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.
Succinic acid is an essential base ingredient for manufacturing various industrial chemicals. Succinic acid has been acknowledged as one of the most significant bio based building block chemicals. Rapid demand for succinic acid has been noticed in the last 10 years. The production methods and mechanisms developed. Hence, these techniques and operations need to be revised. Recently, an omnibus rule for developing succinic acid is to find renewable carbohydrate Feedstocks. The sustainability of the resource is crucial to disintegrate the massive use of petroleum based-production. Accordingly, systematically reviewing the latest findings of bacterial production and related fermentation methods is critical. Therefore, this paper aims to stud
... Show MoreThe interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm
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Discriminant between groups is one of the common procedures because of its ability to analyze many practical phenomena, and there are several methods can be used for this purpose, such as linear and quadratic discriminant functions. recently, neural networks is used as a tool to distinguish between groups.
In this paper the simulation is used to compare neural networks and classical method for classify observations to group that is belong to, in case of some variables that don’t follow the normal distribution. we use the proportion of number of misclassification observations to the all observations as a criterion of comparison.
A new modified differential evolution algorithm DE-BEA, is proposed to improve the reliability of the standard DE/current-to-rand/1/bin by implementing a new mutation scheme inspired by the bacterial evolutionary algorithm (BEA). The crossover and the selection schemes of the DE method are also modified to fit the new DE-BEA mechanism. The new scheme diversifies the population by applying to all the individuals a segment based scheme that generates multiple copies (clones) from each individual one-by-one and applies the BEA segment-wise mechanism. These new steps are embedded in the DE/current-to-rand/bin scheme. The performance of the new algorithm has been compared with several DE variants over eighteen benchmark functions including sever
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Three types of zeolite A were prepared from Iraqi kaoline which are 3A, 4A and 5A by ion exchange method .They were characterized by XRD and atomic absorption techniques .They were used as adsorbents to examine their applicability for H2S adsorption .The adsorption process was performed in a static form and constant volume system which constructed from stainless steel .The effect of zeolite type and temperature on the adsorption properties of H2S at -5 , 25 and 55 oC was studied .The zeolite type 5A has the highest adsorption value (79.384 µmol/g ) and the three types may be arranged in a sequence toward H2S adsorption as 5 A> 4A>3A .The amount of H2S adsorbed increased as temperature decreased from 55 to -5 for all samples. Langmuir , Fre
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In spite of the disappearing of a clear uniform textbook for teaching ESP at different departments and different colleges in both scientific and humanistic studies, the practitioners at those departments and colleges have to teach translation as one of the important requirements to pass the English language exam. The lack of defined translation activities is a noticeable problem therefore; the problem of teaching translation is diagnosed in that the students lack the ability to comprehend the text in English language and other translation knowledge and skills.
The study aims to suggest a translation strategy and then find out the effect of the translation strategy on ESP learners’ achievement in translation. A sample of 50 stud
... Show MoreBackground There is an increasing need for pharmacists to incorporate more patient care targeting. Consequently, the productivity of pharmacy programs can be enhanced by evaluating the advantages and disadvantages of pharmacy curriculum. Objectives To assess the beliefs, perceptions, and challenges of the College of Pharmacy –The University of Baghdad PharmD graduates regarding the PharmD program. Method Qualitative research methodology was implemented. Graduate PharmD candidates were interviewed either inperson or via telephone. The interviews were conducted in a semi-structured format, utilizing a predetermined interview guide that included open-ended questions. Thematic analysis was implemented to analyze the data. Results A total of 2
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