• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2007.11a
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• pp.345-349
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• 2007

In this study a fuzzy trend monitoring method for detecting the engine mechanical faults was proposed through analyzing performance trends of measurement data. The trend monitoring is an engine conditioning method which can find engine faults by monitoring important measuring parameters such as fuel flow, exhaust gas temperatures, rotational speeds, vibration. etc. Using engine condition data set as a input which generated by linear regression analysis of real engine instrument data, an application of fuzzy logic in diagnostics estimate a cause of fault in each components.

• Journal of the Korean Society of Propulsion Engineers
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• v.12 no.6
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• pp.1-6
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• 2008

This work proposes a fuzzy trend monitoring method for the fault detection of a gas turbine engine through analyzing measured performance data trend. The proposed trend monitoring technique can diagnose the engine status by monitoring major engine measured parameters such as fuel flow rate, exhaust gas temperature, rotor rotational speed and vibration, and then analyzing their time deppendent changes. In order to perform this, firstly the measured engine performance data variation is formulated using Linear Regression, and then faults are isolated and identified using fuzzy logic.

• Korean Journal of Pharmacognosy
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• v.45 no.2
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• pp.113-120
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• 2014

Generally, Gwakhyangjeonggi-san has been used for treatment of diarrhea-predominant irritable bowel syndrome. In this study, an ultra-performance liquid chromatography-electrospray ionization-mass spectrometer method was established for the simultaneous quantification of marker compounds 1-20 in Gwakhyangjeonggi-san water extract. All analytes were separated by gradient elution using two mobile phases on a UPLC BEH $C_{18}$ ($100{\times}2.1mm$, $1.7{\mu}m$) column and maintained at $45^{\circ}C$. The injection volume was $2.0{\mu}L$ and the flow rate was 0.3 mL/min with detection at mass spectrometer. Regression equations of the compounds 1-20 were acquired with $r^2$ values ${\geq}0.9950$. The values of limit of detection and quantification of all analytes were 0.01-2.79 ng/mL and 0.03-8.37 ng/mL, respectively. The amounts of the compounds 1-20 in Gwakhyangjeonggi-san water extract were not detected $-3,236.67{\mu}g/g$. The established LC-MS/MS methods will be valuable to improve quality control of traditional herbal formula, Gwakhyangjeonggi-san.

• The KIPS Transactions:PartC
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• v.11C no.1
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• pp.89-98
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• 2004

AQM (Active Queue Management) techniques such as RED (Random Early Detection) which be proposed to solve the congestion of internet perform congestion control effectively for TCP data. However, in the situation where TCP and UDP share the bottleneck link, they can not solve the problems of the unfairness and long queueing delay. In this paper, we proposed an simple queue management algorithm, called PSRED (Protocol Sensitive RED), that improves fairness and decreases queueing delay. PSRED algorithm improves fairness and decreases average queue length by distinguishes each type of flow in using protocol field of packets and applies different drop functions to them respectively.

• Journal of Power System Engineering
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• v.20 no.2
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• pp.66-72
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• 2016

As a method to improve the equipment reliability, early warning researches that can be detected fault symptom of an equipment at an early stage are being performed out among developed countries. In this paper, when abnormal signal is input to actual normal signal of a pump, early detection studies on pump's fault symptom were carried out with auto-associative kernel regression as an advanced pattern recognition algorithm. From analysis, correlations among power of motor driving pump, discharge flow of pump, power output of pump, and discharge pressure of pump are exited. When the abnormal signal is input to one of those normal signals, the other expected values are changed due to the influence of the abnormal signal. Therefore, the fault symptom of pump through the early-warning index is able to detect at an early stage.

• Korean Journal of Veterinary Research
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• v.58 no.1
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• pp.27-31
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• 2018

Canine coronavirus is a single-stranded RNA virus that causes enteritis in dogs of any age. Coronaviral enteritis is seldom definitively diagnosed, since it is usually much less severe than many other types of enteritis and is self-limiting. Conventional diagnostics for the canine coronaviral enteritis such as polymerase chain reaction (PCR), virus isolation, and electron microscopic examination are inappropriate for small animal clinics due to the complicated experimental processes involved. Therefore, a commercially available lateral flow test kit based on chromatographic immunoassay techniques was tested to evaluate its performance as a first-line diagnostic test kit that could be used in clinics. The coronavirus antigen test kit detected canine coronavirus-infected dogs with 93.1% sensitivity and 97.5% specificity. The detection limit of the test kit was between $1.97{\times}10^4/mL$ and $9.85{\times}10^3/mL$ for samples with a 2-fold serial dilution from $1.25{\times}10^6\;TCID_{50}$ ($TCID_{50}$, 50% tissue culture infectious dose). Additionally, the test kit had no cross-reactivity with canine parvovirus, distemper virus, or Escherichia coli. Overall, the commercially available test kit showed good diagnostic performance in a clinical setting, with results similar to those from PCR, confirming their potential for convenient and accurate use in small animal clinics.

