The aim of this work is to study a modified version of the four-dimensional Lotka-Volterra model. In this model, all of the four species grow logistically. This model has at most sixteen possible equilibrium points. Five of them always exist without any restriction on the parameters of the model, while the existence of the other points is subject to the fulfillment of some necessary and sufficient conditions. Eight of the points of equilibrium are unstable and the rest are locally asymptotically stable under certain conditions, In addition, a basin of attraction found for each point that can be asymptotically locally stable. Conditions are provided to ensure that all solutions are bounded. Finally, numerical simulations are given to veri

The present work provides theoretical investigation of laser photoacoustic one dimensional imaging to detect a blood vessel or tumor embedded within normal tissue. The key task in photoacoustic imaging is to have acoustic signal that help to determine the size and location of the target object inside normal tissue. The analytical simulation used a spherical wave model representing target object (blood vessel or tumor) inside normal tissue. A computer program in MATLAB environment has been written to realize this simulation. This model generates time resolved acoustic wave signal that include both expansion and contraction parts of the wave. The photoacoustic signal from the target object is simulated for a range of laser pulse duration 1

        Every finite dimensional normed algebra is isomorphic to the finite direct product of  or , it is also proved these algebras are ultrasemiprime algebras. In this paper, the ultrasemiprime proof of the finite direct product of  and  is generalized to the finite direct product of any ultrasemiprime algebras.

In this paper , it is shown that if is a semiprime ring and  a centralizer of  such that

This paper focuses on developing a self-starting numerical approach that can be used for direct integration of higher-order initial value problems of Ordinary Differential Equations. The method is derived from power series approximation with the resulting equations discretized at the selected grid and off-grid points. The method is applied in a block-by-block approach as a numerical integrator of higher-order initial value problems. The basic properties of the block method are investigated to authenticate its performance and then implemented with some tested experiments to validate the accuracy and convergence of the method.

  Twenty binary liquid crystalline mixture diagrams were investigated with polarizing microscope and differential scanning calorimeter (DSC). Four binary mixture diagrams were constructed to identify the smectic phase which is found to be the same in all components of the homologous series (4-n-alkoxy -2, 3, 5, 6-tetra methyl-4-n-alkoxy azo benzene) (nPA4M). The fifth binary mixture diagram was between the (6PA4M) and the reference liquid crystal compound, terephthlylidene-bis (4-n-butylanaline) (TBAA) to   identify the type of smectic mesophase of these compounds, and the results obtained were compared with the literature. To study the effect of the 4 methyl lateral groups on the thermotropic behavior of the (nPA4M) homol

An algebra has been constructed from a (D, A)-stacked algebra A, under the conditions that , A 1 and . It is shown that when the construction of algebra B is built from a (D, A)-stacked monomial algebra A then B is a d-Koszul monomial algebra.

The aim of this paper is to construct cyclic subgroups of the projective general linear group over  from the companion matrix, and then form caps of various degrees in . Geometric properties of these caps as secant distributions and index distributions are given and determined if they are complete. Also, partitioned of  into disjoint lines is discussed.

Abstract:

      In this research we discussed the parameter estimation and variable selection in Tobit quantile regression model in present of multicollinearity problem. We used elastic net technique as an important technique for dealing with both multicollinearity and variable selection. Depending on the data we proposed Bayesian Tobit hierarchical model with four level prior distributions . We assumed both tuning parameter are random variable and estimated them with the other unknown parameter in the model .Simulation study was used for explain the efficiency of the proposed method and then we compared our approach with (Alhamzwi 2014 & standard QR) .The result illustrated that our approach

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D