Harmonic evaluation of traction system by Monte Carlo simulation

This paper presents a method to predict the harmonic current level of traction system with phase-controlled DC Drives by Monte Carlo simulation. Based on Behavioral Modeling Technique (BMT), a model for electrical unit of traction is proposed. The probability density functions (pdf) of speed and notch numbers are obtained from longtime field measurement. The mean and variance of harmonic current of single electrical unit is obtained based on the speed pdf and traction electrical unit model. The results of Monte Carlo simulation are in good accordance with the experimental and analytic conclusions. The harmonics of a different number of trains are systematically investigated. It is shown the Total Harmonic Distortion (THD) decreases with the increase of the number of trains and the harmonic current per train decreases with the train number because of the harmonic cancellation.published_or_final_versio

Modeling of electric railway vehicle for harmonic analysis of traction power-supply system using spline interpolation in frequency domain

It is essential to model nonlinear traction converter loads for harmonic analysis of traction systems. A behavioral model in frequency domain to represent electric railway vehicle based on testing and measurement is proposed for harmonic analysis. The harmonic current characteristics are represented by a set of polynomials generated from cubic smoothing spline interpolation. The purpose of this paper is to report and discuss the development of an electric railway model for harmonic analysis and demonstrate results from the simulation with this train load model. System simulation based on this model is performed and the results match satisfactorily with field measurement.published_or_final_versio

Probabilistic characterization of current harmonics of electrical traction power supply system by analytic method

Current harmonics of an urban railway traction system in Hong Kong are investigated by analytic approach. With the statistic knowledge of speed and notch number of the trains in the system, the mean and variance of harmonic current of individual trains are computed based on a behavior oriented model of the traction electrical unit. According to the Large Number Law and Central Limit Theorem, current harmonics at a substation, which is a vectorial summation of harmonics of random number of trains electrically connected to it, are normally distributed provided that the number of trains is large enough. A set of equations are established by which probability density functions (pdfs) of current harmonics at a substation are calculated and found to be in good accordance with results obtained by Monte Carlo simulation. This approach of harmonics evaluation for traction system with random loading has evident advantages of cheap, fast and convenience and with no compromise of accuracy.published_or_final_versio

Traction system scheduling to minimize harmonic current level at substation by genetic algorithm

Harmonics of individual trains are closely related to its loading, speed and operation mode. The harmonic current at substations is the sum of the individual components from all the trains electrically connected to the substation. There will be cancellation of the harmonics if the harmonics are not of the same phase angles. It is possible to schedule the traction system so as to minimize the harmonic distortion, improve the power factor and reduce the harmonic currents at substations. In this study genetic algorithm (GA) is used to find out the optimal schedule of the system with minimum harmonic levels. The optimized solution can be integrated into automatic train operation (ATO) controller to control the departure, speed regulation of each train of the system. Mathematical description of the problem is first presented and the genetic algorithm is introduced. The optimal solution is given at the end of this paper. It is demonstrated that the scheduling of traction system is applicable to harmonic reduction and GA is fit for such kinds of optimization problems. Such method of harmonics reduction can bring about considerable saving in filtering equipment.published_or_final_versio

Pitfalls in diagnosing septic arthritis in Hong Kong children: ten years' experience

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Artificial neural network accurately predicts hepatitis B surface antigen seroclearance

