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.
Scheduling considered being one of the most fundamental and essential bases of the project management. Several methods are used for project scheduling such as CPM, PERT and GERT. Since too many uncertainties are involved in methods for estimating the duration and cost of activities, these methods lack the capability of modeling practical projects. Although schedules can be developed for construction projects at early stage, there is always a possibility for unexpected material or technical shortages during construction stage. The objective of this research is to build a fuzzy mathematical model including time cost tradeoff and resource constraints analysis to be applied concurrently. The proposed model has been formulated using fuzzy the
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Sustainability including renewable energy and green power, is one of the important feature in recent years due to environmental constraints and the emission of CO2 from fossil fuel. Pressure retarded osmosis (PRO) process is considered one of the effective technology for power generation. This study assessed the application of pressure retarded osmosis to produce power from Tigris River water in Baghdad City, Iraq. Spiral wound TFC membrane was tested in the PRO process with different variables. The effect of different types of draw solutions (MgCl2, NaCl, Sodium Formate, KCl, Sodium Acetate), applied pressure (0 – 7 bar), and draw solution concentration (0.08 and 0.4 M) were tested in this work. The flux, recovery, and power density for
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Optimizing system performance in dynamic and heterogeneous environments and the efficient management of computational tasks are crucial. This paper therefore looks at task scheduling and resource allocation algorithms in some depth. The work evaluates five algorithms: Genetic Algorithms (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Firefly Algorithm (FA) and Simulated Annealing (SA) across various workloads achieved by varying the task-to-node ratio. The paper identifies Finish Time and Deadline as two key performance metrics for gauging the efficacy of an algorithm, and a comprehensive investigation of the behaviors of these algorithms across different workloads was carried out. Results from the experiment
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Cladophora and Spirulina algae biomass have been used for the removal of Tetracycline (TC) antibiotic from aqueous solution. Different operation conditions were varied in batch process, such as initial antibiotic concentration, different biomass dosage and type, contact time, agitation speed, and initial pH. The result showed that the maximum removal efficiencies by using 1.25 g/100 ml Cladophora and 0.5 g/100 ml Spirulina algae biomass were 95% and 94% respectively. At the optimum experimental condition of temperature 25°C, initial TC concentration 50 mg/l, contact time 2.5hr, agitation speed 200 rpm and pH 6.5. The characterization of Cladophora and Spirulina biomass by Fourier transform infrared (FTIR) indicates that the presenc
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Nowadays power systems are huge networks that consist of electrical energy sources, static and lumped load components, connected over long distances by A.C. transmission lines. Voltage improvement is an important aspect of the power system. If the issue is not dealt with properly, may lead to voltage collapse. In this paper, HVDC links/bipolar connections were inserted in a power system in order to improve the voltage profile. The load flow was simulated by Electrical Transient Analyzer Program (ETAP.16) program in which Newton- Raphson method is used. The load flow simulation studies show a significant enhancement of the power system performance after applying HVDC links on Kurdistan power systems. Th
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In this work, using GPS which has best accuracy that can be established set of GCPs, also two satellite images can be used, first with high resolution QuickBird, and second has low resolution Landsat image and topographic maps with 1:100,000 and 1:250,000 scales. The implementing of these factors (GPS, two satellite images, different scales for topographic maps, and set of GCPs) can be applying. In this study, must be divided this work into two parts geometric accuracy and informative accuracy investigation. The first part is showing geometric correction for two satellite images and maps.
The second part of the results is to demonstrate the features (how the features appearance) of topographic map or pictorial map (image map), Where i
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This study includes Estimating scale parameter, location parameter and reliability function for Extreme Value (EXV) distribution by two methods, namely: -
- Maximum Likelihood Method (MLE).
- Probability Weighted Moments Method (PWM).
Used simulations to generate the required samples to estimate the parameters and reliability function of different sizes(n=10,25,50,100) , and give real values for the parameters are and , replicate the simulation experiments (RP=1000)
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In this work, a magnetic switch was prepared using two typesof ferrofluid materials, the pure ferrofluid and ferrofluid doped with copper nanoparticles (10 nm). The critical magnetic field (Hc) and the state of magnetic saturation (Hs) were studied using three types of laser sources. The main parameters of the magnetic switch measured using pure ferrofluid and He-Ne Laser source were Hc(0.5 mv, 0.4 G), Hs (8.5 mv, 3 G). For the ferrofluid doped with copper nanoparticles were Hc (1 mv, 4 G), Hs (15 mv, 9.6 G), Using green semiconductor laser for the Pure ferrofluid were Hc (0.5 mv, 0.3 G) Hs (15 mv, 2.9 G). While the ferrofluid doped with copper nanoparticles were Hc (0.5 mv, 1 G), Hs (12 mv, 2.8 G) and by using the violet semiconductor l
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Research summarized in applying the model of fuzzy goal programming for aggregate production planning , in General Company for hydraulic industries / plastic factory to get an optimal production plan trying to cope with the impact that fluctuations in demand and employs all available resources using two strategies where they are available inventories strategy and the strategy of change in the level of the workforce, these strategies costs are usually imprecise/fuzzy. The plant administration trying to minimize total production costs, minimize carrying costs and minimize changes in labour levels. depending on the gained data from th
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