Ghāziābād, India
Ghāziābād, India

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Kaushik B.,ABES Engineering College
Applied Soft Computing Journal | Year: 2014

Approximated artificial neural network (AANN) is a meta-heuristics optimization algorithm mixing the features of approximating the computed combinatorial spectrum and ability of neural network to approximate the input from problem domain to the desired output. This paper proposes the use of an approximated artificial neural network (AANN) approach for the case of reliability when complex network design is considered. A mesh network of 256 nodes and hyper-tree network of 496 nodes are considered for evaluating the performance of AANN algorithm for improving reliability and minimizing cost for complex network. Since, evaluating reliability for complex network using formal approach requires substantial computational effort and time equivalent to NP-Hard. The work presented in this paper compares the performance of AANN algorithm with that of Monte Carlo simulation (MCS) and particle swarm optimization (PSO) for improving reliability and minimizing cost for complex network problems. The simulation results show that the performance of AANN algorithm is comparable to those of the mentioned algorithms and can be used to improve reliability and reduce the cost for complex network design problems when amount of complexity is relatively higher. © 2014 Elsevier B.V. All rights reserved.


Sharma A.K.,Northen India Engineering College | Trivedi M.C.,ABES Engineering College
Proceedings - 2016 2nd International Conference on Computational Intelligence and Communication Technology, CICT 2016 | Year: 2016

MANET is a collection of computational devices that creates random topology for communication. The beauty of MANET is that it not required any central controller or base station. The devices used in MANET may be fixed or mobile. MANET is only a network in which devices worked as a host as well as router. The routing protocol used in mobile ad hoc network is broadly classified in three category-proactive, reactive and hybrid routing protocol. In this thesis work performance of AODV, AODVDR and ZRP is compared in the presence of different number of connection, different pause time and different number of communicating devices. In this work, network simulator tool NS2.35 is used for simulation. Simulation result shows the AODVDR is perform better than AODV and ZRP routing protocol. © 2016 IEEE.


Bhati P.S.,Mewar University | Trivedi M.C.,ABES Engineering College
Proceedings - 2016 2nd International Conference on Computational Intelligence and Communication Technology, CICT 2016 | Year: 2016

Enterprise Resource Planning along with Business Intelligence, if implemented effectively can provide several benefits such as improved visibility, real time data access, fast interdepartmental communications etc. In paper presented, a depth studies is carried out over ERP implementation and their issues. Some of the identified issues can be categorized into Misalignment and security aspects. Misalignment can be defined as probability of mismatch between ERP and company needs in which it is implemented. © 2016 IEEE.


Gautam M.,ABES Engineering College
Research Journal of Pharmaceutical, Biological and Chemical Sciences | Year: 2014

The aldehyde (Benzimidazole-2-Carboxyaldehyde) complex of Nickel (II) and Cobalt(II) were prepared by mixing aqueous solution of metal chloride with ethanolic solution of the aldehydes at 1:2 mol ratio. Then with a solution of polyacrylamide coordination polymers were prepared. IR study indicate that the aldehyde reacts with the polymer. Frequency shifts may be attributed to coordination of the metal ion with the azomethine nitrogen and imine oxygen of the carboxylate group. 1H NMR studies suggests the existence of keto and enol forms even in the solution form. The thermal analysis reports the thermo-oxidative degradation of complexes. From the conductivity measurements it has been shown that the conductivity of the nickel complexes are higher than the cobalt complexes.


Tripathi A.K.,Krishna Institute Of Engg And Technology | Radhakrishanan R.,ABES Engineering College | Lather J.S.,National Institute of Technology Kurukshetra
Proceedings of the 2014 International Conference on Issues and Challenges in Intelligent Computing Techniques, ICICT 2014 | Year: 2014

In the last decade tremendous development in the area of mobile and wireless network. Internet Engineering Task Force (IETF) proposed Mobile IPv6 to provide mobility in wireless IPv6 networks. But still transparent mobility over the Internet is one of the biggest in challenges. Recently Hierarchical Mobile IPv6 (HMIPv6) and Proxy Mobile IPv6 (PMIPv6) are proposed to reduce the handover latency and as a result to reduce packet loss. This paper analyzes impact of handover latency wireless link delay on handover latency and compares the results analytically. © 2014 IEEE.


