• Proceedings of the KSMRM Conference
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• 2007.10a
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• pp.19-19
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• 2007

• Korean Journal of Oriental Medicine
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• v.12 no.2 s.17
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• pp.103-113
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• 2006

Objectives we intended to know how much did it relate with the results between the instruments of diagnosis by using methods of three factors - QSCCII, PSSC(Phonetic System for Sasang Constitution)-2004, and body measurement which are usually used in diagnosing the Sasang Constitution in clinics Methods We diagnosed Sasang constitution through QSCCII, PSSC(Phonetic System for Sasang Constitution)-2004, Body measurement as a dignosis factors and we used Kappa coefficient to estimate simularity between diagnosis factors, and SPSS 12.0K to analyze data Results and conchusions 1. The orders of agreement statistics are different in the currency of Sasang Constitution diagnosis, Soeum-in was highest and Taeum-in lowest in the the fricency of Sasang Conctitution Diagnosis in the QSCCII, Soeum-in was highest Soyang-in lowest in the PSSC and Taeum-in highest, Soyang-in lowest in the body measurement so, we analogized incorrection in Sasang Constitution Diagnosis 2. Among 443 subjects, 156 (35.3%) had same dignosis in three Sasang Constitution factors. It means agreement statistics among factors of diagnosis are very low, so it is absolutely nessessary to research connection among those, especially Soyang-in part 3. Totally, it is not robust to apply these factors on Sasang Constitution diagnosis, especially agreement statistics between two kinds of Sasang Constitution diagnosis as $0.358{\sim}0.380$. However, we can have a possibility the more we use Sasang Constitution dignosis factors, the higher the agreement statistics is, through the ascending of agreement statistics as $0.526{\sim}0.592$, among three kinds of Sasang Constitution diagnosis To evaluate accuracy of Sasang Constitution diagnosis, it is nessessary to collect data from the subjects who are dignosed through the evidences such as herb medicine, disease and normal symption observation, etc. Using these data, we have to evaluate correction of seperated Sasang Constitution diagnosis methods and to connect those.

• Journal of Physiology & Pathology in Korean Medicine
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• v.23 no.1
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• pp.186-191
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• 2009

In the study on the waveform analysis of radial artery pulse diagnosis, we need to establish fundaments of contemporary pulse diagnosis research. As we will to do experimental research on the difference of pulse waveform on the radial artery with applied variations of pressure(5 stage-pressure) and measuring position(CHON, KWAN, CHEOG). First of all, in this research, we did the experiment of the study on the waveform analysis of radial artery(left KWAN) pulse dignosis by using 3 dimension pulse meter and analyzer (3D MAC). As a result. we extracted the seven measurement fluents : energy(E), size of cycle(h1), size of reflection cycle(h2), time of reflection cycle(t2), time of contraction (t4), width of cycle(w), area of waveform(A) by the statistically reasonable differences. We expect that the seven measurement fluents contribute to divide the situation through the results of waveform analysis of radial artery.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.537-542
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• 1994

This paper gives a general survey of model-based fault detection and dignosis methods. Specific applications of these ideas to boiler systems will also be discussed. A novel aspect of the fault detection technique described here is that it explicitly accounts for the effects of using simplified models and errors from linearizing a nonlinear system at an operation point. Inclusion of these effects is shown to lead to novel fault detection procedures which outperform existing methods when applied to typical fault scenarios in boiler systems.

• Proceedings of the KIEE Conference
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• 2002.07a
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• pp.151-153
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• 2002

This paper proposes a concept for fault diagnosis system based on the relay coordination to deal with unavoidable uncertainties imposed on fault dignosis of substation. This system uses information on the relay setting values and tripped data to identify the faulted element of power system. The proposed concept will be very useful and efficient for substation and control center operator.

