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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
Tue Jan 01 2019
Journal Name
Journal Of Theoretical And Applied Information Technology
A Survey on the Vein Biometric Recognition Systems: Trends and Challenges
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Vascular patterns were seen to be a probable identification characteristic of the biometric system. Since then, many studies have investigated and proposed different techniques which exploited this feature and used it for the identification and verification purposes. The conventional biometric features like the iris, fingerprints and face recognition have been thoroughly investigated, however, during the past few years, finger vein patterns have been recognized as a reliable biometric feature. This study discusses the application of the vein biometric system. Though the vein pattern can be a very appealing topic of research, there are many challenges in this field and some improvements need to be carried out. Here, the researchers reviewed

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Publication Date
Wed Dec 01 2021
Journal Name
Iraqi Journal Of Science
Interpretation of Potential Fields and Detection of Deep Faults of Kut-Dewania- Fajir Area, Central Iraq
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Gravity and magnetic data are used to study the tectonic situation of Kut- Dewania- Fajir and surrounding areas in central Iraq. The study includes the using of window method with different spacing to separate the residual from regional anomalies of gravity and magnetic data. The Total Horizontal Derivative (THD) techniques used to identify the fault trends in the basement and sedimentary rocks depending upon gravity and magnetic data. The obtained faults trends from gravity data are (N30W), (N60W) (N80E) and (N20E) and from magnetic data are (N30W), (N70E), (N20E),(N10W),(N40E). It is believed that these faults extend from the basement to the lower layers of the sedimentary rocks except the N60W trend that observed clearly in gravity in

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Publication Date
Fri Mar 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
The effect of Analysis of internal environment in the quality of health care service survey study at AL_Elwiya Maternity Teaching Hospital
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he current research aims at showing the correlation and effect of the internal environment analysis in the quality of health service in AL_Elwiya Maternity Teaching Hospital, researcher depended on the integral method in the "analytical descriptive method" for the study of the relation between the main variables and the sub-variables throughout data collection required by the theme of this study, a case study" in tackling the data and information related to the financial aspects of the internal environment.

The problem of the study was manifested in the essential question, that is (is there internal struc

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Publication Date
Thu Jan 14 2021
Journal Name
Iraqi Journal Of Science
Demand-Adapted Service Oriented Architecture Using Lego Model
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Many developments happened in Service Oriented architecture models but with no details in its technology and requirement. This paper presents a new Service Oriented Architecture (SOA) to all Service Enterprise (SE) according to their demands. Therefore, the goal is to build a new complete architecture model for SOA methodologies according to current technology and business requirements that could be used in a real Enterprise environment. To do this, new types of services and new model called Lego Model are explained in details, and the results of the proposed architecture model in analyzed. Consequently, the complications are reduced to support business domains of enterprise and to start associating SOA methodologies in their corporate s

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Publication Date
Thu Mar 09 2023
Journal Name
Coatings
Nondestructive Evaluation of Fiber-Reinforced Polymer Using Microwave Techniques: A Review
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Carbon-fiber-reinforced polymer (CFRP) is widely acknowledged as a leading advanced material structure, offering superior properties compared to traditional materials, and has found diverse applications in several industrial sectors, such as that of automobiles, aircrafts, and power plants. However, the production of CFRP composites is prone to fabrication problems, leading to structural defects arising from cycling and aging processes. Identifying these defects at an early stage is crucial to prevent service issues that could result in catastrophic failures. Hence, routine inspection and maintenance are crucial to prevent system collapse. To achieve this objective, conventional nondestructive testing (NDT) methods are utilized to i

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Publication Date
Wed Oct 20 2021
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Fully Automated Magnetic Resonance Detection and Segmentation of Brain using Convolutional Neural Network
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     The brain's magnetic resonance imaging (MRI) is tasked with finding the pixels or voxels that establish where the brain is in a medical image The Convolutional Neural Network (CNN) can process curved baselines that frequently occur in scanned documents. Next, the lines are separated into characters. In the Convolutional Neural Network (CNN) can process curved baselines that frequently occur in scanned documents case of fonts with a fixed MRI width, the gaps are analyzed and split. Otherwise, a limited region above the baseline is analyzed, separated, and classified. The words with the lowest recognition score are split into further characters x until the result improves. If this does not improve the recognition s

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Crossref
Publication Date
Fri Jul 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Medical service quality, Dimensions the quality of service, satisfaction with medical service
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 the Objective of  study is  to measure the quality of medical service level,  in the  Iraq public hospitals ,presented by  special words ,private hospitals, and compare between them, by knowing the level of recipients satisfaction  of medical service for all dimensions of quality service, and then measuring satisfaction with the quality of medical service as a whole for both of them, which have been prepared in questionnaire form, included two main directions, first to determine the level of satisfaction when, recipients of medical service is not dimensions quality of service in accordance with the Scale Servqual by (Parasurman et .al 1988), consisting of five di

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Crossref
Publication Date
Wed Mar 30 2022
Journal Name
Iraqi Journal Of Science
Crawling and Mining the Dark Web: A Survey on Existing and New Approaches
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    The last two decades have seen a marked increase in the illegal activities on the Dark Web. Prompt evolvement and use of sophisticated protocols make it difficult for security agencies to identify and investigate these activities by conventional methods. Moreover, tracing criminals and terrorists poses a great challenge keeping in mind that cybercrimes are no less serious than real life crimes. At the same time, computer security societies and law enforcement pay a great deal of attention on detecting and monitoring illegal sites on the Dark Web. Retrieval of relevant information is not an easy task because of vastness and ever-changing nature of the Dark Web; as a result, web crawlers play a vital role in achieving this task. The

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Publication Date
Sat Jul 22 2023
Journal Name
Journal Of Engineering
Replacement of Line Loads acting on slabs to equivalent uniformly Distributed Loads
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This study aims to derive a general relation between line loads that acting on two-way slab system and the equivalent uniformly distributed loads. This relation will be so useful to structural designer that are used to working with a uniformly distributed load and enable them to use the traditional methods for analysis of two-way systems (e.g. Direct Design Method). Two types of slab systems, Slab System with Beams and Flat Slab Systems, have been considered in this study to include the effect of aspect ratio and type of slab on the proposed relation. Five aspect ratios, l2/l1 of 0.5, 0.75, 1.0, 1.5 and 2.0, have been considered for both types of two-way systems.
All necessary finite element analyses have been executed with SAFE Soft

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Crossref
Publication Date
Tue Dec 27 2022
Journal Name
2022 3rd Information Technology To Enhance E-learning And Other Application (it-ela)
Diabetes Prediction Using Machine Learning
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Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att

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