Improvement in galvannealed coating of IF-HS steel strips by combined GDOES and colour-etching method

Galvannealed coating of high strength interstitial free (IF-HS) steel was characterised by Glow Discharge Optical Emission Spectroscopy (GDOES) and colour-etching techniques. Overalloyed galvannealed coatings with considerably high amount of Γ and Γ1 phases were detected in the first set of experiments. Necessary process modifications in galvannealing furnace were made to maximise the ä phase in the galvannealed coating, which was confirmed through GDOES and colour-etching techniques. As a result, an improvement in galvannealed product quality with a better powdering resistance property during forming has been achieved.     

Text-dependent speaker verification using classical LBG,adaptive LBG and FCM vector quantization

An important task of speaker verification is to generate speaker specific models and match an input speaker’s utterance with these models. This paper focuses on comparing the performance of text dependent speaker verification system using Mel Frequency Cepstral Coefficients feature and different Vector Quantization (VQ) based speaker modelling techniques to generate the speaker specific models. Speaker-specific information is mainly represented by spectral features and using these features we have developed the model which serves as an important entity for determining the claimed identity of the speaker. In the modelling part, we used Linde, Buzo, Gray (LBG) VQ, proposed adaptive LBG VQ and Fuzzy C Means (FCM) VQ for generating speaker specific model. The experimental results that are performed on microphonic database shows that accuracy significantly depends on the size of the codebook in all VQ techniques, and on FCM VQ accuracy also depend on the value of learning parameter of the objective function. Experiment results shows that how the accuracy of speaker verification system is depend on different representations of the codebook, different size of codebook in VQ modelling techniques and learning parameter in FCM VQ.     

A New Method for Getting Rational Approximation for Fractional Order Differintegrals

In this paper a new algorithm is presented to calculate the poles and zeros to approximate a fractional order (FO) differintegral (s^±α,α∈(0,1)) by a rational function on a finite frequency band ω∈(ω_l,ω_h). The constant phase property of the FO differintegral is the basis for development of the algorithm. Interlacing of real poles and zeros is used to achieve the constant phase. The calculations are done using the asymptotic Bode phase plot. A brief investigation is made to get a good approximation for the Bode phase plot. Two design parameters are introduced to keep the average phase close to the desired phase angle and to keep the error within the allowed bounds. A study is done to empirically understand the relationship between the error and the design parameters. The results thus obtained help in the further calculations. The algorithm is computationally simple and inexpensive, and gives a fairly good approximation of fractance frequency response on the specified frequency band.     

Optimizing Safe Yield Policy Implementation

The presented method enhances groundwater-mandated safe yield management. It is useful for settings that prevent sustained yield or integrated management. To protect hydraulically connected surface water rights, the Utah government’s Cache Valley groundwater management plan proposes that total pumping increase not exceed 84,431 m³/day. To determine how best to spatially distribute additional allowable pumping, stakeholders quantified limits defining acceptable impacts on selected water resource indicators. A new simulation–optimization (S–O) algorithm used these limits while computing optimal spatially distributed perennial yield or safe yield groundwater pumping extraction strategies. The limits prevent unacceptable decreases in: head and net flow between aquifer and surface waters (rivers, surface/subsurface drains, springs, lakes). The optimization objective function maximizes weighted pumping to provide water for 18 growing municipalities. For 16 perennial yield scenarios, computed optimal pumping increases differ in protectiveness toward senior water rights, and range from 16% to 103% of the state plan-proposed increase. Implementing a protective strategy would achieve 90% of the storage changes needed to reach equilibrium within 23 years. Indicator potentiometric heads would reach equilibrium within 10–40 years. At equilibrium, an optimal Cache Valley perennial yield strategy acceptably minimizes net annual non-pumping discharges. By comparison, multi-period 20-year transient groundwater mining optimizations allow more pumping in early years. Pumping then must decline to satisfy seepage and head constraints through year 20. Adverse seepage impact would increase for years thereafter. For situations governed by safe or perennial yield policy, equilibrium-based (steady-state) optimization is very useful. It effectively develops optimal perennial yield strategies.     

Multi-objective optimization in wire-electro-discharge machining of TiC reinforced composite through Neuro-Genetic technique

This paper proposed a Neuro-Genetic technique to optimize the multi-response of wire electro-discharge machining (WEDM) process. The technique was developed through hybridization of a radial basis function network (RBFN) and non-dominated sorting genetic algorithm (NSGA-II). The machining was done on 5 vol% titanium carbide (TiC) reinforced austenitic manganese steel metal matrix composite (MMC). The proposed Neuro-Genetic technique was found to be potential in finding several optimal input machining conditions which can satisfy wide requirements of a process engineer and help in efficient utilization of WEDM in industry.     

