Some of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems.  Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic.  Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance.  In this study, two different sets of select

Lost circulation or losses in drilling fluid is one of the most important problems in the oil and gas industry, and it appeared at the beginning of this industry, which caused many problems during the drilling process, which may lead to closing the well and stopping the drilling process. The drilling muds are relatively expensive, especially the muds that contain oil-based mud or that contain special additives, so it is not economically beneficial to waste and lose these muds. The treatment of drilling fluid losses is also somewhat expensive as a result of the wasted time that it caused, as well as the high cost of materials used in the treatment such as heavy materials, cement, and others. The best way to deal with drilling fluid losses

Background and Aim. Coronary artery disease (CAD) is a major risk factor for the progression to heart failure (HF), which is associated with an increase in left ventricular volume (LVV). This study aims to measure ventricular function and myocardial perfusion imaging markers of the left side of the heart, which can be performed with injection of a 99mTc at stress and rest by using single-photonemission-computed-tomography (SPECT). Subject and methods. The study included 121 patients with CAD, comprising 53 females and 68 males with ages between 25 to 88 years and 265 healthy subjects comprising 84 males and 181 females. All patients and healthy subjects volunteered to participate in this study. They were classified according to

Background: Benign Prostate Hypertrophy(BPH)is a common urological problem worldwide which is defined as denomatous hyperplasia of the periurethralpart of prostate gland that occurs especially in men over 50 years old and that tend to obstruct urination by constriction the urethra Objectives: The study was aimed to investigate the level of Malondialdehyde (MDA), Nitric Oxide (NO) and Superoxide Dismutase (SOD) as an antioxidant, besides other factors such as the level of Lipids Profile (Total Chlosterol (TC), High Density Lipoprotein Cholesterol (HDL-C), Low Density Lipoprotein Cholesterol (LDL-C), Very Low Density Lipoprotein Cholesterol (VLDL-C), and Triglyceride (TG))in patients suffer from BPH . Methods: In this study ;clinical ,spec

Background: The aim of this study was to determine phototoxic effect of visible blue light on anaerobic periodontal pathogens namely Aggregatibacter actinomycetemcomitans and Porphyromonas gingivalis. Materials and methods: Strains of Aggregatibacter actinomycetemcomitans and Porphyromonas gingivalis were isolated from pockets of systemically healthy patients aged between 35-55 years old with pocket depths of 5-6 mm, the bacteria cultured on special blood Agar plates solid media, then subjected to visible blue light emitted from commercially available light cure devise (LED curing light); that emits blue light (400-500nm) of 1000mw energy at different periods of time exposures, then the CFU of each plate was measured by direct colony count

Convolutional Neural Networks (CNN) have high performance in the fields of object recognition and classification. The strength of CNNs comes from the fact that they are able to extract information from raw-pixel content and learn features automatically. Feature extraction and classification algorithms can be either hand-crafted or Deep Learning (DL) based. DL detection approaches can be either two stages (region proposal approaches) detector or a single stage (non-region proposal approach) detector. Region proposal-based techniques include R-CNN, Fast RCNN, and Faster RCNN. Non-region proposal-based techniques include Single Shot Detector (SSD) and You Only Look Once (YOLO). We are going to compare the speed and accuracy of Faster RCNN,

The present study evaluates the effects of Ginkgo biloba extract as monotherapy on the glycemic status, insulin resistance (IR), body mass index (BMI), and visceral adiposity index (VAI), in addition to the inflammatory markers, oxidative status and leptin level in patients with metabolic syndrome in comparison with metformin.

The study is a randomized, double-blind pilot study conducted during the period May to September, 2020. Fifty patients were recruited in the study and they were allocated into two groups (25 per each group): Ginkgo biloba and Metformin groups, they received (120 mg Ginkgo biloba extract/ capsule) and (500 mg Metformin/ capsule) respectively; orally as a single dose for 90 days. Blood samples were taken at z

Background: Anemia of chronic disease (ACD) occurs in the presence of chronic infection, inflammatory conditions or neoplastic conditions despite of adequate iron and vitamins storage. Gingivitis is the inflammation of the gingiva, periodontitis is the inflammation in the periodontium that extend deeper with loss of connective tissue attachment and supporting bone. The main pathogenesis of periodontal diseases and ACD is immune activation. Aims of study: Determine and compare the clinical periodontal parameters (plaque index (PLI), gingival index (GI), bleeding on probing (BOP), probing pocket depth (PPD) and clinical attachment level (CAL)). Evaluate the hematocrit (Hct) level, red blood cells (RBCs) count and white blood cells (WBCs) c