Raju Dara

Work place: Department of Computer Science and Engineering Jawaharlal Nehru Technological University Kakinada, Andhra Pradesh, India

E-mail: rajurdara@gmail.com


Research Interests: Image Processing, Image Manipulation, Image Compression


Mr. Raju Dara is a Research Scholar of Department of Computer Science and Engineering, Jawaharlal Nehru Technological University, Kakinada. He has 8 years of teaching experiences for Graduate and Post Graduate engineering courses. His current research interests are Data Warehousing, Image Processing. He published 8 research papers in international journals and 3 research papers in international conferences.

Author Articles
A Novel Approach for Data Cleaning by Selecting the Optimal Data to Fill the Missing Values for Maintaining Reliable Data Warehouse

By Raju Dara Ch. Satyanarayana A Govardhan

DOI: https://doi.org/10.5815/ijmecs.2016.05.08, Pub. Date: 8 May 2016

At present trillion of bytes of information is being created by projects particularly in web. To accomplish the best choice for business benefits, access to that information in a very much arranged and intuitive way is dependably a fantasy of business administrators and chiefs. Information warehouse is the main feasible arrangement that can bring the fantasy into reality. The upgrade of future attempts to settle on choices relies on upon the accessibility of right data that depends on nature of information basic. The quality information must be created by cleaning information preceding stacking into information distribution center following the information gathered from diverse sources will be grimy. Once the information have been pre-prepared and purified then it produces exact results on applying the information mining question. There are numerous cases where the data is sparse in nature. To get accurate results with sparse data is hard. In this paper the main goal is to fill the missing values in acquired data which is sparse in nature. Precisely caution must be taken to choose minimum number of text pieces to fill the holes for which we have used Jaccard Dissimilarity function for clustering the data which is frequent in nature.

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A Novel Approach for Image Recognition to Enhance the Quality of Decision Making by Applying Degree of Correlation Using Artificial Neural Networks

By Raju Dara Ch. Satyanarayana A Govardhan

DOI: https://doi.org/10.5815/ijigsp.2014.11.04, Pub. Date: 8 Oct. 2014

Many diversified applications do exist in science & technology, which make use of the primary theory of a recognition phenomenon as one of its solutions. Recognition scenario is incorporated with a set of decisions and the action according to the decision purely relies on the quality of extracted information on utmost applications. Thus, the quality decision making absolutely reckons on processing momentum and precision which are entirely coupled with recognition methodology. In this article, a latest rule is formulated based on the degree of correlation to characterize the generalized recognition constraint and the application is explored with respect to image based information extraction. Machine learning based perception called feed forward architecture of Artificial Neural Network has been applied to attain the expected eminence of elucidation. The proposed method furnishes extraordinary advantages such as less memory requirements, extremely high level security for storing data, exceptional speed and gentle implementation approach.

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