• 한국전기전자재료학회논문지
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• 제23권2호
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• pp.148-152
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• 2010

The superconducting fault current limiter (SFCL) applied into the neural line of a power system, which can limit the unsymmetrical fault current from the single-line ground fault or the double-line ground fault, was reported to be the effective application location of the SFCL in a power system. However, the limiting operation for the symmetrical fault current like the triple line-ground fault is not effective because of properties of the balanced three-phase system. In this paper, the limiting method of the symmetrical fault current in a power system with a SFCL applied into neutral line was suggested. Through the short-circuit experiments of the three-phase fault types for the suggested method, the fault current limiting and recovery characteristics of the SFCL in the neutral line were analyzed and the effectiveness of the suggested method was described.

• Transactions on Electrical and Electronic Materials
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• 제18권3호
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• pp.136-140
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• 2017

The state of charge (SOC) is an important parameter in a battery-management system (BMS), and is very significant for accurately estimating the SOC of a battery. Li-ion batteries boast of excellent performance, and can only remain at their best working state by means of accurate SOC estimation that gives full play to their performances and raises their economic benefits. This paper summarizes some measures taken in SOC estimation, including the discharge experiment method, the ampere-hour integral method, the open circuit voltage method, the Kalman filter method, the neural network method, and electrochemical impedance spectroscopy (EIS. The principles of the various SOC estimation methods are introduced, and their advantages and disadvantages, as well as the working conditions adopted during these methods, are discussed and analyzed.

• Journal of information and communication convergence engineering
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• 제21권1호
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• pp.24-31
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• 2023

The solid-state drive (SSD) possesses higher input and output speeds, more resistance to physical shock, and lower latency compared with regular hard disks; hence, it is an increasingly popular storage device. However, tiny components on an internal printed circuit board (PCB) hinder the manual detection of malfunctioning components. With the rapid development of artificial intelligence technologies, automatic detection of components through convolutional neural networks (CNN) can provide a sound solution for this area. This study proposes applying the YOLOv5 model to SSD PCB component detection, which is the first step in detecting defective components. It achieves pioneering state-of-the-art results on the SSD PCB dataset. Contrast experiments are conducted with YOLOX, a neck-and-neck model with YOLOv5; evidently, YOLOv5 obtains an mAP@0.5 of 99.0%, essentially outperforming YOLOX. These experiments prove that the YOLOv5 model is effective for tiny object detection and can be used to study the second step of detecting defective components in the future.

• Applied Microscopy
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• 제50권
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• pp.14.1-14.6
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• 2020

Scanning electron microscopy (SEM) plays a central role in analyzing structures by imaging a large area of brain tissue at nanometer scales. A vast amount of data in the large area are required to study structural changes of cellular organelles in a specific cell, such as neurons, astrocytes, oligodendrocytes, and microglia among brain tissue, at sufficient resolution. Array tomography is a useful method for large-area imaging, and the osmium-thiocarbohydrazide-osmium (OTO) and ferrocyanide-reduced osmium methods are commonly used to enhance membrane contrast. Because many samples prepared using the conventional technique without en bloc staining are considered inadequate for array tomography, we suggested an alternative technique using post-staining conventional samples and compared the advantages.

• Smart Structures and Systems
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• 제29권5호
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• pp.693-703
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• 2022

This study investigates an effective approach to stabilize nonlinear systems. To ensure the asymptotic nonlinear stability in nonlinear discrete-time systems, the present study presents controller for an EBA (Evolved Bat Algorithm) NN (fuzzy neural network) in the algorithm. In fuzzy evolved NN modeling, the auxiliary circuit with high frequency LDI (linear differential inclusions) and NN model representation is developed for the nonlinear arbitrary dynamics. An example is utilized to demonstrate the system more robust compared with traditional control systems.

• 생물정신의학
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• 제12권2호
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• pp.123-135
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• 2005

Objectives:EEG coherence could imply the connectivity between two different areas of the brain, which is known to be important in the pathophysiology of bipolar I disorder(BPD I) and schizophrenia. The authors investigated EEG coherence in patients with BPD I and schizophrenia to examine the connectivity of the neural circuit. Methods:EEGs were recorded in 15 schizophrenia and 14 bipolar disorder patients, and 14 age-matched normal control subjects from 16 electrodes with linked-ear reference. Spectral parameters and coherence were calculated for the alpha bandwidth(8-13Hz) by a multi-channel autoregressive model using 20 artifact-free 2-seconds epochs and the differences were compared among three groups by two different statistical methods;F-test and Kruskal-Wallis test. Furthermore, when there were significant differences among three groups, Scheffe's multiple comparison tests were provided and Jonckheere-Terpstra tests for the ordered alternative were given. Results:In the intra-hemispheric comparison, left frontal coherence was increased in order of control, BPD I and schizophrenia. In the inter-hemispheric comparison, 1) inter-prefrontal coherence in BPD I was signifi- cantly higher than in normal controls, and 2) inter-prefrontal coherence in schizophrenia was significantly lower than in controls. Conclusion:These results suggest that 1) both schizophrenia and BPD I are diseases having the abnormality of neural circuit connectivity in both frontal and prefrontal lobes, and 2) the abnormality is more severe in schizophrenia than in BPD I. Furthermore, the data support that a common pathogenetic process may reside in both schizophrenia and BPD I.

