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Home / programming language / Online Dotnet Projects / A novel image steganography scheme with high embedding capacity and tunable visual image quality based on a genetic algorithm
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Dotnet Project - Networking, Final Year Project
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A novel image steganography scheme with high embedding capacity and tunable visual image quality based on a genetic algorithm

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SKU: PROJ7866 Categories: 2017 Projects, Networking Projects, Online Dotnet Projects Tags: Android Project, Asp.Net Project, C# Project, Computer Engineering Final Year Projects, Computer Science Final Year Projects, Electronics Projects Engineering Students Final Year, Engineering Student Project Ideas, Final Semester Projects, Final Year Project Center, Final Year Projects, ieee ECE Projects, ieee EEE Projects, ieee Final Year Projects, IEEE Projects, ieee Projects Networking, Image Processing Projects, J2EE Project, Java Project, Java Project Code, Matlab Project, PHP Project, Students Projects
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A novel image steganography scheme with high embedding capacity and tunable visual image quality based on a genetic algorithm

Abstract—AbstractIn power system, minimizing the power loss in the transmission lines and/or minimizing the voltage deviation at the load buses by controlling the reactive power is referred as optimal reactive power dispatch (ORPD). This paper presents an improved evolutionary algorithm based on oppositional krill herd algorithm (OKHA) for obtaining optimal steady-state performance of power systems. This article also proposes the effect of UPFC location in steady-state analysis and to demonstrate the capabilities of UPFC in controlling active and reactive power flow within any electrical network. To verify the effectiveness of KHA and OKHA, two different single objective functions such as minimization of real power losses and improvement of voltage profile and a multi-objective function that simultaneously minimizes transmission loss and voltage deviation have been studied through standard IEEE 57-bus and 118-bus test systems and their results have been reported. The study results show that the proposed KHA and OKHA approaches are feasible and efficient.

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