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Pandey B.,Gb Pant University Of Ag And Technology | Pandey K.,Ajay Kumar Garg Engineering College | Agrawal H.M.,Gb Pant University Of Ag And Technology
Annals of Nuclear Energy | Year: 2011

The excitation functions of (n,p) reactions for the stable isotopes of Cr, Fe and Ni were calculated using EMPIRE 3.0 β1 (ARCOLE) from threshold to 20 MeV. The cross-sections are calculated using full featured Hauser-Feshbach statistical model with pre-equilibrium effects by invoking DEGAS option in the code. A good agreement between the calculated and experimental data (EXFOR data base) as well as evaluated data is obtained with option of neutron and proton potentials by Koning (Global) and HFB parity dependent nuclear level density. This is an important step to the validation of nuclear model with superior predictive power. The compound nucleus and pre-equilibrium reaction mechanisms as well as the isotopic effects were also studied. © 2010 Elsevier Ltd. All rights reserved.

Kumar S.,Ajay Kumar Garg Engineering College
Astrophysics and Space Science | Year: 2012

Some recent experimental observations have been shown that inclusion of electron collisions damping in inertial Alfvén wave (IAW) dynamics may be important for laboratory as well as space plasmas. This paper presents the numerical simulation of model equation governing the nonlinear dynamics of IAW in low-beta plasmas. When the nonlinearity arises due to the ponderomotive force and Joule heating driven density perturbations, the model equation turns out to be a modified nonlinear Schrödinger equation (MNLS). The electron collisions are introduced only in the electron momentum equation. The damped localized structures of IAW with sidebands are obtained. Also, the effect of collisional damping on power spectra of magnetic fluctuations with different scaling laws has been studied. These turbulent structures may be responsible for particle acceleration in laboratory and space plasmas. © 2011 Springer Science+Business Media B.V.

Chopra P.K.,Ajay Kumar Garg Engineering College | Chandrasekhar M.G.,Devas Multimedia
Journal of Computational Electronics | Year: 2013

For high quality performance, future efficient wireless communication systems require a Broadband Amplifier in the frequency range under consideration. When such an amplifier is plugged into the measuring path it would enable the system to perceive even the weakest of signals. To achieve this, a new Scattering-parameter model that is valid for a wide frequency range has been developed for microwave analysis of a pseudomorphic high electron mobility transistors (pHEMT). The developed neural network model is used for designing a pHEMT power amplifier. The calculated S-parameters, gain and minimum noise figure from the artificial neural networks (ANN) model are the parameters used to design the low noise pHEMT power amplifier. The various gains so obtained from the S-parameters have been plotted with the frequency and it was found to yield a close fit to the simulated model. Neural network training has been done using Levenberg-Marqaurdt back propagation algorithm implemented in ANN toolbox of MATLAB software. All the results have been compared with the experimental data that showed a close agreement and validated our model. The calculated S-parameters, gain and minimum noise figure from the ANN model are the parameters used to design a stabilized and matched LNA. © 2013 Springer Science+Business Media New York.

Goel S.,Raj Kumar Goel Institute of Technology | Yadav S.,Ajay Kumar Garg Engineering College
Proceedings of the 2013 3rd IEEE International Advance Computing Conference, IACC 2013 | Year: 2013

With the magnificent amount of information present on web, it is very important to identify whether the search engine satisfy all the requirements of users by their search results. So, it is necessary to evaluate search engines based on user point of view. Basically evaluation of search engines is a process of determining how well the search engines meet the information need of users. In this paper we present our approach of search engine evaluation which is based upon page level keywords. Page level keywords are the keywords found in individual pages of a website. Page level keyword is an important factor to measure the relevancy of the search engine results. The result set retrieved by search engines are containing a huge number of useless web pages. Users may have to sift through dirt's in order to find gemstones or to rethink his query. So our work can be a basis to provide more relevant search results to the users. Three Search engines Google, Yahoo and Bing are evaluated based on educational queries in accordance with page level keywords. We verify the results with precision measurement using 40 educational queries at cut off 10. © 2013 IEEE.

Tyagi K.,Ajay Kumar Garg Engineering College | Sharma A.,Krishna Institute of Engineering and Technology
Advances in Engineering Software | Year: 2012

Reliability is one of the most important nonfunctional requirements for software. Accurately estimating reliability for component-based software systems (CBSSs) is not an easy task, and researchers have proposed many approaches to CBSS reliability estimation. Some of these approaches focus on component reliability and others focus on glue code reliability. All of the approaches that have been proposed are mathematical. However, because reliability is a real-world phenomenon with associated real-time issues, it cannot be measured accurately and efficiently with mathematical models. Soft computing techniques that have recently emerged can be used to model the solution of real-world problems that are too difficult to model mathematically. The two basic soft computing techniques are fuzzy computing and probabilistic computing. In this paper, we focus on four factors that have the strongest effect on CBSS reliability. Based on these four factors, we propose a new fuzzy-logic-based model for estimating CBSS reliability. We implemented and validated our proposed model on small applications, and the results confirm the effectiveness of our model. © 2012 Elsevier Ltd. All rights reserved.

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