• Journal of Electrical Engineering and Technology
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• v.10 no.1
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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.

• BMB Reports
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• v.43 no.4
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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.

• Journal of the Korean Society of Radiology
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• v.82 no.4
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• pp.838-850
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• 2021

The incidence and prevalence of nontuberculous mycobacterial pulmonary disease (NTM-PD) is increasing worldwide, including in Korea, and the clinical importance of NTM-PD is also rapidly increasing. The diagnosis and management of NTM-PD is difficult. Radiologic evidence is mandatory to diagnose NTM-PD, and the radiologic findings may be the first evidence of the disease in many patients. Traditionally, NTM-PD demonstrates two different radiologic forms: fibrocavitary and nodular bronchiectatic. However, the disease also shows non-specific and a wide spectrum of radiologic features. Radiologists must be aware of the radiologic features of NTM-PD and should include them in the differential diagnosis. This review focuses on the epidemiology in Korea, diagnostic criteria, and radiological features of NTM-PD for radiologists.

• Nuclear Engineering and Technology
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• v.51 no.3
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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.

• KIEE International Transactions on Electrophysics and Applications
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• v.3C no.5
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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.

• Journal of the Korean Society of Radiology
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• v.85 no.2
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• pp.394-408
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• 2024

Purpose To develop models to predict programmed death ligand 1 (PD-L1) expression in pulmonary squamous cell carcinoma (SCC) using CT. Materials and Methods A total of 97 patients diagnosed with SCC who underwent PD-L1 expression assay were included in this study. We performed a CT analysis of the tumors using pretreatment CT images. Multiple logistic regression models were constructed to predict PD-L1 positivity in the total patient group and in the 40 advanced-stage (≥ stage IIIB) patients. The area under the receiver operating characteristic curve (AUC) was calculated for each model. Results For the total patient group, the AUC of the 'total significant features model' (tumor stage, tumor size, pleural nodularity, and lung metastasis) was 0.652, and that of the 'selected feature model' (pleural nodularity) was 0.556. For advanced-stage patients, the AUC of the 'selected feature model' (tumor size, pleural nodularity, pulmonary oligometastases, and absence of interstitial lung disease) was 0.897. Among these factors, pleural nodularity and pulmonary oligometastases had the highest odds ratios (8.78 and 16.35, respectively). Conclusion Our model could predict PD-L1 expression in patients with lung SCC, and pleural nodularity and pulmonary oligometastases were notable predictive CT features of PD-L1.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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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.

• ETRI Journal
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• v.45 no.1
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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.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.54 no.7
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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.

• Proceedings of the KIEE Conference
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• 2004.07c
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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.