• Animal Bioscience
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• v.35 no.10
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• pp.1499-1511
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• 2022

Objective: This study was aimed to estimate the genetic parameters, including genetic and phenotypic correlations, of milk yield, lactation curve traits and milk composition of Thai dairy cattle from three government research farms. Methods: The data of 25,789 test-day milk yield and milk composition records of 1,468 cattle from lactation 1 to 3 of Holstein Friesian (HF) and crossbred HF dairy cattle calved between 1990 and 2015 from three government research farms in Thailand were analysed. 305-day milk yield was estimated by the Wood model and a test interval method. The Wood model was used for estimating cumulative 305-day milk yield, peak milk yield, days to peak milk yield and persistency. Genetic parameters were estimated using linear mixed models with herd, breed group, year and season of calving as fixed effects, and animals linked to a pedigree as random effects, together with a residual error. Univariate models were used to estimate variance components, heritability, estimated breeding values (EBVs) and repeatability of each trait, while pairwise bivariate models were used to estimate covariance components and correlations between traits in the same lactation and in the same trait across lactations. Results: The heritability of 305-day milk yield, peak milk yield and protein percentage have moderate to high estimates ranging from 0.19 to 0.45 while days to peak milk yield, persistency and fat percentage have low heritability ranging from 0.08 to 0.14 in lactation 1 cows. Further, heritability of most traits considered was higher in lactation 1 compared with lactations 2 and 3. For cows in lactation 1, high genetic correlations were found between 305-day milk yield and peak milk yield (0.86±0.07) and days to peak milk yield and persistency (0.99±0.02) while estimates of genetic correlations between the remaining traits were imprecise due to the high standard errors. The genetic correlations within the traits across lactation were high. There was no consistent trend of EBVs for most traits in the first lactation over the study period. Conclusion: Both the Wood model and test interval method can be used for milk yield estimates in these herds. However, the Wood model has advantages over the test interval method as it can be fitted using fewer test-day records and the estimated model parameters can be used to derive estimates of other lactation curve parameters. Milk yield, peak milk yield and protein percentage can be improved by a selection and mating program while days to peak milk yield, persistency and fat percentage can be improved by including into a selection index.

• The Journal of the Acoustical Society of Korea
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• v.20 no.4
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• pp.35-41
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• 2001

This paper describes Linear Discriminant Analysis and common vector extraction for speech recognition. Voice signal contains psychological and physiological properties of the speaker as well as dialect differences, acoustical environment effects, and phase differences. For these reasons, the same word spelled out by different speakers can be very different heard. This property of speech signal make it very difficult to extract common properties in the same speech class (word or phoneme). Linear algebra method like BT (Karhunen-Loeve Transformation) is generally used for common properties extraction In the speech signals, but common vector extraction which is suggested by M. Bilginer et at. is used in this paper. The method of M. Bilginer et al. extracts the optimized common vector from the speech signals used for training. And it has 100％ recognition accuracy in the trained data which is used for common vector extraction. In spite of these characteristics, the method has some drawback-we cannot use numbers of speech signal for training and the discriminant information among common vectors is not defined. This paper suggests advanced method which can reduce error rate by maximizing the discriminant information among common vectors. And novel method to normalize the size of common vector also added. The result shows improved performance of algorithm and better recognition accuracy of 2％ than conventional method.

• 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.

• Analytical Science and Technology
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• v.31 no.2
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• pp.96-105
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• 2018

This study aimed to improve the method for detecting eight secondary aliphatic amines (SAAs), so as to measure their concentrations in fresh water and tap water samples. NaOH (8 mL, 10 M) and benzenesulfonyl chloride (2 mL) were added to a water sample (200 mL), and the mixture was stirred at $80^{\circ}C$ for 30 min. An additional NaOH solution (10 mL) was added and the stirring was continued for another 30 min. The pH of the cooled mixture was adjusted to 5.5-6.0 by adding HCl (35 %), and the SAAs were extracted using dichloromethane (50 mL). This extraction was repeated once. The extract was then washed with $NaHCO_3$ (15 mL, 0.05 M) and dried over $Na_2SO_4$ (4 g). The extract was finally concentrated to 0.1 mL, of which $1{\mu}L$ was analyzed for SAAs by GC-MS. The linearity of the spike calibration curves was high ($r^2=0.9969-0.9996$). The detection limits of the method ranged from 0.01 to $0.20{\mu}g/L$, and its repeatability and reproducibility (expressed as relative standard deviation) were both less than 10 % (6.6-9.4 %). Its accuracy (measured in percentage error) ranged between 2.4 % and 6.1 %. The established method was applied to the analysis of five surface water and 82 tap water samples. Dimethylamine was the only SAA detected in all the water samples, and its average concentration was $0.79{\mu}g/L$ (range: $0.20-2.54{\mu}g/L$). Therefore, this study improved the analytical method for SAAs in surface water and tap water, and the regional and seasonal concentration distributions were obtained.

• Korean Journal of Food Science and Technology
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• v.36 no.5
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• pp.701-710
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• 2004

Uncertainty was quantified to evaluate calcium determination result in infant formula with AAS (Atomic Absorption Spectrometry) and ICP-AES (Inductively Coupled Plasma-Atomic Emission Spectrometry). Uncertainty sources in measurand, such as sample weight, final volume of sample, sample dilution and the instrumental result were identified and used as parameters for combined standard uncertainty based on the GUM (Guide to the expression of uncertainty in measurement) and Draft EURACHEM/CITAC Guide. Uncertainty components of each sources in measurand were identified as resolution, reproducibility and stability of chemical balance, standard material purity, standard material molecular weight, standard solution concentration, standard solution dilution factor, sample dilution factor, calibration curve, recovery, instrumental precision, reproducibility, and stability, Each uncertainty components were evaluated by uncertainty types and included to calculate combined uncertainty. The kinds of uncertainty sources and components in the analytical method by AAS and ICP-AES were same except sample dilution factor for AAS. The analytical results and combined standard uncertainties of calcium content were estimated within the certification range $(367{\pm}20\;mg/100g)$ of CRM (Certified Reference Material) and were not significantly different between method by AAS followed by ashing and method by ICP-AES followed by acid digestion as $359.52{\pm}23.61\;mg/100g\;and\;354.75{\pm}16.16\;mg/100g$, respectively. Identifying uncertainty sources related with precision, repeatability, stability, and maintaining proper instrumental conditions as well as personal proficiency was needed to reduce analytical error.

