• Journal of Information Technology Services
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• v.14 no.2
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• pp.129-142
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• 2015

The purpose of this study is to suggest an effective regression testing method in order to minimize the scope of test resulting from the modification of software and to prevent mismatch of test case and test objects. As a way to improve the efficiency of regression testing which uses a change-centric testing technique, the method flow is analyzed and grasped through a static analysis based on source code in order to identify modified parts. After the order of priority is set according to the results of user action log-based dynamic analysis on identified regression testing objects, test effect can be raised by adjusting the order of priority using code complexity. Quality assurance coverage can be checked using the user action log suggested in this study, and the progress of test and whether or not each function has been verified can be checked, too. In addition, by minimizing test parts and adjusting the order of test, costs and time can be saved, making it possible to conduct regression testing effectively.

• Asian-Australasian Journal of Animal Sciences
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• v.17 no.4
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• pp.554-559
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• 2004

The objective of the present study was to investigate the accuracy of mastitis diagnostic indicators for different dairy goat breeds. Biweekly milk samples were collected from individual half mammary gland of seven Saanen and seven Alpine dairy goats in the period of 40 to 120 days in milk. With threshold value set at 2.8 and 3.1 for Alpine and Saanen dairy goats, respectively, log (SPC) offered good sensitivity (0.89, 0.93), specificity (0.88, 0.95), positive predictive value (0.75, 0.85) and negative predictive value (0.95, 0.98) as a mastitis diagnostic tool. The correlations of log (SPC) with milk yield, log (SCC), ALP, LDH, $Na^{+}$, $K^{+}$ and EC were significant in Saanen dairy goats (p<0.05), with the highest correlation coefficient (0.653) existing between log (SPC) and log (SCC). The correlations of log (SPC) with milk yield, milk fat, milk protein, log (SCC), $Na^{+}$, $K^{+}$, EC were significant in Alpine dairy goats (p<0.05), with the highest correlation coefficient (0.416) existing between log (SPC) and log (SCC). There were different best-fit regression equations with different multiple diagnostic indicators for Saanen and Alpine dairy goats. In conclusion, different breeds of dairy goats may have to adapt different mastitis diagnostic parameters for a better diagnosis.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.48 no.2
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• pp.137-146
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• 2012

Black porgy and fat greenling are commercially important fish species due to the continuously increasing demand in Korea. When estimating acoustically the fish length by a fish sizing echo sounder, it is of crucial importance to know the target strength (TS) to length dependence. In relation to these needs, the target strength experiments for live fishes were conducted in an acrylic salt water tank using two split-beam echo sounders operating at 70 and 120kHz. The target strength under well-controlled laboratory conditions was simultaneously measured with the swimming movement by digital video recording (DVR) system and analyzed as a function of fish length (L) and frequency (or wavelength ${\lambda}$). Equations of the form TS-alog (L)+blog (1)+c were derived for their TS-length dependence. The best fit regression of TS on fork length for black porgy was TS=20.62 log (L, m)-0.62 log (${\lambda}$, m)-30.68 ($r^2$=0.77). The best fit regression of TS on fork length for fat greenling was TS=12.06 log (L, m)-5.85 log (${\lambda}$, m)-22.15 ($r^2$=0.44).

• Ocean and Polar Research
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• v.44 no.3
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• pp.261-267
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• 2022

We derived a length-weight relationship for Calanus sinicus off Busan, Korea in spring to estimate the biomass of the C. sinicus population around Korean waters, and compared it with the previously derived equations. The developmental stages and prosome length of C. sinicus used in the relationship ranged from 1,376-1,540 ㎛ for copepodite 4 (CIV), 1,753-1,971 ㎛ for copepodite 5 (CV), and 2,160-2,283 ㎛ for adults (CVI). Dry weight and carbon content were measured from a total of 26 replicates. Length-weight relationships derived in the present study are as follows: log C = 3.342 log PL - 9.449, log DW = 3.394 log PL -9.219, where C is carbon content (㎍), DW is dry weight (㎍), and PL is prosome length (㎛). When comparing the present regression equation of length-weight for C. sinicus with the previous one, our regression equation showed an average carbon estimate to a given range of mean prosome length. The length-weight relationship of C. sinicus in the present study can be used to better estimate the biomass of the C. sinicus population in the coastal waters of Korea.

• Journal of Korea Foresty Energy
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• v.25 no.1
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• pp.31-38
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• 2006

Quercus mongolica is the most common hardwood species distributed in Korea. This study was conducted to investigate the biomass and energy content of the belowground biomass of Q. mongolica and to obtain the regression equation for estimating root biomass using the tree height and diameter at breast height (DBH). A total of 18 sample trees ranging 20 to 60 year-old were selected in the study sites. Tree height, DBH, age, and weight of stemwood, sapwood, heartwood, stembark, branch, leaf, and root were measured for total biomass. The highly positive correlation was shown between the biomass of most of variables of aboveground components and root biomass. The regression equation of the aboveground total biomass was $log\;W_A\;=\;1.469\;+\;0.992\;log\;D^2H\;(R^2 =0.99)$. The regression equation of the belowground biomass was $log\;W_R\;=\;1.527\;+\;0.808\;log\;D^2H\;(R^2\;=\;0.97)$. The mean energy contents of sapwood, heartwood, bark, leaf, and root were 19,594 J/g DW, 19,571 J/g DW, 19,999 J/g DW, 20,664 J/g DW, and 19,273 J/g DW, respectively. The results obtained from this study can be used to estimate biomass and energy content of belowground using easily measurable variables such as DBH and tree height ranging from 20 to 60-year-old Q. mongolica stands.

