• Journal of Veterinary Clinics
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• v.16 no.1
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• pp.118-127
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• 1999

The aim of this study was to establish the method of differential diagnosis between developing and regressing corpus luteum in cows. Plasma progesterone (P$_4$) concentrations were determined by radioimmunoassay in slaughtered, cycling and pregnant cows. Ultrasonography was used to measure the corpus luteum size and histogram values for determining the correlationships between corpus luteum area or histogram values and plasma P$_4$ concentrations. The corpora lutea were monitored in vitro (water-bath scanning) by using ultrasonography with 7.5 MHz linear-array transducer in 196 slaughtered cows. The correlation coefficient between corpus luteum area and plasma P$_4$ concentrations was 0.46 (p<0.01), and between histogram values and plasma P$_4$ concentrations was -0.44 (p<0.01), respectively. The corpora lutea were monitored by ultrasonography with 5.0 MHz linear-array transrectal transducer in 188 cycling and 30 pregnant cows. The corpus luteum areas and plasma P4 concentrations were significantly different between regressing and other corpora lutea (p<0.01), and also histogram values were significantly different between regressing and developing corpola lutea (p＜0.01). The correlation coefficients between corpus luteum areas and plasma P$_4$ concentrations were 0.76 (p<0.01), 0.71 (p<0.01), 0.65 (p＜0.05) and 0.68 (p<0.05), and between histogram values and plasma P$_4$ concentrations were 0.74 (p<0.05), 0.71 (p＜0.01), -0.52 (p<0.05) and 0.65 (p＜0.05) in developing, functional, regressing and pregnant corpora lutea, respectively. These results indicate that corpus luteum areas and plasma P$_4$ concentrations were highly correlated in all stages of corpus luteum. The histogram values and plasma P$_4$ concentrations were positive correlated in developing, functional and pregnant corpora lutea, but negative correlated in regressing corpus luteum. Therefore, the measurement of corpus luteum area and histogram value by ultrasonography is reliable method for the assessment of luteal function, specially developing and regressing corpus luteum.

• Journal of Veterinary Clinics
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• v.16 no.1
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• pp.128-137
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• 1999

Plasma progesterone (P$_4$) concentrations were measured for confirming the estrus observation and for the early pregnancy diagnosis in 130 cows of small farmers. Ultrasonographic examinations were performed from day 30 after artificial insemination to establish the characteristic ultrasonographic appearances of gestational structures in each pregnant stages. Of the 130 cows inseminated, 111 cows (85.4%) were an ovulatory estrus, 12 cows (9.2%) were an unovulatory estrus, and 7 cows (5.4%) were the error of estrus detection, respectively. The accuracy for early pregnancy diagnosis in 111 ovulatory estrus cows achieved when the discriminatory concentration at day 21 after artificial insemination was placed at 3.0 ng-/ml in plasma, was 86.7 % for positive diagnosis and 100% for negative diagnosis, respectively. Pregnancy diagnosis by ultrasonography were performed to evaluate gestational structures from day 30 after artificial insemination in 83 cows. Pregnant cows were 72 of 83 cows. The characteristic ultrasonography of gestational structures in each gestational stages was as follows. The embryo proper was observed within anechoic fetal fluid between 28 and 40 days after insemination, and amnion and embryonic heartbeat was also detected in this period. Between days 41 and 50, embryo proper was detected as an discriminated from head and body, and forelimb buds and hindlimb buds were also observed in this period. Between days 51 and 60, an embryo proper was clearly discriminated from head and body, and fetal movement, forelimb buds and hindlimb buds were observed in this period. Between days 61 and 70, fetus was completely developed, and fetal skeleton, organs and cotyledon were observed. After day 71, each organs of fetus were rapidly developed and a fetus was partially observed in screen because fetus was too big and larger, These results indicate that plasma P$_4$ determination at days 0,6 and 21 after artificial insemination can be utilized for confirming the estrus observation and for early pregnancy diagnosis. Also, ultrasonography was reliable method for early pregnancy diagnosis at day 30 after artificial insemination.

