• Proceedings of the KIEE Conference
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• 1999.07e
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• pp.2063-2065
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• 1999

PD pulses have about one nanosecond rise time in the $SF_6$ gas insulation. These pulses propagate through GIS chamber to PD sensors in the form of the electromagnetic radiation. In this paper, we investigated the characteristics of disc sensors and monopole antenna, by putting high frequency signals into the test cell in $SF_6$ gas by means of a Ins rise time pulse generator and 60Hz power supply respectively. Also, we measured PD quantity from the needle electrode and the location effect of output terminal beneath the disk sensors.

• Proceedings of the KIEE Conference
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• 1999.07e
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• pp.2066-2068
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• 1999

In this paper, an optical fiber sensor(OF sensor) utilizing the principal of Sagnac interferometer was proposed to detect the discharge signals which generated from needle-sphere electrode system in insulating oil. The performance of OF sensor was checked by sinusoidal calibration signal generated by PZT acuator at 198kHz. The detected discharge signals consisted of acoustic signal and the electrical noise. The noise signal could be removed by digital low pass filter. It was demonstrated that the OF sensor in this research had a possibility to detect the discharge signals in power apparatus.

• Proceedings of the KSR Conference
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• 2009.05a
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• pp.1977-1983
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• 2009

This paper described partial discharge(PD) patterns depending on types of insulation defects in CNCO-W cable(Concentric Neutral Closs-linked Polyethylene Insulated Polyolefin-Water Proof Sheathed Power Cable). The PD measurement system consists of a coupling network, a detection impedance, and a low noise amplifier. A 16 bit, 250 MS/s data acquisition system was used to analyze PD patterns. To simulate insulation defects in a power cable, a needle with the curvature radius of $10{\mu}m$ was inserted into the insulation part. We measured phase ($\Phi$), magnitude (q), and counts (n) of PD pulse for the defects, and classified PD patterns using the PRPD (phase Resolved Partial Discharge) method. From the analysis of acquired PD signals, we could find that a unique PD pattern is formed according to the types of defect.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 1998.06a
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• pp.285-288
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• 1998

Ultrasonic signal characteristics related with the growth of electrical trees in epoxy resin are examined under 67[Hz] ac voltage application along with a CCD camera and PD current method. The ultrasonic sensor with a resonant frequency of 200[Hz] supported by a mechanical spring is attached directly to the lower-side of plane electrode. The magnitude of Partial discharge and count rate of ultrasonic signals have been measured according to the tree growth from a needle tip in an epoxy sample.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2000.07a
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• pp.581-584
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• 2000

Generally, it is known that many partial discharges are occurred in one voltage cycle. In this case, it is not easy to distinguish between ultrasonic signals caused by the partial discharge. We describes a pattern of the ultrasonic signal by the partial discharge in transformer. The test setup for ultrasonic signal measurement was to simulate a internal partial discharge by using a needle to plane electrodes. We compared the number of partial discharge and ultrasonic signal in one voltage cycle. The results showed that it was possible to distinguish between ultrasonic signals by analysing partial discharge detection method and ultrasonic signal on time domain.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.49 no.11
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• pp.622-626
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• 2000

In this paper, an optical fiber sensor(OF sensor) utilizing the principal of Sagnac interferometer was proposed to detect the discharge signals. The needle-sphere electrode system in insulating oil generated the signals. The performance of OF sensor was checked by sinusoidal calibration signal generated by PZT actuator at 198KHz. The detected discharge signals consisted of acoustic signal and the electrical noise. The noise signal could be removed by digital low pass filter. It was demonstrated that the OF sensor in this research had a possibility to detect the discharge signals in power apparatus.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2004.05a
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• pp.298-303
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• 2004

It is well known that a discharge in oil is the source of various physical phenomena. Ultrasonic-wave detection is a useful method to the diagnosis of the transformer-insulation condition. Conventionally, ultrasonic waves are detected by Piezo-electric transducer, and we use optical method that has many advantages. In this paper, we constructed a Mach-Zehnder interferometer with optical fiber and investigated the principle of operation. Test arrangement is based rut the needle-plane electrode system in oil and applied AC high voltage Ultrasonic waves were detected and showed signal- analysis results with wavelet transform.

