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

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

The maximization of the net present value of the investment in oil field improvements is greatly aided by the optimization of well location, which plays a significant role in the production of oil. However, using of optimization methods in well placement developments is exceedingly difficult since the well placement optimization scenario involves a large number of choice variables, objective functions, and restrictions. In addition, a wide variety of computational approaches, both traditional and unconventional, have been applied in order to maximize the efficiency of well installation operations. This research demonstrates how optimization approaches used in well placement have progressed since the last time they were examined. Fol

     The research aims to study and analysis of concurrent engineering (CE) and cost optimization (CO), and the use of concurrent engineering inputs to outputs to improve the cost, and the statement of the role of concurrent engineering in improving the quality of the product, and achieve savings in the design and manufacturing time and assembly and reduce costs, as well as employing some models to determine how much the savings in time, including the model (Lexmark) model (Pert) to determine the savings in design time for manufacturing and assembly time.

To achieve the search objectives, the General Company for Electrical and Electronic Industries \ Refrigerated Engine

Laser shock peening (LSP) is deemed as a deep-rooted technology for stimulating compressive residual stresses below the surface of metallic elements. As a result, fatigue lifespan is improved, and the substance properties become further resistant to wear and corrosion. The LSP provides more unfailing surface treatment and a potential decrease in microstructural damage. Laser shock peening is a well-organized method measured up to the mechanical shoot peening. This kind of surface handling can be fulfilled via an intense laser pulse focused on a substantial surface in extremely shorter intervals. In this work, Hydrofluoric Acid (HF) and pure water as a coating layer were utilized as a new technique to improve the properti

The present study aimed to evaluate the concentration of Malon dialdehyde (MDA) in pregnant women during different stages of pregnancy (stage of pregnancy, abortion, contraceptives and parity number).The study included (120) blood samples from normal pregnant women in age of the procreating were subdivided into three trimesters of pregnancy (40/group), and (40) samples from non-pregnant women as a control group. The results showed a significant increase in MDA in three stages of pregnancy compared with the control group. The concentration of MDA increased significantly in pregnant women with multipregnancy when compared with pregnant women for the first time, and in pregnant women whom was using contraceptions compared with p

The present research  investigates joints welding of 304L austenitic stainless steel using metal inert gas (MIG) welding method. The research explores the effect of process parameters (arc voltage, wire feed rate, and electrode wire diameter) on the mechanical properties of stainless steel.  The above variables are varied  respectively with 18.5, 19, 19.5 V, 116, 127, 137 mm/s, and 0.8, 1, 1.2 mm, with E308L as a filler electrode. The design matrix of the experiments was determined using the design of experiment (DOE) program Minitab 17 based on the levels of input elements used. The Taguchi orthogonal matrix methodology (Taguchi) technique was used to develop some empirical analysis for the maximum tensile strength and proper surface