• Journal of The Korean Society of Grassland and Forage Science
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• v.40 no.3
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• pp.167-176
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• 2020

The objective of the present study was to determine the best model to describe and quantify the changes in live body weight, height at withers, height at rump, body length and chest girth of Holstein cows raised under Korean feeding conditions for 50 months. The five standard growth models namely polynomial linear regression models, regression of growth variables on the first and second-order of ages in days (model 1) and regression of growth variables on age covariates from first to the third-order (model 2) as well as non-linear models were fitted and evaluated for representing growth pattern of Holstein cows raised in Korean feeding circumstances. Nonlinear models fitted were three exponential growth curve models; Brody, Gompertz, and von Bertalanffy functional models. For this purpose, a total of 22 Holstein cows raised in Korea used in the period from April 2016 to May 2020. Each model fitted to monthly growth curve records of dairy cows by using PROC NLIN procedure in SAS program. On the basis of the results, nonlinear models showed the lower root mean square of error (RMSE) for live body weight, height at withers, height at rump, body length and chest girth (12.22, 1.95, 1.55, 4.04, 2.06) with higher correlation coefficiency (R²) values for live body weight, height at withers, height at rump, body length and chest girth (0.99, 0.99, 0.99, 1.00, 1.00). Overall, the evaluation of the different growth models indicated that the Gompertz model used in the study seemed to be the most appropriate one for standard growth of Holstein cows raised under Korean feeding system.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.30 no.4
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• pp.620-626
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• 1997

Annual biomasses of the hairtail, Trichiurus lepturus, were estimated from the biomass-based cohort analysis (Zhang, 1987), using data of annual catch in weight at age during $1970\~1988$ in Korean waters. Annual biomass of the hairtail was peaked at about 240,000 mt in 1975, and thereafter declined with a slight fluctuation. Adult biomass showed a peak in 1978 with about 55,000 mt. However, it has continuously decreased untill 1980 to the level of 9,000 mt and remained at this level till 1988. Age compositions of the hairtail in the 1980s differed greatly from those in the 1970s. The proportions of older hairtail (>4 years) were very low in the 1980s and even the biomasses of young hairtail $(1\~3\;years)$ were at a low evel in the 1980s compared with the level in 1970s. The 1973 and 1974 year classes appeared to be relatively dominant. The mean value of instantaneous rate of fishing mortality (F) in the 1980s was significantly different from that of the 1910s (P<0.05). Recruitment of the hairtail exhibited a similar trend with stock biomass until 1974, indicating the density-dependent Ricker curve.

• Journal of the Korean Geotechnical Society
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• v.29 no.8
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• pp.5-14
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• 2013

Coarse granular geomaterials containing large gravels are broadly used for construction of large geotechnical systems such as dams, levees, railways and backfills. It is necessary to evaluate deformation characteristics of these materials for dynamic analysis, e.g. seismic design. This study presents evaluation of dynamic deformation characteristics of coarse materials using large scale resonant column testing apparatus, which uses specimens with 200 mm in diameter and 400 mm in height, and the effects of gradation characteristics on maximum shear modulus, shear modulus reduction curve and damping characteristics were investigated. From experimental study using rock-fill materials for a dam, we could see that the largest or mean particle size affects the shape of shear modulus reduction curve. When the specimens are prepared under the same conditions for maximum particle size, the coefficient of uniformity affects the confining stress exponent of maximum shear modulus. It could be concluded that the maximum particle size is an factor which affects shear modulus reduction curve, and that the coefficient of uniformity is for small strain shear modulus, especially for the sensitivity to confining stress.

• Journal of Korea Water Resources Association
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• v.44 no.12
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• pp.975-990
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• 2011

In this study, to develop an assessment method for spatio-temporal riverbed changes, a 1-dimensional model (HEC-RAS) and a 2-dimensional model (CCHE2D) were built and applied. As for the analysis of a riverbed's long-term change in a real stream, three new assessment methods were developed, which are called the "Sediment section cumulative curve", "Sediment section moment", and "Sediment probability distribution function." These methods were used to assess the characteristics of riverbed changes using a consistent valuation standard and to understand changes in quantities intuitively. From the results of this study, sediment characteristics of cross sections can be detected effectively by applying the "Sediment section cumulative curve" method to determine whether there is any sedimentation or erosion in total emission. The amount of sedimentation or erosion occurring in the right or left banks, which divided by center column, could be presented as one criterion by applying the "Sediment section moment" method. This approach could be utilized as an indicator for sediment predictions. Spatio-temporal sediment variables can be presented quantitatively by determining the mean and uncertain boundaries through the "Sediment probability distribution function", and finally, the results can be illustrated for each cross section to provide intuitive recognition.

