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Enhancement of the CAST Block Algorithm Based on Novel S-Box for Image Encryption
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Background and Aim: due to the rapid growth of data communication and multimedia system applications, security becomes a critical issue in the communication and storage of images. This study aims to improve encryption and decryption for various types of images by decreasing time consumption and strengthening security. Methodology: An algorithm is proposed for encrypting images based on the Carlisle Adams and Stafford Tavares CAST block cipher algorithm with 3D and 2D logistic maps. A chaotic function that increases the randomness in the encrypted data and images, thereby breaking the relation sequence through the encryption procedure, is introduced. The time is decreased by using three secure and private S-Boxes rather than using six S-Boxes, as in the traditional method. Moreover, the CAST encryption algorithm was modified to be used on the private keys and substitution stage (S-Boxes), with the keys and S-Boxes of the encryption algorithm being generated according to the 2D and 3D chaotic map functions. The proposed system passed all evaluation criteria, including (MSE, PSNR, EQ, MD, SC, NC, AD, SNR, SIM, MAE, Time, CC, Entropy, and histograms). Results: Moreover, the results also illustrate that the created S-Boxes passed all evaluation criteria; compared with the results of the traditional method that was used in creating S-Box, the proposed method achieved better results than other methods used in the other works. The proposed solution improves the entropy which is between (7.991–7.999), reduces the processing time which is between (0.5–11 s/Images), and improves NCPR, which is between (0.991–1). Conclusions: The proposed solution focuses on reducing the total processing time for encryption and decryption and improving transmission security. Finally, this solution provides a fast security system for surgical telepresence with secure real-time communication. The complexity of this work needs to know the S-Box creation method used, the chaotic method, the values of the chaotic parameters, and which of these methods was used in the encryption process.

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Publication Date
Sat Sep 27 2025
Journal Name
Journal Of College Of Law For Legal And Political Sciences
Management's responsibility for breach of investment administrative contracts
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Publication Date
Fri Jul 01 2016
Journal Name
Al–bahith Al–a'alami
The Discourse of the Absent Woman Novel for Mahdi Issa Al-Saqr
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The semiotic trend of recent monetary trends task that took a wide range of attention of critics and readers alike, especially after the deployment, which accompanied him after widespread acts critic Grimas and powers applicable to the literary texts and is thus expanded its care circle, hence the choice of the novel (absent) woman Iraqi novelist (Mahdi ‘Issa falcon) model to be applied to the study chose to be a semiotic approach through the use of procedural mechanisms for its critical tool (Paris School of semiotics), cash and views of its founder critic Grimas.The research in the introduction and pave came we made it a vision for literary semiotic and its impact trend in cash and cash is and what it desire to clarify some poked suc

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Publication Date
Sat Mar 31 2018
Journal Name
Journal Of Engineering
Effect of Using Extra Fins on the Pin Fin Classic Geometry for Enhancement Heat Sink Performance using EGM Method
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In the present study, the effect of new cross-section fin geometries on overall thermal/fluid performance had been investigated. The cross-section included the base original geometry of (triangular, square, circular, and elliptical pin fins) by adding exterior extra fins along the sides of the origin fins. The present extra fins include rectangular extra fin of 2 mm (height) and 4 mm (width) and triangular extra fin of 2 mm (base) 4 mm (height). The use of entropy generation minimization method (EGM) allows the combined effect of thermal resistance and pressure drop to be assessed through the simultaneous interaction with the heat sink. A general dimensionless expression for the entropy generation rate is obtained by con

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Publication Date
Thu Mar 30 2006
Journal Name
College Of Islamic Sciences
The novel of the innovator and its impact on the differences of jurists
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Praise be to God, Lord of the worlds, and prayers and peace be upon our master and beloved Muhammad, the wise guide and great teacher, the guide to a straight path, the one sent as a mercy to the worlds, and upon his good and chosen family, his chosen companions, the working scholars, and those who follow them in righteousness until the Day of Judgment.

And after:

One of the important controversial topics shared between the sciences of the Noble Hadith and the Fundamentals of God is the issue of the innovator in terms of accepting and rejecting his narration and testimony, and the difference in it leads to disagreement in many branches of jurisprudence that were based on texts narrated by innovated narrators or those accu

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Publication Date
Thu Aug 31 2023
Journal Name
Journal Of Kufa For Mathematics And Computer
Four Points Block Method with Second Derivative for Solving First Order Ordinary Differential Equations
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Publication Date
Mon Jun 01 2020
Journal Name
Life Sciences
Synthesis, characterization and anticancer activity in vitro evaluation of novel dicyanoaurate (I)-based complexes
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Publication Date
Fri Apr 30 2010
Journal Name
Journal Of Applied Computer Science & Mathematics
Image Hiding Using Magnitude Modulation on the DCT Coefficients
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In this paper, we introduce a DCT based steganographic method for gray scale images. The embedding approach is designed to reach efficient tradeoff among the three conflicting goals; maximizing the amount of hidden message, minimizing distortion between the cover image and stego-image,and maximizing the robustness of embedding. The main idea of the method is to create a safe embedding area in the middle and high frequency region of the DCT domain using a magnitude modulation technique. The magnitude modulation is applied using uniform quantization with magnitude Adder/Subtractor modules. The conducted test results indicated that the proposed method satisfy high capacity, high preservation of perceptual and statistical properties of the steg

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Publication Date
Tue Jul 09 2024
Journal Name
Diagnostics
A Novel Hybrid Machine Learning-Based System Using Deep Learning Techniques and Meta-Heuristic Algorithms for Various Medical Datatypes Classification
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Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea

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Publication Date
Sun Jun 01 2008
Journal Name
2008 Ieee International Joint Conference On Neural Networks (ieee World Congress On Computational Intelligence)
Linear block code decoder using neural network
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Publication Date
Sun Jan 01 2017
Journal Name
Australian Journal Of Basic And Applied Sciences
Proposed Algorithm for Gumbel Distribution Estimation
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Gumbel distribution was dealt with great care by researchers and statisticians. There are traditional methods to estimate two parameters of Gumbel distribution known as Maximum Likelihood, the Method of Moments and recently the method of re-sampling called (Jackknife). However, these methods suffer from some mathematical difficulties in solving them analytically. Accordingly, there are other non-traditional methods, like the principle of the nearest neighbors, used in computer science especially, artificial intelligence algorithms, including the genetic algorithm, the artificial neural network algorithm, and others that may to be classified as meta-heuristic methods. Moreover, this principle of nearest neighbors has useful statistical featu

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