Classifying an overlapping object is one of the main challenges faced by researchers who work in object detection and recognition. Most of the available algorithms that have been developed are only able to classify or recognize objects which are either individually separated from each other or a single object in a scene(s), but not overlapping kitchen utensil objects. In this project, Faster R-CNN and YOLOv5 algorithms were proposed to detect and classify an overlapping object in a kitchen area.  The YOLOv5 and Faster R-CNN were applied to overlapping objects where the filter or kernel that are expected to be able to separate the overlapping object in the dedicated layer of applying models. A kitchen utensil benchmark image database and

In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve

P. aeruginosa is a famous bacterium that causes several diseases and has a high ability to be a multidrug resistant organism that is linked with the formation of biofilm. This study aimed to investigate tssC1 gene role in the resistance of different antibiotics in the presence of biofilm. We constructed biofilm for the isolates under the study and showed the effect of different antibiotics on biofilm formation and maturation. The presence of the gene was detected through achieving PCR reaction. Finally, tssC1 gene variation was determined through sequencing and aligning the sequencing products. The results showed that most of the isolates (80%) formed biofilm that played a role in the resistance of different antibiotics which could

A tungsten inert gas (TIG) welding is one of the most popular kinds of welding used to join metals mainly for aluminum alloys.  However, many challenges may be met with this kind of joining process; these challenges arise from decay of mechanical properties of welded materials. In the present study, an attempt was made to enhancing the mechanical properties of TIG weld joint of 6061-T6 aluminum alloy by hardening the surfaces using shoot peening technique. To optimize the shoot peening process three times of exposure (5, 10, and 15) min. was used. All peened and unpeened, and welded and unwelded samples were  characterized by metallographic test to indicate the phase transformation and modification in microstructure occurring d

A liquid-solid chromatography of Bovine Serum Albumin (BSA) on (diethylaminoethyl-cellulose) DEAE-cellulose adsorbent is worked experimentally, to study the effect of changing the influent concentration of (0.125, 0.25, 0.5, and 1 mg/ml) at constant volumetric flow rate Q=1ml/min. And the effect of changing the volumetric flow rate (1, 3, 5, and 10 ml/min) at constant influent concentration of Co=0.125mg/ml. By using a glass column of (1.5cm) I.D and (50cm) length, packed with adsorbent of DEAE-cellulose of height (7cm). The influent is introduced in to the column using peristaltic pump and the effluent concentration is investigated using UV-spectrophotometer at 30oC and 280nm wavelength. A spread (steeper) break-through curve is gained