Narula Institute of Technology

About: Narula Institute of Technology is a based out in . It is known for research contribution in the topics: Quantum dot cellular automaton & Cognitive radio. The organization has 288 authors who have published 490 publications receiving 2258 citations. The organization is also known as: NiT.

Dynamical System Analysis of Modified Chaplygin Gas in Einstein-Aether Gravity

Abstract: In this work we investigate the background dynamics when dark energy is coupled to dark matter with a suitable interaction in the universe described by Einstein-Aether gravity. Dark energy in the form of Modified Chaplygin gas is considered. A suitable interaction between dark energy and dark matter is considered in order to at least alleviate (if not solve) the cosmic coincidence problem. The dynamical system of equations is solved numerically and a stable scaling solution is obtained. A significant attempt towards the solution of the cosmic coincidence problem is taken. The statefinder parameters are also calculated to classify the dark energy models. Graphs and phase diagrams are drawn to study the variations of these parameters. It is also seen that the background dynamics of modified Chaplygin gas in Einstein-Aether gravity is completely consistent with the notion of an accelerated expansion in the late universe. Finally, it has been shown that the universe follows the power law form of expansion around the critical point.

A Fuzzy Hypothesis Testing Based Sample Covariance Matrix for Spectrum Sensing in Cognitive Radio Systems

Abstract: Spectrum Sensing is a key technology in cognitive radio systems. Since orthogonal frequency division multiplexing (OFDM) is one of the major wideband transmission techniques, spectrum sensing of OFDM based primary user signals is considered in this work. This paper proposes a two-stage scheme-Fuzzy Hypothesis Testing based Sample Covariance Matrix (FHTSCM) for primary user signal detection. Firstly, a hypothesis testing scheme with p-value determination from the observed samples is used along with a fuzzy inference scheme for detecting primary user signals with SNR as low as -2dB. We recognize the equivalence of the probability of Type-I error and the probability of false alarm (Pfa) and use an important property of the p-value to form the fuzzy rule base. In the low SNR regime (less than -2dB), the second stage computes the sample covariance matrix from a limited number of observed samples and an appropriate test statistic is extracted and tested using Roy's detector. Since the statistical covariances of the received signal and noise are usually different, they can be used to differentiate the case where the primary user signals are present from the one where there is only noise. The simulations are performed for the 2K mode of the DVB-T transmission and the probability of detection for different SNR levels is presented to verify the methods.

Text Extraction From Image Using MATLAB

Abstract: The goal of this paper is for extricating the text present in image and identify the text written using MATLAB programming language. Text Extrication from image and recognition as a whole have enormous relevance from the point of view of application, like content-based image restoration, document indexing and identification. Moreover, this triggers vast advanced systems. This work is focusing on detecting text in an image. To find a special sign in a natural image is sometimes frustrating. By using this method, it is easy to identify this type of object in an image like traffic sign, using Optical Character Recognition (OCR). Automatic task detection algorithms help to identify such situations in an image and highly efficient. It also uses Canny Edge Detection to discover the boundaries of the text present in the image from the Maximally Stable Extremal Regions (MSER).

To Explore Compounds as Tuberculosis Inhibitors—A Combination of Pharmacophore Modelling, Virtual Screening and Molecular Docking Studies

Abstract: In the present work, a ligand-based 3D pharmacophore and QSAR approach is used for the selection of potentially active compounds for inhibitory action against the enoyl-ACP-reductase (InhA) from Mycobacterium tuberculosis, followed by molecular modelling, dynamic simulation and binding energy calculation methods. The biological activity of the molecules is measured by logIC50 (50% inhibitory concentration). The molecular descriptors are used to build statistical models to predict the biological activity of interest.

Effect of Various Dielectrics to Plasmonic Improvement in Metal-Dielectric-Semiconductor Substrate

Abstract: Recently, Plasmonic gives increased interest that has been received as a way to enhancement in photonic response at optical extinction at metal-dielectric interface. It's highlighted property is that nanostructure can control optical fields due to the strong interaction of the metal-dielectric structure that allows incident photonic propagation at the nanoscale. In this study, we investigate and simulate the effectiveness of various large bandgap dielectric materials like silicon nitride, aluminum oxide and silicon dioxide with various metallic nanoparticle and also simulate finite time-based metal-dielectric-semiconductor nanostructure and find various field component for plasmonic improvement in form of photonic extinction in metal-dielectric nanostructure specifically for solar energy harvesting methodology.