• Korean Journal of Veterinary Research
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• v.31 no.4
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• pp.529-534
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• 1991

Plasma progesterone concentrations were measured from 97 Che-ju native mares throughout the estrous cycle, Day 20 to 23, 5 to7 months of pregnancy, and gestation period (<1 to 7 months) using the radioimmunoassay techniques for pregnancy diagnosis. Plasma progesterone concentrations during the estrous cycle were the lowest (<1.0ng/ml) at estrus, remained high from 9 to 18 days (3.7~7.6ng/ml) and drastically decreased thereafter to reach minimal concentrations at the next estrus. Plasma progesterone concentrations at Day 21 to 24 were a significantly different between in pregnant mares (>5.7ng/ml) and in non-pregnant mares (<1.0ng/ml). The accuracy of the pregnancy diagnosis based on plasma progesterone concentrations at Day 20 to 23 was 86.7% for positive and 100% for negative, whereas on 5 to 7 months was 66.7% for positive and 71.0% for negative, respectively. Plasma progesterone concentrations during the gestation period(1 to 7 months) increased after 1 month of pregnancy, with peak concentrations(>8.0ng/ml) occurring between 60 to 100 days of pregnancy, and decreased below 1.7ng/ml after 6 months of pregnancy.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.138-140
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• 2006

A new diagnosis model was constructed by combining atomic force microscopy (AFM), wavelet, and neural network. Plasma faults were characterized by filtering AFM-measured etch surface roughness with wavelet. The presented technique was evaluated with the data collected during the etching of silicon oxynitride thin film. A total of 17 etch experiments were conducted. Applying wavelet to AFM, surface roughness was detailed into vertical, horizon%at, and diagonal components. For each component, neural network recognition models were constructed and evaluated. Comparisons revealed that the vertical component-based model yielded about 30% improvement in the recognition accuracy over others. The presented technique was evaluated with the data collected during the etching of silicon oxynitride thin film. A total of 17 etch experiments were conducted

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.8
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• pp.4155-4161
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• 2016

Biliary obstruction is a common clinical manifestation of various conditions, including extrahepatic cholangiocarcinoma. However, a screening test for diagnosis of extrahepatic cholangiocarcinoma in patients with biliary obstruction is not yet available. According to the rationale that the biliary system plays a major role in lipid metabolism, biliary obstruction may interfere with lipid profiles in the body. Therefore, plasma lipidomics may help indicate the presence or status of disease in biliary obstruction suspected extrahepatic cholangiocarcinoma. This study aimed to use plasma lipidomics for diagnosis of extrahepatic cholangiocarcinoma in patients with biliary obstruction. Plasma from healthy volunteers, patients with benign biliary obstruction extrahepatic cholangiocarcinoma, and other related cancers were used in this study. Plasma lipids were extracted and lipidomic analysis was performed using matrix-assisted laser desorption ionization time-of-flight mass spectrometry. Lipid profiles from extrahepatic cholangiocarcinoma patients showed significant differences from both normal and benign biliary obstruction conditions, with no distinction between the latter two. Relative intensity of the selected lipid mass was able to successfully differentiate all extrahepatic cholangiocarcinoma samples from patient samples taken from healthy volunteers, patients with benign biliary obstruction, and patients with other related cancers. In conclusion, lipidomics is a non-invasive method with high sensitivity and specificity for identification of extrahepatic cholangiocarcinoma in patients with biliary obstruction.

