• Bulletin of the Korean Chemical Society
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• v.25 no.5
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• pp.757-760
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• 2004

• Journal of Physiology & Pathology in Korean Medicine
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• v.23 no.1
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• pp.97-103
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• 2009

The status and the property of a tongue are the important indicators to diagnose one's health like physiological and clinicopathological changes of inner organs. However, the tongue diagnosis is affected by examination circumstances like a light source, patient's posture, and doctor's condition. To develop an automatic tongue diagnosis system for an objective and standardized diagnosis, classifying tongue coating is inevitable but difficult since the features like color and texture of the tongue coatings and substance have little difference, especially in the neighborhood on the tongue surface. The proposed method has two procedures; the first is to acquire the color table to classify tongue coatings and substance by automatically separating coating regions marked by oriental medical doctors, decomposing the color components of the region into hue, saturation and brightness and obtaining the 2nd order discriminant with statistical data of hue and saturation corresponding to each kind of tongue coatings, and the other is to apply the tongue region in an input image to the color table, resulting in separating the regions of tongue coatings and classifying them automatically. As a result, kinds of tongue coatings and substance were segmented from a face image corresponding to regions marked by oriental medical doctors and the color table for classification took hue and saturation values as inputs and produced the classification of the values into white coating, yellow coating and substance in a digital tongue diagnosis system. The coating regions classified by the proposed method were almost the same to the marked regions. The exactness of classification was 83%, which is the degree of correspondence between what Oriental medical doctors diagnosed and what the proposed method classified. Since the classified regions provide effective information, the proposed method can be used to make an objective and standardized diagnosis and applied to an ubiquitous healthcare system. Therefore, the method will be able to be widely used in Oriental medicine.

• Korean Journal of Digital Imaging in Medicine
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• v.13 no.3
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• pp.105-109
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• 2011

With the development of medical technologies and the growth of household incomes, most of the people have become to be interested in health as it leads to significant early detection and cure of diseases. However the pattern of disease becomes diverse and it makes the imaging diagnosis department crowded with many patients. Therefore the opportunistic infection could be serious there. The hospital becomes the place which provides high risks of infection danger but it is true that the opportunistic infection of the hospital employees is not still recognized well. The imaging diagnosis department has developed a lot but it becomes the medium of secondary infection of patients and employees. So this study analyzesthe status of bacteria infection of the examination table, the handle of diagnostic equipment and the hands of radiation staffs in imaging diagnosis department of the general hospitals and individual ones. And the result shows that some bacteria were found even though it's little. We are trying to make the hospitals to be free of secondary infection securing safety measure to prevent the secondaryinfection from occurring to patients and hospital employees.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.3243-3244
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• 2000

From ancient times, the diagnosis method of the oriental medicine has been performed by curing diseases by means of rectifying and adjusting the unbalance in the physiological function of the five viscera and the six bowels of a human body. Diseases have been diagnosed by the condition of blood circulation that cycles a human body through blood vessels by dint of the vitality of the heart. Based on such a systematic pulse diagnosis method, the article presents parameters that will be beneficial to clinical application on the basis of its analysis of the filtering for eliminating noises from pulse signals inputted from sensor group, the digital hardware dealing with signals necessary for recognition algorithm, and the structure of diagnosis algorithm and components of pulse waveform.

• Journal of Digital Convergence
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• v.9 no.2
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• pp.141-152
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• 2011

The data center has become an increasingly important part of most business operations. An increasing demand for computation has led to increasing industry energy consumption. Therefore, higher-than-normal rates of energy efficiency have become a core issue in the life cycle of data center. In this paper, we proposed the framework of level diagnosis for green data centre that can be used to diagnose the levels of capability maturity model. This framework contains the 5 key areas such as construction, air-conditioning, electricity, information technology, organization and indicators that can be applied as basic level diagnosis guide for green data center.

