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Survey on distributed denial of service attack detection using deep learning: A review
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Distributed Denial of Service (DDoS) attacks on Web-based services have grown in both number and sophistication with the rise of advanced wireless technology and modern computing paradigms. Detecting these attacks in the sea of communication packets is very important. There were a lot of DDoS attacks that were directed at the network and transport layers at first. During the past few years, attackers have changed their strategies to try to get into the application layer. The application layer attacks could be more harmful and stealthier because the attack traffic and the normal traffic flows cannot be told apart. Distributed attacks are hard to fight because they can affect real computing resources as well as network bandwidth. DDoS attacks can also be made with smart devices that connect to the Internet, which can be infected and used as botnets. They use Deep Learning (D.L.) techniques like Convolutional Neural Network (C.N.N.) and variants of Recurrent Neural Networks (R.N.N.), such as Long Short-Term Memory (L.S.T.M.), Bidirectional L.S.T.M., Stacked L.S.T.M., and the Gat G.R.U.. These techniques have been used to detect (DDoS) attacks. The Portmap.csv file from the most recent DDoS dataset, CICDDoS2019, has been used to test D.L. approaches. Before giving the data to the D.L. approaches, the data is cleaned up. The pre-processed dataset is used to train and test the D.L. approaches. In the paper, we show how the D.L. approach works with multiple models and how they compare to each other.

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Publication Date
Fri Jan 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Experimental Investigation on Adsorption of Methyl orange Using eggshells as adsorbent Surface
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The role of residues in the adsorption process for removing contaminants from their aqueous solution was highlighted in this study. The adsorption capacity of eggshells were used to remove the methyl orange dye from its aqueous solution. The highest dye adsorption was found to range between (62.30% to 62.33%). The results of using adsorption isotherms (Freundlich, Langmuir, and Temkin) have been revealed that the Freundlich model was followed and that the Langmuir model did not match, as well as the partial applicability of Temkin's model at temperatures (298,308,318) K. The process of adsorption is a physical one. Three kinetic models of the adsorption process were also used, with the results demonstrating the applicability of the pseud

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Publication Date
Sun Dec 01 2002
Journal Name
Iraqi Journal Of Physics
Study of Gamma — irradiation effects on the Polymethylmethacrylate (PMMA) Using (PAL) Method
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Gamma - irradiation effect on polymethylmethacrylate (PMMA) samples has been studied using Positron Annihilation Lifetime (PAL) method. The orthopositronium (o-Ps) lifetime τ3, hence the o-ps parameters, the volume hole size (Vh) and the free volume fraction (Ꞙh) in the irradiated samples were measured as a function of gamma-irradiation dose up to 28.05 kGy. It has been shown that τ 3, Vh, and Ꞙh, are increasing in general with increasing gamma-dose, to reach a maximum percentage increment of 22.42% in τ3, 60% in Vh and 29.5% in Ꞙh, at. 2.55 kGy, whereas τ2 reaches maximum increment of 119. 7% at 7.65 kGy. The results s

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Publication Date
Sun Oct 30 2022
Journal Name
Iraqi Journal Of Science
Gamma Radiation Effect on Characterizations of Gold Nanoparticles Synthesized Using Green Method
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      Biocompatible gold nanoparticles were successfully synthesized by hibiscus plant leaf extract as a bioreactor. The prepared nanoparticles were evaluated using UV/Vis spectroscopy, Atomic Force Microscopy (AFM), Fourier Transform Infrared Spectroscopy (FT-IR), X-ray Diffraction and Scanning Electron Microscopy (SEM) . The study also investigated the effect of the different gamma irradiation doses on the size and dispersion of the produced nanoparticles. In UV- Vis spectra, the peak of Au NPs' surface plasmon resonance (SPR) was detected as a single peak at 543 nm. The gamma irradiation induced a blue shift in the SPR peak, which indicates that it might be applied as affective factor for size control.  Physical as well as chemi

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Publication Date
Wed Aug 31 2022
Journal Name
Iraqi Journal Of Science
Evaluation of the Physical Parameters on Ischemic Heart Disease Patients Using Echocardiography
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      Background: Left ventricular function and volumes have major diagnostic and prognostic importance in patients with various cardiac diseases, such as ischemic heart disease which is a life-threatening heart disease condition characterized by systolic dysfunction and a decrease in cardiac output. 

