• Journal of Korean Society on Water Environment
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• v.20 no.4
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• pp.321-326
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• 2004

The objective of this study is to test the applicability of neural network models to forecast water quality at Naesa and Pyongchang river. Water quality data devided into rainy day and non-rainy day to find characteristics of them. The mean and maximum data of rainy day show higher than those of non-rainy day. And discharge correlate with TOC at Pyongchang river. Neural network model is trained to the correlation of discharge with water quality. As a result, it is convinced that the proposed neural network model can apply to the analysis of real time water quality monitoring.

• Asian-Australasian Journal of Animal Sciences
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• v.19 no.7
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• pp.915-921
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• 2006

Various random regression models with different order of Legendre polynomials for permanent environmental and genetic effects were constructed to predict future milk yield of Holstein cows in Korea. A total of 257,908 test-day (TD) milk yield records from a total of 28,135 cows belonging to 1,090 herds were considered for estimating (co)variance of the random covariate coefficients using an expectation-maximization REML algorithm in an animal mixed model. The variances did not change much between the models, having different order of Legendre polynomial, but a decreasing trend was observed with increase in the order of Legendre polynomial in the model. The R-squared value of the model increased and the residual variance reduced with the increase in order of Legendre polynomial in the model. Therefore, a model with $5^{th}$ order of Legendre polynomial was considered for predicting future milk yield. For predicting the future milk yield of cows, 132,771 TD records from 28,135 cows were randomly selected from the above data by way of preceding partial TD record, and then future milk yields were estimated using incomplete records from each cow randomly retained. Results suggested that we could predict the next four months milk yield with an error deviation of 4 kg. The correlation of more than 70% between predicted and observed values was estimated for the next four months milk yield. Even using only 3 TD records of some cows, the average milk yield of Korean Holstein cows would be predicted with high accuracy if compared with observed milk yield. Persistency of each cow was estimated which might be useful for selecting the cows with higher persistency. The results of the present study suggested the use of a $5^{th}$ order Legendre polynomial to predict the future milk yield of each cow.

• Journal of Animal Science and Technology
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• v.47 no.2
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• pp.147-158
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• 2005

The purpose of this study was to find out the effects that daughters' incomplete lactation records affect sire's breeding values through genetic evaluation using RRTDM(random regression test-day model). First, we estimated genetic parameters and breeding values on sires having complete lactation records of daughter by RRTDM, second, we changed complete lactation records of specific sires into incomplete records by various methods. Third, the breeding values were compared between complete and incomplete records. Finally, this study aimed to find out the methods to minimize the estimation errors of young bulls' breeding values. Data used in this study were collected from the dairy herd improvement program, and a total of 97,562 records were composed of 10,929 first parity with both parents known, since 1999. Breeding values on the daughters from randomly chosen sires were calculated and compared with among 90 day, 150day, and 200 day's incomplete records. For milk yields, sire's ranks of breeding values used by complete lactation records were very different from sire's ranks of breeding values obtained by incomplete lactation records(Rank_90 cut, 150cut, 200 cut).The differences were also obtained between complete lactation records(per305_full) and incomplete lactation record (per_90 cut, 150cut, 200 cut) in breeding values regarding persistency. Especially, the differences between per_90 cut and per305_full were very large(from 1.8 kg to 145kg).

• Computers and Concrete
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• v.5 no.1
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• pp.21-36
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• 2008

Steel fiber reinforced concrete is increasingly used day by day in various structural applications. An extensive experimentation was carried out with w/cm ratio ranging from 0.25 to 0.40, and fiber content ranging from zero to1.5 percent by volume with an aspect ratio of 80 and silica fume replacement at 5%, 10% and 15%. The influence of steel fiber content in terms of fiber reinforcing index on the compressive strength of high-performance fiber reinforced concrete (HPFRC) with strength ranging from 45 85 MPa is presented. Based on the test results, equations are proposed using statistical methods to predict 28-day strength of HPFRC effecting the fiber addition in terms of fiber reinforcing index. A strength model proposed by modifying the mix design procedure, can utilize the optimum water content and efficiency factor of pozzolan. To examine the validity of the proposed strength model, the experimental results were compared with the values predicted by the model and the absolute variation obtained was within 5 percent.