• International journal of advanced smart convergence
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• v.13 no.3
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• pp.80-88
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• 2024

Breast cancer remains a significant global health burden, necessitating accurate and timely detection for improved patient outcomes. Machine learning techniques have demonstrated remarkable potential in assisting breast cancer diagnosis by learning complex patterns from multi-modal patient data. This study comprehensively evaluates several popular machine learning models, including logistic regression, decision trees, random forests, support vector machines (SVMs), naive Bayes, k-nearest neighbors (KNN), XGBoost, and ensemble methods for breast cancer prediction using the Wisconsin Breast Cancer Dataset (WBCD). Through rigorous benchmarking across metrics like accuracy, precision, recall, F1-score, and area under the ROC curve (AUC), we identify the naive Bayes classifier as the top-performing model, achieving an accuracy of 0.974, F1-score of 0.979, and highest AUC of 0.988. Other strong performers include logistic regression, random forests, and XGBoost, with AUC values exceeding 0.95. Our findings showcase the significant potential of machine learning, particularly the robust naive Bayes algorithm, to provide highly accurate and reliable breast cancer screening from fine needle aspirate (FNA) samples, ultimately enabling earlier intervention and optimized treatment strategies.

• The Korean Journal of Cytopathology
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• v.14 no.2
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• pp.86-90
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• 2003

Kimura's disease is a chronic inflammatory disorder of unknown cause and is most prevalent among Asians. The cytologic findings of Kimura's disease are significant numbers of eosinophils in a background of lymphoid cells, occasional fragments of collagenous tissue, proliferation oi vessels, and Warthin-Finkeldey polykaryocytes. Among these features, the most important cytologic feature of Kimura's disease is a significant numbers of eosinophils. We experienced a case of Kimura's disease in the parotid gland which we fatted to recognize on cytology due to the apparent paucity of eosinophils. On careful retrograde reviewing of the cytologic findings, a few scattered leukocytes, previously interpreted as polymorphous leukocytes, had bilobed nuclei and coarse green but granular cytoplasm on Papanicolaou preparation. These leukocytes showed obvious orange-red intracyloplasmic granules as in eosionophils on Giemsa stain. The paucity of eosinophils may be due to the thick fibrosis around lymphoid follicles or any technical error during aspiration. Whereas the Warthin-Finkeldey type giant cell is not a sensitive cytologic marker of Kimura's disease, it may be a helpful cytologic feature. To reach a correct cytologic diagnosis of Kimura's disease, It is important to keep in mind that searching for Warthin-Finkeldey type giant cells and evaluation of Giemsa stain for detection of eosinophils would be helpful.

• Korean Journal of Clinical Laboratory Science
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• v.45 no.3
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• pp.108-113
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• 2013

The study compared the cytological features of papillary thyroid carcinoma (PTC) in liquid-based preparations (LBPs) and conventional Pap (CP) smears from fine needle aspiration (FNA), and assessed the feasibility of LBP using the Cell Scan $1500^{TM}$ processor on thyroid FNA samples. Thyroid FNA samples were obtained from 883 consecutive patients. Each sample was divided into two and used for LBPs and CP smears. All were screened independently in a double-blind manner. From the 883 cases, 95 cases were diagnosed as PTC in one or both types of preparation (10.8%). PTC was diagnosed via CP smears in 83 cases (87.4%) and via LBPs in 70 cases (73.7%). However, there were differences in categorization between the paired preparations: Twelve (12) PTCs were misinterpreted in CP smears and 25 PTCs in LBPs. There was a significant discrepancy in the rate of detection of the diagnostic features, with LBPs having a lower detection rate. One (1) case (1.2%) of CP smears and 16 cases (22.9%) of LBPs were categorized as unsatisfactory/nondiagnostic in a total of the 95 PTCs. To conclude, the detection rate of the diagnostic features of PTC is lower in Cell Scan 1500TM samples than in CP smears. However, there are some cases in which a diagnosis of PTC is made in LBPs, but not in CP smears. Therefore, definitive cancer diagnosis in thyroid FNA preparations is likely to result from agreement between direct smears and Cell Scan 1500TM preparations.