Advances in Electrical Engineering The latest articles from Hindawi Publishing Corporation © 2014 , Hindawi Publishing Corporation . All rights reserved. Design of Tunable Monopole Arm Planar Spiral Antenna for Cognitive Radio Thu, 24 Jul 2014 14:03:58 +0000 This paper presents a spiral antenna design operating in the frequency range of 1–15 GHz having both selective notch bands and wideband response. The main feed arm of spiral antenna is configured as rectangular monopole of width quarter wavelength to achieve impedance matching with standard 50 Ω excitation. Frequency tuning in the design is achieved by placing varactor diode at an appropriate position along the spiral arms and in the ground plane. The design offers a peak gain of 3.4 dB (simulated) and 3 dB (measured). The unique frequency response of antenna makes its suitable to be used for front-end system of cognitive radio for sensing the spectrum in various modes. Rahul Yadav Copyright © 2014 Rahul Yadav. All rights reserved. Assessment of Electrical Load in Water Distribution Systems Using Representative Load Profiles-Based Method Mon, 21 Jul 2014 07:00:46 +0000 The problem of optimal management of a water distribution system includes the determination of the operation regime for each hydrophore station. The optimal operation of a water distribution system means a maximum attention to assess the demands of the water, with minimum electrical energy consumption. The analysis of load profiles corresponding to a water distribution system can be the first step that water companies must make to assess the electrical energy consumption. This paper presents a new method to assess the electrical load in water distribution systems, taking into account the time-dependent evolution of loads from the hydrophore stations. The proposed method is tested on a real urban water distribution system, showing its effectiveness in obtaining the electrical energy consumption with a relatively low computational burden. Gheorghe Grigoras Copyright © 2014 Gheorghe Grigoras. All rights reserved. Row-Based Dual Assignment, for a Level Converter Free CSA Design and Its Near-Threshold Operation Tue, 15 Jul 2014 12:11:07 +0000 Subthreshold circuit designs are very much popular for some of the ultra-low power applications, where the minimum energy consumption is the primary concern. But, due to the weak driving current, these circuits generally suffer from huge performance degradation. Therefore, in this paper, we primarily targeted analyzing the performance of a near-threshold circuit (NTC), which retains the excellent energy efficiency of the subthreshold design, while improving the performance to a certain extent. A modified row-based dual 4-operand carry save adder (CSA) design has been reported in the present work using 45 nm technology. Moreover, to find out the effectiveness of the near-threshold operation of the 4-operand CSA design, it has been compared with the other design styles. From the simulation results, obtained for the frequency of 20 MHz, we found that the proposed scheme of CSA design consumes Watt of average power (), which is almost 90.9% lesser than that of the conventional CSA design, whereas, looking at the perspective of maximum delay at output, the proposed scheme of CSA design provides a fair 44.37% improvement, compared to that of the subthreshold CSA design. Dipankar Saha, Aanan Chatterjee, Sayan Chatterjee, and C. K. Sarkar Copyright © 2014 Dipankar Saha et al. All rights reserved. A Blind Blur Detection Scheme Using Statistical Features of Phase Congruency and Gradient Magnitude Tue, 15 Jul 2014 07:09:25 +0000 The growing uses of camera-based barcode readers have recently gained a lot of attention. This has boosted interest in no-reference blur detection algorithms. Blur is an undesirable phenomenon which appears as one of the most frequent causes of image degradation. In this paper we present a new no-reference blur detection scheme that is based on the statistical features of phase congruency and gradient magnitude maps. Blur detection is achieved by approximating the functional relationship between these features using a feed forward neural network. Simulation results show that the proposed scheme gives robust blur detection scheme. Shamik Tiwari, V. P. Shukla, S. R. Biradar, and A. K. Singh Copyright © 2014 Shamik Tiwari et al. All rights reserved. Fast Transforms in Image Processing: Compression, Restoration, and Resampling Sun, 06 Jul 2014 11:25:54 +0000 Transform image processing methods are methods that work in domains of image transforms, such as Discrete Fourier, Discrete Cosine, Wavelet, and alike. They proved to be very efficient in image compression, in image restoration, in image resampling, and in geometrical transformations and can be traced back to early 1970s. The paper reviews these methods, with emphasis on their comparison and relationships, from the very first steps of transform image compression methods to adaptive and local adaptive filters for image restoration and up to “compressive sensing” methods that gained popularity in last few years. References are made to both first publications of the corresponding results and