The Electric Discharge (EDM) method is a novel thermoelectric manufacturing technique in which materials are removed by a controlled spark erosion process between two electrodes immersed in a dielectric medium. Because of the difficulties of EDM, determining the optimum cutting parameters to improve cutting performance is extremely tough. As a result, optimizing operating parameters is a critical processing step, particularly for non-traditional machining process like EDM. Adequate selection of processing parameters for the EDM process does not provide ideal conditions, due to the unpredictable processing time required for a given function. Models of Multiple Regression and Genetic Algorithm are considered as effective methods for determ

Utilizing the modern technologies in agriculture such as subsurface water retention techniques were developed to improve water storage capacities in the root zone depth. Moreover, this technique was maximizing the reduction in irrigation losses and increasing the water use efficiency. In this paper, a polyethylene membrane was installed within the root zone of okra crop through the spring growing season 2017 inside the greenhouse to improve water use efficiency and water productivity of okra crop. The research work was conducted in the field located in the north of Babylon Governorate in Sadat Al Hindiya Township seventy-eight kilometers from Baghdad city. Three treatments plots were used for the comparison using surface

Physics and applied mathematics form the basis for understanding natural phenomena using differential equations depicting the flow in porous media, the motion of viscous liquids, and the propagation of waves. These equations provide a thorough study of physical processes, enhancing the understanding of complex applications in engineering, technology, and medicine. This paper presents novel approximate solutions for the Darcy-Brinkmann-Forchheimer moment equation, the Blasius equation and the FalknerSkan equation with initial / boundary conditions by using two iterative methods: the variational iteration method and the optimal variational iteration method. The variational iteration method is effectively developed by adding a control paramete

Porosity is important because it reflects the presence of oil reserves. Hence, the number of underground reserves and a direct influence on the essential petrophysical parameters, such as permeability and saturation, are related to connected pores. Also, the selection of perforation interval and recommended drilling additional infill wells. For the estimation two distinct methods are used to obtain the results: the first method is based on conventional equations that utilize porosity logs. In contrast, the second approach relies on statistical methods based on making matrices dependent on rock and fluid composition and solving the equations (matrices) instantaneously. In which records have entered as equations, and the matrix is sol

Two nanocomposite corrosion inhibitors were synthesized from Aloe vera extract: one incorporating sodium thiosulfate and the other silver nitrate. Both nanocomposites were subjected to structural characterization using atomic force microscopy (AFM), which revealed distinct morphological features. The sodium thiosulfate-based nanocomposite exhibited uniform and well-dispersed nanoparticles with an average size of 47.51 nm, suggesting a stable and homogeneous distribution. In contrast, the silver nitrate-based nanocomposite displayed slightly larger particles with an average diameter of 58.34 nm, indicating a tendency toward moderate aggregation. The corrosion inhibition performance of these nanocomposites for carbon steel (CS1137) was invest

In this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func