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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 Sep 01 2018
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Functional rotation and its impact on tax performance: Applied research in the General Authority for Taxation
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The research aimed at finding out the effect of functional rotation on the tax performance of the employees of the General Authority for Taxes through the five-meter questionnaire prepared according to the required data. The data obtained from the research sample were analyzed. The results showed a significant effect of recycling In the tax performance, and this is evident from the proportion of his contribution to the interpretation of the total variation, which is a good indicator of the impact of functional rotation in the performance of the body sample research.

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Publication Date
Mon Jan 01 2024
Journal Name
Brazilian Dental Science
Evaluation of flexural strength and degree of conversion of temporary crown materials at different aging periods in artificial saliva
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Objective: Evaluate the effects of different storage periods on flexural strength (FS) and degree of conversion (DC) of Bis-Acryl composite and Urethane dimethacrylate provisional restorative materials. Material and Methods: A total of 60 specimens were prepared from four temporary crown materials commercially available and assigned to four tested groups (n = 15 for each group): Prevision Temp, B&E CROWN, Primma Art, and Charm Temp groups. The specimens were stored in artificial saliva, and the FS was tested after 24 h, 7 d, and 14 d. A standard three-point bending test was conducted using a universal testing machine. Additionally, the DC was determined using a Fourier transform infrared spectroscopy (FTIR) device. The data were analyzed st

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Publication Date
Sun Sep 06 2015
Journal Name
Baghdad Science Journal
Evaluation of the level of Some Heavy Metals in Tobacco of Domestic and Imported Cigarette Brands Used in Iraq
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Smoking-related diseases can be attributed to the inhalation of many different toxins, including heavy metals, which have a host of harmful health effects. The primary objective of this study was to determine whether local and imported cigarette brands used in Iraq , have they elevated levels of metals or not .Three metals Lead (Pb) , Cadmium (Cd) and Chromium(Cr) were determined in tobacco of seventeen brands of imported cigarettes commonly available in Iraq and three Iraqi domestic cigarettes , which were randomly taken from retail market in Baghdad by using flame atomic absorption spectrometry. The produced data of imported and local cigarette brands were discussed and compared together and with studies from elsewhere .The result

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Publication Date
Tue Jul 15 2025
Journal Name
The Iraqi Journal For Information And Documentation Studies
The role of performance indicators in evaluating the performance of the University of Technology's Central Library
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University libraries seek to evaluate their performance in order to correct their path and adjust it in the right direction. Therefore, they use (performance indicators), which are a tool used by institutions to evaluate the weaknesses and strengths in their work and the reasons for failure to achieve some goals sometimes. They convert (goals, procedures and actions) into a formula that can be measured mathematically, which contributes to the library determining the gap between its current performance and what those libraries are supposed to be on, clarifying the path that the library is following, controlling the risks that may befall it, and thus enhancing the process of continuous improvement to avoid areas of failure and weakness becaus

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Publication Date
Mon May 09 2022
Journal Name
مجلة كلية التربية الاساسية الجامعة المستنصرية
Detection of sul1 resistance gene in Acinetobacter baumannii from different Clinical cases
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Publication Date
Wed Jun 28 2023
Journal Name
The Iraqi Journal Of Veterinary Medicine
Haemoglobin Epsilon as a Biomarker for the Molecular Detection of Canine ‎Lymphoma
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Lymphoma is a cancer arising from B or T lymphocytes that are central immune system ‎components. It is one of the three most common cancers encountered in the canine; ‎lymphoma affects middle-aged to older dogs and usually stems from lymphatic tissues, ‎such as lymph nodes, lymphoid tissue, or spleen. Despite the advance in the management of ‎canine lymphoma, a better understanding of the subtype and tumor aggressiveness is still ‎crucial for improved clinical diagnosis to differentiate malignancy from hyperplastic ‎conditions and to improve decision-making around treating and what treatment type to use. ‎This study aimed to evaluate a potential novel biomarker related to iron metabolism,

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Publication Date
Sun May 11 2014
Journal Name
World Journal Of Experimental Biosciences
Detection of hydrolytic enzymes produced by Azospirillum brasiliense isolated from root soil
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Publication Date
Sat Jan 01 2022
Journal Name
Tropical Journal Of Natural Product Research
Detection of Herpes Simplex Virus Type 1 in Patients Affected by Conjunctivitis
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Herpes simplex virus (HSV) is a common human pathogen that causes severe infections in newborns and immunocompromised patients. Conjunctivitis or corneal epithelial keratitis is caused by HSV type 1 all over the world and at all times of the year. The present study was aimed at detecting HSV in patients suffering from conjunctivitis. One hundred and ten (110) clinical samples (90 patients and 20 controls, both males and females) of eye conjunctiva swabs were collected from patients of different ages. The samples were analyzed using qPCR and ELISA techniques. The qPCR results revealed that HSV was present in 47 (52.2%) of the 90 patients who were infected. Of these patients, 25 (48.0%) were males and 22 (57.8%) were females, indicati

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Publication Date
Mon Apr 19 2010
Journal Name
Computer And Information Science
Quantitative Detection of Left Ventricular Wall Motion Abnormality by Two-Dimensional Echocardiography
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Echocardiography is a widely used imaging technique to examine various cardiac functions, especially to detect the left ventricular wall motion abnormality. Unfortunately the quality of echocardiograph images and complexities of underlying motion captured, makes it difficult for an in-experienced physicians/ radiologist to describe the motion abnormalities in a crisp way, leading to possible errors in diagnosis. In this study, we present a method to analyze left ventricular wall motion, by using optical flow to estimate velocities of the left ventricular wall segments and find relation between these segments motion. The proposed method will be able to present real clinical help to verify the left ventricular wall motion diagnosis.

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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network
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Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

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