• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.30 no.2
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• pp.150-156
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• 2004

The etiology of the obstructive sleep apnea includes the various factors such as anatomical abnormality in upper airway, craniofacial structure, obesity and personal habit. To establish reasonable treatment plan, multi-department approach is should be emphasized because the treatment modality is depend on the result of analysis for degree & site of obstruction and various behavioral factors. In Sleep Clinic in Keimyung University Medical Center, the standard of care for sleep apnea patient was established according to the Standard of practice committee of Americal Sleep Disorders Association. After one year experience of comprehensive approach for sleep apnea we could achieve following recommendation for the treatment. 1) The multi-department examination and diagnosis could prevent unnessesary treatment because the treatment plan could be established under comprehensive discussion. 2) Determination of the site of obstruction is important for treatment planning. However, no single determinant could be found. We expect multi-department approach can reduce the mistake in detection of obstruction. 3) Further evaluation of treatmet outcome should be succeeded to establish Korean standard of care for sleep apnea treatment.

• The Korean Journal of Nuclear Medicine
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• v.38 no.5
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• pp.331-337
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• 2004

Cardiac neurotransmission imaging allows in vivo assessment of presynaptic reuptake, neurotransmitter storage and postsynaptic receptors. Among the various neurotransmitter, I-123 MIBG is most available and relatively well-established. Metaiodobenzylguanidine (MIBG) is an analogue of the false neurotransmitter guanethidine. It is taken up to adrenergic neurons by uptake-1 mechanism as same as norepinephrine. As tagged with I-123, it can be used to image sympathetic function in various organs including heart with planar or SPECT techniques. I-123 MIBG imaging has a unique advantage to evaluate myocardial neuronal activity in which the heart has no significant structural abnormality or even no functional derangement measured with other conventional examination. In patients with cardiomyopathy and heart failure, this imaging has most sensitive technique to predict prognosis and treatment response of betablocker or ACE inhibitor. In diabetic patients, it allow very early detection of autonomic neuropathy. In patients with dangerous arrhythmia such as ventricular tachycardia or fibrillation, MIBG imaging may be only an abnormal result among various exams. In patients with ischemic heart disease, sympathetic derangement may be used as the method of risk stratification. In heart transplanted patients, sympathetic reinnervation is well evaluated. Adriamycin-induced cardiotoxicity is detected earlier than ventricular dysfunction with sympathetic dysfunction. Neurodegenerative disorder such as Parkinson's disease or dementia with Lewy bodies has also cardiac sympathetic dysfunction. Noninvasive assessment of cardiac sympathetic nerve activity with I-123 MIBG imaging nay be improve understanding of the pathophysiology of cardiac disease and make a contribution to predict survival and therapy efficacy.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.8
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• pp.3825-3827
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• 2012

FISH is one of the most sensitive molecular methods to detect genetic abnormalities with DNA probes. When cytogenetic studies are normal or insufficient, FISH may detect cryptic rearrangements, rare or slowly proliferative abnormal populations in non-mitotic cells. We cytogenetically evaluated 70 childhood ALL - 67.1% were found to have an abnormal karyotype. The 23 patients (32.9%) with a normal karyotype were analyzed by FISH applying two probes; TEL/AML1 and MYB which detect cryptic rearrangements of t(12;21)(p13;q22) and deletion of (6q) respectively, associated with a good prognosis. Out of 23 patients, one was positive for t(12;21)(p13;q22) (4.3%). None of our patients were positive for MYB del(6q). Two patients showed an extra signal for MYB on chromosomes other than 6 (8.6 %) indicating amplification or duplication. Findings were compared with the available literature. Our study clearly indicated the integrated FISH screening method to increase the abnormality detection rate in a narrow range. FISH is less useful for diagnostic study of patients with suspected del(6q) but it helps in detecting known cryptic rearrangements as well as identification of new abnormalities(translocation , duplication and amplification) at the gene level.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.6
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• pp.1215-1221
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• 2009

A novel approach for electrocardiogram (ECG) analysis within a functional sensor node has been developed and evaluated. The main aim is to reduce data collision, traffic overload and power consumption in healthcare applications of wireless sensor networks(WSN). The sensor node attached on the patient's body surface around the heart can perform ECG analysis based on a QRS detection algorithm to detect abnormal condition of the patient. Data transfer is activated only after detected abnormality in the ECG. This system can reduce packet loss during transmission by reducing traffic overload. In addition, it saves power supply energy leading to more reliable, cheap and user-friendly operation in the WSN for ubiquitous health monitoring.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.80-84
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• 1996

