• Asian-Australasian Journal of Animal Sciences
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• v.14 no.7
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• pp.910-914
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• 2001

The teat number of a sow plays an important role for weaning pigs and has been utilized in selection of swine breeding stock. Various linear models have been employed for genetic analyses of teat number although the teat number can be considered as a count trait. Theoretically, Poisson error mixed models are more appropriate for count traits than Normal error mixed models. In this study, the two models were compared by analyzing data simulated with Poisson error. Considering the mean square errors and correlation coefficients between observed and fitted values, the Poisson generalized linear mixed model (PGLMM) fit the data better than the Normal error mixed model. Also these two models were applied to analyzing teat numbers in four breeds of swine (Landrace, Yorkshire, crossbred of Landrace and Yorkshire, crossbred of Landrace, Yorkshire, and Chinese indigenous Min pig) collected in China. However, when analyzed with the field data, the Normal error mixed model, on the contrary, fit better for all the breeds than the PGLMM. The results from both simulated and field data indicate that teat numbers of swine might not have variance equal to mean and thus not have a Poisson distribution.

• Journal of Animal Environmental Science
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• v.8 no.3
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• pp.165-170
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• 2002

This study was carried out to measure the 3D-distance of a cow model teat for an application possibility on Robotic Milking System(RMS). A teat recognition algorithm was made to find 3D-distance of the model by using Gonzalrez's theory. Some of the results are as follows. 1 . In the distance measurement experiment on the test board, as the measured length, and the length between the center of image surface and the measured image point became longer, their error values increased. 2. The model teat was installed and measured the error value at the random position. The error value of X and Y coordinates was less than 5㎜, and that of Z coordinates was less than 20㎜. The error value increased as the distance of camera's increased. 3. The equation for distance information acquirement was satisfied with obtaining accurate distance that was necessary for a milking robot to trace teats, A teat recognition algorithm was recognized well four model cow teats. It's processing time was about 1 second. It appeared that a teat recognition algorithm could be used to determine the 3D-distance of the cow teat to develop a RMS.

• Journal of Animal Science and Technology
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• v.52 no.3
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• pp.187-190
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• 2010

The objective of this study was to estimate genetic parameters for total number of born (TNB), number of born alive (NBA) and teat numbers (TN) of Landrace and Yorkshire breeds in Korean swine population using multiple trait animal model procedures. Total numbers of 4,653 records for teat numbers and 8,907 records for TNB and NBA collected from 2004 to 2008 on imported breeding pigs and their litter size records were used in this study. To find the appropriate model for estimation of genetic parameters (heritabilities and genetic correlations), five statistical models (two models for reproductive traits, two models for teat numbers, one model for combining these traits) considering only direct additive genetic effects, including maternal effects were used and Akaike information criteria (AIC) of each two models for reproductive traits and teat trait were compared. The means and standard deviations of TNB, NBA, and TN were $11.52{\pm}3.34$, $10.55{\pm}2.96$ and $14.30{\pm}0.83$, respectively. Estimated heritabilities for TNB and NBA traits using the model which considered only additive genetic effect were low (0.06 and 0.05, respectively). However, estimated heritabilities considering maternal genetic effects were a little bit higher than that of the model considering only additive genetic effect (0.09 for TNB and NBA, respectively). Estimated heritability for TN using the model which considered only additive genetic effect was 0.40. However, estimated heritability of direct genetic effects from a model considering maternal genetic effect was high (0.60). All results of AIC statistics, the models considering maternal effect was more appropriate than the models considering only additive genetic effect. Genetic correlations of direct additive genetic effect between litter size (TNB, NBA) and teat numbers were low (-0.18 and -0.14, respectively). However, genetic correlations of maternal effect between litter size (TNB, NBA) and teat numbers were a little bit higher than those of direct additive genetic effect (0.08 and 0.16, respectively).