• Nuclear Engineering and Technology
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• v.48 no.5
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• pp.1280-1290
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• 2016

This paper presents an advanced estimation method for obtaining the probability density functions of a damage parameter for valve leakage detection in a reciprocating pump. The estimation method is based on a comparison of model data which are simulated by using a mathematical model, and experimental data which are measured on the inside and outside of the reciprocating pump in operation. The mathematical model, which is simplified and extended on the basis of previous models, describes not only the normal state of the pump, but also its abnormal state caused by valve leakage. The pressure in the cylinder is expressed as a function of the crankshaft angle, and an additional volume flow rate due to the valve leakage is quantified by a damage parameter in the mathematical model. The change in the cylinder pressure profiles due to the suction valve leakage is noticeable in the compression and expansion modes of the pump. The damage parameter value over 300 cycles is calculated in two ways, considering advance or delay in the opening and closing angles of the discharge valves. The probability density functions of the damage parameter are compared for diagnosis and prognosis on the basis of the probabilistic features of valve leakage.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.1
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• pp.123-131
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• 2020

There have been a lot of studies in the past for the method of predicting the failure of a machine, and recently, a lot of researches and applications have been generated to diagnose the physical condition of the machine and the parts and to calculate the remaining life through various methods. Survival models are also used to predict plant failures based on past anomaly cycles. In particular, special machine that reflect the fluid flow and process characteristics of chemical plants are connected to hundreds or thousands of sensors, so there are not many factors that need to be considered, such as process and material data as well as application of derivative variables. In this paper, the data were preprocessed through time series anomaly detection based on unsupervised learning to predict the abnormalities of these special machine. Next, clustering results reflecting clustering-based data characteristics were applied to produce additional variables, and a learning data set was created based on the history of past facility abnormalities. Finally, the prediction methodology based on the supervised learning algorithm was applied, and the model update was confirmed to improve the accuracy of the prediction of facility failure. Through this, it is expected to improve the efficiency of facility operation by flexibly replacing the maintenance time and parts supply and demand by predicting abnormalities of machine and extracting key factors.

• Bulletin of the Korean Chemical Society
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• v.28 no.11
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• pp.2083-2088
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• 2007

Biosensor based on rugate PSi interferometer for the detection of avidin has been described. Rugate PSi fabricated by applying a computer-generated pseudo-sinusoidal current waveform has been prepared for the application as a label-free biosensor based on porous silicon interferometer. The fabrication, optical characterization, and surface derivatization of a rugate PSi has been described. The method to fabricate biotinderivatized rugate PSi has been investigated. The surface and cross sectional morphology of rugate PSi are obtained with SEM. FT-IR spectroscopy is used to characterize the oxidation and functionalization reaction of rugate PSi sample. Binding of the avidin into the biotin-derivatized rugate PSi induces a change in refractive index. A red-shift of reflectivity by 18 nm in the reflectivity spectrum is observed, when the biotin-modified rugate PSi was exposed to a flow of avidin.

• Bulletin of the Korean Chemical Society
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• v.25 no.1
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• pp.73-78
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• 2004

A highly sensitive detecting method has been developed for determining part per billion of sulfur in $H_2S$/Ar plasma. The method is based on the excitation of Ar/$H_2S\;or\;Ar/H_2S/O_2$ mixture in hollow cathode glow discharge sustained by radiofrequency (RF) or 60 Hz AC power and the spectroscopic measurement of the intensity of emission lines from electronically excited $S_2^*\;or\;SO_2^*$ species, respectively. The RF or AC power needed for the excitation did not exceed 30 W at a gas pressure maintained at several mbar. The emission intensity from the $SO_2^*$ species showed excellent linear response to the sulfur concentration ranging from 5 ppbv, which correspond to S/N = 5, to 500 ppbv. But the intensity from the $S_2^*$ species showed a linear response to the $H_2S$ only at low flow rate under 20 sccm (mL/min) of the sample gas. Separate experiments using $SO_2$ gas as the source of sulfur demonstrated that the presence of $O_2$ in the argon plasma is essential for obtaining prominent $SO_2^*$ emission lines.