Learning-Based Fast Iterative Convergence of 3-D MoM via Eigen-AGMRES Method

Three-dimensional (3-D) full-wave electromagnetic simulation using method of moments (MoM) under the framework of fast solver algorithms like fast multipole method (FMM) is often bottlenecked by the speed of convergence of the Krylov-subspace-based iterative process. This is primarily because the electric field integral equation (EFIE) matrix, even with cutting-edge preconditioning techniques, often exhibits bad spectral properties arising from frequency or geometry-based ill-conditioning, which render iterative solvers slow to converge or stagnate occasionally. In this communication, a novel technique to expedite the convergence of MoMmatrix solution at a specific frequency is proposed, by extracting and applying Eigen-vectors from a previously solved neighboring frequency in an augmented generalized minimum residual (AGMRES) iterative framework. This technique can be applied in unison with any preconditioner. Numerical results demonstrate up to 40% speed-up in convergence using the proposed Eigen-AGMRES method.

A survey on compressed domain video analysis techniques

Image and video analysis requires rich features that can characterize various aspects of visual information. These rich features are typically extracted from the pixel values of the images and videos, which require huge amount of computation and seldom useful for real-time analysis. On the contrary, the compressed domain analysis offers relevant information pertaining to the visual content in the form of transform coefficients, motion vectors, quantization steps, coded block patterns with minimal computational burden. The quantum of work done in compressed domain is relatively much less compared to pixel domain. This paper aims to survey various video analysis efforts published during the last decade across the spectrum of video compression standards. In this survey, we have included only the analysis part, excluding the processing aspect of compressed domain. This analysis spans through various computer vision applications such as moving object segmentation, human action recognition, indexing, retrieval, face detection, video classification and object tracking in compressed videos.

Fabrication and Nonlinear Thermomechanical Analysis of SU8 Thermal Actuator

SU8-based micromechanical structures are widely used as thermal actuators in the development of compliant micromanipulation tools. This paper reports the design, nonlinear thermomechanical analysis, fabrication, and thermal actuation of SU8 actuators. The thermomechanical analysis of the actuator incorporates nonlinear temperature-dependent properties of SU8 polymer to accurately model its thermal response during actuation. The designed SU8 thermal actuators are fabricated using surface micromachining techniques and the electrical interconnects are made to them using flip-chip bonding. The issues due to thermal stress during fabrication are discussed and a novel strategy is proposed to release the thermal stress in the fabricated actuators. Subsequent characterization of the actuator using an optical profilometer reveals excellent thermal response, good repeatability, and low hysteresis. The average deflection is similar to 8.5 mu m for an actuation current of similar to 5 mA. The experimentally obtained deflection profile and the tip deflection at different currents are both shown to be in good agreement with the predictions of the nonlinear thermomechanical model. This underscores the need to consider nonlinearities when modeling the response of SU8 thermal actuators. 2015-0087]

A Perspective on Computer Assisted Assessment Techniques for Short Free-Text Answers

Computer Assisted Assessment (CAA) has been existing for several years now. While some forms of CAA do not require sophisticated text understanding (e.g., multiple choice questions), there are also student answers that consist of free text and require analysis of text in the answer. Research towards the latter till date has concentrated on two main sub-tasks: (i) grading of essays, which is done mainly by checking the style, correctness of grammar, and coherence of the essay and (ii) assessment of short free-text answers. In this paper, we present a structured view of relevant research in automated assessment techniques for short free-text answers. We review papers spanning the last 15 years of research with emphasis on recent papers. Our main objectives are two folds. First we present the survey in a structured way by segregating information on dataset, problem formulation, techniques, and evaluation measures. Second we present a discussion on some of the potential future directions in this domain which we hope would be helpful for researchers.

Campaigning in Heterogeneous Social Networks: Optimal Control of SI Information Epidemics

We study the optimal control problem of maximizing the spread of an information epidemic on a social network. Information propagation is modeled as a susceptible-infected (SI) process, and the campaign budget is fixed. Direct recruitment and word-of-mouth incentives are the two strategies to accelerate information spreading (controls). We allow for multiple controls depending on the degree of the nodes/individuals. The solution optimally allocates the scarce resource over the campaign duration and the degree class groups. We study the impact of the degree distribution of the network on the controls and present results for Erdos-Renyi and scale-free networks. Results show that more resource is allocated to high-degree nodes in the case of scale-free networks, but medium-degree nodes in the case of Erdos-Renyi networks. We study the effects of various model parameters on the optimal strategy and quantify the improvement offered by the optimal strategy over the static and bang-bang control strategies. The effect of the time-varying spreading rate on the controls is explored as the interest level of the population in the subject of the campaign may change over time. We show the existence of a solution to the formulated optimal control problem, which has nonlinear isoperimetric constraints, using novel techniques that is general and can be used in other similar optimal control problems. This work may be of interest to political, social awareness, or crowdfunding campaigners and product marketing managers, and with some modifications may be used for mitigating biological epidemics.

