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International Journal of Information Quality (2 papers in press)
Special Issue on: ICAIIS-2019 Advanced Computational Methods for Data and Information Quality
Data Classification Methodology and Pattern Analysis for Knowledge Discovery and Data Mining by Attili Venkata Ramana, Annaluri Sreenivasa Rao, Somula Ramasubbareddy Abstract: Excess usage of information with the help of big data (BD) applications, the society of computer sciences needs to adopt various online classification tools along with different types of pattern reorganization (PR) techniques. The data collected from different types of sensor networks (SN), online patterns, images, etc. are the different sources of big data and to deal with such data, natural processing (NP) and data mining (DM) techniques are not capable of facing the challenges to deal with huge amount of data. To deal with such type of challenges, in this research a new algorithm is proposed based on DM and knowledge discovery (KD) using the network entropy (NE). Initially the needful data is introduced using support vector machine (SVM), neural networks (NN) and decision trees (DT) methods. In the later stages using machine learning (ML) techniques and pattern theory an organizational structure of network graphical pattern is constructed. From different databases, the simulation results obtained from the proposed approach shows good effectiveness and feasibility. Keywords: Data Classification; PA; KD; Information Security; PA and BD.
Adaptive Artificial Bee Colony Algorithm and Optimum Pixel Adjustment Algorithm Based Image Steganography Method by Ambika N, Rajkumar L. Biradar, Vishwanath Burkpalli Abstract: The process of embedding information such as text, image, audio, video in a cover is called steganography. The main aim of this research is to give effective steganography with low imperceptibility of entrenched information. Henceforth in this paper, an Adaptive ABC (Artificial bee Colony) algorithm is involved in selecting the optimal pixel points through setting the objective utility as PSNR. To decrease the embedding error and to bring out the stego image visually equivalent as the cover image, the Optimal Pixel Adjustment algorithm is presented after embedding. The proposed methodology is applied in the working platform of MATLAB and the results were investigated. Keywords: Optimal Pixel Adjustment; Integer Wavelet Transform; Adaptive Artificial Bee Colony; Steganography. DOI: 10.1504/IJIQ.2019.10027812