Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system

In cyber security, the most crucial subject in information security is user authentication. Robust text-based password methods may offer a certain level of protection. Strong passwords are hard to remember, though, so people who use them frequently write them on paper or store them in file for computer .Numerous of computer systems, networks, and Internet-based environments have experimented with using graphical authentication techniques for user authentication in recent years. The two main characteristics of all graphical passwords are their security and usability. Regretfully, none of these methods could adequately address both of these factors concurrently. The ISO usability standards and associated characteristics for graphical

Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither no

THE PROBLEM OF TRANSLATING METAPHOR IN AN ARTISTIC TEXT (ON THE MATERIAL OF RUSSIAN AND ARABIC LANGUAGES)

Background: acrylic resin denture base consider a common denture base material for its acceptable cost, aesthetic and easy processing but still has disadvantages including easy of fracture and low impact strength. Material and method: The experimental group was prepared by addition of 15% phosphoric acid 2-hydroxyethyl methacrylate ester (PA2HEME) with polymethyl methacrylate monomer; the experimental groups was compared with the control one. The specimens were prepared according to ADA specification No. 12 with dimension 65 mm x 10 mm x2.5 mm (length x width x thickness respectively). The prepared specimens were tested by three-point flexural strength utilizing Instron Universal Testing Machine (WDW, Layree Technology Co.), Shore D hard

In this paper the reinforced materials manufactured from steel continues fibers are used in Aluminum matrix to build a composite material. Most of researches concentrated on reinforced materials and its position in the matrix according to its size and distribution, and their effects on the magnitude of different kinds of the stresses, so this paper presents and concentrate on the geometrical shape of reinforced material and its effects on the internal stresses and strains on the composite strength using FEM as a method for analysis after loaded by certain force showing the deference magnitudes of stresses according to the different geometrical shapes of reinforced materials.

Objectives: Maxillofacial silicone is used to restore abnormalities due to congenital or acquired causes. However, the quality of silicone is far from ideal. This study was aimed at assessing the influence of the addition of cellulose nanofibers (CNFs; several nanometers wide and 2-5 micro m long) on the physical and mechanical characteristics of maxillofacial silicone elastomers. Methods: Two CNF weight percentages (0.5% and 1%) were tested, and 180 specimens were divided into one control and two experimental groups. Each group was subdivided into six subgroups. In each subgroup, ten specimens subjected to each of the following tests: tearing strength, Shore-A hardness, tensile strength, elongation percentage, surface roughness, and color