• Asian-Australasian Journal of Animal Sciences
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• 제26권9호
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• pp.1237-1246
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• 2013

The objective of this study was to estimate variance components and genetic parameters for lactation milk yield (LY), lactation length (LL), average milk yield per day (YD), initial milk yield (IY), peak milk yield (PY), days to peak (DP) and parameters (ln(a) and c) of the modified incomplete gamma function (MIG) in an Ethiopian multibreed dairy cattle population. The dataset was composed of 5,507 lactation records collected from 1,639 cows in three locations (Bako, Debre Zeit and Holetta) in Ethiopia from 1977 to 2010. Parameters for MIG were obtained from regression analysis of monthly test-day milk data on days in milk. The cows were purebred (Bos indicus) Boran (B) and Horro (H) and their crosses with different fractions of Friesian (F), Jersey (J) and Simmental (S). There were 23 breed groups (B, H, and their crossbreds with F, J, and S) in the population. Fixed and mixed models were used to analyse the data. The fixed model considered herd-year-season, parity and breed group as fixed effects, and residual as random. The single and two-traits mixed animal repeatability models, considered the fixed effects of herd-year-season and parity subclasses, breed as a function of cow H, F, J, and S breed fractions and general heterosis as a function of heterozygosity, and the random additive animal, permanent environment, and residual effects. For the analysis of LY, LL was added as a fixed covariate to all models. Variance components and genetic parameters were estimated using average information restricted maximum likelihood procedures. The results indicated that all traits were affected (p<0.001) by the considered fixed effects. High grade $B{\times}F$ cows (3/16B 13/16F) had the highest least squares means (LSM) for LY ($2,490{\pm}178.9kg$), IY ($10.5{\pm}0.8kg$), PY ($12.7{\pm}0.9kg$), YD ($7.6{\pm}0.55kg$) and LL ($361.4{\pm}31.2d$), while B cows had the lowest LSM values for these traits. The LSM of LY, IY, YD, and PY tended to increase from the first to the fifth parity. Single-trait analyses yielded low heritability ($0.03{\pm}0.03$ and $0.08{\pm}0.02$) and repeatability ($0.14{\pm}0.01$ to $0.24{\pm}0.02$) estimates for LL, DP and parameter c. Medium heritability ($0.21{\pm}0.03$ to $0.33{\pm}0.04$) and repeatability ($0.27{\pm}0.02$ to $0.53{\pm}0.01$) estimates were obtained for LY, IY, PY, YD and ln(a). Genetic correlations between LY, IY, PY, YD, ln(a), and LL ranged from 0.59 to 0.99. Spearman's rank correlations between sire estimated breeding values for LY, LL, IY, PY, YD, ln(a) and c were positive (0.67 to 0.99, p<0.001). These results suggested that selection for IY, PY, YD, or LY would genetically improve lactation milk yield in this Ethiopian dairy cattle population.

• KSCE Journal of Civil and Environmental Engineering Research
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• 제8권2호
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• pp.109-116
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• 1988

The strength and load of structure are varied with the Passage of time, and become a process of probability. It is possible to estimate the reliability from the relation between strength and load. Considering the safety, It is reasonable to estimate allowable stress from the safety factor based on the reliability. In this study, the method to estimate probability of fracture, which is index of reliability for rail subjeict to long term fatigue load were examined. In estimation of reliablity it is meaningless to evaluate numerical value especially this difficult case estimating parameter of random variable. To overcome this problem, conventional design method estimating relative reliability were proposed. In this study the Cornell method were examined. The uncertainity of random variale, ie coefficient of variation which is the index of variation of strength and load were considered. The effect of uncertainity related to probability of fracture, and safety factor based on reliability were examined. The results of this study are followed. The reliability of weld metal were influenced by variation of strength more then load, and base metal were influenced by load. It is confirmed that the allowable stress range calculating with factor of safety based an reliability is conservative.

• Journal of Korean Society of Coastal and Ocean Engineers
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• 제19권2호
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• pp.105-112
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• 2007

Sediment transport model based on the Lagrangian concept considering the grain size distribution(GSD) was setup and the change of the sediment diffusion range was analysed in the condition of considering and not considering the GSD. The GSD curve is assumed as the Log-normal distribution function in order to consider the GSD with respect to the Lagrangian concept and the random numbers, i.e. sediment particles, are generated based on the distribution function. The sediment particles is assumed as the spherical type and the random numbers based on the sediment weight is converted to the sediment diameters. Sediment transport patterns are analysed by the settling simulation, in which the settling velocity is computed by the van Rijn formulae and the horizontal diffusion coefficient is used as the constant parameter. The diffusion patterns are very similar to the patterns with GSD condition. The diffusion range defined as the range including 90%, 99% sediment weight of the total sediment weight, however, is larger than without considering GSD condition in 90%-option and shorter than with considering GSD condition in 99-option, respectively. The diffusion range is defined as tile p-percentage of the cumulative sediment weight region with reference to the 50% region, 90%- option, 99%-option, respectively.

