• Journal of Korean Society of Forest Science
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• v.110 no.4
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• pp.648-657
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• 2021

This study was conducted to estimate the volume growth by forest type and major species using the national forest resource inventory and to predict the final age of maturity by deriving the mean annual increment (MAI) and the current annual increment (CAI). We estimated the volume growth using the Chapman-Richards model. In the volume estimation equations by forest type, coniferous forests exhibited the highest growth. According to the estimation formula for each major species, Larix kaempferi will grow the highest among coniferous tree species and Quercus mongolica among broad-leaved tree species. And these estimation formulas showed that the fitness index was generally low, such as 0.32 for L. kaempferi and 0.21 for Quercus variabilis. In the analysis of residual amount, which indicates the applicability of the volume estimation formula, the estimates of the estimation formula tended to be underestimated in about 30 years or more, but most of the residuals were evenly distributed around zero. Therefore, these estimation formulas have no difficulty estimating the volume of actual forest species in Korea. The maximum age attained by calculating MAI was 34 years for P. densiflora, 35 years for L. kaempferi, and 31 years for P. rigida among coniferous tree species. In broad-leaved tree species, we discovered that the maximum age was 32 years for Q. variabilis, 30 years for Q. acutissima, and 29 years for Q. mongolica. We calculated MAI and CAI to detect the point at which these two curves intersected. This point was defined by the maximum volume harvesting age. These results revealed no significant difference between the current standard cutting age in public and private forests recommended by the Korea Forest Service, supporting the reliability of forestry policy data.

• Korean Journal of Remote Sensing
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• v.37 no.5_2
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• pp.1259-1268
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• 2021

The 2nd Geostationary Ocean Color Imager (GOCI-II) is the successor to the Geostationary Ocean Color Imager (GOCI), which employs one near-ultraviolet wavelength (380 nm) and eight visible wavelengths(412, 443, 490, 510, 555, 620, 660, 680 nm) and three near-infrared wavelengths(709, 745, 865 nm) to observe the marine environment in Northeast Asia, including the Korean Peninsula. However, the multispectral radiance image observed at satellite altitude includes both the water-leaving radiance and the atmospheric path radiance. Therefore, the atmospheric correction process to estimate the water-leaving radiance without the path radiance is essential for analyzing the ocean environment. This manuscript describes the GOCI-II standard atmospheric correction algorithm and its initial phase validation. The GOCI-II atmospheric correction method is theoretically based on the previous GOCI atmospheric correction, then partially improved for turbid water with the GOCI-II's two additional bands, i.e., 620 and 709 nm. The match-up showed an acceptable result, with the mean absolute percentage errors are fall within 5% in blue bands. It is supposed that part of the deviation over case-II waters arose from a lack of near-infrared vicarious calibration. We expect the GOCI-II atmospheric correction algorithm to be improved and updated regularly to the GOCI-II data processing system through continuous calibration and validation activities.

• Korean Journal of Weed Science
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• v.1 no.1
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• pp.30-43
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• 1981

On unwedded paddy fields, six cropping patterns of rice cultivation, namely direct broadcast seeding, direct row seeding, machine transplanting, early season hand transplanting, standard season hand transplanting, and late season hand transplanting, were detected with two representative rice cultivars (Milyang 23 and Sadominori) to estimate the comparative fluctuation patterns of weed flora. As a result, number of emerged weed species, most crowding stages, differences of weed growth among cropping patterns, possible tendencies of competition in plant heights among plant groups, variations in Importance Values, and Simpson's Index analysis were discussed, respectively.

