• 제목/요약/키워드: PD features

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Features Extraction and Mechanism Analysis of Partial Discharge Development under Protrusion Defect

  • Dong, Yu-Lin;Tang, Ju;Zeng, Fu-Ping;Liu, Min
    • Journal of Electrical Engineering and Technology
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    • 제10권1호
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    • pp.344-354
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    • 2015
  • In order to study the development of partial discharge (PD) under typical protrusion defects in gas-insulated switchgear, we applied step voltages on the defect and obtained the ${\varphi}-u$ and ${\varphi}-n$ spectrograms of ultra-high frequency (UHF) PD signals in various PD stages. Furthermore, we extracted seven kinds of features to characterize the degree of deterioration of insulation and analyzed their values, variation trends, and change rates. These characteristics were inconsistent with the development of PD. Hence, the differences of these features could describe the severity of PD. In addition, these characteristics could provide integrated characteristics regarding PD development and improve the reliability of PD severity assessment because these characteristics were extracted from different angles. To explain the variation laws of these seven kinds of parameters, we analyzed the relevant physical mechanism by considering the microphysical process of PD formation and development as well as the distortion effect generated by the space charges on the initial field. The relevant physical mechanism effectively allocated PD severity among these features for assessment, and the effectiveness and reliability of using these features to assess PD severity were proved by testing a large number of PD samples.

Biochemical and molecular features of LRRK2 and its pathophysiological roles in Parkinson's disease

  • Seol, Won-Gi
    • BMB Reports
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    • 제43권4호
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    • pp.233-244
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    • 2010
  • Parkinson's disease (PD) is the second most common neurodegenerative disease, and 5-10% of the PD cases are genetically inherited as familial PD (FPD). LRRK2 (leucine-rich repeat kinase 2) was first reported in 2004 as a gene corresponding to PARK8, an autosomal gene whose dominant mutations cause familial PD. LRRK2 contains both active kinase and GTPase domains as well as protein-protein interaction motifs such as LRR (leucine-rich repeat) and WD40. Most pathogenic LRRK2 mutations are located in either the GTPase or kinase domain, implying important roles for the enzymatic activities in PD pathogenic mechanisms. In comparison to other PD causative genes such as parkin and PINK1, LRRK2 exhibits two important features. One is that LRRK2's mutations (especially the G2019S mutation) were observed in sporadic as well as familial PD patients. Another is that, among the various PD-causing genes, pathological characteristics observed in patients carrying LRRK2 mutations are the most similar to patients with sporadic PD. Because of these two observations, LRRK2 has been intensively investigated for its pathogenic mechanism (s) and as a target gene for PD therapeutics. In this review, the general biochemical and molecular features of LRRK2, the recent results of LRRK2 studies and LRRK2's therapeutic potential as a PD target gene will be discussed.

비결핵마이코박테륨 폐질환의 영상의학진단 (Radiologic Diagnosis of Nontuberculous Mycobacterial Pulmonary Disease)

  • 강은영
    • 대한영상의학회지
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    • 제82권4호
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    • pp.838-850
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    • 2021
  • 비결핵마이코박테륨(nontuberculous mycobacterium; 이하 NTM) 폐질환은 우리나라를 포함하여 전 세계적으로 발생률과 유병률이 증가하고 있다. 더불어 NTM 폐질환의 임상적 중요성도 빠르게 증가하고 있으나, NTM 폐질환은 진단과 치료가 어려운 질환이다. NTM 폐질환의 진단을 위해서는 영상의학적 근거가 필수이며, 많은 환자에서 영상의학 소견은 NTM 폐질환을 진단하는 첫 번째 근거가 될 수 있다. NTM 폐질환의 영상의학 소견은 일반적으로 섬유공동병변형과 결절기관지확장형의 두 가지 형태로 구분하나, NTM 폐질환은 다양하고 비특이적인 영상의학 소견을 보일 수 있다. 영상의학과 의사는 영상의학 소견에 따라 NTM 폐질환의 가능성을 감별진단에 포함하여야 한다. 본 종설은 영상의학과 의사를 위한 NTM 폐질환의 국내 역학, 진단기준, 영상의학 소견을 중심으로 검토하였다.