Analysis of sine-triangle and zero-sequence injection modulation schemes for split-phase induction motor drive

A split-phase induction motor is fed from two three-phase voltage source inverters for speed control. This study analyses carrier-comparison based pulse width modulation (PWM) schemes for a split-phase motor drive, from a space-vector perspective. Sine-triangle PWM, one zero-sequence injection PWM where the same zero-sequence signal is used for both the inverters, and another zero-sequence injection PWM where different zero-sequence signals are employed for the two inverters are considered. The set of voltage vectors applied, the sequence in which the voltage vectors are applied, and the resulting current ripple vector are analysed for all the PWM methods. Besides all the PWM methods are compared in terms of dc bus utilisation. For the same three-phase sine reference, the PWM method with different zero-sequence signals for the two inverters is found to employ a set of vectors different from the other methods. Both analysis and experimental results show that this method results in lower total harmonic distortion and higher dc bus utilisation than the other two PWM methods.

Investigation Into Harmful Patterns Over Multitrack Shingled Magnetic Detection Using the Voronoi Model

Two-dimensional magnetic recording 2-D (TDMR) is a promising technology for next generation magnetic storage systems based on a systems-level framework involving sophisticated signal processing at the core. The TDMR channel suffers from severe jitter noise along with electronic noise that needs to be mitigated during signal detection and recovery. Recently, we developed noise prediction-based techniques coupled with advanced signal detectors to work with these systems. However, it is important to understand the role of harmful patterns that can be avoided during the encoding process. In this paper, we investigate the Voronoi-based media model to study the harmful patterns over multitrack shingled recording systems. Through realistic quasi-micromagnetic simulation studies, we identify 2-D data patterns that contribute to high media noise. We look into the generic Voronoi model and present our analysis on multitrack detection with constrained coded data. We show that the 2-D constraints imposed on input patterns result in an order of magnitude improvement in the bit-error rate for the TDMR systems. The use of constrained codes can reduce the complexity of 2-D intersymbol interference (ISI) signal detection, since the lesser 2-D ISI span can be accommodated at the cost of a nominal code rate loss. However, a system must be designed carefully so that the rate loss incurred by a 2-D constraint does not offset the detector performance gain due to more distinguishable readback signals.

Comparison of Matching Pursuit Algorithm with Other Signal Processing Techniques for Computation of the Time-Frequency Power Spectrum of Brain Signals

Signals recorded from the brain often show rhythmic patterns at different frequencies, which are tightly coupled to the external stimuli as well as the internal state of the subject. In addition, these signals have very transient structures related to spiking or sudden onset of a stimulus, which have durations not exceeding tens of milliseconds. Further, brain signals are highly nonstationary because both behavioral state and external stimuli can change on a short time scale. It is therefore essential to study brain signals using techniques that can represent both rhythmic and transient components of the signal, something not always possible using standard signal processing techniques such as short time fourier transform, multitaper method, wavelet transform, or Hilbert transform. In this review, we describe a multiscale decomposition technique based on an over-complete dictionary called matching pursuit (MP), and show that it is able to capture both a sharp stimulus-onset transient and a sustained gamma rhythm in local field potential recorded from the primary visual cortex. We compare the performance of MP with other techniques and discuss its advantages and limitations. Data and codes for generating all time-frequency power spectra are provided.

All Inorganic Spin-Coated Nanoparticle-Based Capacitive Memory Devices

We demonstrate all inorganic, robust, cost-effective, spin-coated, two-terminal capacitive memory metal-oxide nanoparticle-oxide-semiconductor devices with cadmium telluride nanoparticles sandwiched between aluminum oxide phosphate layers to form the dielectric memory stack. Using a novel high-speed circuit to decouple reading and writing, experimentally measured memory windows, programming voltages, retention times, and endurance are comparable with or better than the two-terminal memory devices realized using other fabrication techniques.

A Novel Approach for Multispectral Satellite Image Classification Based on the Bat Algorithm

Among the multiple advantages and applications of remote sensing, one of the most important uses is to solve the problem of crop classification, i.e., differentiating between various crop types. Satellite images are a reliable source for investigating the temporal changes in crop cultivated areas. In this letter, we propose a novel bat algorithm (BA)-based clustering approach for solving crop type classification problems using a multispectral satellite image. The proposed partitional clustering algorithm is used to extract information in the form of optimal cluster centers from training samples. The extracted cluster centers are then validated on test samples. A real-time multispectral satellite image and one benchmark data set from the University of California, Irvine (UCI) repository are used to demonstrate the robustness of the proposed algorithm. The performance of the BA is compared with two other nature-inspired metaheuristic techniques, namely, genetic algorithm and particle swarm optimization. The performance is also compared with the existing hybrid approach such as the BA with K-means. From the results obtained, it can be concluded that the BA can be successfully applied to solve crop type classification problems.