• Journal of Oriental Neuropsychiatry
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• v.26 no.1
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• pp.1-10
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• 2015

Objectives: The purpose of this study was to evaluate the effect of breath-counting meditation on anxiety disorder patients with panic attack. Methods: Two anxiety disorder patients with panic attack were treated with Breath-counting Meditation, acupunctures, and herb-medications. The patients have been predicted for anxiety disorder with panic attack through Dignosis and Statistical Manual (DSM-IV), Panic Disorder Severity Scale (PDSS), BDI (Beck Depression Inventory), and BAI (Beck Anxiety Inventory) on their 1st and 6th treatments. Results: After the treatments, both the physical and psychological symptoms have decreased. Conclusions: This study suggests that the breath-counting meditation is an effective way for treating patients who are suffering from anxiety disorder with panic attack.

• Annals of Clinical Neurophysiology
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• v.1 no.1
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• pp.60-63
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• 1999

Transcranial Doppler(TCD) is an important diagnostic tool for evaluating the patients with stroke. It has some advantages and unique role when compared with other neuroimaging modalities. Recent development of transcranial color-coded Doppler(TCD) improves the limitation and pitfalls of TCD. The current indications of TCD are as follows: 1. Screening and evaluation of the intracranial major vessels 2. early detection and follow-up of vasospasm due to SAH 3. emboli detection (high-imtensity transient signals, HITs) 4. dignosis and follow-up of subclavian steal 5. evaluation of intracranial collaterals when the extracranial ICA has severe stenosis or occlusion 6. evaluation of cerebral perfusion pressure (intracranial pressure) 7. evaluation of arteriovenous malformation 8. diagnosis and follow-up of arterial dissenction 9. diagnosis and follow-up of venous sinus thrombosis (experimental).

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.804-805
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• 2011

국내 원자력발전소의 고압 케이블의 체계적인 열화 진단 및 수명예측을 위한 사전작업으로 원자력발전소에서 불리한 환경 하에서 장기간 사용된 후 철거된 XLPE 전력 케이블을 대상으로 성능 측정을 수행하였다. 측정 방법으로는 VLF(Very Low Frequency) Tan${\delta}$ 방법 및 상용주파 부분방전시험을 택하였다. 또한 고주파변류기(HFCT)를 사용하는 부분방전 측정방법(HFPD)에 VLF 내압기를 적용할 수 있는지 확인하였다.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.852-855
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• 1995

In modern plant lndustry, dignosis system is an essential implement because a human operator cannot check the state of system all the time. The recent facility needs a computer system which is able to replace and extense the function of the human expert. Checking the state of the plant system, the computer system uses signals form sensors attached to the plant systems. But, It is difficult to predict the cause of the failure from the sensing signals. Because the relationship among the signals cannot be easily represented by mathematical models. So expert system based on a fuzzy rule and Neural network method is sugguested. Expert system decide whether aa state of the system is ordinary of failure by the evaluation of the signals. If the state of the system is unstable, expert system preprocess the signals. When fault is occurred in the machine, the expert system dignoses the state of the system and find the cause as a primary tool. If the expert system dose not find the adequate cause successfully, neural network system uses the preprocessed signals as an input and propose a cause of the failure.

• Tribology and Lubricants
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• v.14 no.3
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• pp.74-80
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• 1998

The morphologies of the wear particles are directly indicative of wear process occuring in the machine. The analysis of wear particle morphology can therefore provide very early detection of a fault and can also ofen facilitate a dignosis. For this work, the neural network was applied to identify friction coefficient through four shape parameters (50% volumetric diameter, aspect, roundness and reflectivity) of wear debris generated from the machine. The averages of these parameters were used as inputs to the network. It is shown that collect identification of friction coefficient depends on the ranges of these shape parameters learned. The various kinds of the wear debris had a different pattern characteristics and recognized relation between the friction condition and materials very well by neural network. We discuss how the network determines difference in wear debris feature, and this approach can be applied for machine condition monitoring and fault diagnosis.