• Journal of Environmental Health Sciences
• /
• v.40 no.2
• /
• pp.114-126
• /
• 2014

Objectives: We aimed to develop a measurement method of five metabolites of trichloroethylene (TCE) in a concurrent biological sample, e.g., trichloroacetic acid (TCA), dichloroacetic acid (DCA), S-(1,2-dichlorovinyl) glutathione (DCVG), S-(1,2-dichlorovinyl)-L-cysteine (DCVC), and N-Acetyl-S-(1,2-dichlorovinyl)-L-cysteine (NAcDCVC) and to validate the method before application to pharmacokinetic study. Methods: TCE metabolites were simultaneously analyzed using high performance liquid chromatography coupled with electrospray ionization mass spectrometry (HPLC-ESI-MS/MS) with as little as 50 ${\mu}L$ of serum and urine. DCA, TCA and NAcDCVC were extracted with diethyl ether, while DCVC and DCVG were extracted by solid phase extraction. This method was validated according to the guidelines for bioanalytical method validation of the Korean National Institute of Toxicological Research. Then, we determined the five metabolites in five strains of mice at 24 hr after exposure to 1 g TCE /kg body weight. Results: The limits of detection for the five metabolites in biological samples ranged from 0.001 to 0.076 nmol/mL, which is comparable to or better than those previously reported. Most calibration curves showed good linearity ($R^2=0.99$), and between-batch variation was less than 20% expressing acceptable robustness and reproducibility. Using this method, we found TCA and DCA were detected in all test mice at 24 hr after the oral administration while NAcDCVC and DCVC were detected in some strains, which showed strain-dependent metabolism of TCE. Conclusions: The present method could provide robust and accurate measurements of major key metabolites of TCE in biological media, which allowed concurrent analysis of TCE metabolism for limited amounts of biospecimens.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.34 no.9
• /
• pp.1305-1310
• /
• 2010

In a practical design process, the method of extracting the design space information of the complex system for verifying, improving, and optimizing the design process by taking into account the design variables and their shape tolerance is very important. Finite element analysis has been successfully implemented and integrated with design of experiment such as D-Optimal array; thus, a response surface model and optimization tools have been obtained, and design variables can be optimized by using the model and these tools. Then, to guarantee the robustness of the design variables, a robust design should be additionally performed by taking into account the statistical variation of the shape tolerance of the optimized design variables. In this study, a new approach based on the use of the response surface model is proposed; in this approach, the standard normal distribution of the shape tolerance is considered. By adopting this approach, it is possible to simultaneously optimize variables and perform a robust design. This approach can serve as a means of efficiently modeling the trade-off among many conflicting goals in the applications of finite element analysis. A case study on the robust optimal design of disc brakes under thermal loadings was carried out to solve multiple objective functions and determine the constraints of the design variables, such as a thermal deformation and weight.

• The Journal of the Acoustical Society of Korea
• /
• v.18 no.6
• /
• pp.49-56
• /
• 1999

In many continuous speech recognition systems based on HMMs, decision tree-based state tying has been used for not only improving the robustness and accuracy of context dependent acoustic modeling but also synthesizing unseen models. To construct the phonetic decision tree, standard method performs one-level pruning using just single Gaussian triphone models. In this paper, two novel approaches, two-level decision tree and multi-mixture decision tree, are proposed to get better performance through more accurate acoustic modeling. Two-level decision tree performs two level pruning for the state tying and the mixture weight tying. Using the second level, the tied states can have different mixture weights based on the similarities in their phonetic contexts. In the second approach, phonetic decision tree continues to be updated with training sequence, mixture splitting and re-estimation. Multi-mixture Gaussian as well as single Gaussian models are used to construct the multi-mixture decision tree. Continuous speech recognition experiment using these approaches on BN-96 and WSJ5k data showed a reduction in word error rate comparing to the standard decision tree based system given similar number of tied states.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.22 no.3
• /
• pp.446-452
• /
• 2021

As a higher standard for food consumption is required, the consumption of chicken meat that can satisfy the subdivided food preferences is increasing. In March 2003, the quality criteria for chicken carcasses notified by the Livestock Quality Assessment Service suggested quality grades according to fecal contamination and the size and weight of blood and bruises. On the other hand, it is too difficult for human inspection to qualify mass products, which is key to maintaining consistency for grading thousands of chicken carcasses. This paper proposed the computer vision algorithm as a non-destructive inspection, which can identify chicken carcass parts according to the detailed standards. To inspect the chicken carcasses conveyed at high speed, the image calibration was involved in providing robustness to the side effect of external lighting interference. The separation between chicken and background was achieved by a series of image processing, such as binarization based on Expectation Maximization, Erosion, and Labeling. In terms of shape analysis of chicken carcasses, the features are presented to reveal geometric information. After applying the algorithm to 78 chicken carcass samples, the algorithm was effective in segmenting chicken carcass against a background and analyzing its geometric features.

• Korean Journal of Poultry Science
• /
• v.47 no.2
• /
• pp.95-105
• /
• 2020

This study presents the production characteristics and physiological characteristics of five Korean native chicken (KNC) breeds consisting of Hwanggalsaek Jaeraejong (HJ), Korean Rhode Island Red (KR), Korean White Leghorn (KL), Korean Brown Cornish (KC), and Korean Ogye (KO). We investigated their production performances, vitalities, and stress responses. We measured the survival rate, body weight, age at first egg-laying, hen-day egg production, egg weight, amount of telomeric DNA, heterophil-lymphocyte ratio (H/L ratio), and heat shock protein (HSP)-70, HSP-90α and HSP-90β gene expression levels for 493 KNCs. The survival rate was highest in KR, and lowest in KO. Body weights were steadily high in the order of KC, KR, HJ, KO and KL. Average hen-day egg production was highest in KL, and lowest in KC. While the amount of telomeric DNA was highest in KR, and lowest in KC. Furthermore, both the H/L ratio and the HSP-90β gene expression level were highest in KC, and lowest in KR. These results indicated that the KR breed was highly resistant to stress, whereas KC was more susceptible to stress. Taken together, it is considered that with improvements the KC breed would be more suited to be used as a Korean broiler breed while KL would be more appropriately used as a Korean layer breed. In addition, it is considered that the KR breed is appropriate to be used as a maternal chicken breeder based on good production capacity and excellent robustness, while the HJ breed is desirable to be improved as a high-quality Korean meat breed based on its excellent meat quality.