• Asian-Australasian Journal of Animal Sciences
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• v.19 no.12
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• pp.1678-1684
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• 2006

The objectives of this study were to estimate genetic parameters and sire breeding values for average daily gain (ADG) and carcass traits using sire-maternal grandsire model with REML approach, sire model with REML approach, sire model without relationships among sires and with REML and ANOVA approach, and to investigate advantages and disadvantages of these methods. Data were collected from 42,325 Japanese Black steers and heifers finished and slaughtered from 1991 to 2004. Traits analyzed in this study were average daily gain (ADG) during the fattening period, live weight at slaughter (LW), cold carcass weight (CW), estimated lean yield percentage (LYE), longissimus muscle area (LMA), subcutaneous fat thickness (SFT), rib thickness (RT), and marbling score (BMS). Bivariate analyses were also performed to obtain genetic and phenotypic correlation coefficients among traits. Estimated breeding values were obtained from each model, and simple and rank correlations among breeding values from each model were calculated. Estimates of heritability using the four models ranged from 0.25 to 0.31 in ADG, from 0.21 to 0.24 in LW, from 0.23 to 0.27 in CW, from 0.10 to 0.17 in DP, from 0.40 to 0.42 in LYE, from 0.19 to 0.31 in LMA, from 0.31 to 0.34 in SFT, from 0.26 to 0.33 in RT, and from 0.18 to 0.44 in BMS. The differences in heritability estimates using the four models seemed to be feasible in ADG, CW, DP, LMA, RT, and BMS. Genetic correlation coefficients of ADG with CW, SFT, RT and BMS were moderate to high and positive while the genetic correlation coefficients between ADG and LYE was low and negative. Correlation coefficients of BMS with SFT were negligible for both genetic and phenotypic correlations. The correlations of estimates evaluated from sire models with those from sire-maternal grandsire model were not large enough to convincing that breeding values using a sire model were corresponding to those using a sire-maternal grand sire model. If information of maternal grand sires are not available, the sire model with incomplete pedigree information included only sire of sire (Model 2) is optimal among the sire models evaluated in this study.

• The Journal of Fisheries Business Administration
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• v.22 no.2
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• pp.75-99
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• 1991

