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

Background: Surgical injury to alveolar bone can temporarily accelerate tooth movement by increasing the remodeling rate of alveolar bone. The purpose of this study was to clinically evaluate maxillary canine retraction acceleration with corticotomy-facilitated orthodontics, and its effect on vitality of pulp and gingival sulcus depth. Materials and method: The sample consisted of 12 adult patients (4 males, 8 females; mean age, 21.7 years) requiring the therapeutic extraction of the maxillary first premolars, with subsequent retraction of the maxillary canines. Surgical holes were done mesially and distally to the side with more space between canine and second premolar, and the other side served as the control. Canine retraction was done

Electro coagulation treatment was used for zinc removal from electroplating wastewater of the State Company for Electrical Industries . This wastewater, here consists zinc ions with maximum concentration in solution of 90 ppm .

The parameters that influenced the wastewater treatment are: current density in the range  1-1.4 mA/cm2, pH  in the range 5-10, temperature in the range 25-45°C and time in the range 10-180 minute.

The research is a laboratory experimental type using batch system for electrical process with direct current. The cell comprised of aluminum electrode as anode and stainless steel electrode as cathode. Thirty experiments and one hundred fifty sample lab tests were carried out in this research

Background. The use of modern aids and technology has contributed greatly to football development, the goalkeeper is the most important position in the team, and the use of devices gave objective readings about the goalkeeper's ability in terms of skill and physical aspects. Objectives. The research aimed to prepare exercises using an electronic device to measure the knee bending angle because of its great importance in developing the skill of catching and dimensions of the high ball for football goalkeepers. Methods. The researchers used the experimental method, and the sample consisted of (4) male goalkeepers under 15 years of age, one of the research procedures was to determine the biomechanical variables affecting the development of the

BACKGROUND: Transverse fractures of the patella are important fractures with a wide variety of subtypes, the common incidence in the age group of 20–50 years. Surgical interference aims to achieve a perfect alignment of the joint surface, in addition to rigid fixation of the fracture for early re-habitation and early movement to retain the extensor mechanism of the knee joint. AIM: The aim of this study was to compare the radiological and functional outcomes of the displaced transverse patella fracture in adult patients treated by ORIF using tension band wiring versus cannulated screws with wiring. METHODS: A prospective analytic comparative study was conducted in Al-Kindy Teaching Hospital/Baghdad/Iraq for 18 months from Apr

<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver ope