Department of Electrical Engineering

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IIT Jodhpur

In this paper, a dynamic stochastic resonance (DSR)-based blind watermark extraction technique has been proposed for robust extraction of a binary watermark. The watermark embedding has been done in mid-band DCT coefficients using well-known PN sequences. Dynamic stochastic resonance has been strategically used to improve the robustness of the extraction algorithm by utilizing the added noise (or degradation) during attacks itself. DSR is a converging iterative process that tunes the coefficients of the possibly attacked image so that effect of noise is suppressed and hidden information is enhanced. Resilience of this technique has been tested in the presence of various attacks such as noise attacks, geometrical distortions, enhancement, compression and filtering. A simple optimization procedure has been adopted for the selection of bistable double-well system parameters in the DSR step so to achieve maximum correlation coefficient under minimum computational complexity. Using the proposed adaptive DSR-based extraction technique, a very robust extraction of watermark can be done without trading-off with visual quality of the watermarked image. When compared with the plain DCT-based technique, the proposed DSR-based DCT technique has been found to give better performance. © 2011 IEEE.

World University root node

Improved watermark extraction using dynamic stochastic resonance

Due to the electricity market deregulation, the techniques used for load forecasting have gradually improved over the years. Deregulation in the power system industry has caused rising requirement in planning, operating and controlling electric energy systems, which brings electricity load forecasting to a crucial level. Therefore, adequate techniques are desired for accurately predicting the load and hence assisting power companies in generating capacity scheduling, maintenance, energy planning and procurement, etc. An accurate forecast can greatly help power distribution companies to improve their electricity marketing strategies and avoid over or under unitisation of generating capacity and therefore optimises energy prices. But, to predict the load demand in real time requires a considerable amount of efforts. This paper presents a design methodology for a short term load forecasting useful for distribution companies, which are capable of interacting with users, gathering historical load data, performing a statistical analysis on the historical data and plotting graphs of the predicted load using the support vector machine (SVM). SVM is the chosen forecasting technique because many studies have concluded that SVMs produce the optimum accuracy as compared to other methods such as Naive Bayesian, but SVM has not been optimised for the domain. © 2011 Inderscience Enterprises Ltd.

International Journal of Computer Aided Engineering and Technology

Electricity market price forecasting using support vector machines

The study of forecasting identifies the urgent need for special attention in evolving effective energy policies to alleviate an energy famine in the near future. Since power demand is increasing day by day in entire world and it is also one of the fundamental infrastructure input for the development, its prospects and availability sets significant constraints on the socio-economic growth of every person as well as every country. A care full long-term power plan is imperative for the development of power sector. This need assumes more importance in the state of Uttar Pradesh where the demand for electrical energy is growing at a rapid pace. This study analyses the requirement of electricity with respect to the future population for the major forms of energy in the Lucknow city in Uttar Pradesh state of India. A model consisting of significant key energy indicators have been used for the estimation. Model wherever required refined in the second stage to remove the effect of auto-correlation. The accuracy of the model has been checked using standard statistical techniques and validated against the past data by testing for 'expost' forecast accuracy. © Maxwell Scientific Organization, 2011.

Research Journal of Applied Sciences, Engineering and Technology

Electric power demand forecasting: A case study of Lucknow city

An amphiphilic diketopyrrolopyrrole-based oligothiophene (DPP amphi) has been prepared that displays robust self-assembly behavior in the bulk, in solution, and on surfaces. The material has been used as the active component in organic field-effect transistors and molecular bulk-heterojunction solar cells. © 2011 American Chemical Society.

Chemistry of Materials

Self-assembled amphiphilic diketopyrrolopyrrole-based oligothiophenes for field-effect transistors and solar cells

Fetal phonocardiography is a simple and noninvasive diagnostic technique for surveillance of fetal well-being. The fetal phonocardiographic (fPCG) signals carry valuable information about the anatomical and physiological states of the fetal heart. This article is concerned with a study of continuous wavelet transform (CWT)-based scalogram in analyzing the fPCG signals. The scalogram has both spatial and frequency resolution powers, whereas traditional spectral estimation methods only have the frequency resolution ability. The fPCG signals are acquired by a specially developed data recording system. Segmentation of these signals into fundamental components of fetal heart sound (S1 & S2) is carried out through envelope detection and thresholding techniques. CWT-based scalogram is used for time-frequency characterization of the segmented fPCG signals. It has been shown that the wavelet scalogram provides enough features of the fPCG signals that will help to obtain qualitative and quantitative measurements of the time-frequency characteristics of the fPCG signals and consequently, assist in diagnosis. The proposed method for time-frequency analysis (TFA) and the associated pre-processing have been shown to be suitable for the characterization of fPCG signals, yielding relatively good and robust results in the experimental evaluation. © 2011 World Scientific Publishing Company.

