Abstract Software-Defined Networking (commonly referred to as SDN) is a newer paradigm that develops the concept of a software-driven network by separating data and control planes. It can handle the traditional network problems. However, this excellent architecture is subjected to various security threats. One of these issues is the distributed denial of service (DDoS) attack, which is difficult to contain in this kind of software-based network. Several security solutions have been proposed recently to secure SDN against DDoS attacks. This paper aims to analyze and discuss machine learning-based systems for SDN security networks from DDoS attack. The results have indicated that the algorithms for machine learning can be used to detect DDoS

Fisetin is a plant flavonoid found in strawberries and other fruits and vegetables such as apples, persimmons, and onions. It has many pharmacological effects like anti-inflammatory, antioxidant, cardioprotective, neuroprotective, and anti-carcinogenicity which are attributed to its ability to reduce oxidative stress which considers the main reason for different disease conditions. Genotoxicity refers to the genetic material destruction within the cell which can be caused by different chemicals as well as radiation. The present study evaluates the effect of orally-administered fisetin daily for seven constitutive days on genotoxicity induced by cyclophosphamide in rats’ bone marrow and spleen cells. Results showed that fisetin exh

Many reports confirm ulcers as an adverse effect of drugs such as nicorandil and aspirin. The exact responsible mechanisms of ulceration have until now not proved. Mucosal ulcers associated with the onset of ulcer are manifested by an increase in proinflammatory cytokine, excessive prostaglandin, and up-regulation of Endothilin-1 level, which directly impacts the release of leptin. These, released locally within mucosal tissues, have played a role in controlling the extent of local inflammatory responses and processes of mucosal repair.
This study was designed to find out the correlation of plasma leptin and prostaglandin levels as a possible mechanism of oral ulcer formation as an adverse effect of nicorandil. The effect of nicorandi

The present study aimed to explain the dose-dependent possible deleterious effects of 30 day administration of Tramadol on some hematological and biochemical parameters of laboratory male rats (Rattus norvegicus), the study consisted of eighteen adult male rats randomly divided into three equal groups (each of six). Group 1 (control) were treated by intraperitoneal injection of normal saline solution (0.2 ml), group two (low dose) was treated by intraperitonealy (i.p) injection of Tramadol at a dose of 50 mg/kg/day, group three (high dose) was treated by intraperitonealy injection of Tramadol at a dose of 100 mg/kg/day for 30 days. At the end of experimental period, rats were sacrificed. Blood were collected by cardiac puncture to inv

Background: Obesity is becoming the healthcare epidemic world wide.Obesity is associated with reduced life expectancy, increased morbidity and mortality, and greater healthcare costs.Bariatric surgery is the only effective treatment for morbid obesity and is gaining increasing popularity. There has been a steady rise in the numbers and types of bariatric operations done worldwide in recent years butnon of prove to be ideal .Animal studies and use of animal models are significant element in the evolution of medical knowledge and the use of animals as a model for bariatric surgery is of importance to study the mechanisms of these operationsa and also help to develop new technique in management of obesity.Objectives:Study of effects of slee

This study explains the effect of non-thermal (cold) plasma on wound of diabetic rats by (FE-DBD) system, 3cm probe diameter is used. The output power was ranged from (12-20) W. The effect of non-thermal plasma on wounds of a diabetic was observed with different exposure durations (20,30) sec., the plasma exposure duration decreases the sugar level in blood and the diameter of the wound. These results indicate the cold plasma can be used to enhance the insulin level (i.e., blood sugar) and wounds treatment.

Background: This study aims to investigate the effect of fixed orthodontic appliances and/or antihypertensive drugs on the weight of experimental rats. Materials and Methods: Thir-ty-six male Wistar albino rats were subjected to a split-mouth design study, in which an orthodontic appliance was inserted in one side to move the first molar mesially for 2 weeks while the other side acted as a control to tooth movement. The rats were allocated into three groups: group A (n = 12), without any pharmacological treatment; group B (n = 12), subcu-taneous injection of bisoprolol fumarate (5 mg/kg) daily; and group C (n = 12), subcutaneous injection of valsartan (10 mg/kg) daily. A fixed orthodontic appliance with a closing coil spring delivering 5

Leuciscidae species are the abundant and widely distributed fish species in Iraq's inland waters. They are complex species, and morphology makes them difficult to identify. Molecular analysis achieved and confirmed the morphological characters. Twenty specimens of Acanthobrama marmid were collected from two localities at Tigris River, in the middle of Iraq; 15 specimens from the Al-Zubaydia sub-district and five specimens from Al-Tharthar Lake. We used the mitochondrial DNA cytochrome b (cytb) gene to sequence the DNA of A. marmid. The following analysis are compared the sequences with those of other fish genera and species found in the Gene Bank. The barcoding result (DNA sequencing) in fishes found in the same family (Leuciscidae) showed

The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet