A nine-level inverter topology for medium-voltage induction motor drive with open-end stator winding

A new scheme for nine-level voltage space-vector generation for medium-voltage induction motor (IM) drives with open-end stator winding is presented in this paper. The proposed nine-level power converter topology consists of two conventional three-phase two-level voltage source inverters powered by isolated dc sources and six floating-capacitor-connected H-bridges. The H-bridge capacitor voltages are effectively maintained at the required asymmetrical levels by employing a space vector modulation (SVPWM) based control strategy. An interesting feature of this topology is its ability to function in five-or three-level mode, in the entire modulation range, at full-power rating, in the event of any failure in the H-bridges. This feature significantly improves the reliability of the proposed drive system. Each leg of the three-phase two-level inverters used in this topology switches only for a half cycle of the reference voltage waveform. Hence, the effective switching frequency is reduced by half, resulting in switching loss reduction in high-voltage devices. The transient as well as the steady-state performance of the proposed nine-level inverter-fed IM drive system is experimentally verified in the entire modulation range including the overmodulation region.

Noise tolerance under risk minimization

In this paper, we explore noise-tolerant learning of classifiers. We formulate the problem as follows. We assume that there is an unobservable training set that is noise free. The actual training set given to the learning algorithm is obtained from this ideal data set by corrupting the class label of each example. The probability that the class label of an example is corrupted is a function of the feature vector of the example. This would account for most kinds of noisy data one encounters in practice. We say that a learning method is noise tolerant if the classifiers learnt with noise-free data and with noisy data, both have the same classification accuracy on the noise-free data. In this paper, we analyze the noise-tolerance properties of risk minimization (under different loss functions). We show that risk minimization under 0-1 loss function has impressive noise-tolerance properties and that under squared error loss is tolerant only to uniform noise; risk minimization under other loss functions is not noise tolerant. We conclude this paper with some discussion on the implications of these theoretical results.

Joint evaluation of channel feedback schemes, rate adaptation, and scheduling in OFDMA downlinks with feedback delays

Orthogonal frequency-division multiple access (OFDMA) systems divide the available bandwidth into orthogonal subchannels and exploit multiuser diversity and frequency selectivity to achieve high spectral efficiencies. However, they require a significant amount of channel state feedback for scheduling and rate adaptation and are sensitive to feedback delays. We develop a comprehensive analysis for OFDMA system throughput in the presence of feedback delays as a function of the feedback scheme, frequency-domain scheduler, and rate adaptation rule. Also derived are expressions for the outage probability, which captures the inability of a subchannel to successfully carry data due to the feedback scheme or feedback delays. Our model encompasses the popular best-n and threshold-based feedback schemes and the greedy, proportional fair, and round-robin schedulers that cover a wide range of throughput versus fairness tradeoff. It helps quantify the different robustness of the schedulers to feedback overhead and delays. Even at low vehicular speeds, it shows that small feedback delays markedly degrade the throughput and increase the outage probability. Further, given the feedback delay, the throughput degradation depends primarily on the feedback overhead and not on the feedback scheme itself. We also show how to optimize the rate adaptation thresholds as a function of feedback delay.

Experiences with a centralized scheduling approach for performance management of IEEE 802.11 wireless LANs

We present a centralized integrated approach for: 1) enhancing the performance of an IEEE 802.11 infrastructure wireless local area network (WLAN), and 2) managing the access link that connects the WLAN to the Internet. Our approach, which is implemented on a standard Linux platform, and which we call ADvanced Wi-fi Internet Service EnhanceR (ADWISER), is an extension of our previous system WLAN Manager (WM). ADWISER addresses several infrastructure WLAN performance anomalies such as mixed-rate inefficiency, unfair medium sharing between simultaneous TCP uploads and downloads, and inefficient utilization of the Internet access bandwidth when Internet transfers compete with LAN-WLAN transfers, etc. The approach is via centralized queueing and scheduling, using a novel, configurable, cascaded packet queueing and scheduling architecture, with an adaptive service rate. In this paper, we describe the design of ADWISER and report results of extensive experimentation conducted on a hybrid testbed consisting of real end-systems and an emulated WLAN on Qualnet. We also present results from a physical testbed consisting of one access point (AP) and a few end-systems.

