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.
This research a mining at evaluation the efficiency of the nursing performance depended on standards of W.H.O. via application standards of W.H.O on the nursing personnel in medical city office, in light of it, it has design world evaluation list, and a sample was chosen from the nursing personnel in given researched the organization whom they are evaluated according to the standards of W.H.O for the nursing performance included of ten standards, divided in to 45 question , besides the evaluation list, the researcher get assistance of some tools of collection information via actual checking and personal interviews, a number of statistical means were used to manipulate t
... Show MoreKE Sharquie, AA Noaimi, HG Mahmood, SM Al-Ogaily, Journal of Cosmetics, Dermatological Sciences and Applications, 2015 - Cited by 6
The presented study investigated the scheduling regarding jobs on a single machine. Each job will be processed with no interruptions and becomes available for the processing at time 0. The aim is finding a processing order with regard to jobs, minimizing total completion time , total late work , and maximal tardiness which is an NP-hard problem. In the theoretical part of the present work, the mathematical formula for the examined problem will be presented, and a sub-problem of the original problem of minimizing the multi-objective functions is introduced. Also, then the importance regarding the dominance rule (DR) that could be applied to the problem to improve good solutions will be shown. While in the practical part, two
... Show MoreVolleyball is one of the sports that require physical and skill abilities thus many teaching models appeared to teach these abilities like group investigation model. The research aimed at identifying the effect of group investigation model on learning underarm and overhead passing in volleyball. The researchers hypothesized statistical differences between pre and posttests in learning underarm and overhead passing in volleyball as well as differences in posttests of controlling and experimental groups in learning underarm and overhead passing in volleyball. The researcher used the experimental method on (30) second year female students of physical education and sport sciences college/ university of Baghdad. Group investigation model was app
... Show Moreimportumt educational institution as (kindergartens) need teachers which qualified ownes modalities in their education for children , as Marzanu method in a way of learning and own methods of crisis management, because the teachers that own those styles of learning ginekindergarten children knowledge and the childrenIeaving based on theMeaing and knowledge and integration of their information, And teachers that earn methods of crisis management provide for the children of the kindergarten security within the educational institution which in turn affect the growth and development of the Child and then abilities, health physical, mental, psychological …etc.., The aims of the current research have identified to recognize: 1- the dimension
... Show MoreFor over a decade, educational technology has been used sparingly in our schools and universities. Online training courses have been used since 2003 to fill the gaps in our learning system and to add extra program besides classroom learning. This paper aims to investigate the Iraqi EFL instructors’ participating in online training courses and its influence on the process of teaching and learning.
The sample of present study consists of 30 instructors from University of Baghdad. The questionnaire of sixteen items was constructed. After ensuring validity and reliability of questionnaire, it was applied on March 2013 and the result shows that most of instructors improve their teaching methods b
... Show MoreThe successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi
... Show MoreIn this work, we construct projectively distinct (k,3)-arcs in the projective plane PG(2,9) by applying a geometrical method. The cubic curves have been been constructed by using the general equation of the cubic. We found that there are complete (13,3)-arcs, complete (15,3)-arcs and we found that the only (16,3)-arcs lead to maximum completeness