• Journal of Electrical Engineering and Technology
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• v.6 no.5
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• pp.677-683
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• 2011

The present paper describes the setup of standard partial discharge calibrator for measuring partial discharge and estimating uncertainties. The standard PD calibrator was designed and set up, consisting of a digital pulse generator, capacitor modules, and a digital oscilloscope controlled by software developed in the laboratory. Using this software, averages of charges and rising times and their standard deviations in the measured pulses can also be calculated. The standard PD calibrator generates five types of pulses: single, double, random, oscillating, and long-rising. The coefficient sensitivities to estimate the uncertainties of pulses were extracted in the model circuit of the standard PD calibrator. The uncertainties of charges and rising times in pulses of the standard PD calibrator were estimated with single pulses. These values were 0.3%-1.4% in charges and 1.9%-7.0% in rising time; however, these values are lower than the limit values in IEC 60270.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1110-1111
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• 2007

These days, the concerns about maintenance and repair of electric facilities for stable and reliable electric power supply are increasing day by day. Because, we can have enormous damages economically and socially from a problem of the facilities, no matter how it is a small one. Especially, electric facilities in our country had been built abruptly from 40 years ago, so it can be thought that here are great amount of old facilities that must be repaired or replaced with new one, and the number would be increased time by time. On this situation, many researchers are studying the efficient and reliable method of maintenance for electric facilities and the results are applied on the facilities gradually by growing interests of operators and managers of the facilities. In this paper, the IED(Intelligent Electronic Devices) for Diagnosis system of electric machines are described. It takes analog data from a sensing device and operates digital processor to get a optimum digital data for diagnosis system. Now, this device is applied on several high voltage substations to diagnose and maintain GIS. Brief schematic of total diagnosis system and the construction of the IED are included in this paper.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.4
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• pp.69-77
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• 2018

The malignant melanoma accounts for about 1 to 3% of the total malignant tumor in the West, especially in the US, it is a disease that causes more than 9,000 deaths each year. Generally, skin lesions are difficult to detect the features through photography. In this paper, we propose a computer-aided diagnosis algorithm based on deep learning for classification of malignant melanoma and benign skin tumor in RGB channel skin images. The proposed deep learning model configures the tumor lesion segmentation model and a classification model of malignant melanoma. First, U-Net was used to segment a skin lesion area in the dermoscopic image. We could implement algorithms to classify malignant melanoma and benign tumor using skin lesion image and results of expert's labeling in ResNet. The U-Net model obtained a dice similarity coefficient of 83.45% compared with results of expert's labeling. The classification accuracy of malignant melanoma obtained the 83.06%. As the result, it is expected that the proposed artificial intelligence algorithm will utilize as a computer-aided diagnosis algorithm and help to detect malignant melanoma at an early stage.

• Journal of Biomedical Engineering Research
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• v.10 no.1
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• pp.17-24
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• 1989

This papaer presents a new algorithm for the P-wave detection in the ECG signal. Digital differentiation method (7-point derivative) is used for detecting P-waves exactly. This algorithm can detect various parameters of PR, PP, RR interval, which are important to diagnosis AV blocks and WPW syndrome. Especially, this algorithm can detect P-waves very efficiently not only in well-preprocessed waves but in pccr waves with noise and artifact. And it enables to develope more reliable automatic diagnosis algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.9
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• pp.722-727
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• 2013

Medical treatment for animals is very difficult as the opinions of pets' masters take priority over treatment regardless of the seriousness of pets' disease or the needs of medical treatment. In case that a pet has heart disease, especially, it is difficult to get the direct answer from the pet's master on the decision or confirmation of treatment. For those reasons, it is almost impossible to predict and treat the pet before an emergency like the heart failure or an unexpected death happens. Using stethoscope can be the first diagnosis method to check the heart or any kinds of disease inside the body. High-tech equipments like CT, X-ray or Ultrasound can be used, but they can only be used as a second choice of diagnosis method since it requires professional skills and its high price. That's why stethoscope is still the best diagnostic tool when one makes the first diagnosis. In this study, we give a detailed account of digital diagnosis system in which veterinarians can analyze the sound from stethoscope without bringing it to their ears and make a diagnosis wherever they are. And we suggest a new concept of diagnosis system surrounding, which shows the relativeness of disease through Level Crossing Rate(LCR) and energy level from the stethoscope sound made in this system.