Abstract

 This study investigated the optimization of wear behavior of AISI 4340 steel based on the Taguchi method under various testing conditions. In this paper, a neural network and the Taguchi design method have been implemented for minimizing the wear rate in 4340 steel. A back-propagation neural network (BPNN) was developed to predict the wear rate. In the development of a predictive model, wear parameters like sliding speed, applying load and sliding distance were considered as the input model variables of the AISI 4340 steel. An analysis of variance (ANOVA) was used to determine the significant parameter affecting the wear rate. Finally, the Taguchi approach was applied to determine

Rivers Tigris and Euphrates, as well as the wetlands in southern Iraq and the Diyala River, were all included in the evaluation of earlier studies on the variety and factors impacting fish in Iraqi waters. Different studies documented different types, and the number of species recorded varied between the studies, which could be explained by the registration of some species, synonyms, differs from the registration of some species with synonymous names By mistake, as well as recording new species in times that followed some previous studies, Also, the difference in some factors, including the pollution of some waterways, leads to a difference in the existing species, so we find the presence of species that are tolerant of pollution. There are

Copper plasma is generated with the existence of an external magnetic field and without its presence utilizing Nd:YAG laser (1064 nm ,9 ns) in different  pulse laser energy which ranges from(100 to 400) mJ in a vacuum. Plasma parameter beta ) is least than 1, this indicates that the existence of magnetic field confinement effect is proven. Note that both the electron temperature and electron density increases with the laser pulse energy increasing , Both are higher in the presence of a magnetic field.

The study of Mars's ionosphere was made by investigating the measurements of the electron density (Ne) depending of the variation of the solar activities through different local time, different seasons, and different altitudes. The datasets has been taken from MARSIS on board the Mars Express spacecraft, the investigation for the solar indices and the electron density (Ne) have been made for two period of time depending on the strength of the geomagnetic storms, the first one was taken when the geomagnetic storms was low as in years (1998 & 2005), the data was chosen for three seasons of these years, Winter (December), Summer (June) and Spring (April). The second period was taken for the years (2001 & 2002) when the geomagnetic s

The study of Mars's ionosphere was made by investigating the measurements of the electron density (Ne) depending of the variation of the solar activities through different local time, different seasons, and different altitudes. The datasets has been taken from MARSIS on board the Mars Express spacecraft, the investigation for the solar indices and the electron density (Ne) have been made for two period of time depending on the strength of the geomagnetic storms, the first one was taken when the geomagnetic storms was low as in years (1998 & 2005), the data was chosen for three seasons of these years, Winter (December), Summer (June) and Spring (April). The second period was taken for the years (2001 & 2002) when the geomagnetic s

Abstract

Robust controller design requires a proper definition of uncertainty bounds. These uncertainty bounds are commonly selected randomly and conservatively for certain stability, without regard for controller performance.  This issue becomes critically important for multivariable systems with high nonlinearities, as in Active Magnetic Bearings (AMB) System. Flexibility and advanced learning abilities of intelligent techniques make them appealing for uncertainty estimation. The aim of this paper is to describe the development of robust H₂/H_∞ controller for AMB based on intelligent estimation of uncertainty bounds using Adaptive Neuro Fuzzy Inference System (ANFIS).  Simulatio

In this paper, new brain tumour detection method is discovered whereby the normal slices are disassembled from the abnormal ones. Three main phases are deployed including the extraction of the cerebral tissue, the detection of abnormal block and the mechanism of fine-tuning and finally the detection of abnormal slice according to the detected abnormal blocks. Through experimental tests, progress made by the suggested means is assessed and verified. As a result, in terms of qualitative assessment, it is found that the performance of proposed method is satisfactory and may contribute to the development of reliable MRI brain tumour diagnosis and treatments.

    Mixed spinel Mg_1-xZn_xFe₂O₄ ferrites (where x = 0, 0.2, 0.4, and 0.6) nanoparticles were synthesized by using microwave-assisted combustion route. As-synthesized powdered samples were checked by XRD analysis, field emission-scanning electron microscopy, and vibration sample magnetometer to investigate the structural,   morphology, and magnetic properties, respectively. XRD results exhibited that the crystallite size increases with the decrease of Zn⁺² ion concentration for series of mixed spinel Mg_1-xZn_xFe₂O₄ ferrite expect x=0.2. All the mixed spinel Mg_1-xZn_xFe₂O₄ ferrite has different gr