An extensive investigation on gamma ray shielding features of Pd/Ag-based alloys

  • Agar, O.;Sayyed, M.I.;Akman, F.;Tekin, H.O.;Kacal, M.R.
    • Nuclear Engineering and Technology
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    • 제51권3호
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    • pp.853-859
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    • 2019
  • A comprehensive study of photon interaction features has been made for some alloys containing Pd and Ag content to evaluate its possible use as alternative gamma radiations shielding material. The mass attenuation coefficient (${\mu}/{\rho}$) of the present alloys was measured at various photon energies between 81 keV-1333 keV utilizing HPGe detector. The measured ${\mu}/{\rho}$ values were compared to those of theoretical and computational (MCNPX code) results. The results exhibited that the ${\mu}/{\rho}$ values of the studied alloys are in the same line with results of WinXCOM software and MCNPX code results at all energies. Moreover, Pd75/Ag25 alloy sample has the maximum radiation protection efficiency (about 53% at 81 keV) and lowest half value layer, which shows that Pd75/Ag25 has superior gamma radiation shielding performance among the other compared alloys.

Application of RBFN Using LPC of PD Pulse Shapes for Discriminating Among Multi PD Sources

  • Lee, Kang-Won;Lim, Kee-Joe;Kang, Seong-Hwa
    • KIEE International Transactions on Electrophysics and Applications
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    • 제3C권5호
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    • pp.177-181
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    • 2003
  • Partial discharge pulse shapes from variable PD (partial discharge) sources sustain many characteristics such as types of PD. Ultra high frequency antennas have wide bandwidth from 30KHz to 2㎓. Therefore, signals taken from a UHF antenna have important attributes (rising time, falling time, shape factor, etc.) for electromagnetic sources, such as PD sources. We investigated PD pulse shapes from several PD sources using a UHF antenna and the results were used for classification of PD sources. Features for discrimination are extracted from frequency distribution and LPC (Linear Prediction Coefficient) of time signal. RBFN are used for investigating the possibility of classification of multi-PD sources.

편평세포폐암에서 CT 영상 소견을 이용한 PD-L1 발현 예측 (Predictions of PD-L1 Expression Based on CT Imaging Features in Lung Squamous Cell Carcinoma)

  • 여성희;윤현정;김인중;김여진;이영;차윤기;박소현
    • 대한영상의학회지
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    • 제85권2호
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    • pp.394-408
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    • 2024
  • 목적 CT 영상 소견을 이용하여 편평세포폐암에서 programmed death ligand 1 (이하 PD-L1)의 발현을 예측하는 모델을 구축해 보고자 하였다. 대상과 방법 PD-L1 발현검사 결과를 포함하고 있는 97명의 편평세포폐암 환자를 포함하였고 종양 치료 전 시행한 CT 영상 소견을 분석하였다. 전체 환자군과 40명의 진행성(≥ stage IIIB) 병기 환자군에 대하여 PD-L1 발현 예측을 위한 다중 로지스틱 회귀 분석 모델 구축을 시행하였다. 각각의 환자군에 대하여 곡선 아래 면적(areas under the receiver operating characteristic curves; 이하 AUCs)을 분석하여 예측력을 평가하였다. 결과 전체 환자군에서 '전체 유의인자 모델'(종양병기, 종양크기, 흉막결절, 폐전이)의 AUC 값은 0.652이며, '선택 유의인자 모델'(흉막결절)은 0.556이었다. 진행성 병기 환자군에서 '선택 유의인자 모델'(종양크기, 흉막결절, 폐소수전이, 간질성폐렴의 부재)의 AUC 값은 0.897이었다. 이러한 인자들 중 흉막결절과 폐소수전이는 높은 오즈비를 보였다(각각, 8.78과 16.35). 결론 본 연구에서의 모델은 편평세포폐암의 PD-L1 발현예측의 가능성을 보여주었으며 흉막결절과 폐소수전이는 PD-L1 발현을 예측하는데 중요한 CT 예측인자였다.