• Current Optics and Photonics
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• 제1권2호
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• pp.107-112
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• 2017

An adaptive optics system can be simulated or analyzed to predict its closed-loop performance. However, this type of prediction based on various assumptions can occasionally produce outcomes which are far from actual experience. Thus, every adaptive optics system is desired to be tested in a closed loop on an optical test bench before its application to a telescope. In the close-loop test bench, we need an atmospheric simulator that simulates atmospheric disturbances, mostly in phase, in terms of spatial and temporal behavior. We report the development of an atmospheric turbulence simulator consisting of two point sources, a commercially available deformable mirror with a $12{\times}12$ actuator array, and two random phase plates. The simulator generates an atmospherically distorted single or binary star with varying stellar magnitudes and angular separations. We conduct a simulation of a binary star by optically combining two point sources mounted on independent precision stages. The light intensity of each source (an LED with a pin hole) is adjustable to the corresponding stellar magnitude, while its angular separation is precisely adjusted by moving the corresponding stage. First, the atmospheric phase disturbance at a single instance, i.e., a phase screen, is generated via a computer simulation based on the thin-layer Kolmogorov atmospheric model and its temporal evolution is predicted based on the frozen flow hypothesis. The deformable mirror is then continuously best-fitted to the time-sequenced phase screens based on the least square method. Similarly, we also implement another simulation by rotating two random phase plates which were manufactured to have atmospheric-disturbance-like residual aberrations. This later method is limited in its ability to simulate atmospheric disturbances, but it is easy and inexpensive to implement. With these two methods, individually or in unison, we can simulate typical atmospheric disturbances observed at the Bohyun Observatory in South Korea, which corresponds to an area from 7 to 15 cm with regard to the Fried parameter at a telescope pupil plane of 500 nm.

• The Journal of Dong Guk Oriental Medicine
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• 제8권1호
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• pp.107-116
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• 1999

The effects of Sosokmyung-tang(小續命湯) on global cerebral ischemia and cerebral in farction by MCA(middle cerebral artery) occlusion were evaluated in this study. This study was performed to investigate that Sosokmyung-tang would be useful for cerebrovascular diseases. In the case of global cerebral ischemia, ICR mice were used and divided into three group at random. Control group was treated after oral administration of normal saline, experimental group was treated after oral administration of 10.4mg/20g/day of Sosokmyung-tang extract. The multiple parameter of global cerebral ischemia included the duration of coma of KCN(potassium cyanide)-injected(1.2mg/kg, i.v) group and the survival time of KCN-injected(3.0mg/kg, i.v) group. In the case of cerebral infarction by MCA occlusion, Sprague-Dawley rats were used and divided into three group at random. Control group was given nothing before MCA occlusion, experimental group was given 157.2mg/250g/day of Sosokrnyung-tang extract before MCA occlusion. We investigated edema and ischemic ratio in 8 slices of rats' brain after MCA occlusion. The results were obtained as follows : 1. Sosokrnyung-tang significantly shortened the duration of coma of KCN-injected(1.2mg/kg,i.v) group and lengthened the survival time of KCN-injected(3.0mg/kg, i.v) group. 2. Sosokmyung-tang significantly decreased cerebral edema and ischemic ratio in rats after MCA occlusion. From the above results, it was concluded that Sosokmyung-tang can be effectively applied to cerebrovascular diseases.

• Journal of Broadcast Engineering
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• 제24권3호
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• pp.463-471
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• 2019

This paper proposes a method for reducing the complexity of LIC (Local Illuminance Compensation) for bi-directional inter prediction. The LIC performs local illumination compensation using neighboring reconstruction samples of the current block and the reference block to improve the accuracy of the inter prediction. Since the weight and offset required for local illumination compensation are calculated at both sides of the encoder and decoder using the reconstructed samples, there is an advantage that the coding efficiency is improved without signaling any information. Since the weight and the offset are obtained in the encoding prediction step and the decoding step, encoder and decoder complexity are increased. This paper proposes two methods for low complexity LIC. The first method is a method of applying illumination compensation with offset only in bi-directional prediction, and the second is a method of applying LIC after weighted average step of reference block obtained by bidirectional prediction. To evaluate the performance of the proposed method, BD-rate is compared with BMS-2.0.1 using B, C, and D classes of MPEG standard experimental image under RA (Random Access) condition. Experimental results show that the proposed method reduces the average of 0.29%, 0.23%, 0.04% for Y, U, and V in terms of BD-rate performance compared to BMS-2.0.1 and encoding/decoding time is almost same. Although the BD-rate was lost, the calculation complexity of the LIC was greatly reduced as the multiplication operation was removed and the addition operation was halved in the LIC parameter derivation process.

