• Nuclear Engineering and Technology
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• v.52 no.4
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• pp.811-818
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• 2020

Y-containing CLAM steels were melted via vacuum induction melting and electroslag remelting. In this study, the evolution, microstructure, and mechanical properties of the alloy inclusions (ESR-1 (0 wt.% Y), ESR-2 (0.016 wt.% Y) and ESR-3 (0.042 wt.% Y)) were investigated. Further, the number of inclusions in ESRed steel was observed to obviously decrease, and the distributions were more uniform. The fine Y-Al-O inclusions (1-2 ㎛) were the main inclusions in ESR-2. The addition of Y affected the prior austenite grain size (PAGZ), increasing the tensile strength at test temperature. Low ductile-brittle transition temperature (DBTT) was obtained because of the fine PAGZ and dispersive inclusions. For the ESRed CLAM steel with 0.016 wt.% Y, the yield strengths were 621 MPa at 20 ℃ and 354 MPa at 600 ℃ in air. Further, the uniform elongation and elongation of the ESR-2 alloy were 5.5% and 20.1% at 20 ℃, respectively. Meanwhile, the DBTT tested using full-size Charpy impact specimen (55 cm × 10 cm × 10 cm) was reduced to -83 ℃.

• Asian-Australasian Journal of Animal Sciences
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• v.14 no.8
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• pp.1051-1056
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• 2001

Data for teat number for Landrace (L), Yorkshire (Y), crossbred of Landrace and Yorkshire (LY), and crossbred of Landrace, Yorkshire and Chinese indigenous Min Pig (LYM) were analyzed using Gibbs sampling. In Bayesian inference, flat priors and some informative priors were used to examine their influence on posterior estimates. The posterior mean estimates of heritabilities with flat priors were $0.661{\pm}0.035$ for L, $0.540{\pm}0.072$ for Y, $0.789{\pm}0.074$ for LY, and $0.577{\pm}0.058$ for LYM, and they did not differ (p>0.05) from their corresponding estimates of REML. When inverse Gamma densities for variance components were used as priors with the shape parameter of 4, the posterior estimates were still corresponding (p>0.05) to REML estimates and mean estimates using Gibbs sampling with flat priors. However, when the inverse Gamma densities with the shape parameter of 10 were utilized, some posterior estimates differed (p<0.10) from REML estimates and/or from other Gibbs mean estimates. The use of moderate degree of belief was influential to the posterior estimates, especially for Y and for LY where data sizes were small. When the data size is small, REML estimates of variance components have unknown distributions. On the other hand, Bayesian approach gives exact posterior densities of variance components. However, when the data size is small and prior knowledge is lacked, researchers should be careful with even moderate priors.

• The Korean Journal of Physiology and Pharmacology
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• v.4 no.6
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• pp.497-506
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• 2000

In this work, GLUTs phosphorylations by a downstream effector of PI3-kinase, $PKC-{\zeta},$ were studied, and GLUT4 phosphorylation was compared with GLUT2 phosphorylation in relation to the translocation mechanism. Prior to phosphorylation experiment, $PKC-{\zeta}$ kinase activity was determined as $20.76{\pm}4.09$ pmoles Pi/min/25 ng enzymes. GLUT4 was phosphorylated by $PKC-{\zeta}$ and the phosphorylation was increased on the vesicles immunoadsorpted from LDM and on GLUT4 immunoprecipitated from GLUT4- contianing vesicles of adipocytes treated with insulin. However, GLUT2 in hepatocytes was neither phosphorylated by $PKC-{\zeta}$ nor changed in response to insulin treatment. It was confirmed by measuring the subcellular distribution of GLUT2 based on GLUT2 immunoblot density among the four membrane fractions before and after insulin treatment. Total GLUT2 distributions at PM, LYSO, HDM and LDM were $37.7{\pm}12.0%,\;42.4{\pm}12.1%,\;19.2{\pm}5.0%\;and\;0.7{\pm}1.2%$ in the absence of insulin. Total GLUT2 distribution in the presence of insulin was almost same as that in the absence of insulin. Present data with previous findings suggest that GLUT4 translocation may be attributed to GLUT4 phosphorylation by $PKC-{\zeta}$ but GLUT2 does not translocate because GLUT2 is not phosphorylated by the kinase. Therefore, GLUT phosphorylation may be required in GLUT translocation mechanism.