more recent and more easily available ones. The review has a tutorial character and purpose. Leonid P. Yaroslavsky Copyright © 2014 Leonid P. Yaroslavsky. All rights reserved. Modelling and Simulation of Static Excitation System in Synchronous Machine Operation and Investigation of Shaft Voltage Thu, 03 Jul 2014 09:16:21 +0000 Static excitation system (SES) has been implemented in a specially designed synchronous machine installed in a testing laboratory. This is a large capacity single machine operated in dual mode (i.e., motor or generator) with the help of static sources. It is well known that bearings of the rotating machines are vulnerable to the effects of the shaft voltages caused by the static sources. Shaft voltage is the prime concern for this special machine too due to SES. To find out the exact cause of the shaft voltage, SES of this machine has been modelled with Power Systems software. Various waveforms drawn from the model are validated through computer simulations and actual laboratory tests. Sources of shaft voltages are also analysed thereafter with the FFT analysis of the rotor voltage and current waveforms. Arun Kumar Datta, Manisha Dubey, and Shailendra Jain Copyright © 2014 Arun Kumar Datta et al. All rights reserved. Gradient Based Adaptive Algorithm for Echo Cancellation from Recorded Echo Corrupted Speech Wed, 11 Jun 2014 08:13:54 +0000 An offline single channel acoustic echo cancellation (AEC) scheme is proposed based on gradient based adaptive least mean squares (LMS) algorithm considering a major practical application of echo cancellation system for enhancing recorded echo corrupted speech data. The unavailability of a reference signal makes the problem of single channel adaptive echo cancellation to be extremely difficult to handle. Moreover, continuous feedback of the echo corrupted signal to the input microphone can significantly degrade the quality of the original speech signal and may even result in howling. In order to overcome these problems, in the proposed scheme, the delayed version of the echo corrupted speech signal is considered as a reference. An objective function is thus formulated and thereby a modified LMS update equation is derived, which is shown to converge to the optimum Wiener-Hopf solution. The performance of the proposed method is evaluated in terms of both subjective and objective measures via extensive experimentation on several real-life echo corrupted signals and very satisfactory performance is obtained. Upal Mahbub and Shaikh Anowarul Fattah Copyright © 2014 Upal Mahbub and Shaikh Anowarul Fattah. All rights reserved. A Hybrid Short-Term Power Load Forecasting Model Based on the Singular Spectrum Analysis and Autoregressive Model Mon, 05 May 2014 14:06:44 +0000 Short-term power load forecasting is one of the most important issues in the economic and reliable operation of electricity power system. Taking the characteristics of randomness, tendency, and periodicity of short-term power load into account, a new method (SSA-AR model) which combines the univariate singular spectrum analysis and autoregressive model is proposed. Firstly, the singular spectrum analysis (SSA) is employed to decompose and reconstruct the original power load series. Secondly, the autoregressive (AR) model is used to forecast based on the reconstructed power load series. The employed data is the hourly power load series of the Mid-Atlantic region in PJM electricity market. Empirical analysis result shows that, compared with the single autoregressive model (AR), SSA-based linear recurrent method (SSA-LRF), and BPNN (backpropagation neural network) model, the proposed SSA-AR method has a better performance in terms of short-term power load forecasting. Hongze Li, Liuyang Cui, and Sen Guo Copyright © 2014 Hongze Li et al. All rights reserved. Application of Firefly Algorithm in Voltage Stability Environment Incorporating Circuit Element Model of SSSC with Variable Susceptance Model of SVC Thu, 24 Apr 2014 13:08:39 +0000 This paper proposes an application of firefly algorithm (FA) based extended voltage stability margin and minimization of active (or) real power loss incorporating Series-Shunt flexible AC transmission system (FACTS) controller named as static synchronous series compensator (SSSC) combined with static var compensator (SVC). A circuit model of SSSC and variable susceptance model of SVC are utilized to control the line power flows and bus voltage magnitudes, respectively, for real power loss minimization and voltage stability limit improvement. The line quality proximity index (LQP) is used to assess the voltage stability of a power system. The values of voltage profile improvement, real power loss minimization, and the location and size of FACTS devices were optimized by FA. The results are obtained from the IEEE 14- and 30-bus test case systems under different operating conditions and compared with other leading evolutionary techniques such as shuffled frog leaping algorithm (SFLA), differential evolution (DE) and particle swarm optimization (PSO). Luke Jebaraj, Charles Christober Asir Rajan, and Kumar Sriram Copyright © 2014 Luke Jebaraj et al. All rights reserved.