• Asian-Australasian Journal of Animal Sciences
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• v.19 no.12
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• pp.1696-1701
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• 2006

A random regression model was applied for the first time for the analysis of test day records and to study the genetic persistency of first lactation milk yield of Indian Murrah buffaloes. Wilmink's Function was chosen to describe the shape of lactation curves. Heritabilities of test day milk yield varied from 0.33 to 0.58 in different test days. The highest heritability was found in the initial test day ($5^{th}$ day) milk yield. Genetic correlations among test day milk yields were higher in the initial test day milk yield and decreased when the test day interval was increased. The magnitude of genetic correlations between test day and 305 day milk yield varied from 0.25 to 0.99. The genetic persistencies of first lactation milk yield were estimated based on daily breeding values using two methods. $P_1$ is the genetic persistency estimated as a summation of the deviation of estimated daily breeding value on days to attain peak yield from each day after days to attain peak yield to different lactation days. $P_2$ is the genetic persistency estimated as the additional genetic yield (gained or lost) from days to attain peak yield to estimated breeding value on different lactation days relative to an average buffalo having the same yield on days to attain peak yield. The mean genetic persistency on 90, 120, 180, 240, 278 and 305 days in milk was estimated as -4.23, -21.67, -101.67, -229.57, -330.06 and -388.64, respectively by $P_1$, whereas by $P_2$ on same days in milk were estimated as -3.96 (-0.32 kg), -23.94 (-0.87 kg), -112.81 (-1.96 kg), -245.83 (-2.81 kg), -350.04 (-3.28 kg) and -407.58 (-3.40 kg) respectively. Higher magnitude of rank correlations indicated that the ranking of buffaloes based on their genetic persistency in both methods were similar for evaluation of genetic persistency of buffaloes. Based on the estimated range of genetic persistency three types of genetic persistency were identified. Genetic correlations among genetic persistency in different days in milk and between genetic persistencies on the same day in milk were very high. The genetic correlations between genetic persistency for different days in milk and estimated breeding value for 305 DIM was increased from 90 DIM to 180 DIM, and highest around 240 DIM which indicates a minimum of 240 days as an optimum first lactation length might be required for genetic evaluation of Indian Murrah buffaloes.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.282-285
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• 2009

This paper proposes a flame verification algorithm using motion and spatial persistency. Most previous vision-based methods using color information and temporal variations of pixels produce frequent false alarms due to the use of many heuristic features. To solve these problems, we used a Bayesian Networks. In addition, since the shape of flame changes upwards irregularly due to the airflow caused by wind or burning material, we distinct real flame from moving objects by checking the motion orientation and temporal persistency of flame regions to remove the misclassification. As a result, the use of two verification steps and a Bayesian inference improved the detection performance and reduced the missing rate.

• Communications of the Korean Institute of Information Scientists and Engineers
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• v.33 no.2
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• pp.73-79
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• 2015

• Asian-Australasian Journal of Animal Sciences
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• v.24 no.5
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• pp.610-615
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• 2011

We examined the correlations between lactation curve shape, including persistency and changes in body condition score (BCS) during early-stage (0 to 30 days in milk (DIM)), nadir-stage (31 to 90 DIM), and late-stage (91 to 240 DIM) lactation in 191 first-lactation cows. Data used were first-parity BCS records, scored twice every month after calving, and daily milk yields. Individual lactation curves were depicted by the Wilmink function. Lactation persistency was defined as the difference in estimated milk yields between 240 DIM and 60 DIM. Changes in BCSs in the early and late stages were defined as linear regression coefficients. There were no significant correlations between traits for lactation curve shape and change in BCS in early-stage lactation. Peak yield and total milk yield were negatively correlated with BCSs in nadir- and late-stage lactation and with BCS change in late-stage lactation, suggesting that cows with high lactation yields had low body reserves and health status in mid- to late lactation and had delayed recovery of body reserves. Lactation persistency was positively correlated with change in BCS in late-stage lactation, suggesting that cows with high lactation persistency tended to be healthy and to recover their body reserves well in late lactation.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.2_2
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• pp.219-232
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• 2022

The aim of this study is to provide the dynamic convergence index that reflected the inherent characteristics of the convergence phenomenon and utilized the nationally-funded R&D projects data, thereby suggesting useful information about the direction of the national convergence R&D strategy. The dynamic convergence index that we suggested was made of two indicators: persistency and diversity. From a time-series perspective, the persistency index, which measures the degree of continuous convergence of multidisciplinary nationally-funded R&D projects, and the diversity index, which measures the degree of binding with heterogeneous research areas. We conducted the empirical experiment with 151,248 convergence R&D projects during the 2015~2021 time period. The results showed that convergence R&D projects in both public health and life sciences appeared the highest degree of persistency. It was presumed that the degree of persistency has increased again due to the COVID-19 pandemic. Meanwhile, the degree of diversity has risen with combining with disciplinary such as materials, chemical engineering, and brain science areas to solve social problems including mental health, depression, and aging. This study not only provides implications for improving the concept and definition of dynamic convergence in terms of persistency and diversity for national convergence R&D strategy but also presented dynamic convergence index and analysis methods that can be practically applied for directing public R&D programs.

