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Background: In this article, we have proposed a new reversible quantum circuit block along with the Quantum Cost (QC), Constant Input (CI), Garbage Output (GO) and delay optimized code converter using quantum circuit block. Methods: Initially, new quantum circuit block has been designed and later reversible code converter circuits have been implemented using it. The proposed new quantum block used to design 2’s complement code converter (2SCCC), cost efficient BCD to Excess-3 Code Converter (BECC) and can also be used to implement different logic functions. The QC of proposed quantum circuit block is 8. The QC and delay of the proposed 2SCCC is 8 and 1 respectively. Similarly, the QC and delay of the proposed BECC is 11 and 2, respectively. The proposed cost efficient BECC is designed using two NOT gate, one Feynman gate and one new quantum circuit block with QC is 11. Results: The improvement of QC for 2SCCC and BECC is 27.27 % and 21.43%, respectively. The improvement of delay for 2SCCC and BECC are 66.67% and 50%, respectively, compared with respect to the latest reported results. Conclusion: So the improvement of QC and delay are very high using QCB.

Background: Over the last few decades, reversible logic system/circuits have received considerable attention in the diversified fields such as nanotechnology, quantum computing, cryptography, optical computing and low power design of VLSI circuits due to their low power dissipation characteristics. Methods: In this paper, we proposed the design of reversible shift register (SR) i.e. serial-in-serial out (SISO), serial-in-parallel out (SIPO), parallel-in-serial out (PISO) and parallel-in-parallel out (PIPO) SR using a reduced number of reversible logic gates and garbage output. Result: As compared to previously reported results, the improvement in our proposed model of SISO, SIPO, PISO and PIPO was found to be 50 – 66.66 %, 42.85 – 66.66 %, 12.5 – 53.33 % and 50 – 66.66 % respectively, in terms of the number of reversible logic gates.

National critical infrastructures like power plants, power grids, industrial process plants, water distribution systems employ a hierarchy of controllers designed to control the physical/chemical processes safely and optimally. They deploy sophisticated control algorithms implemented in software and exchange control commands and information over networks. Various researches have examined attack scenarios in such embedded control systems from control theoretic perspectives. This paper revisits the theoretical aspects of these attacks and postulates that such attacks can be detected by statistical techniques like sequential probability ratio test (SPRT), cumulative sum (CUSUM), multiple model Kalman filter etc. The proposed techniques are studied closely for their effectiveness by extensive simulations.

In this paper, a search is made to detect any sort of nonlinearity and chaos in the solar irradiance data from the Earth Radiation Budget Satellite during the time period from October 15, 1984 to October 15, 2003 in order to investigate the inherent complexity in it. In this paper, delay vector variance analysis has been applied to trace the nonlinearity; whereas 0-1 test, correlation dimension analysis, information entropy, recurrence plot, and recurrence quantification analysis have been used to explore the signature of chaos in the present time series. Present investigation reveals that though nonlinearity is significantly present in the signal, chaotic behavior is not really observed in it.

We have devised a way of segmentation and progressive transmission of diseased MRI images. We use Particle Swarm Optimization (PSO) to get the region of interest (ROI) of the diseased MRI image. We use the concept of Multi-resolution Wavelet analysis to de-noise the ROI. We use Stationary Wavelet Transform together with Soft Thresholding Technique for de-noising purpose. A variable mask is used to get the segmented image. Varying percentages of DCT coefficients are used for progressive transmission of the diseased MRI image. Clustering of the images using K-Means algorithm result in predominantly two cluster namely that of diseased cells and background. Test on various MRI images show that the small diseased objects are successfully extracted irrespective of the complexity of the background and difference in intensity levels and class sizes. The proposed method only transmits the diseased MRI for further diagnosis of the disease and treatment.

This paper presents a compact asymmetric CPW fed monopole antenna using Denim fabric as substrate applicable for UWB communication and various wireless body area networks (WBANs). The geometry of the antenna consists of a circular monopole antenna with a modified ground plane and introduction of defected ground structures (DGS) to achieve ultra‐wide band (3.10–10.6 GHz) characteristics. The proposed wearable antenna operates from 2.40 to 14.88 GHz providing a fractional bandwidth (FBW) of about 144.44%. Enhancement of the bandwidth is obtained by the insertion of open ended rectangular slit in the ground plane. The final antenna produces a peak gain of about 6.57 dBi at 13.05 GHz and achieved omnidirectional radiation patterns. In terms of return loss, gain, and radiation characteristics, the lightweight flexible wearable antenna is fabricated, and the tested effects are found to be in fair accordance with the simulated ones. Compact asymmetric CPW fed monopole antenna using denim fabric as substrate applicable for UWB communicationThe final antenna produces a peak gain of about 6.57 dBi and achieved omnidirectional radiation patternsOn‐body measurements and deformation through bending is performed to provide validation to the structure Compact asymmetric CPW fed monopole antenna using denim fabric as substrate applicable for UWB communication The final antenna produces a peak gain of about 6.57 dBi and achieved omnidirectional radiation patterns On‐body measurements and deformation through bending is performed to provide validation to the structure

Highlights • Fractality of coronal mass ejection (CME) linear speed time series (February 1999 to December 2007 of solar cycle 23) has been investigated. • Multi-Fractal Detrended Fluctuation Analysis (MFDFA) and Multi-Fractal Detrended Moving Average (MFDMA) methods have been used to judge the multifractal behaviour of the CME linear speed signal. • Both the long-range temporal correlation and the broad probability density function (pdf) are found to be the main source of multifractality in the signal. • The singularities or abruptness present in the signal are found to vary with time and this fluctuation follows an AR (2) model. Abstract In the recent past, coronal mass ejection (CME) has received much research attention for its geo-effectiveness. In this paper, an investigation has been made to identify the scaling pattern of the CME linear speed time series data (February 1999 to December 2007 of solar cycle 23) collected from the Solar and Heliospheric Observatory (SOHO) using Multi-Fractal Detrended Fluctuation Analysis (MFDFA) and Multi-Fractal Detrended Moving Average (MFDMA) method. The scaling exponent, generalized Hurst exponent, singularity strength and also the singularity spectrum have been computed to quantify the multifractality and to identify the singularities of the time series data. An effort has also been made to find out the possible sources which are responsible for the multifractality in the signal by studying the scaling patterns of the shuffled and surrogate version of the original data. It has been revealed in this paper that CME linear speed signal exhibit multifractal behaviour with long-term persistence. Both the long-range temporal correlation and the broad probability density function (pdf) are found to be the primary source of multifractality in the signal. The singularities or abruptness present in the signal are found to vary with time, and this fluctuation follows an AR (2) model. [ABSTRACT FROM AUTHOR]

In order to ascertain the dynamics of temperature variation in India, the scaling properties of the daily mean temperature time series obtained from seven different weather stations viz. Kolkata, Chennai, New Delhi, Mumbai, Bhopal, Agartala and Ahmadabad representing different geographical zones in India has been studied. Scaling properties of the temperature profile across India has been estimated from the calculation of Hurst-Exponent parameter obtained from five different scaling methods. Hurst Exponent values confirm that all temperature time series are Fractional Brownian Motion (FBM), statistically self-affine, anti-persistent and Short Range Dependent (SRD) self similar. As SRD self similarity is a common signature of a nonlinear dynamical process, further investigation has been made to discover the presence of any nonlinear behaviour of the temperature profile of Indian climate using Delay Vector Variance (DVV) method and the present calculation confirms a deterministic nonlinear profile of the same. [ABSTRACT FROM AUTHOR]