This paper aims at reviewing the Possibility application over normal or abnormal, detection used by AE and the wear characteristics of grinding process. In this study, when diamond bur in dentistry with chosen grinding conditions were tuned at grinding. The variation of grinding resistance and hE signal is detected by the use of AE measuring system. The tests are carried out in accordance with diamond burs and workpiece; arcyl and bovine. According to the experiment results, the following can be expected; AE has the possibility to detect the state normality and abnormality. However, the grinding resistance measuring can find it difficult to detect it. It can be accurately excerpted from AE occurrence pattern in contact start point of diamond bur and bovine, grinding condition and derailment point. It is known that AE$\_$rms/ is well compatible with grinding resistance. According to the increase of the material removal rate, the specific energy of the diamond bur is inclined to decrease and the grinding resistance has a tendency to increase.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.3
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• pp.316-321
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• 2003

Recently, support vector learning attracts great interests in the areas of pattern classification, function approximation, and abnormality detection. It is well-known that among the various support vector learning methods, the so-called no-versions are particularly useful in cases that we need to control the total number of support vectors. In this paper, we consider the problem of function approximation utilizing both predetermined basis functions and a no-version support vector learning called $\nu-SVR$. After reviewing $\varepsilon-SVR$, $\nu-SVR$, and a semi-parametric approach, this paper presents an extension of the conventional $\nu-SVR$ method toward the direction that can utilize Predetermined basis functions. Moreover, the applicability of the presented method is illustrated via an example.

• IE interfaces
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• v.24 no.1
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• pp.8-14
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• 2011

Principal Component Analysis (PCA) reduces the dimensionality of the process by creating a new set of variables, Principal components (PCs), which attempt to reflect the true underlying process dimension. However, for highly nonlinear processes, this form of monitoring may not be efficient since the process dimensionality can't be represented by a small number of PCs. Examples include the process of semiconductors, pharmaceuticals and chemicals. Nonlinear correlated process variables can be reduced to a set of nonlinear principal components, through the application of Kernel Principal Component Analysis (KPCA). Support Vector Data Description (SVDD) which has roots in a supervised learning theory is a training algorithm based on structural risk minimization. Its control limit does not depend on the distribution, but adapts to the real data. So, in this paper proposes a non-linear process monitoring technique based on supervised learning methods and KPCA. Through simulated examples, it has been shown that the proposed monitoring chart is more effective than $T^2$ chart for nonlinear processes.

• Journal of Korea Multimedia Society
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• v.25 no.11
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• pp.1547-1556
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• 2022

As mechanical facilities are interacting with each other, the failure of some equipment can affect the entire system, so it is necessary to quickly detect and diagnose the abnormality of mechanical equipment. This study proposes a deep learning model that can effectively diagnose abnormalities in rotating machinery and equipment. CNN is widely used for feature extraction and LSTMs are known to be effective in learning sequential information. In LSTM, the number of parameters and learning time increase as the length of input data increases. In this study, we propose a method of segmenting an input segment signal into shorter-length sub-segment signals, sequentially inputting them to CNN through a time-distributed method for extracting features, and inputting them into LSTM. A failure diagnosis test was performed using the vibration data collected from the motor for ventilation equipment installed at the urban railway station. The experiment showed an accuracy of 99.784% in fault diagnosis. It shows that the proposed method is effective in the fault diagnosis of rotating machinery and equipment.

• ETRI Journal
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• v.43 no.3
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• pp.459-470
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• 2021

This paper presents a low-cost prototype for monitoring online the maximum power produced by a domestic photovoltaic (PV) system using Internet of Things (IoT) technology. The most common tracking algorithms (P&O, InCond, HC, VSS InCond, and FL) were first simulated using MATLAB/Simulink and then implemented in a low-cost microcontroller (Arduino). The current, voltage, load current, load voltage, power at the maximum power point, duty cycle, module temperature, and in-plane solar irradiance are monitored. Using IoT technology, users can check in real time the change in power produced by their installation anywhere and anytime without additional effort or cost. The designed prototype is suitable for domestic PV applications, particularly at remote sites. It can also help users check online whether any abnormality has happened in their system based simply on the variation in the produced maximum power. Experimental results show that the system performs well. Moreover, the prototype is easy to implement, low in cost, saves time, and minimizes human effort. The developed monitoring system could be extended by integrating fault detection and diagnosis algorithms.

• Journal of Electrodiagnosis and Neuromuscular Diseases
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• v.20 no.2
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• pp.144-147
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• 2018

Although dysgeusia can occur as a consequence of stroke attacks, many physicians and patients tend to overlook it. A 50-year old woman complained of a 2-week history of abnormal sense of taste on the anterior two-thirds of right tongue. Blink reflex test demonstrated prolonged ipsilateral and contralateral R2 responses with the right supraorbital nerve stimulations, which suggest the lesion on the descending pathway. Brainstem magnetic resonance imaging (MRI) demonstrated abnormal findings in the right lower dorsal pons, anterior to 4th ventricle, lateral to inferior colliculus, and at the level of the pontomedullary junction, which was compatible with solitary tract nucleus and spinal trigeminal nucleus. Brainstem infarction should be considered in patients who have abnormal sense of taste. Additionally, blink reflex test may be helpful for the detection of central origin dysgeusia.