Partial Discharge Ultrasonic Analysis for Generator Stator Windings

  • Yang, Yong-Ming;Chen, Xue-Jun
    • Journal of Electrical Engineering and Technology
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    • 제9권2호
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    • pp.670-676
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    • 2014
  • The objective of this research is to utilize the ultrasonic method to analyze the property of partial discharge (PD) which is generated by the winding of the insulation stator in the generator. Therefore, a PD measurement system is built based on ultrasonic and virtual instruments. Three types of PD models (internal PD model, surface PD model and slot PD model) have been constructed. With the analysis of these experimental results, this research has identified the ultrasonic signals of the discharges which were produced by three types of PD models. This analysis shows the different features among these PD types. Both the time domain and frequency domain of the ultrasonic signals are obviously different. In addition, an experiment based on a large rotating machine has been done to analyze ultrasonic noises. The result indicates that the ultrasonic noises can be wiped off by the filters and algorithms. The application of this system is convenient for the detection of early signs of insulation failure, which is an effective method for diagnosis of insulation faults.

Automated detection of panic disorder based on multimodal physiological signals using machine learning

  • Eun Hye Jang;Kwan Woo Choi;Ah Young Kim;Han Young Yu;Hong Jin Jeon;Sangwon Byun
    • ETRI Journal
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    • 제45권1호
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    • pp.105-118
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    • 2023
  • We tested the feasibility of automated discrimination of patients with panic disorder (PD) from healthy controls (HCs) based on multimodal physiological responses using machine learning. Electrocardiogram (ECG), electrodermal activity (EDA), respiration (RESP), and peripheral temperature (PT) of the participants were measured during three experimental phases: rest, stress, and recovery. Eleven physiological features were extracted from each phase and used as input data. Logistic regression (LoR), k-nearest neighbor (KNN), support vector machine (SVM), random forest (RF), and multilayer perceptron (MLP) algorithms were implemented with nested cross-validation. Linear regression analysis showed that ECG and PT features obtained in the stress and recovery phases were significant predictors of PD. We achieved the highest accuracy (75.61%) with MLP using all 33 features. With the exception of MLP, applying the significant predictors led to a higher accuracy than using 24 ECG features. These results suggest that combining multimodal physiological signals measured during various states of autonomic arousal has the potential to differentiate patients with PD from HCs.

부분방전 펄스파형의 시간-주파수분포를 이용한 기중부분방전원의 식별 (Discrimination of Air PD Sources Using Time-Frequency Distributions of PD Pulse Waveform)

  • 이강원;강성화;임기조
    • 대한전기학회논문지:전기물성ㆍ응용부문C
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    • 제54권7호
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    • pp.332-338
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    • 2005
  • PD(Partial Discharge) signal emitted from PD sources has their intrinsic features in the region of time and frequency STFT(Short Time Fourier Transform) shows time-frequency distribution at the same time. 2-Dimensional matrices(33$\times$77) from STFT for PD pulse signals are a good feature vectors and can be decreased in dimension by wavelet 2D data compression technique. Decreased feature vectors(13$\times$24) were used as inputs of Back-propagation ANN(Artificial Neural Network) for discrimination of Multi-PD sources(air discharge sources(3), surface discharge(1)). They are a good feature vectors for discriminating Multi-PD sources in the air.

부분방전 펄스파형의 시간-주파수분포의 웨이블렛 2D 압축기술을 이용한 복합부분방전원의 식별 (Discrimination of Multi-PD sources using wavelet 2D compression for T-F distribution of PD pulse waveform)

  • 이강원;김명룡;백광선;강성화;임기조
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2004년도 하계학술대회 논문집 C
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    • pp.1784-1786
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    • 2004
  • PD(Partial Discharge) signal emitted from PD sources has their intrinsic features in the region of time and frequency. STFT(Short Time Fourier Transform) shows time-frequency distribution at the same time. 2-Dimensional matrices(33${\times}$77) from STFT for PD pulse signals are a good feature vectors and can be decreased in dimension by wavelet 2D data compression technique. Decreased feature vectors(13${\times}$24) were used as inputs of Back-propagation ANN(Artificial Neural Network) for discrimination of Multi-PD sources(air discharge sources(3), surface discharge(1)). They are a good feature vectors for discriminating Multi-PD sources.

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