The voltage mirror–current mirror pair as a universal element

The voltage mirror–current mirror (VM–CM) pair is shown to be a universal active element. It provides two alternative realizations for the nullor. The VM–CM pair is also capable of realizing the op amp and all the four types of the current conveyors namely CCII?, CCII+, ICCII? and ICCII+ as special cases. Copyright © 2009 John Wiley & Sons, Ltd.     

Robust decentralized PID-based power system stabilizer design using an ILMI approach

Thanks to its essential functionality and structure simplicity, proportional-integral-derivative (PID) controllers are commonly used by industrial utilities. A robust PID-based power system stabilizer (PSS) is proposed to properly function over a wide range of operating conditions. Uncertainties in plant parameters, due to variation in generation and load patterns, are expressed in the form of a polytopic model. The PID control problem is firstly reduced to a generalized static output feedback (SOF) synthesis. The derivative action is designed and implemented as a high-pass filter based on a low-pass block to reduce its sensitivity to sensor noise. The proposed design algorithm adopts a quadratic Lyapunov approach to guarantee α-decay rate for the entire polytope. A constrained structure of Lyapunov function and SOF gain matrix is considered to enforce a decentralized scheme. Setting of controller parameters is carried out via an iterative linear matrix inequality (ILMI). Simulation results, based on a benchmark model of a two-area four-machine test system, are presented to compare the proposed design to a well-tuned conventional PSS and to the standard IEEE-PSS4B stabilizer.     

Analytical synthesis of voltage‐mode even/odd‐nth‐order differential difference current conveyor and fully differential current conveyor II‐grounded resistor and capacitor universal filter structures

A complete definition of an odd/even‐nth‐order notch or band‐reject filter transfer function is presented. Based on the differences between the input voltage and (i) an nth‐order high‐pass; (ii) a traditional nth‐order notch; and (iii) an nth‐order all‐pass filtering transfer function, a systematic method has been proposed to derive a universal filter structure that can realize voltage‐mode odd/even‐nth‐order low‐pass, band‐pass, high‐pass, all‐pass and traditional notch filters. The intrinsic capability of voltage‐mode addition and subtraction of the two active elements, differential difference current conveyors and fully differential current conveyors, is used to advantage in the aforementioned synthesis procedure. Based upon the definition of an nth‐order notch or band‐reject filter transfer function proposed in this paper, the aforementioned universal one has been further extended to the newly defined nth‐order band rejection filter. The voltage and current tracking errors of the two active elements are compensated by varying the resistances of the proposed filter. Filtering feasibility, stability, component sensitivities, linear and dynamic ranges, power consumption, and noise are simulated using H‐Spice with 0.35 µm process. Compared to some of the recently reported universal biquads, the new one is shown to enjoy the lowest component sensitivities and the best output accuracy for all‐pass signals. Moreover, Monte Carlo and two‐tone tests for intermodulation linearity simulations are also investigated. Copyright © 2014 John Wiley & Sons, Ltd.     

Polyaniline/akaganéite nanocomposite for detoxification of noxious Cr(VI) from aquatic environment

In this work, a removal of toxic hexavalent chromium Cr(VI) ion from aqueous solution was investigated and studied using nanocomposite of polyaniline (PANI) and akaganéite nanoparticles (NP). HCl doped PANI, and akaganéite NPs were prepared by chemical oxidative polymerization and co-precipitation techniques, respectively. The synthesized materials were characterized by Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), scanning electron microscope (SEM), and high-resolution transmission electron microscope (HRTEM). It was indicated that the formed oxide NPs were consisted of akaganéite as dominant phase plus minor phases of hematite, magnetite, and/or maghemite. HRTEM images of the prepared nanocomposite demonstrated that the phases of oxide NPs embedded in the nanocomposite had the same crystallinity and morphology of pristine oxide NPs. It was found that size of nanocomposite particles has diameter ranged from 8.95 to 16.21 nm. Cr(VI) removals in a wide pH range from 2 to 9 were appropriated for prepared nanocomposite. The nanocomposite has demonstrated high removal percentage of 99.2 % and removal capacity of 17.36 mg/g for 7.0 mg/L Cr(VI) polluted aqueous solution at pH 2.0 for 5-min contact time. The synthesized nanocomposite was applied to remove Cr(VI) from a leather tanning wastewater sample with efficiency of 93.4 %.     

Deep learning controller for nonlinear system based on Lyapunov stability criterion

Neural Computing and Applications - For the current paper, the technique of feed-forward neural network deep learning controller (FFNNDLC) for the nonlinear systems is proposed. The FFNNDLC...     

Comparison of estimates using record statistics from Weibull model: Bayesian and non-Bayesian approaches

This paper develops a Bayesian analysis in the context of record statistics values from the two-parameter Weibull distribution. The ML and the Bayes estimates based on record values are derived for the two unknown parameters and some survival time parameters e.g. reliability and hazard functions. The Bayes estimates are obtained based on a conjugate prior for the scale parameter and a discrete prior for the shape parameter of this model. This is done with respect to both symmetric loss function (squared error loss), and asymmetric loss function (linear-exponential (LINEX)) loss function. The maximum likelihood and the different Bayes estimates are compared via a Monte Carlo simulation study. A practical example consisting of real record values using the data from an accelerated test on insulating fluid reported by Nelson was used for illustration and comparison. Finally, Bayesian predictive density function, which is necessary to obtain bounds for predictive interval of future record is derived and discussed using a numerical example. The results may be of interest in a situation where only record values are stored.     

Modeling of microstrip lines using neural networks: Applications to the design and analysis of distributed microstrip circuits

In this article, two models for solving microstrip lines are presented. The models utilize radial-basis-function neural networks. Using the first model, one estimates the effective dielectric constant and the width of the microstrip line, knowing its characteristic impedance and the frequency. The second model provides the effective dielectric constant and the characteristic impedance of the line based on knowledge of its width and the frequency. Besides their remarkably fast responses, the proposed models are capable of estimating the required quantities with very high accuracy. The potential of the proposed models is demonstrated in the design and analysis of two distributed microstrip circuits. © 2004 Wiley Periodicals, Inc. Int J RF and Microwave CAE 14, 166–173, 2004.     

Early detection of Alzheimer’s disease based on the state-of-the-art deep learning approach: a comprehensive survey

Multimedia Tools and Applications - Alzheimer’s disease (AD) is a form of brain disorder that causes functions’ loss in a person’s daily activity. Due to the tremendous progress...     

Developing Iris Recognition System for Smartphone Security

Smartphones have become an important way to store sensitive information; therefore, users’ privacy needs to be highly protected. This can be done by using the most reliable and accurate biometric identification system available today: iris recognition. This paper develops and tests an iris recognition system for smartphones. The system uses eye images that rely on visible wavelength; these images are acquired by the smartphone built-in camera. The development of the system passes through four main phases: the first phase is the iris segmentation phase, which is done in three steps to detect the iris region from the captured image, which contains the eye and part of the face using Haar Cascade Classifier training, pupil localization, and iris localization using a Circular Hough Transform. In the second phase, the system applies normalization using a Rubber Sheet model, which converts the iris image to a fixed size pattern. In the third phase, unique features are extracted from that pattern using a Deep Sparse Filtering algorithm. Finally, in the matching phase, seven different matching techniques are investigated to decide the most appropriate one the system will use to verify the user. Two types of testing are conducted: Offline and Online tests. The BIPLab database and a collected dataset are used to measure the accuracy of the system phases and to calculate the Equal Error Rate (EER) for the whole system. The average EER is 0.18 for the BIPLab database and 0.26 for the collected dataset.