• Geophysics and Geophysical Exploration
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• v.25 no.4
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• pp.167-176
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• 2022

We designed a borehole deviation survey tool applicable for steel-cased holes, K-DEV, and developed a prototype for a depth of 500 m aiming to development of own equipment required to secure deep subsurface characterization technologies. K-DEV is equipped with sensors that provide digital output with verified high performance; moreover, it is also compatible with logging winch systems used in Korea. The K-DEV prototype has a nonmagnetic stainless steel housing with an outer diameter of 48.3 mm, which has been tested in the laboratory for water resistance up to 20 MPa and for durability by running into a 1-km deep borehole. We confirmed the operational stability and data repeatability of the prototype by constantly logging up and down to the depth of 600 m. A high-precision micro-electro-mechanical system (MEMS) gyroscope was used for the K-DEV prototype as the gyro sensor, which is crucial for azimuth determination in cased holes. Additionally, we devised an accurate trajectory survey algorithm by employing Unscented Kalman filtering and data fusion for optimization. The borehole test with K-DEV and a commercial logging tool produced sufficiently similar results. Furthermore, the issue of error accumulation due to drift over time of the MEMS gyro was successfully overcome by compensating with stationary measurements for the same attitude at the wellhead before and after logging, as demonstrated by the nearly identical result to the open hole. We believe that the methodology of K-DEV development and operational stability, as well as the data reliability of the prototype, were confirmed through these test applications.

• Journal of radiological science and technology
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• v.31 no.1
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• pp.17-23
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• 2008

Purpose : Because there is a difference depending on the environment as for an inspection equipment the important part of bone density scan and the precision/accuracy of a tester, the management of quality must be made systematically. The equipment failure caused by overload effect due to the aged equipment and the increase of a patient was made frequently. Thus, the replacement of equipment and additional purchases of new bonedensity equipment caused a compatibility problem in tracking patients. This study wants to know whether the clinical changes of patient's bonedensity can be accurately and precisely reflected when used it compatiblly like the existing equipment after equipment replacement and expansion. Materials and methods : Two equipments of GE Lunar Prodigy Advance(P1 and P2) and the Phantom HOLOGIC Spine Road(HSP) were used to measure equipment precision. Each device scans 20 times so that precision data was acquired from the phantom(Group 1). The precision of a tester was measured by shooting twice the same patient, every 15 members from each of the target equipment in 120 women(average age 48.78, 20-60 years old)(Group 2). In addition, the measurement of the precision of a tester and the cross-calibration data were made by scanning 20 times in each of the equipment using HSP, based on the data obtained from the management of quality using phantom(ASP) every morning (Group 3). The same patient was shot only once in one equipment alternately to make the measurement of the precision of a tester and the cross-calibration data in 120 women(average age 48.78, 20-60 years old)(Group 4). Results : It is steady equipment according to daily Q.C Data with $0.996\;g/cm^2$, change value(%CV) 0.08. The mean${\pm}$SD and a %CV price are ALP in Group 1(P1 : $1.064{\pm}0.002\;g/cm^2$, $%CV=0.190\;g/cm^2$, P2 : $1.061{\pm}0.003\;g/cm^2$, %CV=0.192). The mean${\pm}$SD and a %CV price are P1 : $1.187{\pm}0.002\;g/cm^2$, $%CV=0.164\;g/cm^2$, P2 : $1.198{\pm}0.002\;g/cm^2$, %CV=0.163 in Group 2. The average error${\pm}$2SD and %CV are P1 - (spine: $0.001{\pm}0.03\;g/cm^2$, %CV=0.94, Femur: $0.001{\pm}0.019\;g/cm^2$, %CV=0.96), P2 - (spine: $0.002{\pm}0.018\;g/cm^2$, %CV=0.55, Femur: $0.001{\pm}0.013\;g/cm^2$, %CV=0.48) in Group 3. The average error${\pm}2SD$, %CV, and r value was spine : $0.006{\pm}0.024\;g/cm^2$, %CV=0.86, r=0.995, Femur: $0{\pm}0.014\;g/cm^2$, %CV=0.54, r=0.998 in Group 4. Conclusion: Both LUNAR ASP CV% and HOLOGIC Spine Phantom are included in the normal range of error of ${\pm}2%$ defined in ISCD. BMD measurement keeps a relatively constant value, so showing excellent repeatability. The Phantom has homogeneous characteristics, but it has limitations to reflect the clinical part including variations in patient's body weight or body fat. As a result, it is believed that quality control using Phantom will be useful to check mis-calibration of the equipment used. A value measured a patient two times with one equipment, and that of double-crossed two equipment are all included within 2SD Value in the Bland - Altman Graph compared results of Group 3 with Group 4. The r value of 0.99 or higher in Linear regression analysis(Regression Analysis) indicated high precision and correlation. Therefore, it revealed that two compatible equipment did not affect in tracking the patients. Regular testing equipment and capabilities of a tester, then appropriate calibration will have to be achieved in order to calculate confidential BMD.