A quantitative analysis was carried out to monitor the commercial yield level of walleye pollock Theragra chalcogramma in the east coast of Korea, based on available data on catch and fishing effort, catch per unit of effort including fish prices from 1911 to 1988, using a traditional yield model. The results from the quantitative assessment were based to estimate maximum economic yield (MEY) and optimal fishing effort (E-opt) at MEY. On the other hand, interaction aspects between danish seine fishery and trawl fishery mainly targeting walleye pollock in the east coast of Korea were studied to predict optimal situation in fishing effort level from economic point of view which gives the most benefits to the two fisheries. Total production of walleye pollock in 1911 when its catch record was begun for the first time was about 12, 000 metric tons(M/T), and then the catch trend maintained nearly at the level of 50, 000 M/T per annum, showing a decreasing trend until 1930. The highest production from historical data base on walleye pollock fishery statistics was from the years in 1939 and 1940, about 270, 000 M/T and 26, 000 M/T, respectively. No production of the fish species was recorded during the years from 1943 to 1947, and from 1949 to 1951. From 1952 onwards annual production was only available from the southern part of 38$^{\circ}$N in the east coast. During two decades from 1952 to 1970, the production had sustained about less than 30, 000 M/T every year. Annual production showed an increasing trend from 1971, reaching a maximum level of approximately 162, 000 M/T in 1981. Afterwards, it has deceased sharply year after year and amounted to 180, 000 M/T in 1988. The catch composition of walleye pollock for different fishery segments during 1970~1988 showed that more than 70% of the total catch was from danish seine fishery until 1977 but from 1978 onwards, the catch proportion did not differ from one another, accounting for the nearly same proportion. Catch per unit of effort (CPUE) for both danish seine fishery and trawl fishery maintained a decline tendency after 1977 when the values of CPUE were at level of 800 kg/haul for the former fishery and 1, 300 kg/haul for the latter fishery, respectively. CPUEs of gillnet fishery during 1980~1983 increased to about 3.5 times as high value as in the years, 1970~1979 and during 1987~1988 it decreased again to the level of the years, 1970~1978. The bottom longline fishery's CPUE wa at a very low level (20 kg/basket) through the whole study years, with exception of the value (60 kg/basket) in 1980. Fishing grounds of walleye pollock in the east coast of Korea showed a very limited distribution range. Danish seine fishery concentrated fishing around the coastal areas of Sokcho and Jumunjin during January~February and October~December. Distributions of fishing grounds of trawl fishery were the areas along the coastal regions in the central part of the east coast. Gillnet and bottom longline fisheries fished walleye pollock mainly in the areas of around Sokcho and Jumunjin during January~February and December. Relationship between CPUEs' values from danish seine fishery and trawl fishery was used to standardize fishing effort to apply to surplus production model for estimating maximum sustainable yield (MSY) and optimum fish effort (F-opt) at MSY. The results suggested a MSY of 114, 000 M/T with an estimated F-opt of 173, 000 hauls per year. Based on the estimates of MSY and F-opt, MEY was estimated to be about 94, 000 M/T with a range of 81, 000 to 103, 000 M/T and E-opt 100, 000 hauls per year with a range of 80, 000 to 120, 000 hauls. The estimated values of MEY and E-opt corresponded to 82% of MSY and 58% of F-opt, respectively. An optimal situation in the fishing effort level, which can envisage either simultaneously maximum yield or maximum benefit for both danish seine fishery and trawl fishery, was determined from relationship between revenue and cost of running the fleet : the optimal fishing effort of danish seine fishery was about 52, 000 hauls per year, corresponding to 50 danish seiners and 27, 000 hauls per year which is equal nearly to 36 trawlers, respectively. It was anticipated that the net income from sustainable yield estimated from the respective optimal fishing effort of the two fisheries will be about 3, 800 million won for danish seine fishery and 1, 000 million won for trawl fishery.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.135-149
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• 2020

Artificial intelligences are changing world. Financial market is also not an exception. Robo-Advisor is actively being developed, making up the weakness of traditional asset allocation methods and replacing the parts that are difficult for the traditional methods. It makes automated investment decisions with artificial intelligence algorithms and is used with various asset allocation models such as mean-variance model, Black-Litterman model and risk parity model. Risk parity model is a typical risk-based asset allocation model which is focused on the volatility of assets. It avoids investment risk structurally. So it has stability in the management of large size fund and it has been widely used in financial field. XGBoost model is a parallel tree-boosting method. It is an optimized gradient boosting model designed to be highly efficient and flexible. It not only makes billions of examples in limited memory environments but is also very fast to learn compared to traditional boosting methods. It is frequently used in various fields of data analysis and has a lot of advantages. So in this study, we propose a new asset allocation model that combines risk parity model and XGBoost machine learning model. This model uses XGBoost to predict the risk of assets and applies the predictive risk to the process of covariance estimation. There are estimated errors between the estimation period and the actual investment period because the optimized asset allocation model estimates the proportion of investments based on historical data. these estimated errors adversely affect the optimized portfolio performance. This study aims to improve the stability and portfolio performance of the model by predicting the volatility of the next investment period and reducing estimated errors of optimized asset allocation model. As a result, it narrows the gap between theory and practice and proposes a more advanced asset allocation model. In this study, we used the Korean stock market price data for a total of 17 years from 2003 to 2019 for the empirical test of the suggested model. The data sets are specifically composed of energy, finance, IT, industrial, material, telecommunication, utility, consumer, health care and staple sectors. We accumulated the value of prediction using moving-window method by 1,000 in-sample and 20 out-of-sample, so we produced a total of 154 rebalancing back-testing results. We analyzed portfolio performance in terms of cumulative rate of return and got a lot of sample data because of long period results. Comparing with traditional risk parity model, this experiment recorded improvements in both cumulative yield and reduction of estimated errors. The total cumulative return is 45.748%, about 5% higher than that of risk parity model and also the estimated errors are reduced in 9 out of 10 industry sectors. The reduction of estimated errors increases stability of the model and makes it easy to apply in practical investment. The results of the experiment showed improvement of portfolio performance by reducing the estimated errors of the optimized asset allocation model. Many financial models and asset allocation models are limited in practical investment because of the most fundamental question of whether the past characteristics of assets will continue into the future in the changing financial market. However, this study not only takes advantage of traditional asset allocation models, but also supplements the limitations of traditional methods and increases stability by predicting the risks of assets with the latest algorithm. There are various studies on parametric estimation methods to reduce the estimated errors in the portfolio optimization. We also suggested a new method to reduce estimated errors in optimized asset allocation model using machine learning. So this study is meaningful in that it proposes an advanced artificial intelligence asset allocation model for the fast-developing financial markets.

