In our work present, the application of strong-Lensing observations for some gravitational lenses have been adopted to study the geometry of the universe and to explain the physics and the size of the quasars. The first procedure was to study the geometrical of the Lensing system to determine the relation between the redshift of the gravitational observations with its distances. The second procedure was to compare between the angular diameter distances "DA" calculated from the Euclidean case with that from the Freedman models, then evaluating the diameter of the system lens. The results concluded that the phenomena are restricted to the ratio of distance between lens and source with the diameter of the lens noticing.
In this paper, for the first time we introduce a new four-parameter model called the Gumbel- Pareto distribution by using the T-X method. We obtain some of its mathematical properties. Some structural properties of the new distribution are studied. The method of maximum likelihood is used for estimating the model parameters. Numerical illustration and an application to a real data set are given to show the flexibility and potentiality of the new model.
Owing to their remarkable characteristics, refractory molybdenum nitride (MoN x )-based compounds have been deployed in a wide range of strategic industrial applications. This review reports the electronic and structural properties that render MoN x materials as potent catalytic surfaces for numerous chemical reactions and surveys the syntheses, procedures, and catalytic applications in pertinent industries such as the petroleum industry. In particular, hydrogenation, hydrodesulfurization, and hydrodeoxygenation are essential processes in the refinement of oil segments and their conversions into commodity fuels and platform chemicals. N-vacant sites over a catalyst’s surface are a significant driver of diverse chemical phenomena. Studies
... Show MoreOwing to their remarkable characteristics, refractory molybdenum nitride (MoNx)-based compounds have been deployed in a wide range of strategic industrial applications. This review reports the electronic and structural properties that render MoNx materials as potent catalytic surfaces for numerous chemical reactions and surveys the syntheses, procedures, and catalytic applications in pertinent industries such as the petroleum industry. In particular, hydrogenation, hydrodesulfurization, and hydrodeoxygenation are essential processes in the refinement of oil segments and their conversions into commodity fuels and platform chemicals. N-vacant sites over a catalyst’s surface are a significant driver of diverse chemical phenomena. Studies on
... Show MoreThis paper presents seven modified Adomian Decomposition Method (ADM) techniques for efficiently solving initial value problems, especially those involving non-homogeneous and nonlinear differential equations. While the classical ADM is effective for linear homogeneous cases, it has difficulties solving more complex problems. The proposed modifications—from MADM1 to MLADM—include Maclaurin and Taylor expansions, Laplace transforms, and single-step iterations.• These modifications enhance convergence, reduce complexity, and improve accuracy.• Each method offers specific advantages, such as accelerating convergence (MADM2, RADM4), simplifying computation (TSADM5), and achieving higher accuracy (MLADM).• Numerical examples confirm th
... Show Morethe electron correlation effect for inter-shell can be described by evaluating the fermi hole and partial fermi hole for Li atom comparing with Be+ and B+2 ions
Artificial Neural Networks (ANN) is one of the important statistical methods that are widely used in a range of applications in various fields, which simulates the work of the human brain in terms of receiving a signal, processing data in a human cell and sending to the next cell. It is a system consisting of a number of modules (layers) linked together (input, hidden, output). A comparison was made between three types of neural networks (Feed Forward Neural Network (FFNN), Back propagation network (BPL), Recurrent Neural Network (RNN). he study found that the lowest false prediction rate was for the recurrentt network architecture and using the Data on graduate students at the College of Administration and Economics, Univer
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