Thermoelectric performance of a single-layer graphene sheet for energy harvesting

We investigate the thermoelectric (TE) figure-of-merit of a single-layer graphene (SLG) sheet by a physics-based analytical technique. We first develop analytical models of electrical and thermal resistances and the Seebeck coefficient of SLG by considering electron interactions with the in-plane and flexural phonons. Using those models, we show that both the figure-of-merit and the TE efficiency can be substantially increased with the addition of isotope doping as it significantly reduces the phonon-dominated thermal conductivity. In addition, we report that the TE open circuit output voltage and output power depends weakly on the SLG sheet dimensions and sheet concentration in the strongly diffusive regime. Proposed models agree well with the available experimental data and demonstrate the immense potential of graphene for waste-heat recovery application.

Performance and reliability of Gd2O3 and stacked Gd2O3-Eu2O3 metal-insulator-metal capacitors

Gd2O3-based metal-insulator-metal capacitors have been characterized with single layer (Gd2O3) and bilayer (Gd2O3/Eu2O3 and Eu2O3/Gd2O3) stacks for analog and DRAM applications. Although single layer Gd2O3 capacitors provide highest capacitance density (15 fF/mu m(2)), they suffer from high leakage current density, poor capacitance density-voltage linearity, and reliability. The stacked dielectrics help to reduce leakage current density (1.2x10(-5) A/cm(2) and 2.7 x 10(-5) A/cm(2) for Gd2O3/Eu2O3 and Eu2O3/Gd2O3, respectively, at -1 V), improve quadratic voltage coefficient of capacitance (331 ppm/V-2 and 374 ppm/V-2 for Gd2O3/Eu2O3 and Eu2O3/Gd2O3, respectively, at 1 MHz), and improve reliability, with a marginal reduction in capacitance density. This is attributed to lower trap heights as determined from Poole-Frenkel conduction mechanism, and lower defect density as determined from electrode polarization model.

Crop stage classification of hyperspectral data using unsupervised techniques

The presence of a large number of spectral bands in the hyperspectral images increases the capability to distinguish between various physical structures. However, they suffer from the high dimensionality of the data. Hence, the processing of hyperspectral images is applied in two stages: dimensionality reduction and unsupervised classification techniques. The high dimensionality of the data has been reduced with the help of Principal Component Analysis (PCA). The selected dimensions are classified using Niche Hierarchical Artificial Immune System (NHAIS). The NHAIS combines the splitting method to search for the optimal cluster centers using niching procedure and the merging method is used to group the data points based on majority voting. Results are presented for two hyperspectral images namely EO-1 Hyperion image and Indian pines image. A performance comparison of this proposed hierarchical clustering algorithm with the earlier three unsupervised algorithms is presented. From the results obtained, we deduce that the NHAIS is efficient.

Mitigation of lower order harmonics in a grid-connected single-phase PV inverter

In this paper, a simple single-phase grid-connected photovoltaic (PV) inverter topology consisting of a boost section, a low-voltage single-phase inverter with an inductive filter, and a step-up transformer interfacing the grid is considered. Ideally, this topology will not inject any lower order harmonics into the grid due to high-frequency pulse width modulation operation. However, the nonideal factors in the system such as core saturation-induced distorted magnetizing current of the transformer and the dead time of the inverter, etc., contribute to a significant amount of lower order harmonics in the grid current. A novel design of inverter current control that mitigates lower order harmonics is presented in this paper. An adaptive harmonic compensation technique and its design are proposed for the lower order harmonic compensation. In addition, a proportional-resonant-integral (PRI) controller and its design are also proposed. This controller eliminates the dc component in the control system, which introduces even harmonics in the grid current in the topology considered. The dynamics of the system due to the interaction between the PRI controller and the adaptive compensation scheme is also analyzed. The complete design has been validated with experimental results and good agreement with theoretical analysis of the overall system is observed.

Common-mode filter design for PWM rectifier-based motor drives

A common-mode (CM) filter based on the LCL filter topology is proposed in this paper, which provides a parallel path for ground currents and which also restricts the magnitude of the EMI noise injected into the grid. The CM filter makes use of the components of a line to line LCL filter, which is modified to address the CM voltage with minimal additional components. This leads to a compact filtering solution. The CM voltage of an adjustable speed drive using a PWM rectifier is analyzed for this purpose. The filter design is based on the CM equivalent circuit of the drive system. The filter addresses the adverse effects of the PWM rectifier in an adjustable speed drive. Guidelines are provided on the selection of the filter components. Different variants of the filter topology are evaluated to establish the effectiveness of the proposed circuit. Experimental results based on EMI measurement on the grid side and the CM current measurement on the motor side are presented. These results validate the effectiveness of the filter.

