Ajay Kumar Garg Engineering College

Ghāziābād, India

Ajay Kumar Garg Engineering College

Ghāziābād, India

Time filter

Source Type

Priya,Ajay Kumar Garg Engineering College | Singh S.,Amity University
1st IEEE International Conference on Power Electronics, Intelligent Control and Energy Systems, ICPEICES 2016 | Year: 2016

Application of neural networks for direct prediction of lateral-directional force and moments coefficients from the measured flight data of the research aircraft is proposed in this paper. Proposed model of neural networks appears to be a suitable practical approach to develop relationship between flight variables. This relationship eliminates the need of aerodynamic model as well as thrust model to develop accurate flight simulation software for the aircraft. The validation of proposed feed forward neural networks based technique is done with simulated as well as measured flight data of the aircraft. © 2016 IEEE.

Singh N.,Ajay Kumar Garg Engineering College | Tyagi K.,Ajay Kumar Garg Engineering College
International Journal of Systems Assurance Engineering and Management | Year: 2017

Many approaches are available for finding the reliability of service-oriented architecture (SOA). Here some mathematical works are used to estimate the system reliability. But in present, reliability is real time issue. So, the estimation of system reliability is a very difficult task. For this we have to discuss soft computing technique that is multi-criteria decision making method. This approach is used to provide the rank for each alternative service to select the best service for estimation. In this paper, we have used fuzzy multicriteria analysis with similarity based approach for reliability estimation. Also, we propose some factors that affect the SOA reliability. These factors work as criterion and we have taken three services as alternative. © 2015, The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden.

Rai A.K.,Ajay Kumar Garg Engineering College | Singh B.,Ajay Kumar Garg Engineering College
Solar Energy Materials and Solar Cells | Year: 2011

In this paper the simulation model of an artificial neural network (ANN) based maximum power point tracking controller has been developed. The controller consists of an ANN tracker and the optimal control unit. The ANN tracker estimates the voltages and currents corresponding to a maximum power delivered by solar PV (photovoltaic) array for variable cell temperature and solar radiation. The cell temperature is considered as a function of ambient air temperature, wind speed and solar radiation. The tracker is trained employing a set of 124 patterns using the back propagation algorithm. The mean square error of tracker output and target values is set to be of the order of 10-5 and the successful convergent of learning process takes 1281 epochs. The accuracy of the ANN tracker has been validated by employing different test data sets. The control unit uses the estimates of the ANN tracker to adjust the duty cycle of the chopper to optimum value needed for maximum power transfer to the specified load. © 2010 Elsevier B.V. All rights reserved.

Singh A.P.,Ajay Kumar Garg Engineering College | Tomar P.,Gautam Buddha University
Proceedings of the 2013 3rd IEEE International Advance Computing Conference, IACC 2013 | Year: 2013

Component-Based Software Engineering is a perfect approach for rapid software development with the maturity of components. The estimation of Component-Based Software (CBS) reliability from the reliabilities of constituent components and architecture is a matter of concern. In this paper we propose a Reliability Estimation Model for CBS to estimate the reliability through path propagation probability and component impact factor. This model incorporates the idea of path propagation to estimate overall system reliability after integration of components, which considers the contribution of the individual components that get activated during an execution path. This model also estimates the impact factor of individual components on overall reliability. The impact factor can be used to focus the efforts to obtain the best reliability improvements. To evaluate the Reliability Estimation Model including both the factors, we implement it through JAVA, which is based on an adapted example case study. Lastly we conclude that proposed model is useful to estimate the reliability of CBS and can be used adaptively in early stages of software development. © 2013 IEEE.

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.

Aggarwal N.,Sudan University of Science and Technology | Kumar A.,Sudan University of Science and Technology | Khatter H.,Ajay Kumar Garg Engineering College | Aggarwal V.,Ajay Kumar Garg Engineering College
Advances in Engineering Software | Year: 2012

In today's information society, we witness an explosive growth of the amount of information becoming available in electronic form and stored in large databases. Data mining can help in discovering knowledge. Data mining can dig out valuable information from databases in approaching knowledge discovery and improving business intelligence. In this paper, we have discussed the involvement and effect of data mining techniques on relational database systems, and how its services are accessible in databases, which tool we require to use it, with its major pros and cons in various databases. Through all this discussion we have presented how database technology can be integrated to data mining techniques. © 2011 Elsevier Ltd. All rights reserved.

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.

Goel A.,Ajay Kumar Garg Engineering College | Prasad R.,Ajay Kumar Garg Engineering College
International Journal of Computational Vision and Robotics | Year: 2014

Record matching works on large sets of data, which may be either from single database or several databases. As size of database increases very rapidly, demand of matching process becomes too high. So, there is demand to minimise the number of matching pair records, time and cost in comparing records using efficient matching techniques. Recent researches have been done on record matching by number of researchers using various indexing techniques but as such they are not effective. Suffix array (SA) and q-gram are used indexing technique, but they lack somewhere in computation. This paper proposes two new indexing techniques: inverse suffix array (ISA) and Burrows-Wheeler transformation (BWT) to improve the performance of record matching process. The approach ISA can handle the multiple keywords simultaneously. We compare the performance of the proposed techniques with existing suffix array and q-gram indexing techniques and found that the new techniques are better than the earlier techniques. Copyright © 2014 Inderscience Enterprises Ltd.

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.

Loading Ajay Kumar Garg Engineering College collaborators
Loading Ajay Kumar Garg Engineering College collaborators