• International Journal of Industrial Entomology and Biomaterials
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• v.14 no.1
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• pp.1-7
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• 2007

In order to find out the appropriate parents for the breeding programme, twelve bivoltine and three multivoltine silkworm breeds were evaluated on the basis of multivariate selection index and isozyme analysis. Of which, four [CSR2, D6 (P), SK3, SK4] bivoltine and two multivoltine (Nistari, Cambodge) breeds were selected and breeding initiated to develop higher survival bivoltine silkworm breed suitable for tropical conditions. Among two isozyme (Esterase and acid phosphatase) analyzed, only esterase exhibited polymorphism among the bivoltine breeds. No polymorphism was observed among multivoltine in respect of esterase as well as acid phosphatase.

• Korean Management Science Review
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• v.26 no.2
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• pp.19-35
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• 2009

This paper investigated performance of the Markowitz's portfolio selection model with applications to Korean stock market. We chose Samsung-Group-Funds and KOSPI index for performance comparison with the Markowitz's portfolio selection model. For the most recent one and a half year period between March 2007 and September 2008, KOSPI index almost remained the same with only 0.1% change, Samsung-Group-Funds showed 20.54% return, and Markowitz's model, which is composed of the same 17 Samsung group stocks, achieved 52% return. We performed sensitivity analysis on the duration of financial data and the frequency of portfolio change in order to maximize the return of portfolio. In conclusion, according to our empirical research results with Samsung-Group-Funds, investment by Markowitz's model, which periodically changes portfolio by using nonlinear programming with only financial data, outperformed investment by the fund managers who possess rich experiences on stock trading and actively change portfolio by the minute-by-minute market news and business information.

• Fibers and Polymers
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• v.5 no.4
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• pp.297-302
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• 2004

In many engineering applications, the final decision is based on the evaluation of a number of alternatives in terms of a number of criteria. This problem may become very intricate when the selection criteria are expressed in terms of different units or the pertinent data are difficult to be quantified. The Analytic Hierarchy Process (AHP) is an effective way in dealing with such kind of complicated problems. Cotton fiber is selected or graded, in the spinning industries, based on several quality criteria. However, the existing selection or grading method based on Fiber quality Index (FqI) is rather crude and ambiguous. This paper presents a novel approach of cotton fiber selection using the AHP methodology of Multi Criteria Decision Making.

• Smart Media Journal
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• v.10 no.3
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• pp.39-47
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• 2021

Enhanced index tracking is a problem of optimizing the objective function to generate returns above the index based on the index tracking that follows the market return. In order to avoid problems such as large transaction costs and illiquidity, we used a method of constructing a portfolio by selecting only some of the stocks included in the index. Commonly used enhanced index tracking methods tried to find the optimal portfolio with only one objective function in all tested periods, but it is almost impossible to find the ultimate strategy that always works well in the volatile financial market. In addition, it is important to improve generalization performance beyond optimizing the objective function for training data due to the nature of the financial market, where statistical characteristics change significantly over time, but existing methods have a limitation in that there is no direct discussion for this. In order to solve these problems, this paper proposes ensemble learning that composes a portfolio by combining several objective functions and a 3-stage portfolio selection algorithm that can select a portfolio by applying criteria other than the objective function to the training data. The proposed method in an experiment using the S&P500 index shows Sharpe ratio that is 27% higher than the index and the existing methods, showing that the 3-stage portfolio selection algorithm and ensemble learning are effective in selecting an enhanced index portfolio.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.31 no.3
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• pp.304-310
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• 1986

The studies were intended to clarify the effects of selection in sesame breeding. The 82 cultivars of sesame were used as the materials, and 14 quantitative characters were measured on individual plant basis. Selection indexes and genetic advances were calculated by Robinson's methods. In genetic advance values, combinations of days to flowering + number of capsule per plant, days to flowering + length of stem with capsule + number of capsule per plant and days to flowering + number of nodes with capsule were higher than those of other combinations. The highest genetic advance was the combination of all characters, but unreasonable problems such as the expence, time and labor involved in calculating the selection index are remained. For these reasons, it was realized that the selection index for selection should calculated on the basis of the data of 2-3 useful characters, i.e., days to flowering, length of stem with capsule and number of capsule per plant.

• Asian-Australasian Journal of Animal Sciences
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• v.16 no.12
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• pp.1705-1710
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• 2003

A small body size of Brown Tsaiya laying duck is desirable to reduce maintenance requirements, so the body weight at 40 weeks of age (BW40) has to be maintained at its current level. Egg weight has to be maintained at around 65 g to meet market requirements. Eggshell strength at 40 weeks of age (ES40) must to be increased in order to maintain a low incidence of broken eggs. Thus, number of eggs laid up to 52 weeks of age (EN52) has to be increased without negative correlated response on ES40. A new linear genetic selection index was used: $I_g=a_0{\times}GEW40\;(g)+a_1{\times}GBW40\;(g)+a_2{\times}GES40\;(kg/cm^2)+a_3{\times}GEN52\;(eggs)$ where GEW40, GBW40, GES40 and GEN52 were the multitrait best linear unbiased prediction (MT-BLUP) animal model predictors of the breeding values respectively of egg weight and body weight at 40 weeks of age (EW40, BW40), ES40 and EN52. The coefficients $a_0$, $a_1$, $a_2$ and $a_3$ were calculated with constraints of 0.0 g, 0.0 g and $0.013kg/cm^2$ for expected genetic gains in EW40, BW40 and ES40 respectively and maximum gain in EN52. Since 1997, the drakes and the ducks were selected according to their own indexes, with this new genetic selection index. From G0 to G4, the average per generation predicted genetic responses in female duck were +0.05 g for EW40, +0.92 g for BW40, $+0.035kg/cm^2$ for ES40 and +2.13 eggs for EN52. Which represented respectively 0.07%, 0.06%, 0.67% and 1.0% of the means of the EW40, BW40, ES40 and EN52. For ES40 and EN52, it represented also respectively 16.1% and 21.6% of the additive genetic standard deviation of these traits. Thevse results indicated that selection of laying Brown Tsaiya by a restricted genetic selection index and with MT-BLUP animal model could be an efficient tool for improving the efficiency of egg production, increasing egg shell strength and egg number while holding egg weight and body weight constants.

• Korean Journal of Agricultural Science
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• v.48 no.3
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• pp.527-534
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• 2021

This study investigated the possibility of performing selection using 30-month carcass traits by estimating the genetic parameters of 24- and 30-month carcass traits. Data used in this study were the carcass traits of 13,151 heads slaughter at the age of 24 and 30 months. As a result of the study, the heritability of backfat thickness, carcass weight, eye muscle area and marbling score at 24 months of age were estimated to be 0.588, 0.354, 0.467 and 0.587, respectively. The heritability of backfat thickness, carcass weight, eye muscle area and marbling score at 30 months of age were estimated to be 0.498, 0.577, 0.505 and 0.530, respectively. The ranking correlation was 0.516 between the carcass selection indices of 24 and 30 months of age. By providing a 30-month selection index, it is possible to use semen suitable for farm profits, and more semen information can be provided to farms than previously. Furthermore, studies on a selection index based on 30-month carcass traits are needed to provide highly accurate information.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.6_2
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• pp.601-609
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• 2013

Standard lots, which are used to assess values of individual lots in Korea, have been criticized for their improper distribution. However, there has been very little evaluation for the spatial distribution of standard lots, and an evaluation method has never been developed. In order to overcome this situation, we attempt to assess the appropriateness of the spatial distribution of standard lots using the L-index and Monte Carlo simulation. The L-index is a well-known indicator of the complete spatial randomness (CSR) of points in spatial statistics. If the L-index of standard lots is similar to that of individual lots, the former is considered to be randomly distributed according to the latter. By analyzing L-indices of two study areas, Gangnam and Seongdong, we find a statistically significant difference in Gangnam area and a relatively small difference in Seongdong area. We confirm that the spatial distribution of standard lots is not CSR and that the L-index is useful as an evaluation method. These results suggest that the standard lot selection and management guidelines need to be modified to apply the spatial distribution of individual lots to the standard lot selection process.