• Korean Journal of Soil Science and Fertilizer
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• v.37 no.6
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• pp.365-370
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• 2004

To invesligate the characteristics of silica sorption on soils silica sorption experiments were conducted with 9 soils at 4 pH levels (5, 6, 7, and 8). Silica sorption increased in great extent with increase of pH. At the same pH level silica sorption increased linearly with increase of equilibrium $SiO_2$ concentration. Silica sorption characteristics was C-type. The C-type slope, i.e., the slope of linear regression of silica sorption isotherm, increased exponentially with increase of pH in all soils. Log(C-type slope) increased linearly with increase of pH in all soils. The slopes of linear regression were similar in most soils from 0.29 to 0.34 except Sachon and Jonggog soil. None of the soil properties showed any correlation with the slope of linear regression of Log(C-type slope) to pH. Only $Fe_o$ (oxalate extractable Fe oxides) was significantly correlated with the Log(C-type slope) at pH 7 in simple correlation analysis, and was shown to be the principal contributor as determined by standardized multiple linear regression.

• The Korean Journal of Financial Management
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• v.24 no.2
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• pp.183-206
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• 2007

The price-dividend ratio is one of the most frequently used financial variables to predict long-horizon stock return. However, the persistency of the price-dividend ratio is found to cause the spuriousness of the stock return prediction regression. The stable relationship between the stock price and the dividend, however, seems to weaken after World War II and to experience structural break. In this paper, we identify a structural change in the cointegrating relationship between the log of the stock price and the log of the dividend. Confirming a structural break in 1962, we subdivide the sample and apply the fully modified estimator to correct for the nonstationarity of the regressor. With the subdivided sample, we exercise the nonparametric bootstrap procedure to derive the empirical distribution of the test statistics and fail to find return predictability in each subsample period.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.46 no.3
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• pp.239-247
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• 2010

Species of fish such as striped beakperch, bluefin searobin and konoshiro gizzard shad are commercially very important due to their high demand in the Korean market. When estimating acoustically the abundance of stocks for these species, it is of crucial importance to know the target strength (TS) to the length dependence. In relation to these needs, the TS experiments were conducted on three different species in an acrylic salt water tank using two split-beam echo sounders of 70 and 120 kHz. The TS for these three species under the controlled condition was simultaneously measured with the swimming movement by a DVR system and analyzed as a function of fish length (L) and frequency (or wavelength $\lambda$). The equation of the form TS=a log (L)+b log ($\lambda$)+c was derived for their TS-length dependence. The best fit regression of TS on fork length for striped beakperch was estimated as TS=35.67 log (L, m) -15.67 log ($\lambda$, m) -46.69 ($r^2$=0.78). Furthermore, the best fit regression of TS on fork length for konoshiro gizzard shad was shown to be TS=25.85 log (L, m) -5.85 log ($\lambda$, m) -32.22 ($r^2$=0.51). The averaged TS for 12 bluefin searobins with a mean length of 24.36cm at 70 kHz was analyzed to be -41.55dB. In addition, the averaged tilt angle obtained simultaneously by a DVR system with TS measurements for 27 konoshiro gizzard shads swimming within an acrylic salt water tank was estimated at $-2.7^{\circ}$.

• The Korean Journal of Applied Statistics
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• v.26 no.3
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• pp.389-399
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• 2013

This article introduces Gaussian process regression and shows its application with time-course microarray gene expression data. Gene screening for yeast cell cycle microarray expression data is accomplished with a ratio of log marginal likelihood that uses Gaussian process regression with a squared exponential covariance kernel function. Gaussian process regression fitting with each gene is done and shown with the nine top ranking genes. With the screened data the Gaussian model-based clustering is done and its silhouette values are calculated for cluster validity.

• 모자간호학회지
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• v.1
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• pp.34-44
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• 1991

The purposes of this study were to predict newborn birthweight by use of gestational period and fundal height and to identify growth curve of fundal height according to gestational period and growth curve of newborn birthweight according to fundal height. The subjects for the study were 802 women who delivered the normal newborn babies at Seoul National University Hospital from Sep. 1, 1981 to Aug.31, 1986. The data were collected bit chart review and analyzed nth SPSS program. The results of study were as follows : 1. The multiple regression equation ($R^2$=0.416) used for the prediction of newborn birthweight was y=(newborn birthweight, kg)=-4.421+0.075$x_1$(fundal height, cm)+0.053$x_2$(gestational period, weeks)+0.016$x_3$(abdominal girth, cm)+0.010$x_4$(maternal height, cm) 2. The growth curve of fundal height according to gestational period was obtained by polynomial regression. The regression equation was Y(fundal height, cm)=-36.78+18.58$log_ex$(gestational period, weeks) The growth curve of newborn birth weight according to fundal height was obtained by polynomial regression. The regression equation was Y(newborn birthweight, kg)=-8.09+3.27$log_ex$ (Fundal Height, cm) 3. In the following subgroups no significant difference was found in fundal height : engaged vs. nonengaged presentation, and nulliparous vs. multiparous women.