phosphorus in the reactor pressure vessel material, and initial RTNDT.