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
... Show MoreThe research included studying the effect of different plowing depths (10,20and30) cm and three angles of the disc harrows (18,20and25) when they were combined in one compound machine consisting of a triple plow and disc harrows tied within one structure. Draft force, fuel consumption, practical productivity, and resistance to soil penetration. The results indicated that the plowing depth and disc angle had a significant effect on all studied parameters. The results showed that when the plowing depth increased and the disc angle increased, leads to increased pull force ratio, fuel consumption, resistance to soil penetration, and reduce the machine practical productivity.
Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise
... Show MoreThe hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s
... Show MoreThis study aimed to analyze functional thinking style and its contribution to learn the accuracy of block and smash serve in volleyball among university students. The sample was composed of 120 students of the College of Physical Education and Sports Sciences of the University of Baghdad (academic year 2021/2022). The statistical analyses were carried out with the statistical software SPSS and correlation analyses were conducted. It was found that functional thinking style significantly contributed to learn the accuracy of block and smash serve in volleyball among university students. Therefore, it is necessary to intensify efforts to increase the level of functional thinking among university students, by adopting acad
... Show MoreObjective This study aims to investigate the impact of integrated training on kinematics variables and defensive accuracy in volleyball, focusing on enhancing balance and muscle tension control through proprioceptive neuromuscular facilitation (PNF) exercises. Methods The sample consisted of 14 male volleyball athletes from the first volleyball league of Al-Jaish Sports Club were divided into experimental (n=7) and control group (n=7). In the pre- and post-intervention periods, dynamic balance, muscle tension control and kinematic variables (during a lateral reaching task) as well as defensive performance accuracy upon fatigue onset of recoil laser strikes were assessed. Exposure the intervention program was carried out for six weeks, and t
... Show MoreThis research deals with the design and simulation of a solar power system consisting of a KC200GT solar panel, a closed loop boost converter and a three phase inverter by using Matlab / Simulink. The mathematical equations of the solar panel design are presented. The electrical characteristics of the panel are tested at the values of 1000 for light radiation and 25 °C for temperature environment. The Proportional Integral (PI) controller is connected as feedback with the Boost converter to obtain a stable output voltage by reducing the oscillations in the voltage to charge a battery connected to the output of the converter. Two methods (Particle Swarm Optimization (PSO) and Zeigler- Nichols) are used for tuning
... Show MoreStandards play a vital role in documenting the values of new test results in the form of tables. They are one of the basic requirements that the standardization process aims for as a complement to standardizing test procedures, and contribute to knowing the current reality of the student. The degree of readiness and level as a result of practicing different exercises for sports activities, in addition to the possibility of adopting it for comparison with his group or similar groups, classification, prediction and selection. Developing the skill of handling the football in the educational field is an important matter for achieving distinguished performance among students. This skill requires a level of accuracy, speed and control, and
... Show MoreKey-frame selection plays an important role in facial expression recognition systems. It helps in selecting the most representative frames that capture the different poses of the face. The effect of the number of selected keyframes has been studied in this paper to find its impact on the final accuracy of the emotion recognition system. Dynamic and static information is employed to select the most effective key-frames of the facial video with a short response time. Firstly, the absolute difference between the successive frames is used to reduce the number of frames and select the candidate ones which then contribute to the clustering process. The static-based information of the reduced sets of frames is then given to the fuzzy C-Means algor
... Show MoreThe primary aim of the study was to find out the values of some biomechanical variables for the long serve skill in badminton and to identify the effect of biomechanical feedback on the performance of long serve. The present study had a single group, pre-post experimental study design. The research community was determined by the intentional method of one group with a pre-and post-test. The players of the Assyrian badminton club constituted the research community. A total of 12 players were present in the research community. The badminton players falling within the age group of 15-17 years for the season 2020-2021 were recruited as the participants for the study. A total of five players were selected as the participant
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