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Cloud Data Security through BB84 Protocol and Genetic Algorithm
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In the current digitalized world, cloud computing becomes a feasible solution for the virtualization of cloud computing resources.  Though cloud computing has many advantages to outsourcing an organization’s information, but the strong security is the main aspect of cloud computing. Identity authentication theft becomes a vital part of the protection of cloud computing data. In this process, the intruders violate the security protocols and perform attacks on the organizations or user’s data. The situation of cloud data disclosure leads to the cloud user feeling insecure while using the cloud platform. The different traditional cryptographic techniques are not able to stop such kinds of attacks. BB84 protocol is the first quantum cryptography protocol developed by Bennett and Brassard in the year 1984. In the present work, three ways BB84GA security systems have been demonstrated using trusted cryptographic techniques like an attribute-based authentication system, BB84 protocol, and genetic algorithm. Firstly, attribute-based authentication is used for identity-based access control and thereafter BB84 protocol is used for quantum key distribution between both parties and later the concept of genetic algorithm is applied for encryption/decryption of sensitive information across the private/public clouds. The proposed concept of involvement of hybrid algorithms is highly secure and technologically feasible. It is a unique algorithm which may be used to minimize the security threats over the clouds. The computed results are presented in the form of tables and graphs.

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Publication Date
Tue Mar 01 2022
Journal Name
Results In Engineering
Predictive model for stress at ultimate in internally unbonded steel tendons based on genetic expression programming
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Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Engineering Science And Technology
Gamipog: A deterministic genetic multi-parameter-order strategy for the generation of variabLE STRENGTH COVERING ARRAYS
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Publication Date
Mon Jun 30 2025
Journal Name
Medical Journal Of Babylon
Assessment of Six Polymorphic Variants as Genetic Risks for Coronary Artery Disease: A Case–Control Study
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Abstract<sec> <title>Background:

Coronary artery disease (CAD) is the leading cause of death worldwide. Certain genetic polymorphisms play an important role in this multifactorial disease, being linked with increased risk of early onset CAD.

Objective:

To assess six genetic polymorphisms and clinical risk factors in relation to early onset nondiabetic Iraqi Arab CAD patients compared to controls.

Materials and Methods:

This case–contro

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Publication Date
Sun Apr 30 2023
Journal Name
Sabrao Journal Of Breeding And Genetics
STUDY OF THE GENETIC DIVERSITY OF SOME GENOTYPES OF MAIZE UNDER TWO LEVELS OF NITROGEN FERTILIZATION
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The present study aimed to determine the genetic divergence of seven maize genotypes (Al-Maha, Sumer, Al-Fajr, Baghdad, 5018, 4 × 1 single hybrid, and 4 × 2 single hybrid) under two varied levels of nitrogen fertilization (92 and 276 kg N ha-1). The experiment occurred in 2022 in a randomized complete block design (RCBD) with a split-plot arrangement and three replications at the College of Agricultural Engineering Sciences, University of Baghdad, Iraq. The nitrogen fertilization levels served as main plots, with the maize genotypes allocated as the subplots. The results revealed that genetic variance was higher than the environmental variance for most traits, and the coefficient of phenotypic variation was close to the genetic va

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Publication Date
Sun Jun 07 2009
Journal Name
Baghdad Science Journal
Use of DAF markers (DNA Amplification Fingerprint) to Assess Genetic Diversity of Rice (Oryza satival L.)
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This study was carried out to assess genetic diversity of ten cultivars of Rice (Oryza sativa L.). One of DNA markers based on Polymerase Chain Reaction (PCR) was used namely DAF markers (DNA Amplification Fingerprint). Six primers were tested, the results showed, that no amplification products using the primers OPD.14 and OPM.5. Two primers (OPX.8 and OPT.2) produced monomorphic band across all cultivars, while only two primers generated polymorphic bands. The number of total bands produced from one of them (OPN.7) were sixteen. Also this primer produced ten polymorphic profiles (DAF patterns) which were unique to the ten cultivars that could be distinguished. The number of total bands generated by primer OPX.1 were thirteen and this prim