• Journal of Korea Water Resources Association
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• v.41 no.9
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• pp.943-958
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• 2008

This study employs Bayesian regression analysis for fitting discharge rating curves. The parameter estimates using the Bayesian regression analysis were compared to ordinary least square method using the t-distribution. In these comparisons, the mean values from the t-distribution and the Bayesian regression are not significantly different. However, the difference between upper and lower limits are remarkably reduced with the Bayesian regression. Therefore, from the point of view of uncertainty analysis, the Bayesian regression is more attractive than the conventional method based on a t-distribution because the data size at the site of interest is typically insufficient to estimate the parameters in rating curve. The merits and demerits of the two types of estimation methods are analyzed through the statistical simulation considering heteroscedasticity. The validation of the Bayesian regression is also performed using real stage-discharge data which were observed at 5 gauges on the Anyangcheon basin. Because the true parameters at 5 gauges are unknown, the quantitative accuracy of the Bayesian regression can not be assessed. However, it can be suggested that the uncertainty in rating curves at 5 gauges be reduced by Bayesian regression.

• Ecology and Resilient Infrastructure
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• v.7 no.2
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• pp.114-125
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• 2020

Despite the various artificial neural networks that have been developed, most of the discharge models in previous studies have been developed using deep neural networks. This study aimed to develop a discharge model using a convolution neural network (CNN), which was used to solve classification problems. Furthermore, the applicability of CNN was evaluated. The photographs (pictures or images) for input data to CNN could not clearly show the characteristics of the study area as well as precipitation. Hence, the model employed in this study had to use numerical images. To solve the problem, the CN of NRCS was used to generate images as input data for the model. The generated images showed a good possibility of applicability as input data. Moreover, a new application of CN, which had been used only for discharge prediction, was proposed in this study. As a result of CNN training, the model was trained and generalized stably. Comparison between the actual and predicted values had an R² of 0.79, which was relatively high. The model showed good performance in terms of the Pearson correlation coefficient (0.84), the Nash-Sutcliffe efficiency (NSE) (0.63), and the root mean square error (24.54 ㎥/s).

• Journal of the Korean Geotechnical Society
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• v.32 no.6
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• pp.49-59
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• 2016

We develop liquefaction resistance curves, which represent the correlation between cyclic resistance ratio (CRR) and number of cycles (N) to estimate the build-up of residual excess pore pressure from simple shear tests performed for this study and also from published literature. The liquefaction curve is calculated from two models. The comparisons show that one of the models is not reliable because it underestimates CRR. The scatter of the data is shown to be significantly reduced when CRR is normalized to the resistance ratio at N = 15 ($CRR_{N=15}$). Use of the normalization is particularly useful because CRR can be easily estimated from field tests. From normalization, we propose mean, upper, and lower curves. The corresponding design equation and its parameters are also proposed. We believe that the proposed curves can be used for effective stress site response analyses and evaluation of the seismic performance of port structures.

• Journal of Korean Society of Forest Science
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• v.85 no.4
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• pp.557-564
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• 1996

Based on stem analysis as well as branch analysis data of each tree from 8 plots of circle clear-cutting and 1 biomass plot in Changbai Mountain area, located in Northeast of China, the effective crown form of Changbai larch(Larix olgensis H.) plantation were studied by using the approach of crown curve. The results indicated that the cross-section forms of effective crown were stable and showed approximate circle for different tree size. Because the effective crown was on upper position of the canopy and its form reflects crown architecture under non-competition condition, the architecture is mainly affected by species hereditary feature. Therefore, for the specified species the effective crown form was thought to be relatively stable. The effective crown form of tree was neither related to the tree size within stand nor to the stand condition for different stand. The total effective crown curve of larch plantation could be characterized by using mean effective crown taper.

