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Efficient Intrusion Detection Through the Fusion of AI Algorithms and Feature Selection Methods
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With the proliferation of both Internet access and data traffic, recent breaches have brought into sharp focus the need for Network Intrusion Detection Systems (NIDS) to protect networks from more complex cyberattacks. To differentiate between normal network processes and possible attacks, Intrusion Detection Systems (IDS) often employ pattern recognition and data mining techniques. Network and host system intrusions, assaults, and policy violations can be automatically detected and classified by an Intrusion Detection System (IDS). Using Python Scikit-Learn the results of this study show that Machine Learning (ML) techniques like Decision Tree (DT), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) can enhance the effectiveness of an Intrusion Detection System (IDS). Success is measured by a variety of metrics, including accuracy, precision, recall, F1-Score, and execution time. Applying feature selection approaches such as Analysis of Variance (ANOVA), Mutual Information (MI), and Chi-Square (Ch-2) reduced execution time, increased detection efficiency and accuracy, and boosted overall performance. All classifiers achieve the greatest performance with 99.99% accuracy and the shortest computation time of 0.0089 seconds while using ANOVA with 10% of features.

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Publication Date
Mon Apr 23 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Comparison of Features Extraction Algorithms Used in the Diagnosis of Plant Diseases
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      The detection of diseases affecting plant is very important as it relates to the issue of food security, which is a very serious threat to human life. The system of diagnosis of diseases involves a series of steps starting with the acquisition of images through the pre-processing, segmentation and then features extraction that is our subject finally the process of classification. Features extraction is a very important process in any diagnostic system where we can compare this stage to the spine in this type of system. It is known that the reason behind this great importance of this stage is that the process of extracting features greatly affects the work and accuracy of classification. Proper selection of

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Publication Date
Sun Jan 22 2023
Journal Name
Mesopotamian Journal Of Big Data
Parallel Machine Learning Algorithms
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 To expedite the learning process, a group of algorithms known as parallel machine learning algorithmscan be executed simultaneously on several computers or processors. As data grows in both size andcomplexity, and as businesses seek efficient ways to mine that data for insights, algorithms like thesewill become increasingly crucial. Data parallelism, model parallelism, and hybrid techniques are justsome of the methods described in this article for speeding up machine learning algorithms. We alsocover the benefits and threats associated with parallel machine learning, such as data splitting,communication, and scalability. We compare how well various methods perform on a variety ofmachine learning tasks and datasets, and we talk abo

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Publication Date
Tue Jan 01 2019
Journal Name
Technologies And Materials For Renewable Energy, Environment And Sustainability: Tmrees19gr
Improve studies and calculations for the Bose-Einstein condensation D-D fusion reaction rate
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A theoretical study including the effects of the fusion characteristics parameters on the fundamental fusion rate for the BEC state in D-D fusion reaction is deal with varieties physical parameters such as the fuels density, fuel temperature and the astrophysics S-factor are processed to bring an approximately a comparable results to agree with the others previously studies.

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Publication Date
Fri Mar 04 2022
Journal Name
Baghdad Science Journal
Fusion Reaction Study of some Selected Halo Systems
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The challenge in studying fusion reaction when the projectile is neutron or proton rich halo nuclei is the coupling mechanism between the elastic and the breakup channel, therefore the motivation from the present calculations is to estimate the best coupling parameter to introduce the effect of coupled-channels for the calculations of the total cross section of the fusion , the barrier distribution of the fusion and the average angular momentum ⟨L⟩ for the systems 6He+206Pb, 8B+28Si, 11Be+209Bi, 17F+208Pb, 6He+238U, 8He+197Au and 15C+232Th using quantum mechanical approach. A quantum Coupled-Channel Calculations are performed using CC code. The predictions of quantum mechanical approach are comparable with the measured data that is

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Publication Date
Sat Apr 01 2023
Journal Name
Baghdad Science Journal
Fusion Reaction Study of some Selected Halo Systems
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The challenge in studying fusion reaction when the projectile is neutron or proton rich halo nuclei is the coupling mechanism between the elastic and the breakup channel, therefore the motivation from the present calculations is to estimate the best coupling parameter to introduce the effect of coupled-channels for the calculations of the total cross section of the fusion  , the barrier distribution of the fusion   and the average angular momentum ⟨L⟩ for the systems 6He+206Pb, 8B+28Si, 11Be+209Bi, 17F+208Pb, 6He+238U, 8He+197Au and 15C+232Th using quantum mechanical approach.  A

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Publication Date
Mon May 06 2024
Journal Name
Journal Of Ecological Engineering
Using Machine Learning Algorithms to Predict the Sweetness of Bananas at Different Drying Times
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The consumption of dried bananas has increased because they contain essential nutrients. In order to preserve bananas for a longer period, a drying process is carried out, which makes them a light snack that does not spoil quickly. On the other hand, machine learning algorithms can be used to predict the sweetness of dried bananas. The article aimed to study the effect of different drying times (6, 8, and 10 hours) using an air dryer on some physical and chemical characteristics of bananas, including CIE-L*a*b, water content, carbohydrates, and sweetness. Also predicting the sweetness of dried bananas based on the CIE-L*a*b ratios using machine learn- ing algorithms RF, SVM, LDA, KNN, and CART. The results showed that increasing the drying

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Publication Date
Tue Dec 26 2017
Journal Name
Al-khwarizmi Engineering Journal
Determination of Welding Velocity and Arc Energy for Fusion MAG Welding Joint
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 Abstract

This paper is an experimental work to determinate the effect of welding velocity and formed arc energy for CO2-MAG fusion weld pool. The input parameters (arc voltage, wire feed speed and gas flow rate) were investigated to find their effects on the weld joint efficiency. Design of experiment with response surface methodology technique was used to build empirical mathematical models for welding velocity and arc energy in term of the input welding parameters. The predicted quadratic models were statistically checked for adequacy purpose by ANOVA analysis. Additionally, numerical optimization was conducted to obtain the optimum values for welding velocity and arc energy. A good agree

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Publication Date
Wed Jan 01 2020
Journal Name
Solid State Technology
Image Fusion Using A Convolutional Neural Network
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Image Fusion Using A Convolutional Neural Network

Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
Silver Nanoparticles and their Role in Gene Expression of Motility Gene motB and Repression of AI-2-Controlled Gene
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Antibiotic resistance is the capability of the strains to resist or protect themselves from the effects of an antibiotic. Such a resistance towards the current antimicrobials leads to the search of novel antimicrobials. Nanotechnology has been promising in different field of science and among it is the use of nanoparticles as antibacterial agents. The gastrointestinal tract seems to be the primary reservoir of uropathogenic E.coli (UPEC) in humans. UPEC strains harbour the urinary tract and cause urinary tract infection. They cause serious ailments in terms of humans. They develop resistance and increase their virulence by forming biofilms. They also show a remarkable locomotory movement with the aid of autoinducer controlled ge

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Publication Date
Tue Jun 22 2021
Journal Name
Expert Systems
Hybrid intelligent technology for plant health using the fusion of evolutionary optimization and deep neural networks
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