Evaluation and Minimization of Low-Order Harmonic Torque in Low-Switching-Frequency Inverter-Fed Induction Motor Drives

A low-order harmonic pulsating torque is a major concern in high-power drives, high-speed drives, and motor drives operating in an overmodulation region. This paper attempts to minimize the low-order harmonic torques in induction motor drives, operated at a low pulse number (i.e., a low ratio of switching frequency to fundamental frequency), through a frequency domain (FD) approach as well as a synchronous reference frame (SRF) based approach. This paper first investigates FD-based approximate elimination of harmonic torque as suggested by classical works. This is then extended into a procedure for minimization of low-order pulsating torque components in the FD, which is independent of machine parameters and mechanical load. Furthermore, an SRF-based optimal pulse width modulation (PWM) method is proposed to minimize the low-order harmonic torques, considering the motor parameters and load torque. The two optimal methods are evaluated and compared with sine-triangle (ST) PWM and selective harmonic elimination (SHE) PWM through simulations and experimental studies on a 3.7-kW induction motor drive. The SRF-based optimal PWM results in marginally better performance than the FD-based one. However, the selection of optimal switching angle for any modulation index (M) takes much longer in case of SRF than in case of the FD-based approach. The FD-based optimal solutions can be used as good starting solutions and/or to reasonably restrict the search space for optimal solutions in the SRF-based approach. Both of the FD-based and SRF-based optimal PWM methods reduce the low-order pulsating torque significantly, compared to ST PWM and SHE PWM, as shown by the simulation and experimental results.

Low temperature solution processed high-kappa ZrO2 gate dielectrics for nanoelectonics

The high-kappa gate dielectrics, specifically amorphous films offer salient features such as exceptional mechanical flexibility, smooth surfaces and better uniformity associated with low leakage current density. In this work, similar to 35 nm thick amorphous ZrO2 films were deposited on silicon substrate at low temperature (300 degrees C, 1 h) from facile spin-coating method and characterized by various analytical techniques. The X-ray diffraction and X-ray photoelectron spectroscopy reveal the formation of amorphous phase ZrO2, while ellipsometry analysis together with the Atomic Force Microscope suggest the formation of dense film with surface roughness of 1.5 angstrom, respectively. The fabricated films were integrated in metal-oxide-semiconductor (MOS) structures to check the electrical capabilities. The oxide capacitance (C-ox), flat band capacitance (C-FB), flat band voltage (V-FB), dielectric constant (kappa) and oxide trapped charges (Q(ot)) extracted from high frequency (1 MHz) C-V curve are 186 pF, 104 pF, 0.37V, 15 and 2 x 10(-11) C, respectively. The small flat band voltage 0.37V, narrow hysteresis and very little frequency dispersion between 10 kHz-1 MHz suggest an excellent a-ZrO2/Si interface with very less trapped charges in the oxide. The films exhibit a low leakage current density 4.7 x 10(-9)A/cm(2) at 1V. In addition, the charge transport mechanism across the MOSC is analyzed and found to have a strong bias dependence. The space charge limited conduction mechanism is dominant in the high electric field region (1.3-5 V) due to the presence of traps, while the trap-supported tunneling is prevailed in the intermediate region (0.35-1.3 V). Low temperature solution processed ZrO2 thin films obtained are of high quality and find their importance as a potential dielectric layer on Si and polymer based flexible electronics. (C) 2016 Published by Elsevier B.V.

Nano-hardness Techniques and Its Applications in Mechanical Property Measurements for Surface Engineering

结合纳米硬度技术测量各类薄膜和块体材料表层的纳米压痕硬度、弹性模量、断裂韧性、膜厚、微结构的弯曲变形,采用纳米划痕硬度技术测量各类薄膜和块体材料的粗糙度、临界附着力、摩擦系数、划痕横剖面.纳米硬度计是检测材料表层微米乃至几十纳米力学性能的先进仪器,可广泛应用于表面工程中的质量检测.

Multiphase technique improves mud-pulse velocity calculations

Measurement while drilling (MWD) has become a popular survey technology to monitor directional data, drilling data, formation evaluation data and safety data in the world. And closed loop drilling shows promise in recent years. Obviously, the method of tr