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Performance Evaluation of SDN DDoS Attack Detection and Mitigation Based Random Forest and K-Nearest Neighbors Machine Learning Algorithms
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of network topology have been generated to observe the effectiveness of proposed algorithms on different network architectures. The results reveal that RF performs better than KNN in a single topology, and both have close performance in other topologies.

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Publication Date
Sat Mar 01 2025
Journal Name
Al-khwarizmi Engineering Journal
Deep-Learning-Based Mobile Application for Detecting COVID-19
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Patients infected with the COVID-19 virus develop severe pneumonia, which typically results in death. Radiological data show that the disease involves interstitial lung involvement, lung opacities, bilateral ground-glass opacities, and patchy opacities. This study aimed to improve COVID-19 diagnosis via radiological chest X-ray (CXR) image analysis, making a substantial contribution to the development of a mobile application that efficiently identifies COVID-19, saving medical professionals time and resources. It also allows for timely preventative interventions by using more than 18000 CXR lung images and the MobileNetV2 convolutional neural network (CNN) architecture. The MobileNetV2 deep-learning model performances were evaluated

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
3D scenes semantic segmentation using deep learning based Survey
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Abstract<p>Semantic segmentation realization and understanding is a stringent task not just for computer vision but also in the researches of the sciences of earth, semantic segmentation decompose compound architectures in one elements, the most mutual object in a civil outside or inside senses must classified then reinforced with information meaning of all object, it’s a method for labeling and clustering point cloud automatically. Three dimensions natural scenes classification need a point cloud dataset to representation data format as input, many challenge appeared with working of 3d data like: little number, resolution and accurate of three Dimensional dataset . Deep learning now is the po</p> ... Show More
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Publication Date
Mon Jan 09 2023
Journal Name
2023 15th International Conference On Developments In Esystems Engineering (dese)
Deep Learning-Based Speech Enhancement Algorithm Using Charlier Transform
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Publication Date
Sun Jul 02 2017
Journal Name
Journal Of Educational And Psychological Researches
Prevalence of Posttraumatic Stress Symptomatology and Distribution of Attachment Patterns 1 and 5 Months after a Terrorist Attack
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As a consequence of a terrorist attack, people may experience posttraumatic stress disorder (PTSD) and lack of feeling secure in relationships. This longitudinal study aimed to examine the prevalence of PTSD symptoms over time, the relationship between adult attachment styles and PTSD, as well as their association with degree of exposure, and finally to consider the distribution and the trajectory of attachment styles. The sample consisted of 235 students (M=125, F=110) who were exposed to different levels of trauma intensity in response to a bombing attack. Participants were recruited and assessed approximately 1 month and 5 months after the attack using a battery of questionnaires. Findings revealed, as expected, that 79.5% of the part

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Publication Date
Sat Jun 30 2012
Journal Name
The Iraqi Journal Of Veterinary Medicine
The effect of Foot and Mouth disease on reproductive performance of Holstein bulls in Artificial Insemination Center of Iraq: AL-Badry K I * , Ibrahim F F ** and Rajab BA **
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This study was carried out in Artificial Insemination Center of Iraq to revealed FMD disease effect on some seminal attributer parameters of 14 imported Holstein bulls divided to three groups according to different reproductive efficiency (four High, five medium and five weak). Results showed that FMD disease had significant (P < 0.05) adverse effect on most seminal attributer parameters, mass, individual motility and sperm concentration / ml during post disease in first of two, four, all months of high, medium and weak semen quality bulls respectively .but semen volume didn’t influenced significantly with this disease. So semen collection should be suspended until resume normal fertility of sperm, after two, four month of high and

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Publication Date
Mon Aug 01 2011
Journal Name
Journal Of Engineering
DAMAGE DETECTION AND LOCATION FOR IN AND OUT-OFPLANE CURVED BEAMS USING FUZZY LOGIC BASED ON FREQUENCY DIFFERENCE
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In this study, structures damage identification method based on changes in the dynamic characteristics
(frequencies) of the structure are examined, stiffness as well as mass matrices of the curved
(in and out-of-plane vibration) beam elements is formulated using Hamilton's principle. Each node
of both of them possesses seven degrees of freedom including the warping degree of freedom. The
curved beam element had been derived based on the Kang and Yoo’s thin-walled curved beam theory
in 1994. A computer program was developing to carry out free vibration analyses of the curved
beam as well as straight beam. Comparing with the frequencies for other researchers using the general
purpose program MATLAB. Fuzzy logic syste

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
On Existence of Prime K-Tuples Conjecture for Positive Proportion of Admissible K-Tuples
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Number theorists believe that primes play a central role in Number theory and that solving problems related to primes could lead to the resolution of many other unsolved conjectures, including the prime k-tuples conjecture. This paper aims to demonstrate the existence of this conjecture for admissible k-tuples in a positive proportion. The authors achieved this by refining the methods of “Goldston, Pintz and Yildirim” and “James Maynard” for studying bounded gaps between primes and prime k-tuples. These refinements enabled to overcome the previous limitations and restrictions and to show that for a positive proportion of admissible k-tuples, there is the existence of the prime k-tuples conjecture holding for each “k”. The sig

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Publication Date
Sun Dec 25 2022
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Detection of Epicatechin in Camellia sinensis Leaves by Thin Layer Chromatography and High Performance Liquid Chromatography Techniques
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    The current study performed in order to detect and quantify epicatechin in two tea samples of Camellia sinensis (black and green tea) by thin layer chromatography (TLC) and high performance liquid chromatography (HPLC). Extraction of epicatechin from black and green tea was done by using two different methods: maceration (cold extraction method) and decoction (hot extraction method) involved using three different solvents which are  absolute ethanol, 50% aqueous ethanol and water  for both extraction methods using room temperature and direct heat respectively. Crude extracts of two tea samples that obtained from two methods were fractionated by using two solvents with different polarity (chloroform and

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Publication Date
Fri Dec 01 2017
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Integration between value chain analysis and balanced scorecard to for performance evaluation
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The performance evaluation process requires a set of criteria and for the purpose of measuring the level of performance achieved by the Unit and the actual level of development of its activities, and in view of the changes and of rapid and continuous variables surrounding the Performance is a reflection of the unit's ability to achieve its objectives, as these units are designed to achieve the objectives of exploiting a range of economic resources available to it, and the performance evaluation process is a form of censorship, focusing on the analysis of the results obtained from the achievement All its activities with a view to determining the extent to which the Unit has achieved its objectives using the resources available to it and h

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of The Mechanical Behavior Of Materials
Mitigation of collapse characteristics of gypseous soils by activated carbon, sodium metasilicate, and cement dust: An experimental study
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This study includes adding chemicals to gypseous soil to improve its collapse characteristics. The collapse behavior of gypseous soil brought from the north of Iraq (Salah El-Deen governorate) with a gypsum content of 59% was investigated using five types of additions (cement dust, powder sodium meta-silicate, powder activated carbon, sodium silicate solution, and granular activated carbon). The soil was mixed by weight with cement dust (10, 20, and 30%), powder sodium meta-silicate (6%), powder activated carbon (10%), sodium silicate solution (3, 6, and 9%), and granular activated carbon (5, 10, and 15%). The collapse potential is reduced by 86, 71, 43, 37, and 35% when 30% cement dust, 6% powder sodium meta-silicate, 10% powder activated

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