• Journal of Korean Society for Atmospheric Environment
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• v.15 no.5
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• pp.657-665
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• 1999

Particulate matter produced by diesel engines is of concern to cngine manufactures because of its environmental impact. The majority of diesel particles are in the range of smaller than 1 ${\mu}{\textrm}{m}$. Because of their tiny volume, ultrafine diesel particles contribute very little to the total mass concentration which is currently regulated for automobile emissions. Ultrafinc particles are known to have deleterious effects upon human health cspecially because they penetrate deeply human respiratory tract and have negative effects on the health. In this study, the engine exhaust gas was diluted in a dilution tunnel and the particle size distribution was measured using the scanning mobility particel sizer system. Measurements of the number and the mass concentrations of the diesel exhaust were made under different engine ooperating conditions. The dilution sampling system provided a common basis for collection of the exhaust by cooling and diluting the source emission prior to the measurement. The measurement results showed that the particle size distributions of the exhaust from the diesel vehicles equipment with either heavy-duty or lignt-duty diesel engines, were similar in the particle size range of 0.08~0.2${\mu}{\textrm}{m}$.

• Journal of Advanced Marine Engineering and Technology
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• v.31 no.4
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• pp.401-409
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• 2007

Because of the various excellent characteristics of cast basalt materials. such as, anti-corrosion, anti-wearing, good hardness. high chemical stability, of which steel may not possess, the steel-basalt composite pipes are used in severe environments for compensating the defects of steel. However. without sufficient mechanical investigation prior to application. the basalt liners in steel-basalt composite pipes may be cracked and broken or the basalt liners are omitted from steel pipes in applications. In these cases, the merits of basalt materials may disappear and the basalt liners may not play their good roles as expected. Therefore, it is required that mechanical behavior of steel-basalt composite pipes and surrounding environments be fully examined before installation. The limit of bending moment with which steel-basalt composite pipe may safely endure is calculated and the limit curvature of the composite pipe in the safe range is presented in this paper. The temperature distributions and the thermal stresses are also computed and the limit difference of temperatures between inner and outer side of composite pipe is given together.

• Journal of Environmental Science International
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• v.27 no.7
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• pp.499-507
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• 2018

Agricultural meteorological information is an important resource that affects farmers' income, food security, and agricultural conditions. Thus, such data are used in various fields that are responsible for planning, enforcing, and evaluating agricultural policies. The meteorological information obtained from automatic weather observation systems operated by rural development agencies contains missing values owing to temporary mechanical or communication deficiencies. It is known that missing values lead to reduction in the reliability and validity of the model. In this study, the hierarchical Bayesian spatio-temporal model suggests replacements for missing values because the meteorological information includes spatio-temporal correlation. The prior distribution is very important in the Bayesian approach. However, we found a problem where the spatial decay parameter was not converged through the trace plot. A suitable spatial decay parameter, estimated on the bias of root-mean-square error (RMSE), which was determined to be the difference between the predicted and observed values. The latitude, longitude, and altitude were considered as covariates. The estimated spatial decay parameters were 0.041 and 0.039, for the spatio-temporal model with latitude and longitude and for latitude, longitude, and altitude, respectively. The posterior distributions were stable after the spatial decay parameter was fixed. root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and bias were calculated for model validation. Finally, the missing values were generated using the independent Gaussian process model.