• Asian-Australasian Journal of Animal Sciences
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• v.17 no.2
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• pp.159-163
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• 2004

Data pertaining to first lactation records of 316 Murrah buffaloes, progeny of 47 sires, maintained at NDRI Farm for a period of 18 years were analysed to construct selection indices and to examine their robustness by changing the relative economic values of different economic traits. A total of 120 selection indices were constructed for three sets of relative economic values ( 40 for each set) considering different combinations of seven first lactation traits viz. age at first calving (AFC), first lactation 305 day or less milk yield (FLMY), first lactation length (FLL), first calving interval (FCI), milk yield per day of first lactation length (MY/FLL), milk yield per day of first calving interval (MY/FCI) and milk yield per day age at second calving (MY/ASC). The three sets of relative economic values were based on economic values of different traits, 1% standard deviation of different traits and regression of different traits on FLMY. The 'optimum' indices for the first two sets had five traits each namely AFC, FLMY, FLL, FCI and MY/ASC giving improvement in aggregate genotype of Rupees 269.11 and Rs. 174.88, respectively. The accuracy of selection from both indices was 70.79 and 69.39%, respectively. The 'best' selection index from the third set of data again had five traits (AFC, FLMY, FLL, FCI and MY/FLL) giving genetic gain of Rs. 124.16 and accuracy of selection of 71.81%. The critcal levels or break-even points for FLMY for varying levels of AFC and FCI estimated from the "optimum index" suggested the need of enhancement of present production level of the herd or reduction of AFC or FCI. It was concluded that economic values of various first lactation traits were the most appropriate to construct selection indices as compared to other criteria of assigning relative economic weights in Murrah buffaloes.

• Asian-Australasian Journal of Animal Sciences
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• v.11 no.2
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• pp.117-120
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• 1998

Relationships of breeding values of sires for first lactation milk yield with pedigree information or indices were examined to identify the optimal criteria of selecting young dairy bulls for future use in artificial insemination (AI). Records of performance data on 1087 crossbred daughters (Holstein - Friesian, Jersey and Brown Swiss with Hariana) of 147 sires, generated at Livestock Production Research (Cattle and Buffaloes) Farm, IVRI, Izatnagar, U.P., during 1972 - 1995 were used to obtain the estimates of sire's breeding values (EBV) using the Best Linear Unbiased Prediction Procedures. The correlations between young bull's EBV and the dam's first lactation milk yield was non-significantly different from zero. However, the young bull's EBV was negatively and significantly related (r = - 0.275 ; P < 0.05) to the dam's best lactation milk yield, suggesting that the selection of young dairy bulls from high yielding elite dams is not a suitable criteria for genetic improvement. The correlations of sire's and paternal grandsire's EBV's with young bull's EBV were high and positive (0.532, 0.844; P < 0.01). The maternal grandsire's EBV was positively but non-significantly related to grandson's EBV. The pedigree index incorporating dam's milk records and sire's EBV's showed a negative and non-significant correlation with young bull's EBV. However, the correlation of a pedigree index $(I_3)$ combining information on sire's and paternal grand-sire's EBV's with young bull's EBV's was considerably high and positive (0.797; P < 0.01). The regression coefficients of young bull's EBV on pedigree index $I_3$, was higher than those on other pedigree information. These results revealed that there was no advantage in basing selection on dam's performance or maternal grand-sire's EBV and that sire's and paternal grandsire's EBV's were reliable pedigree information for selection of young dairy bulls for future use in AI.