Journal of Mechanics in Medicine and Biology

Time-frequency characterization of fetal phonocardiographic signals using wavelet scalogram

In this paper we proposed a new computationally efficient interpolation algorithm for natural images in which unknown pixels are divided into few bins. The categorization of these unknown pixels into bins is based upon the characteristics of the neighboring pixels. These characteristics are obtained by taking difference of two slopes which are in orthogonal direction and these slopes are calculated from a set of neighboring pixels. We used the Least-Squares (LS) based approach to find optimal predictors for pixels belonging to various slope bins. We also presented a simplified proposed algorithm in which we used bilinear interpolation algorithm instead of estimating LS based predictor for some bins and it results into further reduction in computational complexity without sacrificing the much performance. Our proposed algorithm gives better interpolation quality with significantly lower computational complexity as compared to recently reported interpolation algorithms. © 2011 IEEE.

Conference Record - IEEE Instrumentation and Measurement Technology Conference

A computationally efficient context based switched image interpolation algorithm for natural images

The removal of native oxide from Si (1 1 1) surfaces was investigated by X-ray photoelectron spectroscopy (XPS) and secondary ion mass spectra (SIMS) depth profiles. Two different oxide removal methods, performed under ultrahigh-vacuum (UHV) conditions, were carried out and compared. The first cleaning method is thermal desorption of oxide at 900 °C. The second method is the deposition of metallic gallium followed by redesorption. A significant decrease in oxygen was achieved by thermal desorption at 900 °C under UHV conditions. By applying a subsequent Ga deposition/redesorption, a further reduction in oxygen could be achieved. We examine the merits of an alternative oxide desorption method via conversion of the stable SiO2 surface oxide into a volatile Ga2O oxide by a supply of Ga metals. Furthermore, ultra thin films of pure silicon nitride buffer layer were grown on a Si (1 1 1) surface by exposing the surface to radio-frequency (RF) nitrogen plasma followed by GaN growth. The SIMS depth profile shows that the oxygen impurity can be reduced at GaN/β-Si3N4/Si interfaces by applying a subsequent Ga deposition/redesorption. © 2011 Elsevier B.V. All rights reserved.

Journal of Crystal Growth

Reduction of oxygen impurity at GaN/β-Si3N4/Si interface via SiO2 to Ga2O conversion by exposing of Si surface under Ga flux

The band offsets in InN/p-Si heterojunctions are determined by high resolution x-ray photoemission spectroscopy. The valence band of InN is found to be 1.39 eV below that of Si. Given the bandgap of 0.7 eV for InN, a type-III heterojunction with a conduction band offset of 1.81 eV was found. Agreement between the simulated and experimental data obtained from the heterojunction spectra was found to be excellent, establishing that the method of determination was accurate. The charge neutrality level (CNL) model provided a reasonable description of the band alignment of the InN/p-Si interface and a change in the interface dipole by 0.06 eV was observed for InN/p-Si interface. © 2011 American Institute of Physics.

Fulltext

Journal of Applied Physics

Band alignment studies in InN/p-Si(100) heterojunctions by x-ray photoelectron spectroscopy

InN/GaN heterostructure based Schottky diodes were fabricated by plasma-assisted molecular beam epitaxy. The temperature dependent electrical transport properties were carried out for InN/GaN heterostructure. The barrier height and the ideality factor of the Schottky diodes were found to be temperature dependent. The temperature dependence of the barrier height indicates that the Schottky barrier height is inhomogeneous in nature at the heterostructure interface. The higher value of the ideality factor and its temperature dependence suggest that the current transport is primarily dominated by thermionic field emission (TFE) other than thermionic emission (TE). The room temperature barrier height obtained by using TE and TFE models were 1.08 and 1.43 eV, respectively. © 2011 American Institute of Physics.

Temperature dependent electrical transport behavior of InN/GaN heterostructure based Schottky diodes

Indium nitride (InN) is an interesting and potentially important semiconductor material with superior electronic transport properties. Compared to all other group III-nitrides, InN possesses the lowest effective mass, the highest mobility, the highest saturation velocity and narrow band gap of 0.7-0.9 eV. The present paper deals with the fabrication of InN nanostructures on silicon and sapphire substrates by plasma-assisted molecular beam epitaxy. The droplet epitaxy and Stranski-Krastanov(S-K) growth modes were used to grow the nanostructures. © 2011 American Institute of Physics.