• Journal of KIISE:Computer Systems and Theory
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• v.28 no.9
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• pp.434-441
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• 2001

The concept of network memory was introduced for the efficient exploitation of main memory in a cluster. Network memory can be used to speed up applications that frequently access large amount of disk data. In this paper, we present a memory a management algorithm that does not require prior knowledge of access patterns and that is practical to implement under the web server cluster, In addition, our scheme has a good user response time for various access distributions of web documents. Through a detailed simulation, we evaluate the performance of our memory managment algorithms.

• Fisheries and Aquatic Sciences
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• v.24 no.4
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• pp.139-152
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• 2021

The main purpose of this study is to fit catch-per-unit-effort (CPUE) data about Korea chub mackerel (Scomber japonicus) stock with a state-space production (SSP) model, and to provide stock assessment results. We chose a surplus production model for the chub mackerel data, namely annual yield and CPUE. Then we employed a state-space layer for a production model to consider two sources of variability arising from unmodelled factors (process error) and noise in the data (observation error). We implemented the model via script software ADMB-RE because it reduces the computational cost of high-dimensional integration and provides Markov Chain Monte Carlo sampling, which is required for Bayesian approaches. To stabilize the numerical optimization, we considered prior distributions for model parameters. Applying the SSP model to data collected from commercial fisheries from 1999 to 2017, we estimated model parameters and management references, as well as uncertainties for the estimates. We also applied various production models and showed parameter estimates and goodness of fit statistics to compare the model performance. This study presents two significant findings. First, we concluded that the stock has been overexploited in terms of harvest rate from 1999 to 2017. Second, we suggest a SSP model for the smallest goodness of fit statistics among several production models, especially for fitting CPUE data with fluctuations.

• Structural Engineering and Mechanics
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• v.81 no.1
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• pp.103-115
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• 2022

The prediction error variances for frequencies are usually considered as unknown in the Bayesian system identification process. However, the error variances for mode shapes are taken as known to reduce the dimension of an identification problem. The present study attempts to explore the effectiveness of Bayesian approach of model parameters updating using Markov Chain Monte Carlo (MCMC) technique considering the prediction error variances for both the frequencies and mode shapes. To remove the ergodicity of Markov Chain, the posterior distribution is obtained by Gaussian Random walk over the proposal distribution. The prior distributions of prediction error variances of modal evidences are implemented through inverse gamma distribution to assess the effectiveness of estimation of posterior values of model parameters. The issue of incomplete data that makes the problem ill-conditioned and the associated singularity problem is prudently dealt in by adopting a regularization technique. The proposed approach is demonstrated numerically by considering an eight-storey frame model with both complete and incomplete modal data sets. Further, to study the effectiveness of the proposed approach, a comparative study with regard to accuracy and computational efficacy of the proposed approach is made with the Sequential Monte Carlo approach of model parameter updating.

• Korea Trade Review
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• v.45 no.3
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• pp.55-69
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• 2020

This study examines the research trends and knowledge structure of international trade studies using topic modeling method, which is one of the main methodologies of text mining. We collected and analyzed English abstracts of 1,868 papers of three Korean major journals in the area of international trade from 2003 to 2019. We used the Latent Dirichlet Allocation(LDA), an unsupervised machine learning algorithm to extract the latent topics from the large quantity of research abstracts. 20 topics are identified without any prior human judgement. The topics reveal topographical maps of research in international trade and are representative and meaningful in the sense that most of them correspond to previously established sub-topics in trade studies. Then we conducted a regression analysis on the document-topic distributions generated by LDA to identify hot and cold topics. We discovered 2 hot topics(internationalization capacity and performance of export companies, economic effect of trade) and 2 cold topics(exchange rate and current account, trade finance). Trade studies are characterized as a interdisciplinary study of three agendas(i.e. international economy, International Business, trade practice), and 20 topics identified can be grouped into these 3 agendas. From the estimated results of the study, we find that the Korean government's active pursuit of FTA and consequent necessity of capacity building in Korean export firms lie behind the popularity of topic selection by the Korean researchers in the area of int'l trade.