• Korean Journal of Veterinary Research
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• v.30 no.2
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• pp.249-253
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• 1990

Plasma progesterone concentrations were measured in 24 Korean native cows by a radioimmunoassay at 0, 6 and 20 days after insemination. As a result, 23 cows (95.8%) were judged to be in estrus with ovulation and one cow (4.2%) was judged to be in estrus without ovulation. Plasma progesterone concentrations at 20 days after insemination were $5.11{\pm}1.33$ (mean${\pm}$SD, range 3.20~7.86) ng/ml in pregnant cows and $0.35{\pm}0.10$ (range 0.30~0.50) ng/ml in nonpregnant cows. Of the 20 cows, 18 cows were confirmed the pregnant by rectal palpation at 60 days after insemination. The accuracy of the pregnancy diagnosis based on plasma progesterone concentration was 90 % for positive case and 100% for negative case.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.16 no.1
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• pp.11-18
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• 2003

In this study we attempted to diagnose the states and properties of plasma generated while depositing SiON thin films using PECVD (Plasma enhanced chemical vapor deposition). The temperature and density of electron gases formed in a PECVD chamber were measured by Langmuir probe method. Their values were also estimated under some assumptions we made in this work. Comparison between experimental and theoretical values of the temperature and density of electron gases was made. The experimental and estimated results revealed that, as RF Power gets higher, the electron density linearly increases, but that the electron temperature does not vary.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2006.12a
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• pp.71-74
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• 2006

Discharge of the flat lamp lighting source research arc requested very much. For improving brightness, life time, efficiency of flat lamp, plasma diagnosis of the flat lamp lighting source to understand property of lighting source is very important. distance of discharge electrode is 5.5mm and width is 16.5mm, we measured electron temperature and electron density measured with single langmuir probe in flat lamp. we tested the discharge from 100 Torr to 300 Torr pressure. the Pulse is rectangular pulse with frequency 20kHz and Duty ratio 20%. Resultly, electron temperature decreases and electron density increase as increase the gas pressure and electron temperature decreases and electron density increase as increase the voltage.

• Proceedings of the Korean Vacuum Society Conference
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• 2010.02a
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• pp.413-413
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• 2010

In semiconductor manufacturing field, all equipments have various sensors to diagnosis the situations of processes. For increasing the accuracy of diagnosis, hundreds of sensors are emplyed. As sensors provide millions of data, the process diagnosis from them are unrealistic. Besides, in some cases, the results from some data which have same conditions are different. We want to find some information, such as data and knowledge, from the data. Nowadays, fault detection and classification (FDC) has been concerned to increasing the yield. Certain faults and no-faults can be classified by various FDC tools. The uncertainty in semiconductor manufacturing, no-faulty in faulty and faulty in no-faulty, has been caused the productivity to decreased. From the uncertainty, the rough set theory is a viable approach for extraction of meaningful knowledge and making predictions. Reduction of data sets, finding hidden data patterns, and generation of decision rules contrasts other approaches such as regression analysis and neural networks. In this research, a RGB sensor was used for diagnosis plasma instead of optical emission spectroscopy (OES). RGB data has just three variables (red, green and blue), while OES data has thousands of variables. RGB data, however, is difficult to analyze by human's eyes. Same outputs in a variable show different outcomes. In other words, RGB data includes the uncertainty. In this research, by rough set theory, decision rules were generated. In decision rules, we could find the hidden data patterns from the uncertainty. RGB sensor can diagnosis the change of plasma condition as over 90% accuracy by the rough set theory. Although we only present a preliminary research result, in this paper, we will continuously develop uncertainty problem solving data mining algorithm for the application of semiconductor process diagnosis.

• Proceedings of the Korean Vacuum Society Conference
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• 2015.08a
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• pp.153-153
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• 2015

Application of the plasma is already highlighted as a new technology in the last few years. In these days, there are lots of attempt in various application with plasma in that it is known as an effective treatment to animal, plants, material and so on. Plasma in liquid, one of new plasma applications, has advantages in ability to treat bio-cell or solutions. For example, electro-surgery, water purification, radical generation and so on. Especially, plasma discharge in solutions is very useful technique and difficult to generate due to electrolysis, vaporization and something else. In this study, we have performed plasma discharge and checked sustainability of plasma in solution(saline 0.9%). And we have measured basic characteristics of plasma in liquid. Such as electrical energy and plasma density are calculated from discharging current and voltage. Also, its thermal energy is measured with IR camera.