Rong-Ching Wu

Parameter Identification of Induction Machine With a Starting No-Load Low-Voltage Test

This paper proposes the use of a steady-state model to identify the parameters of an induction motor. A time-varying impedance can be found with the time-varying voltages and currents under a starting no-load low-voltage test, where time-varying slip rates were also recorded. With a proper conversion, the variations of impedance versus slip rates could be acquired as sampled data for identification, and both electrical and mechanical parameters can be found. A least mean square (LMS) method was used with a particle swarm optimization method to solve the aforementioned problem. The method to find a good set of initial values for LMS is also described in this paper. Many tests were conducted to simulate the starting phases of an induction machine to compare with the existing data. From various tests, the practicability and accuracy of this method can be proven.

EARLY PREDICTION OF MEDICATION REFRACTORINESS IN CHILDREN WITH IDIOPATHIC EPILEPSY BASED ON SCALP EEG ANALYSIS

Refractory epilepsy often has deleterious effects on an individuals health and quality of life. Early identification of patients whose seizures are refractory to antiepileptic drugs is important in considering the use of alternative treatments. Although idiopathic epilepsy is regarded as having a significantly lower risk factor of developing refractory epilepsy, still a subset of patients with idiopathic epilepsy might be refractory to medical treatment. In this study, we developed an effective method to predict the refractoriness of idiopathic epilepsy. Sixteen EEG segments from 12 well-controlled patients and 14 EEG segments from 11 refractory patients were analyzed at the time of first EEG recordings before antiepileptic drug treatment. Ten crucial EEG feature descriptors were selected for classification. Three of 10 were related to decorrelation time, and four of 10 were related to relative power of delta/gamma. There were significantly higher values in these seven feature descriptors in the well-controlled group as compared to the refractory group. On the contrary, the remaining three feature descriptors related to spectral edge frequency, kurtosis, and energy of wavelet coefficients demonstrated significantly lower values in the well-controlled group as compared to the refractory group. The analyses yielded a weighted precision rate of 94.2%, and a 93.3% recall rate. Therefore, the developed method is a useful tool in identifying the possibility of developing refractory epilepsy in patients with idiopathic epilepsy.

Parameter estimation of induction machines under no-load test

This paper uses time-varied signals of voltage, current and rotor speed to compute the equivalent circuit parameters, moment of inertia, and friction coefficient of an induction machine. A time-varied impedance can be found by the time-varied voltage and current. From the variation of impedance to the rotor speed, the parameters of steady equivalent circuit can be found. According to the equivalent circuit and rotor speed, the torque can be found via established dynamic system model. On the basis of torque and rotor speed with time, moment of inertia and friction coefficient of the motor can be obtained. This paper uses the least mean square method to solve the above parameters. The initial values of least mean square are also described in this paper. This paper used estimated parameters to simulate the starting states of an induction machine to compare with the real one, accordingly, practicability and accuracy of this method has been proven.

Fast analysis for power parameters by the Newton method

This paper proposes a method to rapidly analyze power parameters. This method uses two adjacent data to compute the fundamental frequency component of voltage or current. The parameters of fundamental frequency component include frequency, amplitude, and phase. Under the condition of varied parameters, the frequency and the phase are dependent. This method fixes the frequency and computes the amplitude and phase, and then stable results will be obtained. The Newton method, which can rapidly find the parameters, is used to calculate the amplitude and the phase. Harmonic and noise both exist in the practical measured signal; these interferences will influence the calculated result. This paper designs a band pass filter to reduce the interferences and to retain the fundamental frequency component. The method can track the varied parameters of voltage and current, and subsequently, the time-varying impedance will be found.

Revisiting effectiveness of content-aware switching for Web traffic distribution

Over the past few years, there has been significant interest in content-aware routing that use the information found in the payload of packets to provide intelligent content distribution. However, the effectiveness of the idea of content-aware routing is still unclear though these mechanisms have become increasingly important building block for Internet service providers. The aim of this paper is to evaluate the load distribution policies on a production Web cluster with the content-aware routing mechanism. While most of published performance results are measured with simulation or artificial workload in the lab, this is the first performance study using extensive real traffics. We also find a special effect caused by code 304, which may significantly diminish the benefits of the content-aware routing techniques. We then propose a mechanism that can effectively support to shield off the effects.

Support Vector Machine and Polynomial Fitting Approach for radio effective zones under Power Lines in Taiwan Railway

The purpose of this paper is to research the radio effective zones related to the service of a radio system for the dispatch of trolleys and the operation of level-crossings in the service of Taiwan Railways. The service uses radio and radio propagation to dispatch messages to trolleys and level-crossings throughout the railway system when the critical situation is occurred or the emergency button is pressed by users to allow the train driver to break subsequently. In order to estimate the radio effective zone, we perform some realistic measurements related to level-crossings and trolleys. Then, the data is analyzed using a combination of support vector machine (SVM) and polynomial approximation to estimate the radio effective zone, and create a new optimal model specific to the needs of Western Line, Pingtung Line and the Kaohsiung City local line in the Taiwan Railway context.

