• Proceedings of the Korean Vacuum Society Conference
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• 2010.02a
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• pp.473-473
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• 2010

Plasma is widely used in various commercial etchers and chemical vapor deposition. Unfortunately, real-time plasma process monitoring is still difficult. Some methods of plasma diagnosis is improved, however, it is possible for real-time plasma diagnosis to use non-intrusive probe only. In this research, the object is to investigate the suitability of using impedance analysis and optical emission spectroscopy (OES) for real-time plasma process monitoring. It is assumed that plasma system is a equivalent circuit. Therefore, V-I probe is used for measuring impedance, which can be a new non-intrusive probe for plasma diagnosis. From impedance data, we tried to analyse physical properties of plasma. And OES, the other method of plasma diagnosis, is a typical non-intrusive probe for analyzing chemical properties. The amount of the OES data is typically large, so this poses a difficulty in extracting relevant information. To solve this problem, principal component analysis (PCA) can be used. For fundamental information, Ar plasma and $O_2$ plasma are used in this experiment. This method can be applied to real-time endpoint and fault detections.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.132-134
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• 2006

To improve equipment throughput and device yield, a malfunction in plasma equipment should be accurately diagnosed. A recognition model for plasma diagnosis was constructed by applying neural network to scanning electron microscope (SEM) image of plasma-etched patterns. The experimental data were collected from a plasma etching of tungsten thin films. Faults in plasma were generated by simulating a variation in process parameters. Feature vectors were obtained by applying direct and wavelet techniques to SEM Images. The wavelet techniques generated three feature vectors composed of detailed components. The diagnosis models constructed were evaluated in terms of the recognition accuracy. The direct technique yielded much smaller recognition accuracy with respect to the wavelet technique. The improvement was about 82%. This demonstrates that the direct method is more effective in constructing a neural network model of SEM profile information.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.96-98
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• 2006

A new ex-situ model to diagnose a plasma processing equipment was presented. The model was constructed by combining wavelet, scanning electron microscope, ex-situ measurement of etching profile, and neural network. The diagnosis technique was applied to a tungsten etching process, conducted in a $SF_6$ helicon plasma. The wavelet was used to characterize detailed variations of plasma-etched surface. The diagnosis model was constructed with the vertical wavelet component. For comparison, a conventional model was built by using the estimated profile data. Compared to the conventional model, the wavelet-based model, demonstrated a much improved diagnosis.

• Journal of the Semiconductor & Display Technology
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• v.17 no.2
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• pp.16-19
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• 2018

The development speed of semiconductor and display device manufacturing technology is growing faster than the development speed of process equipment. So, there is a growing need for process diagnostic technology that can measure process conditions in real time and directly. In this study, a plasma diagnosis was carried out using impedance variation due to the plasma discharge. Variation of the measurement impedance appears as a voltage change at the reference impedance, and the plasma density is calculated using this. The above experiment was conducted by integrating the plasma diagnosis system and the linear atmospheric pressure DBD plasma source. It was confirmed that plasma density varies depending on various parameters (gas flow rate, $Ar/O_2$ mixture ratio, Input power).

• Journal of Preventive Medicine and Public Health
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• v.43 no.5
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• pp.451-454
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• 2010

Objectives: The American Diabetes Association (ADA) has recently recommended the HbA1c assay as one of four options for making the diagnosis of diabetes mellitus, with a cut-point of $\geq$ 6.5%. We compared the HbA1c assay and the fasting plasma glucose level for making the diagnosis of diabetes among Korean adults. Methods: We analyzed 8710 adults (age 45-74 years), who were not diagnosed as having diabetes mellitus, from the Namwon study population. A fasting plasma glucose level of $\geq$126 mg/dL and an A1c of $\geq$ 6.5% were used for the diagnosis of diabetes. The kappa index of agreement was calculated to measure the agreement between the diagnosis based on the fasting plasma glucose level and the HbA1c. Results: The kappa index of agreement between the fasting plasma glucose level and HbA1c was 0.50. Conclusions: The agreement between the fasting plasma glucose and HbA1c for the diagnosis of diabetes was moderate for Korean adults.

• Journal of Surface Science and Engineering
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• v.54 no.6
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• pp.348-356
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• 2021

In this study, optical diagnosis of plasma was performed for nitrogen doping in graphene using a horizontal inductively coupled plasma (ICP) system. Graphene was prepared by mechanical exfoliation and the ICP system using nitrogen gas was ignited for plasma-induced and defect-suppressed nitrogen doping. In order to derive the optimum condition for the doping, plasma power, working pressure, and treatment time were changed. Optical emission spectroscopy (OES) was used as plasma diagnosis method. The Boltzmann plot method was adopted to estimate the electron excitation temperature using obtained OES spectra. Ar ion peaks were interpreted as a reference peak. As a result, the change in the concentration of nitrogen active species and electron excitation temperature depending on process parameters were confirmed. Doping characteristics of graphene were quantitatively evaluated by comparison of intensity ratio of graphite (G)-band to 2-D band, peak position, and shape of G-band in Raman profiles. X-ray photoelectron spectroscopy also revealed the nitrogen doping in graphene.

