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Enhancing Cloud Security Implementing AI-Based Intrusion Detection Systems
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The increasing complexity of assaults necessitates the use of innovative intrusion detection systems (IDS) to safeguard critical assets and data. There is a higher risk of cyberattacks like data breaches and unauthorised access since cloud services have been used more frequently. The project's goal is to find out how Artificial Intelligence (AI) could enhance the IDS's ability to identify and classify network traffic and identify anomalous activities. Online dangers could be identified with IDS. An intrusion detection system, or IDS, is required to keep networks secure. We must create efficient IDS for the cloud platform as well, since it is constantly growing and permeating more aspects of our daily life. However, using standard intrusion detection systems in the cloud may provide challenges. The pre-established IDS design may overburden a cloud segment due to the additional detection overhead. Within the framework of an adaptively designed networked system. We demonstrate how to fully use available resources without placing undue load on any one cloud server using an intrusion detection system (IDS) based on neural networks. To even more successfully detect new threats, the suggested IDS make use of neural network machine learning (ML).

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Publication Date
Wed Mar 25 2020
Journal Name
International Journal Of Drug Delivery Technology
Detection of Single Nucleotide Polymorphisms (SNPs) for Genes Cause Drug-Resistant in Iraqi Mycobacterium Tuberculosis isolates by new Pyrophosphate Technique.
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In this search, a new pyrophosphate technique was proved. The technique was employed to single- nucleotide polymorphisms (SNPs), which diagnosis using a one-base extension reaction. Three Mycobacterium tuberculosis genes were chosen (Rpob, InhA, KatG) genes. Fifty-four specimens were used in this study fifty-three proved as drug-resistant specimens by The Iraqi Institute of Chest and Respiratory Diseases in Baghdad.; also one specimen was used as a negative control. The steps of this technique were by used a specific primer within each aliquot that has a short 3-OH end of the base of the target gene that was hybridized to the single-stranded DNA template. Then, the Taq polymerase enzyme and one of either α-thio-dATP, dTTP, dGTP, or dCTP

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Publication Date
Tue Nov 01 2022
Journal Name
Journal Of Photochemistry And Photobiology B: Biology
High efficiency of Ag0 decorated Cu2MoO4 nanoparticles for heterogeneous photocatalytic activation, bactericidal system, and detection of glucose from blood sample
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Publication Date
Thu Jan 07 2021
Journal Name
Indian Journal Of Forensic Medicine & Toxicology
Assessment of Employees’ Knowledge Concerning Contributing Factors and Early Detection for Prostate Cancer in Baghdad University Colleges in bab-Almudam
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Publication Date
Fri Oct 24 2025
Journal Name
Chemical Papers
Development of an advanced flow injection method using curcumin nanoparticle fluorescence for sensitive detection of cobalt (II) and nitrite ions
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Publication Date
Mon Dec 31 2018
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Detection of Thiopurine S-Methyltransferase (TPMT) Polymorphisms TPMT*3A, TPMT*3B and TPMT*3C in Children with Acute Lymphoblastic Leukemia
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Publication Date
Fri Mar 31 2017
Journal Name
Al-khwarizmi Engineering Journal
Design of Nonlinear PID Neural Controller for the Speed Control of a Permanent Magnet DC Motor Model based on Optimization Algorithm
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In this paper, the speed control of the real DC motor is experimentally investigated using nonlinear PID neural network controller. As a simple and fast tuning algorithm, two optimization techniques are used; trial and error method and particle swarm optimization PSO algorithm in order to tune the nonlinear PID neural controller's parameters and to find best speed response of the DC motor. To save time in the real system, a Matlab simulation package is used to carry out these algorithms to tune and find the best values of the nonlinear PID parameters. Then these parameters are used in the designed real time nonlinear PID controller system based on LabVIEW package. Simulation and experimental results are compared with each other and showe

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Publication Date
Mon Jan 01 2018
Journal Name
Matec Web Of Conferences
Carbon-13 Characterization and Modelling for Temperature Measurement-Based Proton Frequency
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The physical substance at high energy level with specific circumstances; tend to behave harsh and complicated, meanwhile, sustaining equilibrium or non-equilibrium thermodynamic of the system. Measurement of the temperature by ordinary techniques in these cases is not applicable at all. Likewise, there is a need to apply mathematical models in numerous critical applications to measure the temperature accurately at an atomic level of the matter. Those mathematical models follow statistical rules with different distribution approaches of quantities energy of the system. However, these approaches have functional effects at microscopic and macroscopic levels of that system. Therefore, this research study represents an innovative of a wi

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Preparing a New Type of Concrete Based on Sulfur-melamine Modifier
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In this research work, a new type of concrete based on sulfur-melamine modification was introduced, and its various properties were studied. This new type of concrete was prepared based on the sulfur-melamine modification and various ingredients. The new sulfur-melamine modifier was fabricated, and its fabrication was confirmed by IR spectroscopy and TG analysis. The surface morphology resulted from this modifier was studied by SEM and EDS analysis. The components ratios in concrete, chemical and physical characteristics resulted from sulfur-melamine modifier, chemical and corrosion resistance of concrete, stability of concrete against water adsorption, stability of concrete against freezing, physical and mechanical properties and durabi

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Publication Date
Tue Feb 01 2022
Journal Name
Int. J. Nonlinear Anal. Appl.
Finger Vein Recognition Based on PCA and Fusion Convolutional Neural Network
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Finger vein recognition and user identification is a relatively recent biometric recognition technology with a broad variety of applications, and biometric authentication is extensively employed in the information age. As one of the most essential authentication technologies available today, finger vein recognition captures our attention owing to its high level of security, dependability, and track record of performance. Embedded convolutional neural networks are based on the early or intermediate fusing of input. In early fusion, pictures are categorized according to their location in the input space. In this study, we employ a highly optimized network and late fusion rather than early fusion to create a Fusion convolutional neural network

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Publication Date
Tue Jan 01 2019
Journal Name
Ieee Access
Speech Enhancement Algorithm Based on Super-Gaussian Modeling and Orthogonal Polynomials
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