Critical Density for Coverage and Connectivity in Three-Dimensional Wireless Sensor Networks Using Continuum Percolation

Although most of the studies on coverage and connectivity in wireless sensor networks (WSNs) considered two-dimensional (2D) settings, such networks can in reality be accurately modeled in a three-dimensional (3D) space. The concepts of continuum percolation theory best fit the problem of connectivity in WSNs to find out whether the network provides long-distance multihop communication. In this paper, we focus on percolation in coverage and connectivity in 3D WSNs. We say that the network exhibits a coverage percolation (respectively, connectivity percolation) when a giant covered region (respectively, giant connected component) almost surely spans the entire network for the first time. Because of the dependency between coverage and connectivity, the problem is not only a continuum percolation problem but also an integrated continuum percolation problem. Thus, we propose an integrated-concentric-sphere model to address coverage and connectivity in 3D WSNs in an integrated way. First, we compute the critical density lambda_C ^con above which coverage percolation in 3D WSNs will almost surely occur. Second, we compute the critical density lambda_c ^con above which connectivity percolation in 3D WSNs will almost surely occur. Third, we compute the critical density lambda_c ^cov-con above which both coverage and connectivity percolation in 3D WSNs will almost surely occur. For each of these three problems, we also compute their corresponding critical network degree. Our results can be helpful in the design of energy-efficient topology control protocols for 3D WSNs in terms of coverage and connectivity.     

An electromyographic investigation of asymmetric lifting and moving of a load: III. Models for determining muscle activity based on anthropometric characteristics

Regression models for six muscles, the left and right iliocostalis, the left and right erector spinae, and the left and right external oblique, were developed for asymmetry and height effects for floor and knuckle lifts. The models were based on participant anthropometric and other measures. Stepwise regression was performed for developing the prediction models. The models developed were discrete in terms of specific height and asymmetry. © 2009 Wiley Periodicals, Inc.     

Stabilizing adaptive controller for uncertain dynamical systems: An LMI approach

Adaptive stabilization of a class of linear systems with matched and unmatched uncertainties is considered in this paper. The proposed controller indeed stabilizes the uncertain system for any positive values of its non-adaptive gain that may be tuned to enhance dynamic response of system. The performance of uncertain system along with the Algebraic Riccati Equation that arises from the adaptive stabilizing controller is now formulated as a multi-objective Linear Matrix Inequality optimization problem. The decay rate and a factor governing the ultimate bound of the system states are considered to characterize the closed loop system performance. Finally, the effectiveness of the proposed controller is illustrated via stabilizing a mass-spring system. Recommended by Editorial Board member Gang Tao under the direction of Editor Young Il Lee. The authors would like to thank the reviewers for their valuable comments and suggestions that have improved the quality of this paper. Sandip Ghosh received the B.E. in Electrical Engineering from Bengal Engineering College (D.U.), Howrah, and Master in Control System Engineering from Jadavpur University, Kolkata, India, in 1999 and 2003 respectively. Presently he is pursuing the Ph.D. degree at Indian Institute of Technology, Kharagpur, India. His research interests include adaptive control, robust control and control of time-delay systems. Sarit K. Das is a Professor of Electrical Engineering Department, Indian Institute of Technology, Kharagpur, India. He received the Ph.D. degree in 1985 from the same department. His research interests include design of periodic controller, decoupling of multivariable systems, modeling and robust control of complex systems. Goshaidas Ray is a Professor of Electrical Engineering Department, Indian Institute of Technology, Kharagpur, India. He received the Ph.D. degree in 1982 from Indian Institute of Technology Delhi, India. His research interests include modeling, estimation, model-based control, intelligent control, robotic systems and distributed control systems.     

Striate cortex extracts higher-order spatial correlations from visual textures

Spatial correlations define the statistical structure of any visual image. Two-point correlations inform the visual system about the spatial frequency content of an image. Higher-order correlations can capture salient features such as object contours. We studied "isodipole" texture discrimination in V1 to determine if higher-order spatial correlations can be extracted by early stages of cortical processing. We made epicortical, local field potential, and single-cell recordings of responses elicited by isodipole texture interchange in anesthetized monkeys. Our studies demonstrate that single neurons in V1 can signal the presence of higher-order spatial correlations in visual textures. This places a computational mechanism, which may be essential for form vision at the earliest stage of cortical processing.