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 ne

This study aimed to know the attitudes and practice of pharmacists regarding the management of minor ailments in Iraqi community pharmacies. A cross-sectional study for 320 community pharmacists was conducted during February 2020 using a newly developed and validated questionnaire. Only 4.4% of pharmacists prefer not to deal with minor ailment cases. Minority (15.6%) of participated pharmacists refer more than half of minor ailment cases they face to the physician. Regarding the assessment of minor ailments using WWHAM technique, what are the symptoms are the most commonly asked questions by pharmacists. Only 49.1% mentioned that they ask all WWHAM questions. On the other hand, most pharmacists (90%) educate their patients about the dosi

Supervised By : Prof. dr. Shaker Jaseem Mohammed This research aims to identify the (effectiveness of Bayer's strategy in the development of deductive thinking among students in the fifth grade literary material European history) and to achieve the goal set researcher null hypothesis of the following: • There is no statistically significant difference between the average scores of the experimental group which studied the use of Bayer's strategy and the control group, which studied the use of the usual way in the development of deductive reasoning. The study sample consisted of (84 students) of the students in the fifth grade literary breeding Baghdad / Karkh second Directorate for the academic year 2015-2016 were distributed Aanhaldras

Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

      Products’ quality inspection is an important stage in every production route, in which the quality of the produced goods is estimated and compared with the desired specifications. With traditional inspection, the process rely on manual methods that generates various costs and large time consumption. On the contrary, today’s inspection systems that use modern techniques like computer vision, are more accurate and efficient. However, the amount of work needed to build a computer vision system based on classic techniques is relatively large, due to the issue of manually selecting and extracting features from digital images, which also produces labor costs for the system engineers.

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      Products’ quality inspection is an important stage in every production route, in which the quality of the produced goods is estimated and compared with the desired specifications. With traditional inspection, the process rely on manual methods that generates various costs and large time consumption. On the contrary, today’s inspection systems that use modern techniques like computer vision, are more accurate and efficient. However, the amount of work needed to build a computer vision system based on classic techniques is relatively large, due to the issue of manually selecting and extracting features from digital images, which also produces labor costs for the system engineers.       In this research, we pr

This study employs evolutionary optimization and Artificial Intelligence algorithms to determine an individual’s age using a single-faced image as the basis for the identification process. Additionally, we used the WIKI dataset, widely considered the most comprehensive collection of facial images to date, including descriptions of age and gender attributes. However, estimating age from facial images is a recent topic of study, even though much research has been undertaken on establishing chronological age from facial photographs. Retrained artificial neural networks are used for classification after applying reprocessing and optimization techniques to achieve this goal. It is possible that the difficulty of determining age could be reduce

The recent advancements in security approaches have significantly increased the ability to identify and mitigate any type of threat or attack in any network infrastructure, such as a software-defined network (SDN), and protect the internet security architecture against a variety of threats or attacks. Machine learning (ML) and deep learning (DL) are among the most popular techniques for preventing distributed denial-of-service (DDoS) attacks on any kind of network. The objective of this systematic review is to identify, evaluate, and discuss new efforts on ML/DL-based DDoS attack detection strategies in SDN networks. To reach our objective, we conducted a systematic review in which we looked for publications that used ML/DL approach

Abstract

The research aims to identify the level of effectiveness of the teaching practices of science and mathematics teachers in light of the national framework for future skills in Omani schools. To achieve the objectives of the study, the researchers used the descriptive approach, as he designed a note card consisting of (30) phrases distributed on three axes: basic skills, practical skills, and technical skills. After verifying the validity and reliability of the tools, they were applied to a sample of (116) teachers. The results of the research revealed that the level of effectiveness of the teaching practices of mathematics teachers has recorded a medium degree with a mean (3.05). The results a