• Journal of Animal Science and Technology
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• v.46 no.4
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• pp.517-524
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• 2004

The objective of this study was to investigate the environmental effects on duration time of milk flow, peak milk flow, and average milk flow in teats, and to estimate their relationships with milk yields in morning and evening milking, and to provide fimdamental information for the further study on their relationships with clinical mastitis and somatic cell in milk. A total of 6,768 milking records were studied in 72 Holstein cows. The influences of season, parity, lactation month, and milking interval on characteristics of milk flow considering in linear model were significant(p<.05). Duration of milk flow was longest at milking in fall, past first parity and second month of lactation, and with milking interval over than 13.5hrs. Average milk flow rate and peak milk flow rate were highest at milking in summer, past first parity and 8${\sim}$10 months of lactation, and with milking interval over than 13.5hrs. Milk flow rate was positively correlated to milk yield, and negatively correlated to the duration of milk flow. However duration milk flow was positively correlated to the milk yield with high level of correlation coefficient(+.60). For the establishment of optimum selection criteria on these traits, other aspects such as the udder health, disease and respective economic weights of milk flow characteristics in this study must be considered to develop the indices.

• Journal of Korean Society on Water Environment
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• v.26 no.4
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• pp.637-647
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• 2010

The Universal Soil Loss Equation (USLE)-based modeling systems have been widely used to simulate soil erosion studies. However the GIS-based USLE modeling systems have limitation in gully erosion evaluation which is one of the most important factor in soil erosion estimation. In this study, the integrated soil erosion evaluation system using with Sediment Assessment Tool for Effective Erosion Control (SATEEC) system, nLS and Unit Stream Power-based Erosion/Deposition (USPED) model was developed to simulate gully erosion. Gully head location using nLS model, USPED for gully erosion, and the SATEEC estimated sheet and rill erosion were evaluated and combined together with the integrated soil erosion evaluation system. This system was applied to the Haean-myeon watershed, annual average sediment-yield considering sheet, rill and gully erosion was simulated as 101,933 ton/year at the study watershed. if the integrated soil erosion evaluation system is calibrated and validated with the measured data, this system could be efficiently used in developing site-specific soil erosion best management system to reduce soil erosion and muddy water inflow into the receiving waterbody.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.46 no.4
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• pp.445-453
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• 2013

Walleye pollock Theragra chalcogramma fisheries in Korean waters have changed dramatically during the last three decades: the highest catches occurred in 1981, followed by continuous decreases through the 1990s, ending with a complete collapse of the population in the 2000s. The major spawning ground of walleye pollock is located in North Korean waters, and some juveniles (called nogari in Korean, <300 mm) migrate to the south for feeding and growth. Since the 1960s, Korean fishermen have often caught juveniles, and the weight (metric tons) of juvenile catch was recorded from 1975-1997. However, because the walleye pollock were not aged, the population age structure was not delineated. We developed a model to estimate the number of walleye pollock of each size class based on catch statistics of adults and juveniles, the catch proportion of each size class, and length and weight information on specimens collected by Danish-seine and drift-gill-net fisheries. The model results demonstrated that the recruitment size of walleye pollock was consistently within the 200-250mm size class, and the highest number of this size class occurred in 1981, although values greatly fluctuated interannually. The number of juvenile pollock was 10.4 times higher than that of adult pollock during 1975-1997. The total yield of juvenile pollock was 0.95 million tons, which was equivalent to about 68.2% of total pollock production. The number of juvenile pollock caught during the same period, however, was 16 billion, comprising about 91.2% of the total number caught. Such high fishing pressure on juvenile pollock is considered one of the main factors causing the collapse of the pollock population.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.3
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• pp.1-10
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• 2003

