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

The problem of divorce from the phenomena that characterized the nature of privacy,
although their impact beyond the individual to include the community as a whole, the parties
to the relationship affected by divorce caused them harm moral and material for a long time,
resulting imbalance in the personal relationship and family and social relations because of the
high divorce rates, particularly in Iraq high rates of 28690 thousand cases in 2004 to 59 515
thousand cases in 2011 and an increase of more than (100%) during the period above, and this
rise caused by aggravation of many of the problems led the reasons for social, economic and
incompatibility spouses, health and lack of reproduction, not spending The wife a

In this study, a mathematical model is presented to study the chemisorption of two interacting atoms on solid surface in the presence of laser field. Our mathematical model is based on the occupation numbers formula that depends on the laser field which we derived according to Anderson model for single atom adsorbed on solid surface. Occupation numbers formula and chemisorption energy formula are derived for two interacting atoms (as a diatomic molecule) as they approach to the surface taking into account the correlation effects on each atom and between atoms. This model is characterized by obvious dependence of all relations on the system variables and the laser field characteristics which gives precise description for the molecule –

wind load coefficient

Assessing the accuracy of classification algorithms is paramount as it provides insights into reliability and effectiveness in solving real-world problems. Accuracy examination is essential in any remote sensing-based classification practice, given that classification maps consistently include misclassified pixels and classification misconceptions. In this study, two imaginary satellites for Duhok province, Iraq, were captured at regular intervals, and the photos were analyzed using spatial analysis tools to provide supervised classifications. Some processes were conducted to enhance the categorization, like smoothing. The classification results indicate that Duhok province is divided into four classes: vegetation cover, buildings,

With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect

اثناء تفاعل الديزنة تكونت صبغة أزو جديدة عن طريق تفاعل 3-امينوفينول مع 2,4,6-ثلاثي هيدروكسي اسيتوفينون . ثم تم تفاعل هذا الليكاند مع بعض ايونات العناصر الكروم والحديد الروديوم والروثينيوم بتكفؤهم الثلاثي والكوبلت الثنائي والموليبدينوم سداسي التكافؤ مكونة معقدات فلزية مختلفة بأشكال هندسية متعددة. تم ملاحظة تناسق مجموعة الازو مع ايونات العناصر من خلال ملاحظة ظهور حزم امتصاص الفلز مع النتروجين والاوكسجين ب

At atmospheric pressure and at a frequency of 9.1 kHz, a constructed magnetically stabilized tornado gliding arc discharge (MSGAD) system was utilized in this study to generate a non-thermal plasma with an alternating voltage source from 2,4,6,8 to 10 kV. Argon gas was used to generate the arc plasma with an adjustable flow rate using a flow meter regulator to stabilize the gas flow rate to 2 L/min. A gliding plasma discharge is achieved by a magnetic field for the purpose of a planned investigation. The influence of the magnetically stabilized tornado gliding arc discharge parameters such as magnetic field and applied voltage on microscopic tornado plasma parameters was studied. The electron temperature1was measured using a Boltzmann plot