Cumulative effect of transcranial direct current stimulation in patients with partial refractory epilepsy and its association with phase lag index-A preliminary study

There is an urgent need for alternative treatments for refractory epilepsy. We investigated the effect of two courses of cathodal transcranial direct current stimulation (tDCS) in nine patients with partial refractory epilepsy. A two-course treatment (1 month per course, with six sessions of stimulation per course within the first 2 weeks by 2-mA cathodal tDCS for 20 min) was administered to each patient. After the first course of tDCS, the average seizure frequency had decreased by 37.8 ± 21.9% compared with baseline (p = 0.001). After the second course, the average seizure frequency had decreased by 48.9 ± 31.2% compared with baseline (p = 0.002). Only seven of the nine patients maintained the same state of wakefulness in three electroencephalogram (EEG) recordings. We analyzed the EEG recordings of these seven patients on day 0 immediately posttreatment and on days 4 and 9 in the first course of tDCS. When compared with baseline, no significant change in the number of epileptiform discharges was observed. The day 9 phase lag index (PLI) decreased in five patients with seizure reduction after tDCS but increased in two patients without seizure reduction after tDCS. A significant negative correlation was observed between the day 9 PLI of alpha band and first-course seizure reduction (R2 = 0.6515) (p = 0.028). The results revealed that tDCS may be considered as an alternative treatment option for patients with refractory epilepsy, and its effect might be cumulative after repeated stimulations and associated with a decrease in PLI.

Quantitative EEG findings and response to treatment with antiepileptic medications in children with epilepsy

BACKGROUND Epilepsy is a common chronic disorder in pediatric neurology. Nowadays, a variety of antiepileptic drugs (AEDs) are available. A scientific method designed to evaluate the effectiveness of AEDs in the early stage of treatment has not been reported. PURPOSE In this study, we try to use quantitative EEG (QEEG) analysis as a biomarker to evaluate therapeutic effectiveness. METHODS 20 epileptic children were enrolled in this study. Participants were classified as effective if they achieved a reduction in seizure frequency over 50%. Ineffective was defined as a reduction in seizure frequency less than 50%. Eleven participants were placed in the effective group, the remaining 9 participants were placed in the ineffective group. EEG segments before and after 1-3months of antiepileptic drugs start/change were analyzed and compared by QEEG analysis. The follow-up EEG segments after the 2nd examinations were used to test the accuracy of the analytic results. RESULTS Six crucial EEG feature descriptors were selected for classifying the effective and ineffective groups. Significantly increased RelPowAlpha_avg_AVG, RelPowAlpha_snr_AVG, HjorthM_avg_AVG, and DecorrTime_snr_AVG values were found in the effective group as compared to the ineffective group. On the contrary, there were significantly decreases in DecorrTime_std_AVG, and Wavelet_db4_EnergyBand_5_avg_AVG values in the effective group as compared to the ineffective group. The analyses yielded a precision rate of 100%. When the follow-up EEG segments were used to test the analytic results, the accuracy was 83.3%. CONCLUSION The developed method is a useful tool in analyzing the effectiveness of antiepileptic drugs. This method may assist pediatric neurologists in evaluating the efficacy of AEDs and making antiepileptic drug adjustments when managing epileptic patients in the early stage.

Listening to Mozart K.448 decreases electroencephalography oscillatory power associated with an increase in sympathetic tone in adults: a post-intervention study

Summary Objective Listening to Mozart K.448 has been demonstrated to improve spatial task scores, leading to what is known as the Mozart Effect. However, most of these reports only describe the phenomena but lack the scientific evidence needed to properly investigate the mechanism of Mozart Effect. In this study, we used electroencephalography (EEG) and heart rate variability (HRV) to evaluate the effects of Mozart K.448 on healthy volunteers to explore Mozart Effect. Design An EEG-based post-intervention analysis. Setting Kaohsiung Medical University Hospital, Kaohsiung, Taiwan. Participants Twenty-nine college students were enrolled. They received EEG and electrocardiogram examinations simultaneously before, during and after listening to the first movement of Mozart K.448. Main outcome measure EEG alpha, theta and beta power and HRV were compared in each stage. Results The results showed a significant decrease in alpha, theta and beta power when they listened to Mozart K.448. In addition, the average root mean square successive difference, the proportion derived by dividing NN50 by the total number of NN intervals, standard deviations of NN intervals and standard deviations of differences between adjacent NN intervals showed a significant decrease, while the high frequency revealed a significant decrease with a significantly elevated low-frequency/high-frequency ratio. Conclusion Listening to Mozart K.448 significantly decreased EEG alpha, theta and beta power and HRV. This study indicates that there is brain cortical function and sympathetic tone activation in healthy adults when listening to Mozart K.448, which may play an important role in the mechanism of Mozart Effect.

Complete parameter estimation of induction machines by time-varied parameters

This paper proposes a method to find the equivalent circuit parameters, moment of inertia, and friction coefficient of an induction machine. The reference data include time-varied signals of voltage, current and rotor speed. By the time-varied voltage and current, a time-varied impedance can be found. The parameters of equivalent circuit can be found from the variation of impedance to the rotor speed. And then, the torque can be found via dynamic system model and rotor speed. From the torque and rotor speed with time, moment of inertia and friction coefficient of the motor can be obtained, too. The least mean square method is used to solve the above parameters in this paper. The initial values of least mean square are also described. The comparison of the simulated performance in starting states of an induction machine with the real one is discussed in this paper, accordingly, practicability and accuracy of this method has been proven.