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Comparison between RSA and CAST-128 with Adaptive Key for Video Frames Encryption with Highest Average Entropy
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Encryption of data is translating data to another shape or symbol which enables people only with an access to the secret key or a password that can read it. The data which are encrypted are generally referred to as cipher text, while data which are unencrypted are known plain text. Entropy can be used as a measure which gives the number of bits that are needed for coding the data of an image. As the values of pixel within an image are dispensed through further gray-levels, the entropy increases. The aim of this research is to compare between CAST-128 with proposed adaptive key and RSA encryption methods for video frames to determine the more accurate method with highest entropy. The first method is achieved by applying the "CAST-128" and the second is achieved by applying the "RSA ". CAST-128 utilizes a pair of sub-keys for each round as a quantum of  five bits that was utilized as a key of rotation for each round and a quantum of 32 (bits) was utilized as a key of masking into a round . The proposed adaptive 128-bits key can be extracted from the main diagonal of each frame before encryption. RSA is a public-key cryptographic technique which can be known as (asymmetric) cryptography. An asymmetry of a key depends on factoring a product of two big prime values. A comparison was applied on several videos and the results showed that CAST-128 method proved the highest degree of entropy even if the frames have lots of distorted data or unclear image pixels. For example, the entropy value of a sample of a girl video is 2581.921 when using CAST-128, while it is 2271.329 when using the RSA; also the entropy value of a sample of a scooter video is 2569.814 when using the CAST-128, while it is 2282.844 when using RSA.

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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Science
A Class of Harmonic Multivalent Functions for Higher Derivatives Associated with General Linear Operator
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    The main goal of this paper is to introduce the higher derivatives multivalent harmonic function class, which is defined by the general linear operator. As a result, geometric properties such as coefficient estimation, convex combination, extreme point, distortion theorem and convolution property are obtained. Finally, we show that this class is invariant under the Bernandi-Libera-Livingston integral for harmonic functions.

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Publication Date
Tue Jan 14 2025
Journal Name
South Eastern European Journal Of Public Health
Deep learning-based threat Intelligence system for IoT Network in Compliance With IEEE Standard
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The continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre

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Publication Date
Mon Aug 04 2014
Journal Name
Iraqi National Journal Of Chemistry
Comparative Study for Antibacterial Activity of Some Maleamic acid Derivatives with Some Commercial Antibiotic
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Publication Date
Wed Mar 10 2021
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
A hybrid Grey Wolf optimizer with multi-population differential evolution for global optimization problems
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Publication Date
Fri Jan 01 2016
Journal Name
Statistics And Its Interface
Search for risk haplotype segments with GWAS data by use of finite mixture models
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The region-based association analysis has been proposed to capture the collective behavior of sets of variants by testing the association of each set instead of individual variants with the disease. Such an analysis typically involves a list of unphased multiple-locus genotypes with potentially sparse frequencies in cases and controls. To tackle the problem of the sparse distribution, a two-stage approach was proposed in literature: In the first stage, haplotypes are computationally inferred from genotypes, followed by a haplotype coclassification. In the second stage, the association analysis is performed on the inferred haplotype groups. If a haplotype is unevenly distributed between the case and control samples, this haplotype is labeled

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Publication Date
Tue Jun 10 2025
Journal Name
Steel And Composite Structures
Flexural behaviour of prefabricated demountable composite beams with LockBolt shear connectors for accelerated construction
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To promote sustainable steel-concrete composite structures, it is essential to develop special shear connectors that facilitate accelerated construction and deconstruction. A lockbolt demountable shear connector (LBDSC) was recently proposed. While the LBDSC has been evaluated using horizontal and vertical (standard) push-out tests, it is essential to further assess the disassembly mechanism and the positive flexural performance of prefabricated demountable composite beams (PDCBs) under both serviceability and ultimate limit states. Two full-scale test specimens of PDCBs with LBDSC were designed with partial shear connections and assessed using a three or four-point load beam setup under both cyclic and static monotonic loading conditions.

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Publication Date
Thu Oct 31 2019
Journal Name
Journal Of Theoretical And Applied Information Technology
AN ENHANCED EVOLUTIONARY ALGORITHM WITH LOCAL HEURISTIC APPROACH FOR DETECTING COMMUNITY IN COMPLEX NETWORKS
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Publication Date
Mon Apr 03 2023
Journal Name
International Journal Of Online And Biomedical Engineering (ijoe)
An Integrated Grasshopper Optimization Algorithm with Artificial Neural Network for Trusted Nodes Classification Problem
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Wireless Body Area Network (WBAN) is a tool that improves real-time patient health observation in hospitals, asylums, especially at home. WBAN has grown popularity in recent years due to its critical role and vast range of medical applications. Due to the sensitive nature of the patient information being transmitted through the WBAN network, security is of paramount importance. To guarantee the safe movement of data between sensor nodes and various WBAN networks, a high level of security is required in a WBAN network. This research introduces a novel technique named Integrated Grasshopper Optimization Algorithm with Artificial Neural Network (IGO-ANN) for distinguishing between trusted nodes in WBAN networks by means of a classifica

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Publication Date
Thu May 18 2023
Journal Name
Journal Of Engineering
Genetic Algorithm Optimization Model for Central Marches Restoration Flows with Different Water Quality Scenarios
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A Genetic Algorithm optimization model is used in this study to find the optimum flow values of the Tigris river branches near Ammara city, which their water is to be used for central marshes restoration after mixing in Maissan River. These tributaries are Al-Areed, AlBittera and Al-Majar Al-Kabeer Rivers. The aim of this model is to enhance the water quality in Maissan River, hence provide acceptable water quality for marsh restoration. The model is applied for different water quality change scenarios ,i.e. , 10%,20% increase in EC,TDS and BOD. The model output are the optimum flow values for the three rivers while, the input data are monthly flows(1994-2011),monthly water requirements and water quality parameters (EC, TDS, BOD, DO and

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Publication Date
Tue Mar 26 2024
Journal Name
World Electric Vehicle Journal
Fast Finite-Time Composite Controller for Vehicle Steer-by-Wire Systems with Communication Delays
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The modern steer-by-wire (SBW) systems represent a revolutionary departure from traditional automotive designs, replacing mechanical linkages with electronic control mechanisms. However, the integration of such cutting-edge technologies is not without its challenges, and one critical aspect that demands thorough consideration is the presence of nonlinear dynamics and communication network time delays. Therefore, to handle the tracking error caused by the challenge of time delays and to overcome the parameter uncertainties and external perturbations, a robust fast finite-time composite controller (FFTCC) is proposed for improving the performance and safety of the SBW systems in the present article. By lumping the uncertainties, parameter var

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