• Asian-Australasian Journal of Animal Sciences
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• v.22 no.7
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• pp.923-930
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• 2009

This study was conducted to compare three models: two random regression models with and without considering heterogeneity in the residual variances and a lactation model (LM) for evaluating the genetic ability of Holstein cows in Korea. Two datasets were prepared for this study. To apply the test-day random regression model, 94,390 test-day records were prepared from 15,263 cows. The second data set consisted of 14,704 lactation records covering milk production over 305 days. Raw milk yield and composition data were collected from 1998 to 2002 by the National Agricultural Cooperative Federation' dairy cattle improvement center by way of its milk testing program, which is nationally based. The pedigree information for this analysis was collected by the Korean Animal Improvement Association. The random regression models (RRMs) are single-trait animal models that consider each lactation record as an independent trait. Estimates of covariance were assumed to be different ones. In order to consider heterogeneity of residual variance in the analysis, test-days were classified into 29 classes. By considering heterogeneity of residual variance, variation for lactation performance in the early lactation classes was higher than during the middle classes and variance was lower in the late lactation classes than in the other two classes. This may be due to feeding management system and physiological properties of Holstein cows in Korea. Over classes e6 to e26 (covering 61 to 270 DIM), there was little change in residual variance, suggesting that a model with homogeneity of variance be used restricting the data to these days only. Estimates of heritability for milk yield ranged from 0.154 to 0.455, for which the estimates were variable depending on different lactation periods. Most of the heritabilities for milk yield using the RRM were higher than in the lactation model, and the estimate of genetic variance of milk yield was lower in the late lactation period than in the early or middle periods.

• Asian-Australasian Journal of Animal Sciences
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• v.9 no.4
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• pp.439-447
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• 1996

Monthly test day production for 12,020 records, were collected from six of the largest specialized dairy farms located in central region of the Kingdom of Saudi Arabia. The records described lactating cows in four parities and two seasons of calving. Monthly test day records were fitted using Wood's model $At{{^b}{_e}}^{-ct}$ with multiple and additive error term. Linear and non-linear regression models were used to find the estimates of the parameters necessary to draw the lactation curves. The shape of the lactation curves of different parities showed that third lactation has the heighest peak (43.08 kg) for linear regression model and (42.08 kg) for non-linear regression model. Fourth lactation has the lowest peak (24.00kg) for linear regression model and (25.64 kg) for non-linear regression models. Cows of second and third lactations reached the peak at 58 day for both linear and non-linear regression models. Cows of first lactation were more persistent and had late peak at 68 and 67 days for both models respectively. While, third lactation cows were lower persistent and had early peak at 58 day for both models. Cows calved at winter months have higher starting values (A), higher ascending slope (b) and higher decending slope (c). Least square means of milk yield of the first four parities and for overall data were 6,653, 7,659, 7,482, 6,988 and 7,614 kg respectively. The corresponding lactation period were 358, 367, 350, 363 and 364 days respectively.

• The Journal of Korean Physical Therapy
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• v.16 no.2
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• pp.72-89
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• 2004

The purposes of this study were to test the effect of balance training and environmental enrichment on motor performance after traumatic cerebellar injury in the rat. Traumatic cerebellar injury was induced by weight drop model and after operation they were housed in individual standard cages for 24 hours. Twenty two Sprague-Dawley rats were randomly assigned into control and experimental groups. The control group was housed in standard cage for 7 days. The experimental group I was housed in standard cage after balance training for 7 days. The experimental group II was housed in environmental enrichment cage after balance training for 7 days. Vestibular drop test and tilting plane test was examined at preoperation, on 1st day after operation and 7th day after operation to the rats. The results of this experiment were as follows: 1. In motor behavioral test, at preoperation and on 1 day after operation, the outcomes were not different among the groups. But on 7th day after operation, the outcomes of group I were better than that in control group, and group II were better than group I. These results suggest that behavioral motor outcome by simultaneously application of balance training and environmental enrichment in traumatic cerebellar injured rats were more improve than that by just balance training.

• Nutrition Research and Practice
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• v.12 no.3
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• pp.233-242
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• 2018

BACKGROUND/OBJECTIVES: The effects of fish consumption by subjects with prediabetes on the metabolic risk factors were examined based on the data from the $6^{th}$ Korea National Health and Nutrition Examination Surveys in 2015. SUBJECTS/METHODS: A total of 1,520 subjects who agreed to participate in a blood test and dietary intake survey were divided into a prediabetes group and normal blood glucose group, and the level of the subjects' fish consumption was divided into ${\leq}17.0g/day$, 18.0-93.0 g/day, and ${\geq}94g/day$. The correlation between the level of fish intake and the metabolic risk factors was evaluated by multinomial logistic regression analysis. RESULTS: A significant difference in the gender distribution was observed in the prediabetes group, which is a group with a high risk of non-communicable diseases, according to the fish intake, and there were significant differences in the total energy intake, protein intake, n-3 fatty acids intake, and the intakes of sodium and micro-nutrients according to the intake group (P < 0.05). In addition, the blood total cholesterol (TC) decreased 0.422 fold in model 1 (unadjusted) [95% confidence interval (CI): 0.211-0.845] and 0.422 fold in model 2 (adjusted for sex) (95% CI: 0.210-0.846) in those with a fish intake of 18.0-93.0 g/day (P < 0.05) compared to those with a fish intake of ${\leq}17.0g/day$. The blood TC decreased 0.555 fold (95% CI: 0.311-0.989) in model 1 and 0.549 fold (95% CI: 0.302-0.997) in model 2 in those with a fish intake of ${\geq}94g/day$ compared to those with a fish intake of ${\leq}17.0g/day$ (P < 0.05). CONCLUSION: Subjects with prediabetes or the metabolic risk factors can maintain their blood low density lipoprotein cholesterol (LDL-C) and blood TC concentrations at the optimal level by consuming fish (18.0-93.0 g/day).