According to left ventricular ejection fraction, the degree of ischemic heart disease was classified as mild, moderate, and severe. To determine cardiac function and hemodynamics, the echocardiography technique is used, which is a noninvasive diagnostic method.

Patients and Methods: The study included 216 patients between 25 and 75 years old; 121 males and 95 females; 265 normal individuals (age range: 25 to 75 years ol

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Modeling and Control of Fuel Cell Using Artificial Neural Networks
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This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback

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Publication Date
Wed May 10 2017
Journal Name
Journal Of The College Of Languages (jcl)
РОЛЬ СРЕДСТВ НАГЛЯДНОСТИ В ПРОЦЕССЕ ОБУЧЕНИЯ РУССКОМУ ЯЗЫКУ КАК ИНОСТРАННОМУ В ИРАСКОЙ АУДИТОРИИ The Role of the Use of Visual Aids in the Process Of Learning Russian Language in Lraq as a Foreign Language
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В статье рассматриваются понятие наглядности и ее классификация, эффективное применение принципа наглядности, возможность и преимущество использования наглядности и современные инструменты ее реализации в ираке.

 

Вследствие глобальных изменений во всем мире изменилась и роль иностранного языка в системе образования. Современный человек, шагающий в ногу со временем, не мыслит себя без зна

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Publication Date
Mon Jan 01 2018
Journal Name
Portugaliae Electrochimica Acta
A Kinetic Study of Oxalic Acid Electrochemical Oxidation on a Manganese Dioxide Rotating Cylinder Anode
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Publication Date
Wed Jun 28 2023
Journal Name
Mathematics
The Impact of Fear on a Harvested Prey–Predator System with Disease in a Prey
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A mathematical eco-epidemiological model consisting of harvested prey–predator system involving fear and disease in the prey population is formulated and studied. The prey population is supposed to be separated into two groups: susceptible and infected. The susceptible prey grows logistically, whereas the infected prey cannot reproduce and instead competes for the environment’s carrying capacity. Furthermore, the disease is transferred through contact from infected to susceptible individuals, and there is no inherited transmission. The existence, positivity, and boundedness of the model’s solution are discussed. The local stability analysis is carried out. The persistence requirements are established. The global behavior of th

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Publication Date
Wed Jan 13 2021
Journal Name
Iraqi Journal Of Science
MRI Probabilistic Neural Network Screening System: a benign and malignant recognition case study
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This work is aimed to design a system which is able to diagnose two types of tumors in a human brain (benign and malignant), using curvelet transform and probabilistic neural network. Our proposed method follows an approach in which the stages are preprocessing using Gaussian filter, segmentation using fuzzy c-means and feature extraction using curvelet transform. These features are trained and tested the probabilistic neural network. Curvelet transform is to extract the feature of MRI images. The proposed screening technique has successfully detected the brain cancer from MRI images of an almost 100% recognition rate accuracy.

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Publication Date
Thu Sep 14 2023
Journal Name
Al-khwarizmi Engineering Journal
Applying Scikit-learn of Machine Learning to Predict Consumed Energy in Al-Khwarizmi College of Engineering, Baghdad, Iraq
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Globally, buildings use about 40% of energy. Many elements, such as the physical properties of the structure, the efficiency of the cooling and heating systems, the activity of the occupants, and the building’s sustainability, affect the energy consumption of a building. It is really difficult to predict how much energy a building will need. To improve the building’s sustainability and create sustainable energy sources to reduce carbon dioxide emissions from fossil fuel combustion, estimating the building's energy use is necessary. This paper explains the energy consumed in the lecture building of the Al-Khwarizmi College of Engineering, University of Baghdad (UOB), Baghdad, Iraq. The weather data and the building construction informati

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