デンリョク キキ セツビ シンダン ノ タメ ノ コガタ デンジハ センシング システム ノ カイハツ

Partial discharge (PD) is a symptom of insulation degradation of electric power apparatus and facilities. This paper shows a new small receiver for detecting the electromagnetic waves emitted from PD. The receiver has an analog to digital converter (ADC) with 8 bits and a field programmable gate array (FPGA). It is confirmed that the receiver synchronously can obtain two signals generated by using a generator. The comparison of dynamic range of the receiver and spectrum analyzer (SA), which has been widely used, and the investigation of effect of pulse repetition frequency (PRF) are carried out

デンリョク キキ セツビ ノ タメ ノ ジュシン アンテナ ノ コガタカ

Partial discharge (PD) is a symptom of insulation degradation of electric power apparatus and facilities. We have developed remote sensing system to receive the electromagnetic (EM) waves emitted from PD. In this project, we investigated the EM waves at the antenna of remote sensing system using the finite difference time domain (FDTD) method and the resonant frequency components of EM waves in a shielded metal room using a spectrum analyzer. These results are useful for downsizing the antennas

デンリョク キキ セツビ ゼツエン レッカ シンダン ノ タメ ノ デンジハ センシング システム ノ カイハツ

Partial discharge (PD) is a symptom of the insulation degradation of the electric power apparatus and facilities. In this study a new method was developed for finding the direction of arrival (DOA) of the electromagnetic waves emitted from PD using Bayesian Network. The time delay between two antennas computed from digital data generally has error because of the effect of sampling time. Therefore the angle of arrival estimated from the time delay also has the estimation error. The probabilistic method of reasoning with uncertain information was investigated. This method provides the probabilities of each angle based on Bayes’ Theorem. The proposed method is able to estimate the angle of arrival of the electromagnetic waves

Why Are Outcomes Different for Registry Patients Enrolled Prospectively and Retrospectively? Insights from the Global Anticoagulant Registry in the FIELD-Atrial Fibrillation (GARFIELD-AF).

Background: Retrospective and prospective observational studies are designed to reflect real-world evidence on clinical practice, but can yield conflicting results. The GARFIELD-AF Registry includes both methods of enrolment and allows analysis of differences in patient characteristics and outcomes that may result. Methods and Results: Patients with atrial fibrillation (AF) and ≥1 risk factor for stroke at diagnosis of AF were recruited either retrospectively (n = 5069) or prospectively (n = 5501) from 19 countries and then followed prospectively. The retrospectively enrolled cohort comprised patients with established AF (for a least 6, and up to 24 months before enrolment), who were identified retrospectively (and baseline and partial follow-up data were collected from the emedical records) and then followed prospectively between 0-18 months (such that the total time of follow-up was 24 months; data collection Dec-2009 and Oct-2010). In the prospectively enrolled cohort, patients with newly diagnosed AF (≤6 weeks after diagnosis) were recruited between Mar-2010 and Oct-2011 and were followed for 24 months after enrolment. Differences between the cohorts were observed in clinical characteristics, including type of AF, stroke prevention strategies, and event rates. More patients in the retrospectively identified cohort received vitamin K antagonists (62.1% vs. 53.2%) and fewer received non-vitamin K oral anticoagulants (1.8% vs . 4.2%). All-cause mortality rates per 100 person-years during the prospective follow-up (starting the first study visit up to 1 year) were significantly lower in the retrospective than prospectively identified cohort (3.04 [95% CI 2.51 to 3.67] vs . 4.05 [95% CI 3.53 to 4.63]; p = 0.016). Conclusions: Interpretations of data from registries that aim to evaluate the characteristics and outcomes of patients with AF must take account of differences in registry design and the impact of recall bias and survivorship bias that is incurred with retrospective enrolment. Clinical Trial Registration: - URL: http://www.clinicaltrials.gov . Unique identifier for GARFIELD-AF (NCT01090362)

Discriminating apneic snorers and benign snorers based on snoring formant extracted via a noise-robust linear prediction technique

Snoring is the earliest and the most common symptom of Obstructive Sleep Apnea (OSA). Quantitative analysis of snoring, however, is not used at present in the clinical diagnosis of the disease. Several researchers have reported differences in the formant frequencies of Apneic and benign snoring sounds (SS) based on linear prediction coding (LPC) analysis. However, SS is complex signal and at local low signal to noise ratio (SNR). This signal complexity should reduce the accuracy of formant estimation. In this paper, we propose a novel approach to the diagnosis of OSA based on the formants of SSs, extracted via a noise-robust linear prediction technique. The proposed method and existing LPC-based method are compared via a measure, a which indicates the standard deviation of first formant frequencies. The performance of the proposed method was evaluated on a database of clinical snoring sounds recorded overnight in the laboratory of a hospital sleep diagnostic center. Compared with existing LPC-based method, we show that the proposed method can differentiate (sensitivity: 88.9%, specificity: 88.9%, AUC: 0.85) between benign snoring (Apnea Hypopnea Index, AHI = 6.0 ± 3.2 event/h; 6188 episodes) and apneic snoring (AHI = 40.7 ± 20.2 event/h; 14066 episodes)