Multiobjective discrete particle swarm optimization for multisensor image alignment

A new technique is proposed for multisensor image registration by matching the features using discrete particle swarm optimization (DPSO). The feature points are first extracted from the reference and sensed image using improved Harris corner detector available in the literature. From the extracted corner points, DPSO finds the three corresponding points in the sensed and reference images using multiobjective optimization of distance and angle conditions through objective switching technique. By this, the global best matched points are obtained which are used to evaluate the affine transformation for the sensed image. The performance of the image registration is evaluated and concluded that the proposed approach is efficient.

Estimating wind stress at the ocean surface from scatterometer observations

Wind stress is the most important ocean forcing for driving tropical surface currents. Stress can be estimated from scatterometer-reported wind measurements at 10 m that have been extrapolated to the surface, assuming a neutrally stable atmosphere and no surface current. Scatterometer calibration is designed to account for the assumption of neutral stability; however, the assumption of a particular sea state and negligible current often introduces an error in wind stress estimations. Since the fundamental scatterometer measurement is of the surface radar backscatter (sigma-0) which is related to surface roughness and, thus, stress, we develop a method to estimate wind stress directly from the scatterometer measurements of sigma-0 and their associated azimuth angle and incidence angle using a neural network approach. We compare the results with in situ estimations and observe that the wind stress estimations from this approach are more accurate compared with those obtained from the conventional estimations using 10-m-height wind measurements.

Calibration of etched fiber bragg grating sensor arrays for measurement of molecular surface adsorption

Etched Fiber Bragg Grating (EFBG) sensors are attractive from the point of the inherently high multiplexing ability of fiber based sensors. However, the strong dependence of the sensitivity of EFBG sensors on the fiber diameter requires robust methods for calibration when used for distributed sensing in a large array format. Using experimental data and numerical modelling, we show that knowledge of the wavelength shift during the etch process is necessary for high-fidelity calibration of EFBG arrays. However as this approach requires the monitoring of every element of the sensor array during etching, we also proposed and demonstrated a calibration scheme using data from bulk refractometry measurements conducted post-fabrication without needing any information about the etching process. Although this approach is not as precise as the first one, it may be more practical as there is no requirement to monitor each element of the sensor array. We were able to calibrate the response of the sensors to within 3% with the approach using information acquired during etching and to within 5% using the post-fabrication bulk refractometry approach in spite of the sensitivities of the array element differing by more than a factor of 4. These two approaches present a tradeoff between accuracy and practicality.

Detection limit of etched fiber bragg grating sensors

While Fiber Bragg Grating (FBG) sensors have been extensively used for temperature and strain sensing, clad etched FBGs (EFBGs) have only recently been explored for refractive index sensing. Prior literature in EFBG based refractive index sensing predominantly deals with bulk refractometry only, where the Bragg wavelength shift of the sensor as a function of the bulk refractive index of the sample can be analytically modeled, unlike the situation for adsorption of molecular thin films on the sensor surface. We used a finite element model to calculate the Bragg wavelength change as a function of thickness and refractive index of the adsorbing molecular layer and compared the model with the real-time, in-situ measurement of electrostatic layer-by-layer (LbL) assembly of weak polyelectrolytes on the silica surface of EFBGs. We then used this model to calculate the layer thickness of LbL films and found them to be in agreement with literature. Further, we used this model to arrive at a realistic estimate of the limit of detection of EFBG sensors based on nominal measurement noise levels in current FBG interrogation systems and found that sufficiently thinned EFBGs can provide a competitive platform for real-time measurement of molecular interactions while simultaneously leveraging the high multiplexing capabilities of fiber optics.

Nonquasi-static charge model for common double-gate MOSFETs adapted to gate oxide thickness asymmetry

With the unique quasi-linear relationship between the surface potentials along the channel, recently we have proposed a quasi-static terminal charge model for common double-gate MOSFETs, which might have asymmetric gate oxide thickness. In this brief, we extend this concept to develop the nonquasi-static (NQS) charge model for the same by solving the governing continuity equations. The proposed NQS model shows good agreement against TCAD simulations and appears to be useful for efficient circuit simulation.