• Journal of Korean Society of Forest Science
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• 제111권4호
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• pp.603-612
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• 2022

The study aims were to evaluate a machine-learning, algorithm-based, forest biomass-estimation model to estimate subnational forest biomass and to comparatively analyze REDD+ forest reference emission levels. Time-series Landsat satellite imagery and ESA Biomass Climate Change Initiative information were used to build a machine-learning-based biomass estimation model. The k-nearest neighbors algorithm (kNN), which is a non-parametric learning model, and the tree-based random forest (RF) model were applied to the machine-learning algorithm, and the estimated biomasses were compared with the forest reference emission levels (FREL) data, which was provided by the Paraguayan government. The root mean square error (RMSE), which was the optimum parameter of the kNN model, was 35.9, and the RMSE of the RF model was lower at 34.41, showing that the RF model was superior. As a result of separately using the FREL, kNN, and RF methods to set the reference emission levels, the gradient was set to approximately -33,000 tons, -253,000 tons, and -92,000 tons, respectively. These results showed that the machine learning-based estimation model was more suitable than the existing methods for setting reference emission levels.

• Journal of the Earthquake Engineering Society of Korea
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• 제26권5호
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• pp.191-202
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• 2022

Markov envelope as a theoretical solution of the parabolic wave equation with Markov approximation for the von Kármán type random medium is studied and approximated with the convolution of two probability density functions (pdf) of normal and gamma distributions considering the previous studies on the applications of Radiative Transfer Theory (RTT) and the analysis results of earthquake records. Through the approximation with gamma pdf, the constant shape parameter of 2 was determined regardless of the source distance r_o. This finding means that the scattering process has the property of an inhomogeneous single-scattering Poisson process, unlike the previous studies, which resulted in a homogeneous multiple-scattering Poisson process. Approximated Markov envelope can be treated as the normalized mean square (MS) envelope for ground acceleration because of the flat source Fourier spectrum. Based on such characteristics, the path duration is estimated from the approximated MS envelope and compared to the empirical formula derived by Boore and Thompson. The results clearly show that the path duration increases proportionately to r_o^1/2-r_o², and the peak value of the RMS envelope is attenuated by exp (-0.0033r_o), excluding the geometrical attenuation. The attenuation slope for r_o≤100 km is quite similar to that of effective attenuation for shallow crustal earthquakes, and it may be difficult to distinguish the contribution of intrinsic attenuation from effective attenuation. Slowly varying dispersive delay, also called the medium effect, represented by regular pdf, governs the path duration for the source distance shorter than 100 km. Moreover, the diffraction term, also called the distance effect because of scattering, fully controls the path duration beyond the source distance of 300 km and has a steep gradient compared to the medium effect. Source distance 100-300 km is a transition range of the path duration governing effect from random medium to distance. This means that the scattering may not be the prime cause of peak attenuation and envelope broadening for the source distance of less than 200 km. Furthermore, it is also shown that normal distribution is appropriate for the probability distribution of phase difference, as asserted in the previous studies.

• Advanced Industrial SCIence
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• 제3권2호
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• pp.8-16
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• 2024

This paper shows the system of drug classification, the goal of this is to foretell the apt drug for the patients based on their demographic and physiological traits. The dataset consists of various attributes like Age, Sex, BP (Blood Pressure), Cholesterol Level, and Na_to_K (Sodium to Potassium ratio), with the objective to determine the kind of drug being given. The models used in this paper are K-Nearest Neighbors (KNN), Logistic Regression and Random Forest. Further to fine-tune hyper parameters using 5-fold cross-validation, GridSearchCV was used and each model was trained and tested on the dataset. To assess the performance of each model both with and without hyper parameter tuning evaluation metrics like accuracy, confusion matrices, and classification reports were used and the accuracy of the models without GridSearchCV was 0.7, 0.875, 0.975 and with GridSearchCV was 0.75, 1.0, 0.975. According to GridSearchCV Logistic Regression is the most suitable model for drug classification among the three-model used followed by the K-Nearest Neighbors. Also, Na_to_K is an essential feature in predicting the outcome.

• Journal of Korean Society of Environmental Engineers
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• 제31권4호
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• pp.300-307
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• 2009

The transport of landfill leachate in the subsurface formations of unlined landfill sites is considered. The impacts of hydrogeological and chemical heterogeneities on the leachate transport are assessed by examining the results from a series of Monte-Carlo simulations. The landfill system simulated in this study is hypothetically represented with three levels of spatial variability for the hydrogeological and chemical parameter; (1) homogeneous hydraulic conductivity (K) and distribution coefficient ($K_d$), (2) K heterogeneity only, and (3) combined heterogeneities of K and $K_d$. To calculate the transport of leachate through negatively-correlated random hypothetical K-$K_d$ fields generated using geostatistical input parameters, a saturated flow model is linked with a contaminant transport model. Point statistic values such as mean, standard deviation, and coefficient of variation of the concentration were obtained from 100 Monte-Carlo trials. Results of point statistics show that the heterogeneities of K and $K_d$ in the landfill site prove to be an important parameter in controlling leachate concentrations. Consideration of combined K and $K_d$ heterogeneities results in enhancing the variability of contaminant transport. The variability in the leachate concentration for different realizations also increases as the distance between source and monitoring well increase.