• Journal of Environmental Health Sciences
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• v.44 no.5
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• pp.468-479
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• 2018

Objectives: Recently, a report was published that the humidifier disinfectant CMIT/MIT did not cause developmental toxicity and was not detected in systemic circulation as a result of an inhalation toxicity test. Therefore, this study was carried out to investigate any associations between CMIT/MIT exposure and developmental toxicity using the in vivo apical toxicity test method. Methods: Groups of pregnant ICR mice were instilled in the trachea with chloromethylisothiazolinone/methylisothiazolinone (CMIT/MIT) using a visual instillobot over a period of seven days from days 11 to 17 days post-coitum. For the in vivo apical toxicity test method, an $LD_{50}$-based dose-range finding model was applied to decide the dose range for inducing developmental toxicity. Results: Among the groups of 0, 0.1, 0.5, 1.0, and 1.5 mg ai/kg/day CMIT/MIT, the exposure groups of 0.5 mg and 1.0 ai/kg/day CMIT/MIT were estimated to reflect the thresholds for the stillbirth and death of pregnant mice, respectively. The groups of 0.5, 1.0, and 1.5 mg ai/kg/day CMIT/MIT induced stillbirth rates of 2.57, 10, and 53.8%, respectively. Another exposure group of 0.75 mg ai/kg/day CMIT/MIT did not induce any deaths of pregnant mice and resulted in a stillbirth rate of 8% in only one of six pregnant mice. Conclusions: CMIT/MIT can induce stillbirth in pregnant mice. It was also concluded that CMIT/MIT moves through the pulmonary circulation system and then continues on through systemic circulation and the placenta. There is a possibility of stillbirth and other health causalities in humans beyond the lungs caused by CMIT/MIT exposure.

• Asian-Australasian Journal of Animal Sciences
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• v.29 no.5
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• pp.607-614
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• 2016

The objectives of the study were to estimate genetic parameters for milk production traits of Holstein cattle using random regression models (RRMs), and to compare the goodness of fit of various RRMs with homogeneous and heterogeneous residual variances. A total of 126,980 test-day milk production records of the first parity Holstein cows between 2007 and 2014 from the Dairy Cattle Improvement Center of National Agricultural Cooperative Federation in South Korea were used. These records included milk yield (MILK), fat yield (FAT), protein yield (PROT), and solids-not-fat yield (SNF). The statistical models included random effects of genetic and permanent environments using Legendre polynomials (LP) of the third to fifth order (L3-L5), fixed effects of herd-test day, year-season at calving, and a fixed regression for the test-day record (third to fifth order). The residual variances in the models were either homogeneous (HOM) or heterogeneous (15 classes, HET15; 60 classes, HET60). A total of nine models (3 orders of $polynomials{\times}3$ types of residual variance) including L3-HOM, L3-HET15, L3-HET60, L4-HOM, L4-HET15, L4-HET60, L5-HOM, L5-HET15, and L5-HET60 were compared using Akaike information criteria (AIC) and/or Schwarz Bayesian information criteria (BIC) statistics to identify the model(s) of best fit for their respective traits. The lowest BIC value was observed for the models L5-HET15 (MILK; PROT; SNF) and L4-HET15 (FAT), which fit the best. In general, the BIC values of HET15 models for a particular polynomial order was lower than that of the HET60 model in most cases. This implies that the orders of LP and types of residual variances affect the goodness of models. Also, the heterogeneity of residual variances should be considered for the test-day analysis. The heritability estimates of from the best fitted models ranged from 0.08 to 0.15 for MILK, 0.06 to 0.14 for FAT, 0.08 to 0.12 for PROT, and 0.07 to 0.13 for SNF according to days in milk of first lactation. Genetic variances for studied traits tended to decrease during the earlier stages of lactation, which were followed by increases in the middle and decreases further at the end of lactation. With regards to the fitness of the models and the differential genetic parameters across the lactation stages, we could estimate genetic parameters more accurately from RRMs than from lactation models. Therefore, we suggest using RRMs in place of lactation models to make national dairy cattle genetic evaluations for milk production traits in Korea.