• Korean Journal of Veterinary Research
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• v.36 no.1
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• pp.75-82
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• 1996

Erythrocyte sedimentation rate is influenced by plasma protein, red cell itself and physiological conditions and it is clear that the measurement of erythrocyte sedimentation rate varies with technique and various environmental factors. The effect of temperature, angle of test tube, and osmobility with different percent of NaCl solution on erythrocyte sedimentation rate on sheep was determined by modified Westergren method. In sheep, as the angle of Westergren tube was decreased from $90^{\circ}$ to $45^{\circ}$, erythrocyte sedimentation rate was increased in both diluted plasma and NaCl solutions. As temperature was increased from $4^{\circ}C$ to $20^{\circ}C$ at $45^{\circ}$ angle. erythrocyte sedimentation rate was increased. In ruminants, this modified Westergren methods, erythrocyte 1 : plasma 9 instead of erythrocyte 4 : plasma 6(whole blood), enable them to have meanings as dog therefor, using this method, clinical can determine the erythrocyte sedimentation rate of ruminants for diagnosis. Because erythrocyte sedimentation rate was changed according to the angle of Westergren tube, temperature as erythrocyte diluted with NaCl, this study detected that the change of temperature, the angle of Westergren tube could change erythrocyte sedimentation rate by effecting red cell itself. The increase of osmobility owing to change of NaCl percent resulted in the decrease of rapid erythrocyte sedimentation rate. So this fact indicate that deformibility and the change of red cell volume have meaning in the change of erythrocyte sedimentation rate.

• BMB Reports
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• v.39 no.2
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• pp.167-170
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• 2006

Bovine adenosine deaminase undergoes a nondenaturational conformational change at $29^{\circ}C$ upon heating which is characterized by a large increase in heat capacity. We have determined the transition state thermodynamics of the conformational change using a novel application of differential scanning calorimetry (DSC) which employs very slow scan rates. DSC scans at the conventional, and arbitrary, scan rate of $1^{\circ}C/min$ show no evidence of the transition. Scan rates from 0.030 to $0.20^{\circ}C/min$ reveal the transition indicating it is under kinetic control. The transition temperature $T_t$ and the transition temperature interval ${\Delta}T$ increase with scan rate. A first order rate constant $k_1$ is calculated at each $T_t$ from $k_1\;=\;r_{scan}/{\Delta}T$, where $r_{scan}$ is the scan rate, and an Arrhenius plot is constructed. Standard transition state analysis reveals an activation free energy ${\Delta}G^{\neq}$ of 88.1 kJ/mole and suggests that the conformational change has an unfolding quality that appears to be on the direct path to the physiological-temperature conformer.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.327-327
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• 2020

Increase in Earth's surface temperature, higher rainfall intensity rate, and rapid changes in land cover are just some of the most evident effects of climate change. Flooding, and river sedimentation are two inevitable natural processes in our environment, and both issues poses great risks in the dam industry when not addressed properly. River sedimentation is a significant issue that causes reservoir deposition, and thus causes the dam to gradually lose its ability to store water. In this study, the long-term effects of climate change on the sediment discharge in Yongdam Dam watershed is analyzed through the utilization of SWAT, a semi-distributed watershed model. Based from the results of this study, an abrupt increase on the annual sediment inflow trend in Yongdam Dam watershed was observed; which may suggests that due to the effects of climate change, higher rainfall intensity, land use and land cover changes, the sedimentation rate also increased. An efficient sedimentation management should consider the increasing trend in sedimentation rate due to the effects of climate change.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2000.11a
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• pp.417-426
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• 2000

This study suggests integrated neural network models for Interest rate forecasting using change-point detection, classifiers, and classification functions based on structural change. The proposed model is composed of three phases with tee-staged learning. The first phase is to detect successive and appropriate structural changes in interest rare dataset. The second phase is to forecast change-point group with classifiers (discriminant analysis, logistic regression, and backpropagation neural networks) and their. combined classification functions. The fecal phase is to forecast the interest rate with backpropagation neural networks. We propose some classification functions to overcome the problems of two-staged learning that cannot measure the performance of the first learning. Subsequently, we compare the structured models with a neural network model alone and, in addition, determine which of classifiers and classification functions can perform better. This article then examines the predictability of the proposed classification functions for interest rate forecasting using structural change.

• Korean Management Science Review
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• v.18 no.1
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• pp.119-133
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• 2001

It is important to find the equilibrium level of real interest rate for it affects real and financial sector of economy. However, it is difficult to find the equilibrium level because like the most macroeconomic model the real interest model has parameter instability problem caused by structural change and it is supported by various theories and definitions. Hence, in order to cover these problems structural change detection model of real interest rate is developed to combine the real interest rate equilibrium model and the procedure to detect structural change points. 3 equations are established to find various effects of other interest-related macroeconomic variables and from each equation, structural changes are found. Those structural change points are consistent with common expectation. Oil Crisis (December, 1987), the starting point of Economic Stabilization Policy (January, 1982), the starting point of capital liberalization (January, 1988), the starting and finishing points of Interest deregulation (January, 1992 and December, 1994), Foreign Exchange Crisis (December, 1977) are detected as important points. From the equation of fisher and real effects, real interest rate level is estimated as 4.09% (October, 1988) and dependent on the underlying model, it is estimated as 0%∼13.56% (October, 1988), so it varies so much. It is expected that this result is connected to the large scale simultaneous equations to detect the parameter instability in real time, so induces the flexible economic policies.

