Suresh B.,MITS Engineering College |
Rath G.S.,National Institute of Technology Rourkela
ACM International Conference Proceeding Series | Year: 2011
This paper presents a novel approach for image Encryption Different type of modular Orthonormal Transforms has been used. Although Hadamard Transform, Walsh Transform were used for image compression, nobody has used so far modular Transform for image encryption. A set of discrete modular Orthonormal transforms has been generated and used for encryption image. A novel approach of image authentication by introducing a known bit pattern (signature) into the encrypted image also studied. A 4 bit Cyclic Redundancy Check (CRC) code is introduced to detected the bit position signature as an error bits subsequently CRC code are inserted column wise to detect and correct single bit errors that occur during transmission of image. The MSE, PSNR and correlation coefficient of detected image for discrete Orthonormal transforms have been obtained by simulation. The results shows good future prospect. Copyright © 2011 ACM.
Gundu Rao H.K.,Vijaya College |
Manjunatha Rao L.,Dayananda Sagar Institutions |
Rajasekhar Reddy N.,MITS Engineering College
IET Conference Publications | Year: 2012
The present paper proposes a Machine learning technique for defect forecasting and handling for SQA called appendage log training and analysis, can be referred as ALTA. The proposed defect forecasting of in-appendage software development logs works is to deal the forecasted defects accurately and spontaneously while developing the software. The present proposed mechanism helps in minimizing the difficulty of SQA. The overall study is conducted on evaluating the proposed model which indicates the defect forecasting in-appendage software development log training and analysis is significant growth to lessen the complexity of Software Quality Assessment.
Gantayat S.S.,GMRIT |
Misra A.,CUTM |
Panda B.S.,MITS Engineering College
Advances in Intelligent Systems and Computing | Year: 2014
Incomplete data are questions without answers or variables without observations. Even a small percentage of missing data can cause serious problems with the analysis leading to draw wrong conclusions and imperfect knowledge. There are many techniques to overcome the imperfect knowledge and manage data with incomplete items, but no one is absolutely better than the others. To handle such problems, researchers are trying to solve it in different directions and then proposed to handle the information system. The attribute values are important for information processing. In the field of databases, various efforts have been made for the improvement and enhance of database query process to handle the data. The different researchers have tried and are trying to handle the imprecise and/or uncertainty in databases. The methodology followed by different approaches like: Fuzzy sets, Rough sets, Boolean Logic, Possibility Theory, Statistically Similarity etc. © Springer International Publishing Switzerland 2014.
Panigrahi S.,National Institute of Science and Technology |
Rath B.,MITS Engineering College |
Santosh Kumar P.,MITS Engineering College
Smart Innovation, Systems and Technologies | Year: 2015
Over the past few decades clustering algorithms have been used in diversified fields of engineering and science. Out of various methods, K-Means algorithm is one of the most popular clustering algorithms. However, K-Means algorithm has a major drawback of trapping to local optima. Motivated by this, this paper attempts to hybridize Chemical Reaction Optimization (CRO) algorithm with K-Means algorithm for data clustering. In this method K-Means algorithm is used as an on-wall ineffective collision reaction in the CRO algorithm, thereby enjoying the intensification property of K-Means algorithm and diversification of intermolecular reactions of CRO algorithm. The performance of the proposed methodology is evaluated by comparing the obtained results on four real world datasets with three other algorithms including K-Means algorithm, CRO-based and differential evolution (DE) based clustering algorithm. Experimental result shows that the performance of proposed clustering algorithm is better than K-Means, DE-based, CRO-based clustering algorithm on the datasets considered. © Springer India 2015.
Satpathy R.,MITS Engineering College |
Guru R.K.,MITS Engineering College |
Behera R.,MITS Engineering College
International Journal of Pharmacy and Pharmaceutical Sciences | Year: 2012
Curcuma longa plant produces Curcumin which is widely used as spices and colouring agent in food. Curcumin is also used to treat various diseases due to its medicinal and pharmacological activities. The present study is based on analysis of anti-influenza activity of Curcumin by using computational methods. The Curcumin derivatives obtained from the data base were docked against the HA protein of influenza (2009 H1N1) virus. Further analysis by evaluating the biological activity and pharmacophore modeling results about the pharmacophoric features responsible for the inhibition activity. The results demonstrated that some of the specific Curcumin derivatives can be successfully used against influenza virus infection.