Dielectric studies of tin based chalcogenide glasses

The dc conductivity and dielectric parameters of glassy system of a-Se₇₀Te_30−x Sn _x (x = 0, 2, 4, 6, 8 and 10) glasses have been investigated. Frequency and temperature dependence of dielectric constants (ε′) and dielectric loss (ε′′) are studied in the frequency range 120–100 kHz and temperature range 300–390 K. Dielectric dispersion is observed when Tin (Sn) is incorporated to a-Se–Te system in the entire temperature range. These results explain that the dc conduction loss is dominated in the present system. From dc conductivity studies it is observed that the dc conductivity and activation energy increases with increasing tin concentration in the present system.     

Optical,structural and electrical investigations on PbTe<Subscript>1−<Emphasis Type="Italic">x</Emphasis></Subscript>S<Subscript><Emphasis Type="Italic">x</Emphasis></Subscript> alloys

The fabrication of devices with lead salts and their alloys with detecting and lasing capabilities has been an important technological development. The high quality polycrystalline thin films of PbTe_1−x S _x with variable composition (0 ≤ x ≤ 1) have been deposited onto ultra clean glass substrates by vacuum evaporation technique. Optical, structural and electrical properties of PbTe_1−x S _x thin films have been examined. Absorption coefficient and band gap of the films were determined by absorbance measurements in wavelength range 2,500–5,000 nm using FTIR spectrophotometer. Sample nature, crystal structure and lattice parameter of the films were determined from X-ray diffraction patterns. DC conductivity and activation energy of the films were measured in temperature range 300–380 K through I–V measurements.     

A Fourier Series Generalized Geometry-Based Analytical Model of Switched Reluctance Machines

A novel invertible generalized flux/current switched reluctance machine (SRM) model based on the Fourier series expansion is presented. This model, which is derived from machine geometry and materials properties, is accurate enough to be used for actual machine representation and can also be simplified for real-time controller applications. Simulation and experimental results illustrate that the proposed modeling approach provides better representation of the SRM than other existing techniques     

Diagnosis of attention deficit hyperactivity disorder using non‐linear analysis of the EEG signal

Attention deficit hyperactivity disorder (ADHD) is a common behavioural disorder that may be found in 5%–8% of the children. Early diagnosis of ADHD is crucial for treating the disease and reducing its harmful effects on education, employment, relationships, and life quality. On the other hand, non‐linear analysis methods are widely applied in processing the electroencephalogram (EEG) signals. It has been proved that the brain neuronal activity and its related EEG signals have chaotic behaviour. Hence, chaotic indices can be employed to classify the EEG signals. In this study, a new approach is proposed based on the combination of some non‐linear features to distinguish ADHD from normal children. Lyapunov exponent, fractal dimension, correlation dimension and sample, fuzzy and approximate entropies are the non‐linear extracted features. For computing, the chaotic time series of obtained EEG in the brain frontal lobe (FP1, FP2, F3, F4, and Fz) need to be analysed. Experiments on a set of EEG signal obtained from 50 ADHD and 26 normal cases yielded a sensitivity, specificity, and accuracy of 98, 92.31, and 96.05%, respectively. The obtained accuracy provides a significant improvement in comparison to the other similar studies in identifying and classifying children with ADHD.Inspec keywords: feature extraction, time series, fractals, electroencephalography, medical disorders, neurophysiology, medical signal processing, entropy, signal classification, Lyapunov methodsOther keywords: nonlinear extracted features, chaotic time series, identifying classifying children, attention deficit hyperactivity disorder, nonlinear analysis methods, electroencephalogram signals, brain neuronal activity, chaotic behaviour, chaotic indices, EEG signals, nonlinear features, approximate entropies, common behavioural disorder, early diagnosis, life quality, ADHD     

Modeling, Simulation, and control of switched reluctance motor drives

This paper presents the modeling, simulation, and control aspects of four-quadrant switched reluctance motor (SRM) drives. The design of SRM drive systems must be focused on application-based appropriate control and engineering solutions needed to overcome the practical issues. A complex model is described for the physical motor simulation to incorporate the important dynamics of the SRM. A simpler, but quite accurate, model is presented for the SRM controller. Various practical limitations have been incorporated in the simulation model to make it closer to the experimental setup. The SRM control parameters are chosen based on torque-per-ampere maximization requirement. Experimental results for a 1.0-kW SRM obtained on a digital platform are presented along with useful guidelines for prototype implementation.     

SYNERGISTIC EFFECTS OF ANIONIC SURFACTANT AND NONIONIC POLYMER ADDITIVES ON DRAG REDUCTION

Turbulent drag reduction (DR) behavior of mixed nonionic polymer and anionic surfactant solutions in water was studied in a pipeline set up to explore the synergic effects of mixed additives on DR. The concentration of polymer polyethylene oxide (PEO) was varied from 0 to 2000 ppm and the concentration of surfactant sodium dodecyl sulfate (SDS) was varied from 0 to 5000 ppm. The critical aggregation concentration (CAC), where the interaction between the polymer and the surfactant begins, and the polymer saturation point (PSP), where the polymer molecules become saturated with the surfactant, were determined using electrical conductivity and surface tension measurements. As the polymer concentration was increased the CAC decreased but the PSP increased. The relative viscosity showed a remarkable increase upon the addition of surfactant to the polymer solution due to extension of polymer chains caused by the formation of micelles on the backbone of the polymer molecules. The data exhibited a considerable increase in DR in the case of mixed polymer/surfactant systems. The percent reduction in friction factor was as high as 79 when 3000 ppm or more surfactant was added to the 500 ppm polymer solution. Furthermore, the drag reduction behavior of the polymer solution changed from so-called Type A to Type B. In Type A drag reduction, a transition from laminar to turbulent regime is observed with a clear-cut onset point. In Type B drag reduction, no transition or onset point is observed; the data fall on a gradual extension of the laminar line.