• Health Policy and Management
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• v.11 no.3
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• pp.121-150
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• 2001

This study was conducted to investigate provider's behavior change after releasing the information on the Cesarean section rate. Claims data filed at the National Health Insurance Corporation was used for this analysis and the focus of this study was the change of cesarean rate after the public disclosure of information. Average rates of the year 1999 and 2000 were compared, on the institutional basis, and range and coefficient of variation were estimated. For the last decade, Cesarean section rate has been increased dramatically. Clinical or demographic factors could not adequately explain the increase. Instead, nonclinical factors, such as financial incentive, physician's convenience, practice characteristics, etc., were more significant in explaining the increasing rate. Providers' behavior was significantly affected by the public release of information: after the release, average rate was decreased by 10.2%, and variations were also decreased. In particular, the extent of decrease was explained mainly by nonclinical factor rather than clinical ones. The results suggest that disseminating practice information to providers and consumers could contribute to reducing unnecessary medical service.

• Ocean and Polar Research
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• v.36 no.4
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• pp.327-341
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• 2014

This study aims to analyze causality among Wando abalone producer prices by size using a vector autoregressive model to expiscate the leading-price of Wando abalone in various price classes by size per kg. This study, using an analytical approach, applies a unit-root test for stability of data, a Granger causality test to learn about interaction among price classes by size for Wando abalone, and a vector autoregressive model to estimate the statistical impact among t-1 variables used in the model. As a result of our leading-price analysis of Wando abalone producer prices by shell size using a VAR model, first, DF, PP, and KPSS tests showed that the Wando abalone monthly price change rate by size differentiated by logarithm were stable. Second, the Granger causality relationship analysis showed that the price change rate for big size abalone weakly led the price change rate for the small and medium sizes of abalone. Third, the vector autoregressive model showed that three price change rates of t-1 period variables statistically, significantly impacted price change rates of own size and other sizes in t period. Fourth, the impulse response analysis indicated that the impulse responses of structural shocks for price change rate for big size abalone was relatively more powerful in its own size and in other sizes than shocks emanating from other sizes. Fifth, the variance decomposition analysis indicated that the price change rate for big size abalone was relatively more influential than the price change rates for medium and small size abalone.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.2
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• pp.72-81
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• 2015

This paper studied the differences of the inventories asset turnover change ratio and several characteristics variable between large and small manufacturing firm group. Large and small firm group were determined based on number of labors and asset size. Several characteristics variable of firms such as assets size, sales growth rate, return on assets, leverage ratio, credit rating and age of firm were used to find out the differences of firm group. As a result, the inventory asset turnover change ratio of large firm was 5.16% and that of the middle and small firm was 9.3%. For the large firm, sales growth rate, ROA and credit rating affect inventory assets turnover change ratio. For the middle and small sized firm, Assets size, sales growth rate and credit rating affect inventory assets turnover change ratio. Using this result, we can say that manufacturing company need to consider their firm size and their characteristics to make their own operation strategy of inventory.

• Journal of the Korean Chemical Society
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• v.51 no.4
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• pp.365-374
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• 2007

The purpose of this study is to investigate the students' conceptions about the reaction rate changes during the chemical equilibrium shifts and also whether the questions about basic concepts of the reaction rate are helpful for the students' understanding of reaction rate changes during the chemical equilibrium shifts. The subjects were 100 students in the 12th grade. The questionnaires were composed of A, B, and A' set, which had to be answered sequentially. The A set consisted of questions asking the change of reaction rate when chemical equilibrium was shifted, the B set was to testify the basic concepts of the reaction rate, and the A' set was the same as the A set. The results showed that the students' understanding of the reverse reaction rate change was lower than that of the forward reaction rate change during the equilibrium shift. Also it was found that students' understanding of the reaction rate change caused by adding the reactant was fairly good while their understanding of the reaction rate change caused by temperature increment was very poor. Since the students marked very high scores in the B set questions, their poor understanding for the reaction rate changes during the equilibrium shifts was not seemed to be due to the lacks of the basic knowledge of reaction rate. Instead, it was due to the failure of applying the basic knowledge of reaction rate to the changes of reaction conditions. It was also found that the average scores of A' set were statistically higher than those of A set. It means the B set items were helpful for the students to solve the A' set items. These results evidenced the possibility of set questionnaires could help the students to connect the related concepts in solving the problems.

• The Journal of Fisheries Business Administration
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• v.45 no.2
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• pp.29-38
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• 2014

This study is to analyse the timing of the structural change of price volatility and the asymmetry of price volatility during the period before and after the timing of the structural change of price volatility using Jeju Farming Olive Flounder's production area market price data from January 1, 2007 to June 30, 2013. The analysis methods of Quandt-Andrews break point test and Threshold GARCH model are employed. The empirical results of this study are summarized as follows: First, the result of Quandt-Andrews break point test shows that a single structural change in price volatility occurred on May 4, 2010 over the sample period. Second, during the period before structural change, daily price change rate has averagely positive value which means price increase, but during the period after structural change daily price change rate has averagely negative value which means price decrease. Also, daily volatility of price change rate during the period before structural change is higher than during the period after structural change. This indicates that price volatility decreases after structural change. Third, the estimation results of Threshold GARCH Model show that the volatility response against price increase is larger during the period after structural change than during the period before structural change. Also the result shows the volatility response against price decrease is larger during the period after structural change than during the period before structural change. And, irrespective of the timing of structural change, price increase has an larger effect on volatility than price decrease. This means volatility is asymmetric at price increase.