• Korean Journal of Veterinary Research
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• v.32 no.2
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• pp.259-265
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• 1992

A study was conducted to improve the reproductive performance of Korean native goats. The length of estrous cycle and plasma progesterone concentrations during each cycles were determined by both radioimmunoassay and estrus behaviours, and the results were used in the early pregnancy diagnosis. The estrous cycles were classified into the short(l8 days or shorter, average 16.7 days), normal(19 to 22 days, average 20.9 days) and long(23 days and longer, average 23.8 days)cycle. The average length of the 19 estrous cycles was 20.8 days. Plasma progesterone concentrations in 12 normal cycles were the lowest(0.10 ng/ml) at estrus, remained high from 6 to 16 days(range : 4.43~7.93 ng/ml) and drastically decreased thereafter to reach minimal concentrations at the next estrus. Plasma progesterone concentrations were measured for early pregnancy diagnosis at 0, 10 and 20 days after mating in the 12 Korean native goats. Plasma progesterone concentrations in the pregnant goats at 20 days after mating were significantly higher than in the non-pregnant goats(p<0.001). Of the 12 goats, 10 were confirmed pregnancy by both progesterone concentrations and kidding. The accuracy of the pregnancy diagnosis based on plasma progesterone concentrations was 100% for positive as well as for negative.

• Journal of Embryo Transfer
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• v.11 no.1
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• pp.85-91
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• 1996

Plasma progesterone concentrations were measured by using radjoimmunoassay for early diagnosis of pregnancy in Cheju-native mares. A total of 226 pony mares were examined for pregnancy during breeding and non breeding seasons. Plasma progesterone levels 20~23 days after the onset of oestrus were 4.67+O.67ng /rnl and O.55+O.O4ng /ml for mares becornrning pregnant and not pregnant after the estrus, respectively, and there was a significant differences (p<0.01) between the two groups. Progesterone concentration of pregnant mares gradually increased in 30 days andreached a peak (10.3ng /ml) during the third month of gestation. However, the concentration decresed to the base line (1.llng /rnl) at 7 months and gradually increased again as foaling approached (2.lng /ml). Early diagnosis for pregnancy of Cheju mares by progesterone level at 20~23 days after onset of oestrus was 88% accurate when 4.6ng /ml was used to classify mares as pregnancy and below 1.3ng /rnl was used to determine nonpregnant mares. However, the accuracy of the diagnosis was improved to 96% when a progesterone level of above 2ng /mi was used to classify mares for pregnancy. Diagnosis for pregnancy was 69.6% accurate when mares were classified as pregnancy by horse owners during breeding season. The progesterone levels of pregnant and non-pregnant mares during non-breeding season varied greatly between individual animals, Plasma progesterone levels of pregnant animals ranged from 3.5ng /mi to above 6.2ng /mi whereas similar values were observed in non-pregnant animals. Radioirnrnunoassay technicjues can be applied for the early pregnant diagnosis of Cheju native mares when progesterone levels are measured during the early gestation period (18~23 days after onset of oestrus). However, progesterone concentration of mares in non-breeding season is conisidered unsuitable as a indicator of pregnant diagnosis.

• Journal of Veterinary Clinics
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• v.32 no.1
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• pp.62-68
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• 2015

There is no reliable indicator available for the diagnosis of horse laminitis, although the disease is common and costly. This study was performed to develop a specific diagnostic biomarker for laminitis. We have identified 33 differentially expressed proteins in plasma of a horse suffering laminitis that is experimentally induced by an overdose of oligofructose, in comparison with normal horse plasma. Among the proteins, myosin-9 mRNA was found in RNA sequencing analysis to be expressed specifically in laminitis tissues compared to other horse tissues. It is thus suggested that expression of plasma myosin-9 may be used for the diagnosis of equine laminitis.

• Journal of the Semiconductor & Display Technology
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• v.2 no.4
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• pp.13-17
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• 2003

An adaptor is designed for chamber impedance measurement of plasma process. Copper rod, fixed board and compensation circuit are the major components of the adaptor. An adaptor can be to measure chamber impedance on time unless stopping a process and Data to measure can do the database. We can use it to a criteria data for a failure diagnosis. So developed adaptor could be used for diagnosis the plasma process chamber in semiconductor industry.