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Pradeep Kumar K.G.,SDM Institute of Technology
IET Conference Publications | Year: 2013

This paper proposes combining the concepts of quantum computing and big data. The idea of using the concept of quantum computing for processing the big data is suggested. Quantum computing is the advanced computing technology where we think ahead of our conventional binary bits. This is based on the quantum physics which states that a material can be at more than one place at a time. This concept, when used in our conventional computing systems, will have the third bit called the superimposed bit that can be in two states at a time. The term big data is used to refer to the huge amounts of data collected. The data being collected is increasing exponentially. According to a study conducted by McKinsey Global Institute, the data volume is growing 40% every year; and with the increasing number of users and research areas, one can expect much more growth in the data volume. With this kind of growing data, the need arises for faster processing and analysis methods giving better performance to the end users and the analytics. In this paper, a new algorithm, named as PQ-Key, is proposed for processing the big data using quantum computing. Source


Hegde G.P.,SDM Institute of Technology | Seetha M.,G N Institute Of Technology And Science
Proceedings of the 2015 International Conference on Applied and Theoretical Computing and Communication Technology, iCATccT 2015 | Year: 2015

Most of the earlier expression recognition system based on nonlinear subspace methods not able to solve the discriminative problems of feature extraction, locality structure preservation and dimensional reduction by increasing the Fishers ratio of discriminant analysis. In this work, adaptive combination approach is framed by combining geometrical and holistic features. Both Gabor magnitude feature vector (GMFY) and enhanced Gabor phase feature vector (GPFV) are separately isolated and feature level fusion is carried out by combining with geometrical distance feature vector (GDFY). Fused phase part was aligned with discrete wavelet moment (DWT) features. High dimensional space was projected into low dimensional subspace by kernel locality preserving Fisher discriminant analysis method. Projected subspace is normalized and final scores of projected space were fused using maximum fusion rule. Expressions are classified using Euclidean distance matching and support vector machine radial basis function kernel classifier. The whole proposed approach is abbreviated as ACEGKLPFDA. An experimental result reveals that the proposed approach is effective for dimension reduction, efficient recognition and classification. Performance of proposed approach is measured in comparison with related subspace approaches. The best average recognition rate achieves 97.61% for JAFFE and 95.62% FD database respectively. © 2015 IEEE. Source


Hegde G.P.,SDM Institute of Technology | Seetha M.,G N Institute Of Technology And Science
Proceedings of the 2015 International Conference on Green Computing and Internet of Things, ICGCIoT 2015 | Year: 2015

The important objective of this work is to utilization of entire Gabor features by enhancing the phase part of the Gabor and maximizing the Fishers ratio in nonlinear domain space by preserving the local information. Entire Gabor kernel locality preserving Fisher discriminant analysis (EGKLPFDA) approach is proposed. Both Gabor magnitude and spatially enhanced phase congruency parts are separately used for feature extraction. These two vector feature space is projected into KLPFDA subspace method by preserving the kernel discriminant locality structure of data. Projected subspace is normalized by Z-score normalization. Both normalized scores are fused by maximum fusion rule. Final score obtained from train and test image sets are used to distance matching using Euclidean distance algorithm and support vector machine (SVM) classifier is implemented to classify the expressions. Performance analysis is carried out by comparing earlier approaches. Experimental results on JAFFE, Yale, and FD database demonstrate the effectiveness of the proposed approach. © 2015 IEEE. Source


Hegde R.,SDM Institute of Technology
IET Conference Publications | Year: 2013

This review paper is concentrating on two data hiding approaches using compressed MPEG video files. The first approach by modulating the quantization scale[26] of a constant bitrate video, message bits are hided. A payload of one message bit per macroblock is achieved. Asecond order multivariate regression[26] is used to find an association between macroblocklevel feature variables and the values of a hidden message bit. The regression model is then used by the decoder to predict the values of the hidden message bits with very high prediction accuracy. The second approach uses the flexible macroblock ordering feature of H.264/AVC to hide message bits. Macroblocks are assigned to arbitrary slice groups according tothe content of the message bits to be hidden. A maximum payload of three message bits per macroblock is achieved. The experimental solutions are analyzed in terms of message extraction accuracy, message payload, excessive bitrate and quality distortion. And also we are reviewing the paper which presents an improved data hiding techniques based on BCH (n,k,t) coding. Source


Somashekar D.P.,SDM Institute of Technology
IET Conference Publications | Year: 2013

The continuous service for customers is complicated process in distribution system, when the system apparatus and customers are get affected by various large number of outages which caused by improper maintenance of system utilities and some environmental factors results block-out regions in the systems. The impact of distributed generation on distribution system, stability will be negligible when connected in small amounts. However, if it's penetration level become higher, distributed generation may start to influence the dynamic behavior of the system as a whole. So, the fuel cells (SOFC) are used as distributed generation system which is penetrates in distribution network to enhance the continuous service for customers. In this paper, we are analyzing the system stability by describing the dynamic modeling of fuel cell to the system utility grid by using MATLAB/SIMULINK. Source

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