Titlebook: Data Science and Computational Intelligence; Sixteenth Internatio K. R. Venugopal,P. Deepa Shenoy,Sitharama S. Iyeng Conference proceedings

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Highly Accurate Optical Encryption for Image Security Applications Using FFT and Block Swappingsmission plays a major role in various applications such as biomedical engineering, Remote sensing, Robotics, and industrial automation, etc. Previously, various techniques have been proposed to perform the optical image encryption process with a high degree of security. The main issue of previous w

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persistence

DRP-DBAS: Dynamic Resource Provisioning for Deadline and Budget Aware Workflow Scheduling in IaaS Clles the IaaS provider to offer infinite resources based on the pay-per-use model. Although the workflow scheduling problem has been widely investigated, however, most of them are concerned with a single QoS constraint and ignores the consideration of multiple QoS constrained problems. Therefore, thi

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Predicting the Movement of Cryptocurrency “Bitcoin” Using Random Forest current study focuses on predicting the direction of the cryptocurrency ‘Bitcoin’ for trading window of 3?days, 5?days, and 10?days ahead of the current day. The predictive model proposed is built using ensemble learning via random forest. The model uses feature matrix drawn on technical indicators

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Prediction of Essential Protein Using Machine Learning Techniqueand drug design. Essential proteins are predicted from many protein-protein interactions (PPI) networks that are developed using high-throughput techniques. Computational methods are used by many existing proposed techniques to identify essential proteins. Many of them considered topological feature

VAN

Runtime Program Semantics Based Malware Detection in Virtual Machines of Cloud Computing applied to the anomaly detection module at hypervisor level, where an ensemble of Random forest, Extra trees and Kernel SVM with majority voting technique is used to detect any malware. The alerts generated by signature based technique and anomaly detection from all the VMs are analyzed to check an

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Topic Models for Re-Id from Curbed Video Tracess based on re-identification perspective. Several experiments were carried-out on well-known public re-identification datasets, and the superiority of the proposed novel re-identification technique is proved with the rigorous analysis on these datasets.