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Vasagiri K.,VNRVJIET | Parvata S.R.,Vignan Womens College for Technology and Management
Proceedings of the 2016 2nd International Conference on Applied and Theoretical Computing and Communication Technology, iCATccT 2016 | Year: 2017

People are depending on information very much and it is becoming essential to carry out different activities every day. The degree of security in many situations becoming critical and need to be paid attention because of increase of crime rate with sophisticated technology. To increase the privacy and safety of information care must be taken to protect the information. Individual authentication is achieved using Biometric traits in different fields. As biometric authentication, there are methods using finger print, iris, and voice and so on. For the disadvantages of other biometric recognition methods, dorsal hand vein pattern has emerged as new biometric because the vascular structure is unique to every individual. The vein is the inner features of body and can't be fabricated and they are lasting. So it can be used for identification of individuals in highly secured areas. In this project, a new approach is proposed for extracting critical features from the dorsal hand vein pattern using the concepts of Walsh transform and Euclidean distance similarity measure. The proposed methodology has been tested on a dataset of 100 dorsal hand vein images and the experimental results are found to be promising. © 2016 IEEE.

Srinivasa Rao M.S.,VNRVJIET | Manzoor Hussain M.,JNTUH College of Engineering
Materials Today: Proceedings | Year: 2017

The friction stir welding (FSW) process was relatively new welding process applied in this research work to join 5mm thick IS:65032 aluminum alloys. IS:65032 aluminum alloy has gathered wide acceptance in the fabrication of light weight structures requiring a high strength-to-weight ratio and good corrosion resistance. Compared to the fusion welding processes that are routinely used for joining structural aluminum alloys, friction stir welding (FSW) process is an emerging solid state joining processes in which the material that is being welded does not melt and recast. This process uses a non-consumable tool to generate frictional heat in the abutting surfaces. In this investigation, an attempt has been made to understand the effect of rotational speed, welding speed and tool pin profiles on the tensile strength and weld joint efficiencies were studied. Three different tool pin profiles (taper cylindrical,taper triangular and taper square) have been used to fabricate the joints at three different rotational speeds i.e., 1000, 1300 and 1600 rpm and three different welding speeds i.e., 60, 80 and 100 mm/min. The results have been evaluated and compared with each other. © 2017 Elsevier Ltd.

Srikanth P.,VNRVJIET
2016 IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2016 | Year: 2017

This paper defines the problem and design of the appropriate similarity with distribution function of the omics data is a critical objective. Data mining integrate methodical section at the large explosion of huge amount data that can be obtained to utilize and innovative knowledge. Researchers present and future the omics technologies permit to imitate as highly dimensional of omics data. This paper main objective to distance measure is using to concern as clustering algorithms. In order to particular tasks based on reduced high-dimensional omics data of dimensional reduction applying proposed distance measure is designed with distribution function based on PDF and CDF using designed average function and distance measure. It is using training and testing reduce data based on clusters. Reduced data using with class and without class of the OMICS data with accurate results. © 2016 IEEE.

Poornima S.,VNRVJIET | Ravindra K.,JNTUH College of Engineering
International Conference on Signal Processing, Communication, Power and Embedded System, SCOPES 2016 - Proceedings | Year: 2017

This paper mainly presents comparison between intelligent algorithms based on Continuous Wavelet Transform (CWT) and Discrete Wavelet Transform (DWT) in combination with Artificial Neural Network to discriminate the magnetizing inrush current signals from the internal fault current signals of the power transformer. This work also includes development of CWT and DWT based preprocessing units to extract distinguishing attributes from inrush and internals fault signals, which are quicker, completely independent from the traditional second harmonic restraining methodologies. Extracted attributes are fed to ANN based post processing unit to classify inrush current and internal fault current of power transformer. Proposed scheme achieves proper classification with high discrimination rate and least error, avoiding mal tripping of power transformer. © 2016 IEEE.

Chaitanya N.S.,VNRVJIET | Ramachandram S.,Osmania University
Proceedings of the 2016 2nd International Conference on Contemporary Computing and Informatics, IC3I 2016 | Year: 2017

We present a chunk based bandwidth prediction (CBP) to implement end-to-end traffic redundancy elimination (TRE) framework for users register and verified using Digital Signature in multi cloud environments. Our model describes that the data owner performs decomposing and Access Control Policies (ACPs) so that the risk overhead fior key management and information exposure were reduced. With this approach the primary benefit is its capacity of offloading the Multi cloud servers thereby minimizing the expenses. To handle implementation of two layer encryption process the ACPs should be properly defined and decomposed. We provides the confidentiality of the information and also protects the security of users in Multi cloud by achieving the access control policies. CBP is focused around a novel TRE scheme, We show a completely practical CBP execution with two layer encryption which reduce redundancy and provides high security. © 2016 IEEE.