• 방송공학회논문지
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• 제26권4호
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• pp.409-418
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• 2021

컨포멀 코팅은 PCB(Printed Circuit Board)를 보호하는 기술로 PCB의 고장을 최소화한다. 코팅의 결함은 PCB의 고장과 연결되기 때문에 성공적인 컨포멀 코팅 조건을 만족하기 위해서 코팅면에 기포가 발생했는지 검사한다. 본 논문에서는 영상 신호 처리를 적용하여 고위험군의 문제성 기포를 검출하는 알고리즘을 제안한다. 알고리즘은 문제성 기포의 후보를 구하는 단계와 후보를 검증하는 단계로 구성된다. 기포는 가시광 영상에서 나타나지 않지만, UV(Ultra Violet) 광원에서는 육안으로 구별이 가능하다. 특히, 문제성 기포의 중심은 밝기가 어둡고 테두리는 높은 밝기를 가진다. 이러한 밝기 특성을 논문에서는 협곡과 산맥 특징이라 부르고 두 가지 특징이 동시에 나타나는 영역을 문제성 기포의 후보라 하였다. 그러나 후보 중에는 기포가 아닌 후보가 존재할 수 있기 때문에 후보를 검증하는 단계가 필요하다. 후보 검증 단계에서는 합성곱 신경망 모델을 이용하였고, ResNet이 다른 모델과 비교하였을 때 성능이 가장 우수하였다. 본 논문에서 제시한 알고리즘은 정확률(Precision) 0.805, 재현율(Recall) 0.763, F1-점수(F1-score) 0.767의 성능을 보였고, 이러한 결과는 기포 검사 자동화에 대한 충분한 가능성을 보여준다.

• 대한기계학회논문집B
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• 제36권2호
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• pp.125-130
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• 2012

예쁜 꼬마선충은 모델 생물로서 지금까지 행동과 이를 제어하는 신경세포들 사이의 관계를 밝히기 위한 많은 연구들이 수행되었다. 본 연구에서는 표면의 강성이 다른 고체 환경에서 꼬마선충의 운동관련 적응 행동을 연구하였다. 꼬마선충은 고체 위에서 움직일 때 기는 파형을 조절함으로써 기계적으로 다른 환경에 적응을 한다. 즉, 외부환경이 더 단단해질수록 꼬마선충의 기는 파형의 진폭과 파장이 감소하게 된다. 흥미로운 사실은 기계적인 감각에 결함이 있는 돌연변이의 경우 정상 꼬마선충과는 다른 적응행동을 보인다는 것이다. 이것은 기계적으로 다른 환경에 효과적으로 적응하기 위해서 기계적인 자극을 감지하고 반응하고 적응하는 기작이 있음을 의미한다. 이에 본 연구에서는 꼬마선충이 기계적으로 다른 환경에 적응하는 과정을 설명할 수 있는 신경회로 모델을 제안하였다.

• 한국산업정보학회논문지
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• 제19권2호
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• pp.73-83
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• 2014

다양한 오디오 편집 기술이 개발됨으로써 오디오 데이터의 변경이 보다 쉬워지고 그 결과로 위변조 같은 다양한 사회 문제가 발생하고 있다. 현재 이런 문제를 해결하기 위해 디지털 포렌식 기술이 활발히 연구되어지고 있다. 본 논문에서는 이러한 디지털 포렌식 기술 중의 하나로 모바일 기기를 판별하는 방법을 제안하였다. 제안 방법에서는 사람에게는 들리지 않지만 기기의 디자인과 IC로부터 발생하는 노이즈 특징을 이용한다. 위너필터를 사용하여 기기의 노이즈 음을 추출하고 MIRtoolbox를 이용하여 특징들을 추출한 후 이를 다층 신경망에 학습시켜 기기를 판별한다. 총 6개의 모바일 기기를 사용하였으며 5-fold test를 통하여 99.9%의 판별 성능을 보였다. 또한 UCC 사이트에 업로드 된 데이터에서도 노이즈 음을 통한 판별이 가능한지 실험을 진행하였으며 99.8%의 판별 성능을 보였다.

• Journal of Electrical Engineering and Technology
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• 제9권4호
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• pp.1385-1393
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• 2014

Gas insulated switchgear (GIS) is widely used in the power systems, however, the contacts overheating of the inside circuit breaker or disconnector may be a potential cause of developing accidents. As the temperature of the contacts cannot be directly acquired due to existence of the metallic shield, an infrared sensor is adopted to directly measure the temperature of the shield and then the contacts temperature can be indirectly obtained by data fitting, based on which the on-line temperature monitoring technology specifically for GIS contacts based on infrared sensing is proposed in this paper. A real GIS test platform is constructed and experimental studies are carried out to account for the influential factors that affect the accuracy of the infrared temperature measurement. A heat transfer model of the GIS module is also developed, together with experimental studies, the nonlinear temperature relationship among the contacts, the metallic shield and the environment based on a neural network algorithm is established. Finally, an integrated on-line temperature monitoring system for the GIS contacts is developed for on-site applications.