• Asian-Australasian Journal of Animal Sciences
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• v.25 no.8
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• pp.1073-1082
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• 2012

We first sought to clarify the effects of discounted rate, survival rate, and lactation persistency as a component trait of the selection index on net merit, defined as the first five lactation milks and herd life (HL) weighted by 1 and 0.389 (currently used in Japan), respectively, in units of genetic standard deviation. Survival rate increased the relative economic importance of later lactation traits and the first five lactation milk yields during the first 120 months from the start of the breeding scheme. In contrast, reliabilities of the estimated breeding value (EBV) in later lactation traits are lower than those of earlier lactation traits. We then sought to clarify the effects of applying single nucleotide polymorphism (SNP) on net merit to improve the reliability of EBV of later lactation traits to maximize their increased economic importance due to increase in survival rate. Net merit, selection accuracy, and HL increased by adding lactation persistency to the selection index whose component traits were only milk yields. Lactation persistency of the second and (especially) third parities contributed to increasing HL while maintaining the first five lactation milk yields compared with the selection index whose only component traits were milk yields. A selection index comprising the first three lactation milk yields and persistency accounted for 99.4% of net merit derived from a selection index whose components were identical to those for net merit. We consider that the selection index comprising the first three lactation milk yields and persistency is a practical method for increasing lifetime milk yield in the absence of data regarding HL. Applying SNP to the second- and third-lactation traits and HL increased net merit and HL by maximizing the increased economic importance of later lactation traits, reducing the effect of first-lactation milk yield on HL (genetic correlation ($r_G$) = -0.006), and by augmenting the effects of the second- and third-lactation milk yields on HL ($r_G$ = 0.118 and 0.257, respectively).

• Asian-Australasian Journal of Animal Sciences
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• v.15 no.3
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• pp.315-320
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• 2002

Test-day records (n=13677) sampled from 896 ewes in 5-9 (${\mu}$=7.5) monthly test-days were used to estimate genetic and phenotypic parameters of test-day yields, lactation milk yield (TMY), length of the milking period (DAYS) and three measures of persistency of milk yield in Boutsico dairy sheep. Τhe measures of persistency were the slope of the regression line (${\beta}$), the coefficient of variation (CV) of the test-day milk yields and the maximum to average daily milk yield ratio (MA). The estimates of variance components were obtained under a linear mixed model by restricted maximum likelihood. The heritability of test-day yields ranged from 0.15 to 0.24. DAYS were found to be heritable ($h^2$=0.11). Heritability estimates of ${\beta}$, CV and MA were 0.15, 0.13, 0.10, respectively. Selection for maximum lactation yields is expected to result in prolonged milking periods, high rates of decline of yields after peak production, variable test-day yields and higher litter sizes. Selection for flatter lactation curves would reduce lactation yields, increase slightly the length of the milking period and decrease yield variation as well as litter size. The most accurate prediction of TMY was obtained with a linear regression model with the first five test-day records.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.10
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• pp.1157-1163
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• 1992

The development of adaptive control algorithms for possibly nonminimum phase systems has been hampered by singularities that may arise in the control law. To solve this problem, one securing convergence of the estimates to their true values by inducing persistency of excitation in the plant signals using direct adaptive control method and indirect adaptive control method, and another in which the estimates are adequately modified to meet the controllability requirements using indirect adaptive control method, without persistency of excitation. This paper presents an adaptive scheme that achieves regulation without persistent excitation condition using direct adaptive control method and reduces estimation algorithms with direct estimation of controller parameters without estimation of plant parameters.

• Journal of Animal Science and Technology
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• v.55 no.3
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• pp.173-178
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• 2013

The characteristics of lactation persistency was investigated for new evaluation trait using 4,366,900 milk yield records from 436,690 heads of Korean Holstein dairy cattle. The average lactation persistencies of first parity, second parity and over third parity were 97.5%, 95.1% and 94.6%, respectively and there was a trend that after the peak yield, lactation persistency decreased collectively. The average days of peak milk yields after calving was about 50 days, but only 33.2% of cows reached peak yields at 36~66 days (second test day). Also, there was a difference between the milk yield of cows which reached peak yields at first test day by lactation days and that of cows which reached peak yields at second to fourth test day. The estimates of heritabilty and repeatability for mean lactation persistency were 0.16 and 0.35, respectively. The genetic correlation between cumulative lactation persistency from third to tenth test day and that from third to seventh test day was 0.91 and while it increased in later test day, it decreased sharply in earlier test day. The breeding value correlations of Data II and III for Data I were 0.80 and 0.72, respectively, while the rank correlations were 0.78 and 0.71, respectively. Based on the results, the breeding value and rank correlations decreased when more data were added.

• Asian-Australasian Journal of Animal Sciences
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• v.28 no.10
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• pp.1407-1418
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• 2015

A total of 32,817 test-day milk yield (TDMY) records of the first lactation of 4,056 Girolando cows daughters of 276 sires, collected from 118 herds between 2000 and 2011 were utilized to estimate the genetic parameters for TDMY via random regression models (RRM) using Legendre's polynomial functions whose orders varied from 3 to 5. In addition, nine measures of persistency in milk yield ($PS_i$) and the genetic trend of 305-day milk yield (305MY) were evaluated. The fit quality criteria used indicated RRM employing the Legendre's polynomial of orders 3 and 5 for fitting the genetic additive and permanent environment effects, respectively, as the best model. The heritability and genetic correlation for TDMY throughout the lactation, obtained with the best model, varied from 0.18 to 0.23 and from -0.03 to 1.00, respectively. The heritability and genetic correlation for persistency and 305MY varied from 0.10 to 0.33 and from -0.98 to 1.00, respectively. The use of $PS_7$ would be the most suitable option for the evaluation of Girolando cattle. The estimated breeding values for 305MY of sires and cows showed significant and positive genetic trends. Thus, the use of selection indices would be indicated in the genetic evaluation of Girolando cattle for both traits.