• Korean Journal of Poultry Science
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• v.11 no.2
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• pp.86-92
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• 1984

Present study was carried out to estimate phenotypic and genetic parameters influencing body weight (BW) at 4 weeks of age egg breadth (EB), egg length(EL), egg shape index (SI) and egg weight (EW) at 32 weeks of age and egg numbers (EN) up to 38 weeks of age in broiler male and female lines. The data were collected from closed White Plymouth Rock (female line; G) and Cornish (male line; C) flocks involving 1193 pullets from 211 dams and 48 sires in 1982. The results obtained are summarized as follow: 1. General performance for various trails of lines C and G. The means and standard deviations of BW, EB, EL, SI, EW and EN were 668.34${\pm}$47.18, 4.23${\pm}$0,11, 5.49 ${\pm}$0.19, 77.06${\pm}$2.98, 55.73${\pm}$3.54 and 59.72${\pm}$13.39 in line C, respectively and 487.89${\pm}$ 41.43, 4.22${\pm}$0.11, 5.51${\pm}$0.19, 76.72${\pm}$3.20, 55.43${\pm}$3.26 and 76.93${\pm}$12.17 in line G, respectively. 2. Heritability Heritabilities were estimated from sire, dam and combined components. Estimates for BW, EB, EL, SI, EW and EN from combined components were 0.30, 0.29, 0,40, 0.22, 0.45 and 0.60 in line C, respectively and 0.33, 0.23, 0.28, 0.13, 0.49 and. 0.33 in line G, respectively. 3. Correlation Genetic and phenotypic correlations showed similar trend in line C and G. Genetic correlations, estimated EW with EB and EL, were high and positive (line C; 0.99, 0.75, respectively and line G; 0.94, 0.82, respectively), also correlation of EB with EL was 0.58 (both lines; 0.58). High and negative genetic correlations were shown between SI and EL in line C and G (-0.70, -0.65, respectively). Genetic correlations between SI and EW were relatively low and negative in line C and G (-0.11, -0.19, respectively) and between SI and EN were relatively low and positive in line C and G (0.25, 0.17, respectively). Between other traits, low genetic correlations were shown in both lines, High and positive correlation was estimated between hatchability and egg shape index and polynomial regression of egg shape index on hatchability was estimated; Y=-216.77＋7.6216X-0.0146939X$^2$.

• Progress in Medical Physics
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• v.17 no.2
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• pp.89-95
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• 2006

The purpose of this study was to evaluate the radiation doses during CT transmission scan by changing tube voltage and tube current, and to estimate the radiation dose during our clinical whole body $^{137}Cs$ transmission scan and high quality CT scan. Radiation doses were evaluated for Philips GEMINI 16 slices PET/CT system. Radiation dose was measured with standard CTDI head and body phantoms in a variety of CT tube voltage and tube current. A pencil ionization chamber with an active length of 100 mm and electrometer were used for radiation dose measurement. The measurement is carried out at the free-in-air, at the center, and at the periphery. The averaged absorbed dose was calculated by the weighted CTDI ($CTDI_w=1/3CTDI_{100,c}+2/3CTDI_{100,p}$) and then equivalent dose were calculated with $CTDI_w$. Specific organ dose was measured with our clinical whole body $^{137}Cs$ transmission scan and high quality CT scan using Alderson phantom and TLDs. The TLDs used for measurements were selected for an accuracy of ${\pm}5%$ and calibrated in 10 MeV X-ray radiation field. The organ or tissue was selected by the recommendations of ICRP 60. The radiation dose during CT scan is affected by the tube voltage and the tube current. The effective dose for $^{137}Cs$ transmission scan and high qualify CT scan are 0.14 mSv and 29.49 mSv, respectively. Radiation dose during transmission scan in the PET/CT system can measure using CTDI phantom with ionization chamber and anthropomorphic phantom with TLDs. further study need to be peformed to find optimal PET/CT acquisition protocols for reducing the patient exposure with same image qualify.