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
An Improved Cuckoo Search Algorithm for Maximizing the Coverage Range of Wireless Sensor Networks
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The issue of increasing the range covered by a wireless sensor network with restricted sensors is addressed utilizing improved CS employing the PSO algorithm and opposition-based learning (ICS-PSO-OBL). At first, the iteration is carried out by updating the old solution dimension by dimension to achieve independent updating across the dimensions in the high-dimensional optimization problem. The PSO operator is then incorporated to lessen the preference random walk stage's imbalance between exploration and exploitation ability. Exceptional individuals are selected from the population using OBL to boost the chance of finding the optimal solution based on the fitness value. The ICS-PSO-OBL is used to maximize coverage in WSN by converting r

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Publication Date
Thu Dec 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
Dynamic algorithm (DRBLTS) and potentially weighted (WBP) to estimate hippocampal regression parameters using a techniqueBootstrap (comparative study)
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Bootstrap is one of an important re-sampling technique which has given the attention of  researches recently. The presence of outliers in the original data set may cause serious problem to the classical bootstrap when the percentage of outliers are higher than the original one. Many methods are proposed to overcome this problem such  Dynamic Robust Bootstrap for LTS (DRBLTS) and Weighted Bootstrap with Probability (WBP). This paper try to show the accuracy of parameters estimation by comparison the results of both methods. The bias , MSE and RMSE are considered. The criterion of the accuracy is based on the RMSE value since the method that provide us RMSE value smaller than other is con

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Publication Date
Thu May 30 2024
Journal Name
Iraqi Journal Of Science
An Evolutionary Algorithm for Improving the Quantity and Quality of the Detected Complexes from Protein Interaction Networks
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One of the recent significant but challenging research studies in computational biology and bioinformatics is to unveil protein complexes from protein-protein interaction networks (PPINs). However, the development of a reliable algorithm to detect more complexes with high quality is still ongoing in many studies. The main contribution of this paper is to improve the effectiveness of the well-known modularity density ( ) model when used as a single objective optimization function in the framework of the canonical evolutionary algorithm (EA). To this end, the design of the EA is modified with a gene ontology-based mutation operator, where the aim is to make a positive collaboration between the modularity density model and the proposed

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Digital Image Authentication Algorithm Based on Fragile Invisible Watermark and MD-5 Function in the DWT Domain
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Using watermarking techniques and digital signatures can better solve the problems of digital images transmitted on the Internet like forgery, tampering, altering, etc. In this paper we proposed invisible fragile watermark and MD-5 based algorithm for digital image authenticating and tampers detecting in the Discrete Wavelet Transform DWT domain. The digital image is decomposed using 2-level DWT and the middle and high frequency sub-bands are used for watermark and digital signature embedding. The authentication data are embedded in number of the coefficients of these sub-bands according to the adaptive threshold based on the watermark length and the coefficients of each DWT level. These sub-bands are used because they a

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Publication Date
Mon Jul 11 2022
Journal Name
International Journal Of Online And Biomedical Engineering (ijoe)
Dynamic Background Subtraction in Video Surveillance Using Color-Histogram and Fuzzy C-Means Algorithm with Cosine Similarity
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The background subtraction is a leading technique adopted for detecting the moving objects in video surveillance systems. Various background subtraction models have been applied to tackle different challenges in many surveillance environments. In this paper, we propose a model of pixel-based color-histogram and Fuzzy C-means (FCM) to obtain the background model using cosine similarity (CS) to measure the closeness between the current pixel and the background model and eventually determine the background and foreground pixel according to a tuned threshold. The performance of this model is benchmarked on CDnet2014 dynamic scenes dataset using statistical metrics. The results show a better performance against the state-of the art

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