• Journal of Animal Environmental Science
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• v.6 no.2
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• pp.105-112
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• 2000

The objective of this study was to determine the teat locations and to develop a teat cup handling system operated by a robot. The results of this study were summarized as follows: 1. The teat cup attaching and detaching operation system developed in this study consists of a control computer, a five-dimensional robot(PERFORMER-MK2), a DC servo gripper, a robot controller, two CCD-cameras (WV-vp410), an image grabber board(DT3153), a model cow, and a teat cup unit. 2. The coordinates of teat locations were measured by a stereo image processing unit. The error ranges of teats coordinates measured were (x, y, z) = (0.83, 1.95, 0.81) mm. When those were transferred into the Robot Coordinate System(RCS) coordinate, the total error ranges measured were x = 0.9 mm, y = 2.0 mm, z = 0.9 mm. 3. The rates of success of teat cup attaching and detaching operation by a robot system were 91.5% on average; the operation time needed were 27.8 sec. Total working hours for the teat cup handling including image processing were 86.1 sec.

• Journal of Embryo Transfer
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• v.31 no.4
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• pp.313-318
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• 2016

The aim of this study was to identify quantitative trait loci (QTLs) influencing teat number traits in an $F_2$ intercross between Landrace and Korean native pigs (KNP). Three teat number traits (left;right;and total) were measured in 1105 $F_2$ progeny. All experimental animals were genotyped with 173 informative microsatellite markers located throughout the pig genome. We detect that seven chromosomes harbored QTLs for teat number traits: genome regions on SSC1;3;7;8;10;11;and 13. Six of fourteen identified QTL reached genome-wide significance. In SSC7;we identified a major QTL affecting total teat number that accounted for 5.6 % of the phenotypic variance;which was the highest test statistic (F-ratio = 61.1 under the additive model;nominal $P=1.3{\times}10^{-14}$) observed in this study. In this region;QTL for left and right teat number were also detected with genome-wide significance. With exception of the QTL in SSC10;the allele from KNP in all 6 identified QTLs was associated with decreased phenotypic values. In conclusion;our study identified both previously reported and novel QTL affecting teat number traits. These results can play an important role in determining the genetic structure underlying the variation of teat number in pigs.

• Journal of Animal Environmental Science
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• v.17 no.2
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• pp.93-100
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• 2011

This study was conducted to verify the applicability of robot milking system through acquisition and analysis of model teat's position information using scanning range finder (SRF). Model teats, same size and shape as real teats, were designed to analyze the properties according to the material, distance error and angle error of the sensor. In addition, 2-dimensional distance information of each teats was obtained at same time with 4 teat models and the result were as follows. 1. In the case of the fingers on the experiment for selection of materials for teat model, the distance error was from 4.3 mm to 1.3 mm, average was 2.8 mm as a minimum record. In the case of rubber material, average distance error was 4.3 mm. So, this material was considered to be a most suitable model. 2. The distance error was maximum at 100 mm distance. The more distance increased, the less error increased up to 300 mm. Then the error increased after 300 mm and decreased again. 3. The maximum angle error of 10.1 mm was measured at $170^{\circ}$, in case of $70^{\circ}$ the error was 0.2 mm as a minimum value. There was no specific tendency to error of angle. 4. In the 2-dimensional location error for 4 teat models, distance error was 3.8 mm as minimum and 7.2 mm as maximum. The angle error was $1.2^{\circ}$ as maximum. All of errors were included within the accuracy of sensor, the robot milking system was considered to be applicable to measure the distance of teats due to the measuring velocity of SRF and the hole size of teat-cup.

• Animal Bioscience
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• v.37 no.4
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• pp.555-566
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• 2024

Objective: This study aimed to assess the genetic parameters and accuracy of genomic predictions for twenty-four linear body conformation traits and overall conformation scores in Korean Holstein dairy cows. Methods: A dataset of 2,206 Korean Holsteins was collected, and genotyping was performed using the Illumina Bovine 50K single nucleotide polymorphism (SNP) chip. The traits investigated included body traits (stature, height at front end, chest width, body depth, angularity, body condition score, and locomotion), rump traits (rump angle, rump width, and loin strength), feet and leg traits (rear leg set, rear leg rear view, foot angle, heel depth, and bone quality), udder traits (udder depth, udder texture, udder support, fore udder attachment, front teat placement, front teat length, rear udder height, rear udder width, and rear teat placement), and overall conformation score. Accuracy of genomic predictions was assessed using the single-trait animal model genomic best linear unbiased prediction method implemented in the ASReml-SA v4.2 software. Results: Heritability estimates ranged from 0.10 to 0.50 for body traits, 0.21 to 0.35 for rump traits, 0.13 to 0.29 for feet and leg traits, and 0.05 to 0.46 for udder traits. Rump traits exhibited the highest average heritability (0.29), while feet and leg traits had the lowest estimates (0.21). Accuracy of genomic predictions varied among the twenty-four linear body conformation traits, ranging from 0.26 to 0.49. The heritability and prediction accuracy of genomic estimated breeding value (GEBV) for the overall conformation score were 0.45 and 0.46, respectively. The GEBVs for body conformation traits in Korean Holstein cows had low accuracy, falling below the 50% threshold. Conclusion: The limited response to selection for body conformation traits in Korean Holsteins may be attributed to both the low heritability of these traits and the lower accuracy estimates for GEBVs. Further research is needed to enhance the accuracy of GEBVs and improve the selection response for these traits.

• Asian-Australasian Journal of Animal Sciences
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• v.21 no.5
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• pp.617-623
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• 2008

A fine-mapping method exploiting linkage disequilibrium was used to detect quantitative trait loci (QTL) on the X chromosome affecting milk production, body conformation and productivity traits. The pedigree comprised 22 paternal half-sib families of Black-and-White Holstein bulls in the Netherlands in a grand-daughter design for a total of 955 sons. Twenty-five microsatellite markers were genotyped to construct a linkage map on the chromosome X spanning 170 Haldane cM with an average inter-marker distance of 7.1 cM. A covariance matrix including elements about identical-by-descent probabilities between haplotypes regarding QTL allele effects was incorporated into the animal model, and a restricted maximum-likelihood method was applied for the presence of QTL using the LDVCM program. Significance thresholds were obtained by permuting haplotypes to phenotypes and by using a false discovery rate procedure. Seven QTL responsible for conformation types (teat length, rump width, rear leg set, angularity and fore udder attachment), behavior (temperament) and a mixture of production and health (durable prestation) were detected at the suggestive level. Some QTL affecting teat length, rump width, durable prestation and rear leg set had small numbers of haplotype clusters, which may indicate good classification of alleles for causal genes or markers that are tightly associated with the causal mutation. However, higher maker density is required to better refine the QTL position and to better characterize functionally distinct haplotypes which will provide information to find causal genes for the traits.

• Journal of KSNVE
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• v.6 no.3
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• pp.305-315
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• 1996

Present paper aims at the correlation of modal characteristics of folding fin between test and analysis using an optimization theory. Folding fin is composed of a movable fin, a base fin, and many functional components related to the folding mechanism. Joint parts of folding fin in FEM are initially modeled as rigid elements resulting some difference between test and analysis in modal characteristics. Therefore, some equivalent springs representing joint parts are introduced to improve the FEM model. The springs were set as design variables, while the frequency difference between test and analysis was set as the object function. Bayesian procedure was ujsed for the minimization.

• Proceedings of the Korea Concrete Institute Conference
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• 1993.10a
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• pp.207-212
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• 1993

When constructing highly precise production plants, for example, super LSI plants or semiconductor plants, it is important to take the necessary control countermeasures into consideration to obtain the working microvibration environment, which is directly related to product precision. Working environment of a clean room means vibration-free and there are only ultra-miro vibration which human cannot sense. In order to provide an place having a vibration-free working environment with only ultra-micro vibration it is necessary to posses a great number of vibration isolation technlogies, wide-ranging and abundant survey and teat data, and a high level of knowledge enabling comprehensive judgments to be made. In this study, experimental modal analysis is used to analyze the dynamic characteristics of double floor for vibration-proofing near apparatus which generate vibration. It is concluded that the double floor system with rubber pad inserted between floor panel and pedestal is good for vibration proof.