• The Korean Journal of Financial Management
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• v.20 no.1
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• pp.93-124
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• 2003

This paper studies the financial analyst's forecasting activities on the firm's operating performance during the period from 1999 to 2003. In this study, financial analyst's forecasting activities are focused on the sales, operating income and net income and financial analyst's forecasting accuracy, forecasting revising patterns and forecasting activities to the unexpected firm's operating performance are studied. Some empirical findings in this study are as follows. First, standard estimate error on the sales, operating income and net income are all significantly negative value and so financial analyst's forecast on the firm's operating performance are upwardly biased. Second, domestic financial analyst's forecasting activities is relatively more accuracy than foreign financial analyst's forecasting activities. Third, forecasting time is more close to the end of the operating performance announcement day, forecasting activities are more accuracy. Fourth, comparing with individual financial analyst's forecast, consensus forecast is more accuracy. Fifth, in the comparative forecasting activities study according to the prior firm's operating performance, financial analyst's forecasting revision activities are found to be upward or downward. Sixth, financial analysts overreact in the sales forecast and underreact in the operating income and net income forecast. Seventh, in the empirical analysis on the Easterwood-Nutt's test model(1999) which the firm's performance change are divided into the expected performance change and the unexpected performance change, it is found that financial analyst's forecasting activities on the firm's operating performance are systematically optimistic.

• Journal of Preventive Medicine and Public Health
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• v.24 no.3 s.35
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• pp.428-440
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• 1991

This study was conducted to estimate the prevalence rate of cervical cancer and to investigate its risk factors. 5,417 asymptomatic married women were screened from March, 1984 to December, 1990 in Taegu city. Of 5,417 examinees, 3,817 (70.46%) were normal, 1,542 (28.7%) showed inflammatory change, 51 (0.94%) were dysplasia and 7 (0.13%) were carcinoma in situ or invasive carcinomas. The prevalence of abnormal finding (dysplasia, carcinoma in situ or invasive carcinoma) was 1,070 per 100,000 population. The prevalence of dysplasia was 940 per 100,000 and that of carcinoma in situ or invasive carcinoma was 130 per 100,000. Age-adjusted prevalence rate for abnormal finding adjusted with standard population of Taegu city was estimated to be 850 per 100,000. The prevalence of cervical cancer was significantly increased with age (P<0.05). The prevalence of cervical cancer was significantly decreased with age at marriage and educational level (P<0.05). The history of induced abortion and the number of pregnancies were significantly associated with the prevalence of cervical cancer (p<0.05), whereas, the number of parity was not. Age at marriage was significantly associated with the prevalence of cervical cancer after stratification by age (p<0.05). However, the level of education, parity, induced abortion, number of pregnancies were not significant. Inflammation and human papiloma virus infection were associated with cervical cancer with odds ratio of 13.48 (95% confidence interval $7.80{\sim}23.40$) and 474.29 (95% confidence interval $196.80{\sim}1143.10$), respectively. In conclusion, for early detection of cervical cancer it should be recommended to perform mass cytological screening. In particular, regular and periodic cytologic screening, starting at age 25, for cervical cancer should be recommended for those women who have frequent cervical inflammation and for those women married before age of 20.

• Journal of Animal Science and Technology
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• v.52 no.5
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• pp.349-356
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• 2010