Khatter H.,ABES Engineering College | Aggarwal V.,Krishna Institute of Engineering and Technology
Proceedings of the 2014 International Conference on Issues and Challenges in Intelligent Computing Techniques, ICICT 2014 | Year: 2014

In this digital world, more than 90% of desktop and notebook computers have integrated Graphics Processing Units i.e. GPU's, for better graphics processing. Graphics Processing Unit is not only for graphics applications, even for non-graphics applications too. In the past few years, the graphics programmable processor has evolved into an increasingly convincing computational resource. But GPU sits idle if graphics job queue is empty, which decreases the GPU's efficiency. This paper focuses on various tact to overcome this problem and to make the CPU-GPU processing more powerful and efficient. The graphics programmable processor or Graphics processing unit is especially well suited to address problem sets expressed as data parallel computation with the same program executed on many data elements concurrently. The objective of this paper is to increase the capabilities and flexibility of recent GPU hardware combined with high level GPU programming languages: to accelerate the building of images in a frame buffer intended for output to a display, and, to provide tremendous acceleration for numerically intensive scientific applications. This paper also gives some light on major applicative areas where GPU is in use and where GPU can be used in future. © 2014 IEEE.


Garg S.,ABES Engineering College | Trivedi M.C.,ABES Engineering College
Smart Innovation, Systems and Technologies | Year: 2016

Recognition of gender from face image has attracted a huge attention now a days. Many identification systems are being developed to identify a person, as most of the technique for gender classification stand on facial features. In this paper, we presented a gender classification framework consist of a series of phases for determining the gender as the final output. Initially we start by detecting the face from an image using Viola Jones and then extract the facial feature using the Topographic Independent Component Analysis. The features extracted here are used to train the SVM classifier for the classification step. Our experimental result gives the best accuracy in determining the images as of male or female and gives average performance of 96% correct gender identification on images. © Springer International Publishing Switzerland 2016.


Pandey A.,ABES Engineering College | Sinha A.,ABES Engineering College
Proceedings - 2016 2nd International Conference on Computational Intelligence and Communication Technology, CICT 2016 | Year: 2016

The status of any state of India depends significantly on various natural resources. The status may be developed, developing and under developed while natural resources may be climate, rivers flowing and the length of rainfall etc. In this paper, two natural resources such as number of rivers flowing and rainfall in that state have been taken at different times and their dependencies on the development are analytically done. This analytical work is implemented through Adaptive Neuro Fuzzy Inference System (ANFIS) with a set of values, number of rivers and height of rainfall. A trend has been observed corresponding to each status of the states. The present paper gives an idea to predict the development of any state in different time span. The work is validated through various known results and found a significant improvement over the previous work. © 2016 IEEE.


Goel A.,ABES Engineering College | Srivastava S.K.,ABES Engineering College
Proceedings - 2016 2nd International Conference on Computational Intelligence and Communication Technology, CICT 2016 | Year: 2016

Identifying performance of classifier is a challenging task. SVM plays an important role in classification. Here different kernel parameters are used as a tuning parameter to improve the classification accuracy. There are mainly four different types of kernels (Linear, Polynomial, RBF, and Sigmoid) that are popular in SVM classifier. The paper presents SVM classification results with above mentioned kernels on two different datasets (Diabetic Retinopathy dataset and Lung Cancer dataset). To evaluate the performance of the classifier we have used True positive rate, False Positive rate, Precision, Recall, F-measure and accuracy as performance measures of SVM. Finally we evaluated that SVM with linear kernel performs best among all. © 2016 IEEE.


Sharma S.,ABES Engineering College | Srivastava S.K.,ABES Engineering College
Proceedings - 2016 2nd International Conference on Computational Intelligence and Communication Technology, CICT 2016 | Year: 2016

Classification is a challenging phenomenon. Text classification uses terms as features which can be grouped to vote for belongingness of a class. This paper explores the performance of Support Vector Machine (SVM) on variation of text features. Empirical results support the findings. The reported result shows significant degradation in SVM classifier as we reduce features from 100 to 50 and then to 25. Short text messages (tweets) are used as a data set and balanced binary classes are used with 841 tweets each. We have used radial basis function as a kernel parameter. TP Rate, FP Rate, Precision, Recall, F Measure are used as a measure of performance evaluator. Confusion matrix is used for quick review of classifier and 10 fold cross validation is used for estimation of prediction model. © 2016 IEEE.

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