BACKGROUND & AIMS: Hepatitis B surface antigen (HBsAg) seroclearance and seroconversion are regarded as favorable outcomes of chronic hepatitis B (CHB). This study aimed to develop artificial neural networks (ANNs) that could accurately predict HBsAg seroclearance or seroconversion on the basis of available serum variables. METHODS: Data from 203 untreated, HBeAg-negative CHB patients with spontaneous HBsAg seroclearance (63 with HBsAg seroconversion), and 203 age- and sex-matched HBeAg-negative controls were analyzed. ANNs and logistic regression models (LRMs) were built and tested according to HBsAg seroclearance and seroconversion. Predictive accuracy was assessed with area under the receiver operating characteristic curve (AUROC). RESULTS: Serum quantitative HBsAg (qHBsAg) and HBV DNA levels, qHBsAg and HBV DNA reduction were related to HBsAg seroclearance (P<0.001) and were used for ANN/LRM-HBsAg seroclearance building, whereas, qHBsAg reduction was not associated with ANN-HBsAg seroconversion (P = 0.197) and LRM-HBsAg seroconversion was solely based on qHBsAg (P = 0.01). For HBsAg seroclearance, AUROCs of ANN were 0.96, 0.93 and 0.95 for the training, testing and genotype B subgroups respectively. They were significantly higher than those of LRM, qHBsAg and HBV DNA (all P<0.05). Although the performance of ANN-HBsAg seroconversion (AUROC 0.757) was inferior to that for HBsAg seroclearance, it tended to be better than those of LRM, qHBsAg and HBV DNA. CONCLUSIONS: ANN identifies spontaneous HBsAg seroclearance in HBeAg-negative CHB patients with better accuracy, on the basis of easily available serum data. More useful predictors for HBsAg seroconversion are still needed to be explored in the future.published_or_final_versio

Nature of light correlations in ghost imaging

We investigate the nature of correlations in Gaussian light sources used for ghost imaging. We adopt methods from quantum information theory to distinguish genuinely quantum from classical correlations. Combining a microscopic analysis of speckle-speckle correlations with an effective coarse-grained description of the beams, we show that quantum correlations exist even in `classical'-like thermal light sources, and appear relevant for the implementation of ghost imaging in the regime of low illumination. We further demonstrate that the total correlations in the thermal source beams effectively determine the quality of the imaging, as quantified by the signal-to-noise ratio.Comment: 12 pages, 5 figures. To appear in Scientific Reports (NPG

Platform-independent Secure Blockchain-Based Voting System

Cryptographic techniques are employed to ensure the security of voting systems in order to increase its wide adoption. However, in such electronic voting systems, the public bulletin board that is hosted by the third party for publishing and auditing the voting results should be trusted by all participants. Recently a number of blockchain-based solutions have been proposed to address this issue. However, these systems are impractical to use due to the limitations on the voter and candidate numbers supported, and their security framework, which highly depends on the underlying blockchain protocol and suffers from potential attacks (e.g., force-abstention attacks). To deal with two aforementioned issues, we propose a practical platform-independent secure and verifiable voting system that can be deployed on any blockchain that supports an execution of a smart contract. Verifiability is inherently provided by the underlying blockchain platform, whereas cryptographic techniques like Paillier encryption, proof-of-knowledge, and linkable ring signature are employed to provide a framework for system security and user-privacy that are independent from the security and privacy features of the blockchain platform. We analyse the correctness and coercion-resistance of our proposed voting system. We employ Hyperledger Fabric to deploy our voting system and analyse the performance of our deployed scheme numerically

Twist and snai1 expression in pharyngeal squamous cell carcinoma stroma is related to cancer progression

<p>Abstract</p> <p>Background</p> <p>Epithelial-mesenchymal transition (EMT) is a crucial process in tumorigenesis since tumor cells attain fibroblast-like features enabling them to invade to surrounding tissue. Two transcription factors, <it>TWIST </it>and <it>SNAI1</it>, are fundamental in regulating EMT.</p> <p>Methods</p> <p>Immunohistochemistry was used to study the expression of TWIST and SNAI1 in 109 pharyngeal squamous cell carcinomas.</p> <p>Results</p> <p>Tumors with intense stromal staining of TWIST relapsed more frequently (p = 0.04). Tumors with both positive TWIST and SNAI1 immunoreactivity in the stroma were at least Stage II (p = 0.05) and located more often in hypopharynx (p = 0.035). Tumors with negative immunostaining of TWIST and SNAI1 in the stromal compartment were smaller (T1-2) (p = 0.008), less advanced (SI-II) (p = 0.031) and located more often in the oropharynx (p = 0.007). Patients with negative SNAI1 and TWIST immunostaining in tumor stroma had a better 5-year disease-specific and overall survival (p = 0.037 and p = 0.014 respectively).</p> <p>Conclusion</p> <p>TWIST and SNAI1 expression in stromal cells is associated with clinical and histopathological characteristics that indicate progressive disease. Negative expression of these EMT-promoting transcription factors predicts a better outcome.</p