This study was conducted to estimate heritabilities, repeatabilities and rank correlation coefficients among breeding values for litter size and sex ratio of Yorkshire and Landrace pigs using various single trait animal models. The analyses were carried out the data comprising 26,390 litters of Yorkshire and 26,173 litters of Landrace collected from the year 1998 to 2008 at a private swine breeding farm located in central part of Korea. Five different analytical models were used for genetic parameter estimation. Model 1 was most simple basic model fitted with year-month contemporary group fixed effect, random additive genetic effect and random residual effect. Model 2 was similar to the model 1 but permanent maternal environmental effect added as random effect, and model 3 was similar with the model 2 but linear and quadratic effects of sow age were added as fixed covariate effect. Model 4 was similar as model 2 except that the parity was added as fixed effect and model 5 was similar to model 3 or model 4 but covariate of sow age was nested within parity effect. The results obtained in this study are summarized as follows: The means and standard error of total number of pigs born per litter (TNB) and number of pigs born alive per litter (NBA) were $11.35{\pm}0.02$ and $10.04{\pm}0.02$ for Yorkshire, $10.97{\pm}0.02$ and $9.98{\pm}0.02$ for Landrace, respectively. The sex ratio (percentage of female per litter) was $45.75{\pm}0.11%$ and $45.75{\pm}0.11%$ for Yorkshire and Landrace, respectively. The heritability estimates of TNB (0.243) and NBA (0.192) from model 1 tended to be higher than those from any other models in both breeds. Differences in heritability and repeatability for TNB were not large among models 3, 4 and 5 and same tendency of negligible differences among estimates by models 3, 4 and 5 were observed for NBA, where heritability and repeatability ranged from 0.096 to 0.099 and from 0.188 to 0.193, respectively, in Yorkshire; and ranged from 0.092 to 0.098 and from 0.193 and 0.196, respectively, in Landrace. The heritability estimates for sex ratio were close to zero which was ranged from 0.002 to 0.003 for TNB and from 0.001 to 0.003 for NBA over the models applied. The rank correlation coefficients of breeding values by model 1 with those from other models (model 2, 3, 4 and 5), and breeding values by model 2 with those from other models (model 1, 3, 4 and 5) were highly positive but lower than the coefficients among breeding values by model 3, model 4 and model 5 which were high of 0.99, approximately, for TNB and NBA of both breeds.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.32 no.6
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• pp.737-747
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• 1999

To estimate biomass and distribution of the Antarctic krill (Euphausia superba), hydroacoustic survey was conducted on board of R/V Yuzhmorgeologiya, which was chartered by Korea Antarctic Research Program (KARP) group from 18 to 21 December 1998, in the northern part of the South Shetland Islands, Antarctic Ocean, The scientific echo sounder (towing body type) used was EK- 500 (SIMRAD, Norway) with echo integrator (BI-500) at 38 kHz frequency and recorded mean backscattering cross-section coefficient (SA) per 1 $mile^2$ of sea surface. Also, Bongo net sampling was carried out to determine the size of krill and CTD (Conductivity, Temperature and Depth) casting to understand physical structure. Water column was divided into 5 layers (22$\~$65 m, 65$\~$115 m, l15$\~$65 m, 165$\~$215 m and 215$\~$315 m) to know vertical distribution of krill biomass. The standard length of krill collected was between 30 mm and 51 mm, and adult krill had single mode (41 mm). Maximum horizontal length of krill patch was about 35 nautical mile and vertical thickness was about 275 m. High density of krill was appeared in frontal area between Circumpolar Deep Water (>$1^{\circ}C$) and very low temperature water mass (< $-0.5^{\circ}C$) that originate from Weddell Sea. According to the results calculated using target strength equation, krill density was totally higher in continental slope and open water areas than in coastal area. In the study area, krill seems to distribute in depth; density was low at first layer ($\={\rho}=17.0\;g/m^2$) and higher at fourth layer ($\={\rho}=40.19\;g/m^2$). The estimated krill biomass at total survey area and water column was about 2.77 million metric ion ($\={\rho}=151.0\;g/m^2$) and coefficient of valiance ( CV, $\%$) was 19.92. The proportions and biomass of krill biomass at each layer were as follows; layer 1 ($11.3\%$, 0.31 million metric ton, CV=16.24), layer 2 ($13.3\%$, 0.37 million metric ton, CV=34.91), layer 3 ($23.7\%$, 0.66 million metric ton, CV=41.5), layer 4 ($26.6\%$, 0.74 million metric ton, CV=27.84) and layer 5 ($25\%$, 0.69 million metric ton, CV= 26.83).

• Journal of Sericultural and Entomological Science
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• v.8
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• pp.11-25
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• 1968

Various formulae for estimation of leaf production in mulberry trees were investigated and obtained. Four varieties of mulberry trees were used as the materials, and seven characters namely branch length. branch diameter, node number per branch, total branch weight, branch weight except leaves, leaf weight and leaf area, were studied. The formulae to estimate the leaf yield of mulberry trees are as follows: 1. Varietal differences were appeared in means, variances, standard devitations and standard errors of seven characters studied as shown in table 1. 2. Y$_1$=a$_1$X$_1$${\times}$P$_1$......(l) where Y$_1$ means yield per l0a by branch number and leaf weight determination. a$_1$.........leaf weight per branch. X$_1$.......branch number per plant. P$_1$........plant number per l0a. 3. Y$_2$=(a$_2$${\pm}$S. E.${\times}$X$_2$)+P$_1$.......(2) where Y$_2$ means leaf yield per l0a by branch length and leaf weight determination. a$_2$......leaf weight per meter of branch length. S. E. ......standard error. X$_2$....total branch length per plant. P$_1$........plant number per l0a as written above. 4. Y$_3$=(a$_3$${\pm}$S. E${\times}$X$_3$)${\times}$P$_1$.....(3) where Y$_3$ means of yield per l0a by branch diameter measurement. a$_3$.......leaf weight per 1cm of branch diameter. X$_3$......total branch diameter per plant. 5. Y$_4$=(a$_4$${\pm}$S. E.${\times}$X$_4$)P$_1$......(4) where Y$_4$ means leaf yield per 10a by node number determination. a$_4$.......leaf weight per node X$_4$.....total node number per plant. 6. Y$\sub$5/= {(a$\sub$5/${\pm}$S. E.${\times}$X$_2$)Kv}${\times}$P$_1$.......(5) where Y$\sub$5/ means leaf yield per l0a by branch length and leaf area measurement. a$\sub$5/......leaf area per 1 meter of branch length. K$\sub$v/......leaf weight per 100$\textrm{cm}^2$ of leaf area. 7. Y$\sub$6/={(X$_2$$\div$a$\sub$6/${\pm}$S. E.)}${\times}$K$\sub$v/${\times}$P$_1$......(6) where Y$\sub$6/ means leaf yield estimated by leaf area and branch length measurement. a$\sub$6/......branch length per l00$\textrm{cm}^2$ of leaf area. X$_2$, K$\sub$v/ and P$_1$ are written above. 8. Y$\sub$7/= {(a$\sub$7/${\pm}$S. E. ${\times}$X$_3$)}${\times}$K$\sub$v/${\times}$P$_1$.......(7) where Y$\sub$7/ means leaf yield estimates by branch diameter and leaf area measurement. a$\sub$7/......leaf area per lcm of branch diameter. X$_3$, K$\sub$v/ and P$_1$ are written above. 9. Y$\sub$8/= {(X$_3$$\div$a$\sub$8/${\pm}$S. E.)}${\times}$K$\sub$v/${\times}$P$_1$.......(8) where Y$\sub$8/ means leaf yield estimates by leaf area branch diameter. a$\sub$8/......branch diameter per l00$\textrm{cm}^2$ of leaf area. X$_3$, K$\sub$v/, P$_1$ are written above. 10. Y$\sub$9/= {(a$\sub$9/${\pm}$S. E.${\times}$X$_4$)${\times}$K$\sub$v/}${\times}$P$_1$......(9) where Y$\sub$7/ means leaf yield estimates by node number and leaf measurement. a$\sub$9/......leaf area per node of branch. X$_4$, K$\sub$v/, P$_1$ are written above. 11. Y$\sub$10/= {(X$_4$$\div$a$\sub$10/$\div$S. E.)${\times}$K$\sub$v/}${\times}$P$_1$.......(10) where Y$\sub$10/ means leaf yield estimates by leaf area and node number determination. a$\sub$10/.....node number per l00$\textrm{cm}^2$ of leaf area. X$_4$, K$\sub$v/, P$_1$ are written above. Among many estimation methods. estimation method by the branch is the better than the methods by the measurement of node number and branch diameter. Estimation method, by branch length and leaf area determination, by formulae (6), could be the best method to determine the leaf yield of mulberry trees without destroying the leaves and without weighting the leaves of mulberry trees.