• Journal of Chest Surgery
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• v.16 no.3
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• pp.281-288
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• 1983

Heparinization is an essential step in extracorporeal circulation for open heart surgery. But wide individual variation to heparin effect sometimes makes it difficult to anticoagulate safely or neutralize appropriately. Because the conventional set protocol of heparinization did not consider this individual variation, a new method of control of heparinization was proposed by Dr. Brian Bull in 1974. We compared the group in which a conventional set protocol was used [Control group] with the other in which a new protocol modified from that of Bull was used [ACT group], on the aspects of the dosages of heparin and protamine administered and postoperative bleeding. Our conventional protocol [Control group] consisted of: 1. Initial heparin was given at dose of 350U/Kg into the right atrium prior to bypass. 2. Additional heparin was given every hour during E.C.C., as much as a half of the Initial dose. 3. 600U of heparin was mixed into every 100ml. of priming solution. 4. The protamine dose was calculated by totalling the units of heparin given to the patient and giving 1 .8mg. of protamine per 100 units of heparin. ACT protocol [ACT group] consisted of: 1. Initial heparinization was same as that of conventional protocol. 2. ACT`s were checked before [A point] and 10 minutes after initial heparinization [B point]. With these 2 points, a dose response curve was drawn. 3. Heparin for the priming solution was same as in control group. 4. Every 30 minutes during E.C.C., ACT`s were checked with Hemochron [International Technidyne Corp.]. ACT between 450 and 600 seconds was regarded as safety zone. If ACT checked at a time was below 450 seconds, heparin dose was calculated on the dose-response curve to lengthen ACT to 480 seconds and was given into the oxygenator. 5. About 10 minutes before the term of E.C.C., ACT was checked to estimate the blood heparin level at the time. Then, protamine dose was calculated at dose of 1.Stag per 100 units of heparin. The calculated dose of protamine was mixed into 50 to lO0ml of 5% Dextrose Water and dripped intravenously during the period of 15 minutes. Compared these two groups mentioned above, results were obtained as follows: 1. Mean value of normal ACT checked with Hemochron on 30 preoperative patients was 124 seconds [range 95-145 sec.]. 2. Doses of heparin and protamine given to the patient were decreased in ACT group as much as 32.2% and 62.2% respectively. 3. Postoperative bleeding and transfusion were also decreased in ACT group in 60.5% and 67.1% respectively. 4. Our modified dose-response curve did not cause any problems in the control of heparinization. 5. Initial heparinization [Heparin 350U/Kg] was sufficient for the most patients until 60 minutes under extracorporeal circulation. 6. We used 1.5mg of protamine to neutralize 100 units of heparin. But smaller dose of protamine may be sufficient for appropriate neutralization.

• Korean Journal of Radiology
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• v.23 no.8
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• pp.811-820
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• 2022

Objective: To develop a model incorporating radiomic features and clinical factors to accurately predict acute ischemic stroke (AIS) outcomes. Materials and Methods: Data from 522 AIS patients (382 male [73.2%]; mean age ± standard deviation, 58.9 ± 11.5 years) were randomly divided into the training (n = 311) and validation cohorts (n = 211). According to the modified Rankin Scale (mRS) at 6 months after hospital discharge, prognosis was dichotomized into good (mRS ≤ 2) and poor (mRS > 2); 1310 radiomics features were extracted from diffusion-weighted imaging and apparent diffusion coefficient maps. The minimum redundancy maximum relevance algorithm and the least absolute shrinkage and selection operator logistic regression method were implemented to select the features and establish a radiomics model. Univariable and multivariable logistic regression analyses were performed to identify the clinical factors and construct a clinical model. Ultimately, a multivariable logistic regression analysis incorporating independent clinical factors and radiomics score was implemented to establish the final combined prediction model using a backward step-down selection procedure, and a clinical-radiomics nomogram was developed. The models were evaluated using calibration, receiver operating characteristic (ROC), and decision curve analyses. Results: Age, sex, stroke history, diabetes, baseline mRS, baseline National Institutes of Health Stroke Scale score, and radiomics score were independent predictors of AIS outcomes. The area under the ROC curve of the clinical-radiomics model was 0.868 (95% confidence interval, 0.825-0.910) in the training cohort and 0.890 (0.844-0.936) in the validation cohort, which was significantly larger than that of the clinical or radiomics models. The clinical radiomics nomogram was well calibrated (p > 0.05). The decision curve analysis indicated its clinical usefulness. Conclusion: The clinical-radiomics model outperformed individual clinical or radiomics models and achieved satisfactory performance in predicting AIS outcomes.