RUSLE(revised universal soil loss equation) has been widely used for estimating soil loss. It is very difficult to validate the model estimation since the calculated soil loss should be compared with the survey data for quantification. The input variables for RUSLE model were estimated to grid cell for raster analysis in Bosung basin. Both reconnaissance(1:250,000) and detailed(1:25,000) soil maps were used to derive the input variables for soil erodibility factor. Soil loss calculated using RUSLE were compared to the unit sediment deposit surveyed by KICT(Korea Institute of Construction Technology, 1992) in Bosung basin for assessment. Unit sediment deposit from the cell size of 120m and 150m were the closest to the survey data in 1:250,000 and 1:25,000 map scale, respectively.

• Journal of Korea Water Resources Association
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• v.40 no.1 s.174
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• pp.1-10
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• 2007

Reallocation procedure of multipurpose reservoir storage capacity between flood control and conservation is presented as an alternative to secure more water resources. Storage reallocation is an adaptive management mechanism for converting existing normal pool level of reservoirs to more beneficial uses without requirement for physical alteration. This study is intended to develop a reservoir storage reallocation methodology that allows increased water supply storage without minimizing adverse impacts on flood control. The methodology consists of flood control reservoir simulation for inflows with various return periods, flow routing from reservoir to a potential damage site, analyzing river carrying capacity, and reservoir yields estimation for reallocated storages. For the flood control model, a simulation model called Rigid ROM(Reservoir Operation Method) and HEC-5 are used. The approach is illustrated by applying it to two reservoirs system in Geum River basin. Especially with and without new project conditions are considered to analyze trade-offs between competing objectives.

• Journal of agriculture & life science
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• v.44 no.3
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• pp.89-97
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• 2010

In the contingent valuation method (CVM) survey, we employed double-bounded discrete choice (DBDC) question to investigate the willingness to pay (WTP). The estimation results for the bivariate logit model show that respondents are willing to pay 329,256 won per year. The model with covariate variables suggests that the covariate effects help describe behavioral or preference tendencies. Double-bounded models increase efficiency over single dichotomous choice models, because the answers yes-no or no-yes yield clear bounds on WTP.

• Journal of Environmental Science International
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• v.33 no.7
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• pp.453-462
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• 2024

This study was carried out for the purpose of selecting the most appropriate taper equation for the actual stands of Pinus thunbergii in the southern coastal region of Korea and then developing a stem volume table to provide basic data for rational management. To develop a volume table of Pinus thunbergii in this region of Korea, 59 sample trees with various diameter distributions were selected and stem analysis was performed. As a result of stem analysis, two trees with abnormal diameter and height growth as the age increased were rejected, and 57 trees were analyzed. To develop the taper equation, seven major variable exponential equations were used, including Kozak 1988, 1994, 2001, 2002, Bi 2000, Muhairwe 1999, and Sharma and Parton 2009. As a result of parameter estimation and statistical verification, the Kozak 1988 model showed the highest goodness of fit with Fit I (Fit Index), RMSE 1.5620, Bias 0.0031, and MAD 1.0784. The diameter of each 10cm stem ridge for the selected model was estimated, and a stem volume table was produced using the mensuration of division (end area formula) using the Smalian equation. As a result of two-sample T-test for volume table of this study and current yield table, the volume for this study was found to be significantly larger at all observation points (p < 0.001). Even for the same tree species, it is judged that differentiated volume tables are needed for each growth environment characteristic.