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Encryption of Medical Image Based on Cascaded Design of AES Block Algorithm and Chaotic Map
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Security concerns in the transfer of medical images have drawn a lot of attention to the topic of medical picture encryption as of late. Furthermore, recent events have brought attention to the fact that medical photographs are constantly being produced and circulated online, necessitating safeguards against their inappropriate use. To improve the design of the AES algorithm standard for medical picture encryption, this research presents several new criteria. It was created so that needs for higher levels of safety and higher levels of performance could be met. First, the pixels in the image are diffused to randomly mix them up and disperse them all over the screen. Rather than using rounds, the suggested technique utilizes a cascaded-looking composition of F-functions in a quadrate architecture. The proposed F-function architecture is a three-input, three-output Type-3 AES-Feistel network with additional integer parameters representing the subkeys in use. The suggested system makes use of the AES block cipher as a function on a Type-3 AES-Feistel network. Blocks in the proposed system are 896 bits in length, whereas keys are 128 bits. The production of subkeys is encrypted using a chain of E8- algorithms. The necessary subkeys are then generated with a recursion. The results are reviewed to verify that the new layout improves the security of the AES block cipher when used to encrypt medical images in a computer system.

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Publication Date
Sun Jan 01 2023
Journal Name
Ieee Access
Fuzzy-Based Ensemble Feature Selection for Automated Estimation of Speaker Height and Age Using Vocal Characteristics
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Publication Date
Thu Dec 01 2022
Journal Name
Case Studies In Construction Materials
Push-out test of waste sawdust-based steel-concrete – Steel composite sections: Experimental and environmental study
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Publication Date
Thu Dec 01 2022
Journal Name
Case Studies In Construction Materials
Push-out test of waste sawdust-based steel-concrete – Steel composite sections: Experimental and environmental study
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Publication Date
Fri Jan 01 2016
Journal Name
8th Conference On Power Electronics, Machines And Drives (pemd), Glasgow, Uk
Design of tubular moving magnet linear alternator for use with an external combustion - free piston engine
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Publication Date
Sun Sep 15 2019
Journal Name
Al-academy
The Effectiveness of the Virtual Design Environment in Digital Advertising: بتول راضي كاظم-ابراهيم حمدان سبتي
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   Advertising design is one of the arts of communication of various levels and one of the aspects of the fields of design arts, and that the construction of the design environment in the advertising is one of the important entry points in making the recipient feel this environment and feel as if being one of its elements. It is an entrance worthy of study and research and is a problem worth raising according to the following question: - What is the effectiveness achieved in the virtual design environment for digital advertising? The two  researchers dealt with the research in three frameworks, the methodological framework which identified (the problem of research, its importance, purpose, limits, and the definition of ter

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Publication Date
Wed Apr 01 2020
Journal Name
Isa Transactions
Design of a Complex fractional Order PID controller for a First Order Plus Time Delay system
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Publication Date
Mon Dec 01 2025
Journal Name
Applied Thermal Engineering
Efficient thermal management of PVT systems via water-PCM hybridization: New design with optimized geometrical configuration
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Publication Date
Wed Oct 11 2023
Journal Name
Journal Of Educational And Psychological Researches
Designing a Proposed Educational Program Based on Augmented Reality Technology and Measuring Its Effectiveness in Developing the Skills of Research and Historical Imagination Among Students of the Humanities Track in The Secondary Stage in the City of Mak
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The current study aims to develop a proposed educational program based on augmented reality (AR) technology, in addition to assessing its effectiveness in developing research and historical imagination skills of the Humanities Track's female students at the secondary stage, as well as assessing the correlative and predictive relationships between the amount of growth for the two dependent variables. To achieve this, a secondary school in the city of Makkah Al-Mukarramah was chosen, and an available random sample of (30) female students from the study population was selected. The quasi-experimental approach was followed by this study, particularly one group design. In addition, two tools were used to collect study data, namely: a test of

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Publication Date
Fri Jan 01 2021
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
BotDetectorFW: an optimized botnet detection framework based on five features-distance measures supported by comparisons of four machine learning classifiers using CICIDS2017 dataset
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<p><span>A Botnet is one of many attacks that can execute malicious tasks and develop continuously. Therefore, current research introduces a comparison framework, called BotDetectorFW, with classification and complexity improvements for the detection of Botnet attack using CICIDS2017 dataset. It is a free online dataset consist of several attacks with high-dimensions features. The process of feature selection is a significant step to obtain the least features by eliminating irrelated features and consequently reduces the detection time. This process implemented inside BotDetectorFW using two steps; data clustering and five distance measure formulas (cosine, dice, driver &amp; kroeber, overlap, and pearson correlation

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Publication Date
Sat Apr 30 2022
Journal Name
Revue D'intelligence Artificielle
Performance Evaluation of SDN DDoS Attack Detection and Mitigation Based Random Forest and K-Nearest Neighbors Machine Learning Algorithms
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

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