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.
In this paper, an experimental study was conducted to enhance the thermal performance of a double-pass solar air heater (SAH) using phase change material (PCM) for thermal storage at climatic conditions of Baghdad city - Iraq. The double-pass solar air heater integrated with thermal storage system was manufactured and tested to ensure that the air heating reserved after the absence of the sun. The rectangular cavity filled with paraffin wax was used as a latent heat storage and incorporated into the lower channel of solar air heater. Experiments were carried out to evaluate the charging and discharging characteristics of two similar designed solar air collectors with and without using phase change material at a constant
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Aleppo bentonite was investigated to remove ciprofloxacin hydrochloride from aqueous solution. Batch adsorption experiments were conducted to study the several factors affecting the removal process, including contact time, pH of solution, bentonite dosage, ion strength, and temperature. The optimum contact time, pH of solution and bentonite dosage were determined to be 60 minutes, 6 and 0.15 g/50 ml, respectively. The bentonite efficiency in removing CIP decreased from 89.9% to 53.21% with increasing Ionic strength from 0 to 500mM, and it increased from 89% to 96.9% when the temperature increased from 298 to 318 K. Kinetic studies showed that the pseudo second-order model was the best in describing the adsorption sys
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In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial
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The traditional centralized network management approach presents severe efficiency and scalability limitations in large scale networks. The process of data collection and analysis typically involves huge transfers of management data to the manager which cause considerable network throughput and bottlenecks at the manager side. All these problems processed using the Agent technology as a solution to distribute the management functionality over the network elements. The proposed system consists of the server agent that is working together with clients agents to monitor the logging (off, on) of the clients computers and which user is working on it. file system watcher mechanism is used to indicate any change in files. The results were presente
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The effect of cognitive trips via the Internet (web quest) accompanying practical lessons in learning some basic handball skills for female students
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The thermal performance of a flat-plate solar collector (FPSC) using novel heat transfer fluids of aqueous colloidal dispersions of covalently functionalized multi-walled carbon nanotubes with β-Alanine (Ala-MWCNTs) has been studied. Multi-walled carbon nanotubes (MWCNTs) with outside diameters of (< 8 nm) and (20–30 nm) having specific surface areas (SSAs) of (500 m2/g) and (110 m2/g), respectively, were utilized. For each Ala-MWCNTs, waterbased nanofluids were synthesized using weight concentrations of 0.025%, 0.05%, 0.075%, and 0.1%. A MATLAB code was built and a test rig was designed and developed. Heat flux intensities of 600, 800, and 1000 W/m2; mass flow rates of 0.6, 1.0, and 1.4 kg/min; and inlet fluid temperatures of 30, 40, an
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Electronic properties including (bond length, energy gap, HOMO, LUMO and density of state) as well as spectroscopic properties such like infrared, Raman scattering, force constant, reduced mass and longitu- dinal optical mode as a function of frequency are based on size and concentration of the molecular and nanostructures of aluminum nitride ALN, boron nitride BN and AlxB7-XN7 as nanotubes has calculated using Ab –initio approximation method dependent on density functional theory and generalized gradient approximation. The geometrical structure are calculated by using Gauss view 05 as a complementary program. Shows the energy gap of ALN, BN and AlxB7-XN7 as a function of the total number of atoms , start from smallest molecule to reached
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Striae distensae SD or stretch mark are frequent skin lesion that cause considerable aesthetic concern. The 1064nm long pulsed Nd:YAG Laser has been used to promote an increase in dermal collagen and is known to be a Laser that has a high affinity to vascular chromphores. Also by using fractional CO2 Laser 10600nm as an effective modality in treatment of striae distensae SD. It works to stimulate fibroblast and enhance Collagen formation, which is important for newly generated skin tissue.
Objectives: This study aims to verify the efficacy of long pulsed Nd: YAG Laser (1064nm) in the treatment of immature striae distensae (SD) and the efficacy of C02 fractional Laser (10600nm) in treatment o
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