• Proceedings of the KSME Conference
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• 2000.11a
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• pp.705-711
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• 2000

This paper presents a fast 3D mesh generation method using a surface based method with a stitching algorithm. This method uses the surface based method since the volume based method that uses 3D Delaunay triangulation can hardly deal with a large scale of scanned points. To reduce the processing time, this method also uses a stitching algorithm: after dividing the whole point data into several sections and performing mesh generation on individual sections, the meshes from several sections are stitched into one mesh. Stitching method prevents the surface based method from increasing the processing time exponentially as the number of the points increases. This method works well with different types of scanned points: a scattered type points from a conventional 3D scanner and a cross-sectional type from CT or MRI.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.314-316
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• 2003

To prevent maloperation during magnetic inrush and over-excitation, a current differential relay for power transformers uses harmonic current based restraining or blocking scheme; it also uses dual slope characteristics to prevent maloperation for an external fault with CT saturation. This paper proposes a current differential relaying algorithm for power transformers with an advanced compensation algorithm for the secondary current of CTs. The comparative study was conducted with and without the compensating algorithm. The algorithm can reduce the operating time of the relay in the case of an internal fault and improve security for external faults.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.3
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• pp.158-164
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• 2003

This paper proposes a percentage current differential relaying algorithm for bus protection using an advanced compensating algorithm of the secondary current of current transformers (CTs). The compensating algorithm estimates the core flux at the start of the first saturation based on the value of the second-difference of the secondary current. Then, it calculates the core flux and compensates distorted currents using the magnetization curve. The algorithm Is unaffected by a remanent flux. The simulation results indicate that the proposed algorithm can discriminate internal faults from external faults when the CT saturates. This paper concludes by implementing the algorithm into a TMS320C6701 digital signal processor. The results of hardware implementation are also satisfactory. The proposed algorithm can improve not only stability of the relay in the case of an external fault but sensitivity of the relay in the case of an internal fault.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.1094-1096
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• 1998

An intelligent power transformer protective relaying algorithm based on fuzzy decision-making is proposed. To distinguish external faults with CT saturation, overexcitation and inrush conditions from internal faults, a newly designed fuzzy-rule base is used. The Dempster-Shafer's rule of combition is used for fuzzy inference. A series of the S/W and H/W tests show the proposed protection algorithm has practically sufficient sensitivity and selectivity.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.5
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• pp.879-884
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• 2009

A Method for detection of saturation of a current transformer(CT) is proposed. The algorithm is initiated when the end point of a saturation period is detected. This detection is achieved by checking the time interval between the adjacent zero-crossing points of the second derivative of the secondary current. Once the end point of the saturation period is detected, the beginning point of the corresponding saturation period is determined by backward examination of the sum of the secondary current from the end point. The performance of the algorithm was evaluated for a-g faults on a 345 kV 100km overhead transmission line. The Electromagnetic Transient Program(EMTP) was used to generate fault current signals for different fault inception angles and different remanent fluxes. The performance evaluation shows that the proposed algorithm successfully detects the saturation period even in the presence of a remanent flux.

• Proceedings of the Korean Information Science Society Conference
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• 2007.06b
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• pp.161-166
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• 2007

본 논문에서는 크로노스 그룹에서 제정한 스케일러블 벡터 그래픽 하드웨어 가속을 위한 표준인 OpenVG를 소프트웨어 렌더링 방식으로 구현한 참조 구현을 제안한다. EGL과 OpenVG 엔진이 다양한 임베디드 환경에 쉽게 이식이 가능하도록 설계한 방식을 제시한다 또한 성능 개선을 위해, 채택한 수학 함수와 알고리즘의 선택 배경을 기술하고 최적의 렌더링 방법을 제안한다. 소프트웨어 렌더링 방법으로 구현한 OpenVG를 통해 벡터 이미지를 화면에 출력하는 모습을 보인다. 또한 호환성 테스트 툴인 CTS의 테스트 결과를 제시하며 기존 참조 구현인 Hybrid 사의 참조 구현과 성능 비교 실험 결과를 보인다.

• Proceedings of the KIEE Conference
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• summer
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• pp.384-387
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• 2004

The direction and the type of a fault on a transmission line need to be identified rapidly and correctly, The work described in this paper addresses the problem encountered by a conventional algorithm in a fault type classification in double circuit line, this arises due to a mutual coupling and CT saturation under the fault condition. We present an approach to identify fault type with novel neural network on double circuit transmission line. The neural network based on combined unsupervised training method provides the ability classify the fault type by different patterns of the associated voltages and currents.

