Reduction of current ripple and acoustic noise in dual-inverter pole-changing induction motor drives

In this paper, a new dual-inverter pole-changing induction motor drive is proposed and analyzed. The two keys are to adopt a new pole-changing induction motor to extend the constant-power operating range and to develop a new dual-inverter to significantly suppress the harmonic torques (hence the acoustic noise). The correspondingly maximum torque capability and harmonic torque cancellation are particularly analyzed and discussed.published_or_final_versio

Spectral analysis of a new six-phase pole-changing induction motor drive for electric vehicles

In this paper, a new six-phase pole-changing induction motor drive is proposed to extend the constant-power operating range for electric vehicle application. The double Fourier series is newly employed to analyze the spectra of the motor phase voltage and current. Consequently, the harmonic expression of the inverter-dc-link current can be derived. In order to reduce the dc-link harmonics, a new sinusoidal pulsewidth-modulation strategy is developed for the proposed six-phase inverter. Experimental results, particularly the spectra of the phase current and the dc-link current, are given to verify the theoretical analysis.published_or_final_versio

Modeling and analysis of chaotic behavior in switched reluctance motor drives

In this paper, modeling and analysis of chaotic behavior in switched reluctance (SR) motor drives using voltage PWM regulation is presented. The key is to derive a Poincare map that is based on the nonlinear flux linkage model. Its Jacobian matrix can be evaluated by solving the corresponding variational equation. Based on the Poincare map and its Jacobian matrix, the analysis of chaotic behavior is presented. Furthermore, bifurcation diagrams are also figured out. They facilitate to determine the stable range of various system parameters so as to avoid the occurrence of chaos. Both computer simulations and experimental measurements are given to verify the theoretical modeling and analysis.published_or_final_versio

Sample entropy analysis of EEG signals via artificial neural networks to model patients' consciousness level based on anesthesiologists experience.

Electroencephalogram (EEG) signals, as it can express the human brain's activities and reflect awareness, have been widely used in many research and medical equipment to build a noninvasive monitoring index to the depth of anesthesia (DOA). Bispectral (BIS) index monitor is one of the famous and important indicators for anesthesiologists primarily using EEG signals when assessing the DOA. In this study, an attempt is made to build a new indicator using EEG signals to provide a more valuable reference to the DOA for clinical researchers. The EEG signals are collected from patients under anesthetic surgery which are filtered using multivariate empirical mode decomposition (MEMD) method and analyzed using sample entropy (SampEn) analysis. The calculated signals from SampEn are utilized to train an artificial neural network (ANN) model through using expert assessment of consciousness level (EACL) which is assessed by experienced anesthesiologists as the target to train, validate, and test the ANN. The results that are achieved using the proposed system are compared to BIS index. The proposed system results show that it is not only having similar characteristic to BIS index but also more close to experienced anesthesiologists which illustrates the consciousness level and reflects the DOA successfully.This research is supported by the Center forDynamical Biomarkers and Translational Medicine, National Central University, Taiwan, which is sponsored by Ministry of Science and Technology (Grant no. MOST103-2911-I-008-001). Also, it is supported by National Chung-Shan Institute of Science & Technology in Taiwan (Grant nos. CSIST-095-V301 and CSIST-095-V302)

Primary Care Workforce And Continuous Medical Education In China: Lessons To Learn From A Nationwide Cross-sectional Survey

published_or_final_versio

Hamiltonian structure for dispersive and dissipative dynamical systems

We develop a Hamiltonian theory of a time dispersive and dissipative inhomogeneous medium, as described by a linear response equation respecting causality and power dissipation. The proposed Hamiltonian couples the given system to auxiliary fields, in the universal form of a so-called canonical heat bath. After integrating out the heat bath the original dissipative evolution is exactly reproduced. Furthermore, we show that the dynamics associated to a minimal Hamiltonian are essentially unique, up to a natural class of isomorphisms. Using this formalism, we obtain closed form expressions for the energy density, energy flux, momentum density, and stress tensor involving the auxiliary fields, from which we derive an approximate, ``Brillouin-type,'' formula for the time averaged energy density and stress tensor associated to an almost mono-chromatic wave.Comment: 68 pages, 1 figure; introduction revised, typos correcte

A photometric monitoring of bright high-amplitude delta Scuti stars. II. Period updates for seven stars

We present new photometric data for seven high-amplitude delta Scuti stars. The observations were acquired between 1996 and 2002, mostly in the Johnson photometric system. For one star (GW UMa), our observations are the first since the discovery of its pulsational nature from the Hipparcos data.The primary goal of this project was to update our knowledge on the period variations of the target stars. For this, we have collected all available photometric observations from the literature and constructed decades-long O-C diagrams of the stars. This traditional method is useful because of the single-periodic nature of the light variations. Text-book examples of slow period evolution (XX Cyg, DY Her, DY Peg) and cyclic period changes due to light-time effect (LITE) in a binary system (SZ Lyn) are updated with the new observations. For YZ Boo, we find a period decrease instead of increase. The previously suggested LITE-solution of BE Lyn (Kiss & Szatmary 1995) is not supported with the new O-C diagram. Instead of that, we suspect the presence of transient light curve shape variations mimicking small period changes.Comment: 11 pages, 15 figures, accepted for publication in A&

Nanofluids Containing γ-Fe2O3 Nanoparticles and Their Heat Transfer Enhancements

Homogeneous and stable magnetic nanofluids containing γ-Fe2O3 nanoparticles were prepared using a two-step method, and their thermal transport properties were investigated. Thermal conductivities of the nanofluids were measured to be higher than that of base fluid, and the enhanced values increase with the volume fraction of the nanoparticles. Viscosity measurements showed that the nanofluids demonstrated Newtonian behavior and the viscosity of the nanofluids depended strongly on the tested temperatures and the nanoparticles loadings. Convective heat transfer coefficients tested in a laminar flow showed that the coefficients increased with the augment of Reynolds number and the volume fraction

A Web-Based Intervention for Social Media Addiction Disorder Management in Higher Education: Quantitative Survey Study.

BACKGROUND: Social media addiction disorder has recently become a major concern and has been reported to have negative impacts on postgraduate studies, particularly addiction to Facebook. Although previous studies have investigated the effects of Facebook addiction disorder in learning settings, there still has been a lack of studies investigating the relationship between online intervention features for Facebook addiction focusing on postgraduate studies. OBJECTIVE: In an attempt to understand this relationship, this study aimed to carry out an investigation on online intervention features for effective management of Facebook addiction in higher education. METHODS: This study was conducted quantitatively using surveys and partial least square-structural equational modeling. The study involved 200 postgraduates in a Facebook support group for postgraduates. The Bergen Facebook Addiction test was used to assess postgraduates' Facebook addiction level, whereas online intervention features were used to assess postgraduates' perceptions of online intervention features for Facebook addiction, which are as follows: (1) self-monitoring features, (2) manual control features, (3) notification features, (4) automatic control features, and (5) reward features. RESULTS: The study discovered six Facebook addiction factors (relapse, conflict, salience, tolerance, withdrawal, and mood modification) and five intervention features (notification, auto-control, reward, manual control, and self-monitoring) that could be used in the management of Facebook addiction in postgraduate education. The study also revealed that relapse is the most important factor and mood modification is the least important factor. Furthermore, findings indicated that notification was the most important intervention feature, whereas self-monitoring was the least important feature. CONCLUSIONS: The study's findings (addiction factors and intervention features) could assist future developers and educators in the development of online intervention tools for Facebook addiction management in postgraduate education