Kodela R.,SR Engineering College | Vanagala P.,VNRVJIET
IETE Journal of Research | Year: 2017

Thyroid tissue samples, pathologically characterized as normal and malignant type, containing both the epithelial and stromal regions are prepared on two different glass slides. Polarized light scattering from these individual slides is used to record the intensity images by Polarimetric Imaging technique. These images are processed further to obtain Mueller intensity images respectively for normal and malignant tissue types. Polar decomposition of these Mueller intensity images results in obtaining Depolarization, Diattenuation, and Retardance images; their potentiality to understand the structural and morphological changes in the samples is reported for comparison. © 2017 IETE

Nireekshana T.,VNRVJIET | Kesava Rao G.,Vasireddy Venkatadri Institute of Technology | Siva Naga Raju S.,Jawaharlal Nehru Technological University Kakinada
International Journal of Electrical Power and Energy Systems | Year: 2012

Determination and enhancement of Available Transfer Capability (ATC) are important issues in deregulated operation of power systems. This paper investigates the use of FACTs devices, like SVC and TCSC, to maximize power transfer transactions during normal and contingency situations. ATC is computed using Continuation Power Flow (CPF) method considering both thermal limits and voltage profile. Real-code Genetic Algorithm (RGA) is used as an optimization tool to determine the location and controlling parameters of SVC and TCSC. The suggested methodology is tested on IEEE 14-bus system and also on IEEE 24-bus reliability test system for normal and different contingency cases. © 2012 Elsevier Ltd. All rights reserved.

Reddy G.S.,VNRVJIET | Rajinikanth T.V.,SNIST | Rao A.A.,JNTUA
Souvenir of the 2014 IEEE International Advance Computing Conference, IACC 2014 | Year: 2014

Text clustering is an unsupervised process forming its basis solely on finding the similarity relationship between documents with the output as a set of clusters [14]. In this research, a commonality measure is defined to find commonality between two text files which is used as a similarity measure. The main idea is to apply any existing frequent item finding algorithm such as apriori or fp-tree to the initial set of text files to reduce the dimension of the input text files. A document feature vector is formed for all the documents. Then a vector is formed for all the static text input files. The algorithm outputs a set of clusters from the initial input of text files considered. © 2014 IEEE.

Naveen Kumar G.,VNRVJIET | Surya Kalavathi M.,JNTUH College of Engineering
International Journal of Electrical Power and Energy Systems | Year: 2014

Voltage stability categorized under various classifications of power system stability is considered one of the important subjects in power systems stability studies. A power system, experiencing disturbances, is at risks of voltage instability. Main reason for the cause of voltage instability is the sag in reactive power at various locations due to circuit contingencies classified under large disturbance voltage stability. The aim of this paper is to identify the optimal location of Unified Power Flow Controller in an interconnected power system under N-1 contingency. As the size and the cost of the FACTS devices are high, an optimal location and size has to be identified before they are actually installed. We are trying to improve the voltage profile and Maximum Loading Parameter using Unified Power Flow Controller while determining their optimal location based upon Cat Swarm Optimization. © 2013 Elsevier Ltd. All rights reserved.

Babu B.R.,VNRVJIET | Lakshmieenivasa Reddy D.,Chaitanya Bharathi Institute of Technology
Proceedings - IEEE 30th International Conference on Advanced Information Networking and Applications Workshops, WAINA 2016 | Year: 2016

Outlier analysis is an essential task in data science to find out inconsistencies in data, to build a good classifier and in decision making. Finding outliers from categorical data is a tough task. In this work, a comparative study is made between classifier accuracies which are built by different outlier analysis methods generated by frequent and infrequent itemsets from categorical data. In modeling a classifier for categorical data, high frequent records are most useful and the infrequent records are obstacles in modeling the classifiers. The experiments are done on Bank dataset and Nursery dataset, taken from UCI ML Repository to compare the available methods with the proposed method. For normally distributed OFI, the number of outliers to be eliminated need not be given as input since it generates the number of outliers automatically. However the threshold value is needed to be given to generate infrequent item sets for NOFI. © 2016 IEEE.

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