• Journal of Korea Multimedia Society
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• v.24 no.4
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• pp.519-527
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• 2021

Alzheimer's disease is one of the challenges to tackle in the coming aging era and is attempting to diagnose and predict through various biomarkers. While the application of various deep learning-based technologies as powerful imaging technologies has recently expanded across the medical industry, empirical design is not easy because there are various deep earning neural networks architecture and categorical hyperparameters that rely on problems and data to solve. In this paper, we show the possibility of optimizing a deep learning neural network structure and hyperparameters for Alzheimer's disease classification in amyloid brain images in a representative deep earning neural networks architecture using genetic algorithms. It was observed that the optimal deep learning neural network structure and hyperparameter were chosen as the values of the experiment were converging.

• Journal of the Korean Society of Radiology
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• v.14 no.1
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• pp.23-29
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• 2020

The standard uptake values (SUVs) strongly depend on positron emission tomographs (PETs) and image reconstruction methods. Various image reconstruction algorithms in GE Discovery MIDR (DMIDR) and Discovery Ste (DSte) installed at Department of Nuclear Medicine, Seoul Samsung Medical Center were applied to measure the SUVs in an anthropomorphic torso phantom. The measured SUVs in the heart, liver, and background were compared to the actual SUVs. Applied image reconstruction algorithms were VPFX-S (TOF+PSF), QCFX-S-350 (Q.Clear+TOF+PSF), QCFX-S-50, VPHD-S (OSEM+PSF) for DMIDR, and VUE Point (OSEM) and FORE-FBP for DSte. To reduce the radiation exposure to radiation technologists, only the small amount of radiation source ¹⁸F-FDG was mixed with the distilled water: 2.28 MBq in the 52.5 ml heart, 20.3 MBq in the 1,290 ml liver and 45.7 MBq for the 9,590 ml in the background region. SUV values in the heart with the algorithms of VPFX-S, QCFX-S-350, QCFX-S-50, VPHD-S, VUE Point, and FOR-FBP were 27.1, 28.0, 27.1, 26.5, 8.0, and 7.4 with the expected SUV of 5.9, and in the background 4.2, 4.1, 4.2, 4.1, 1.1, and 1.2 with the expected SUV of 0.8, respectively. Although the SUVs in each region were different for the six reconstruction algorithms in two PET/CTs, the SUV ratios between heart and background were found to be relatively consistent; 6.5, 6.8, 6.5, 6.5, 7.3, and 6.2 for the six reconstruction algorithms with the expected ratio of 7.8, respectively. Mean SNRs (Signal to Noise Ratios) in the heart were 8.3, 12.8, 8.3, 8.4, 17.2, and 16.6, respectively. In conclusion, the performance of PETs may be checked by using with the SUV ratios between two regions and a relatively small amount of radioactivity.

• Progress in Medical Physics
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• v.13 no.4
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• pp.209-217
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• 2002

There have been many studies on the application of the reciprocal advantages of multimodality image to define accurate target volume in the Process of radiation treatment planning. For the proper use of the multimodality images, the registration works between different modality images should be performed in advance. In this study, we selected chamfer matching method and mutual information method as most popular methods in recent image registration studies considering the registration accuracy and clinical practicality. And the two registration methods were analyzed to deduce the optimal registration method according to the characteristics of images. Lung phantom of which multimodality images could be acquired was fabricated and CT, MRI and SPECT images of the phantom were used in this study. We developed the registration program which can perform the two registration methods properly and analyzed the registration results which were produced by the developed program in many different images' conditions. Although the overall accuracy of the registration in both chamfer matching method and mutual information method was acceptable, the registration errors in SPECT images which had lower resolution and in degraded images of which data were removed in some part were increased when chamfer matching method was applied. Especially in the case of degraded reference image, chamfer matching methods produce relatively large errors compared with mutual information method. Mutual information method can be estimated as more robust registration method than chamfer matching method in this study because it did not need the prerequisite works, the extraction of accurate contour points, and it produced more accurate registration results consistently regardless of the images' characteristics. The analysis of the registration methods in this study can be expected to provide useful information to the utilization of multimodality images in delineating target volume for radiation treatment planning and in many other clinical applications.