In this paper, an algorithm is suggested to train a single layer feedforward neural network to function as a heteroassociative memory. This algorithm enhances the ability of the memory to recall the stored patterns when partially described noisy inputs patterns are presented. The algorithm relies on adapting the standard delta rule by introducing new terms, first order term and second order term to it. Results show that the heteroassociative neural network trained with this algorithm perfectly recalls the desired stored pattern when 1.6% and 3.2% special partially described noisy inputs patterns are presented.

It is very difficult to obtain the value of a rock strength along the wellbore.  The value of Rock strength utilizing to perform different analysis, for example, preventing failure of the wellbore, deciding a completion design and, control the production of sand.  In this study, utilizing sonic log data from (Bu-50) and (BU-47) wells at Buzurgan oil field.  Five formations have been studied (Mishrif, Sadia, Middle lower Kirkuk, Upper Kirkuk, and Jaddala) Firstly, calculated unconfined compressive strength (UCS) for each formation, using a sonic log method.  Then, the derived confined compressive rock strengthens from (UCS) by entering the effect of bore and hydrostatic pressure for each formation.  Evaluations th

This study presents a practical method for solving fractional order delay variational problems. The fractional derivative is given in the Caputo sense. The suggested approach is based on the Laplace transform and the shifted Legendre polynomials by approximating the candidate function by the shifted Legendre series with unknown coefficients yet to be determined. The proposed method converts the fractional order delay variational problem into a set of (n ＋ 1) algebraic equations, where the solution to the resultant equation provides us the unknown coefficients of the terminated series that have been utilized to approximate the solution to the considered variational problem. Illustrative examples are given to show that the recommended appro

Praise to Allah, Lord of the Worlds. Thank you very much. Blessed. As his face should be majestic and great. His authority, and may peace and blessings be upon our master Muhammad, a perpetual blessing until the Day of Judgment

And upon the God of purity, His righteous companions, and those who follow them in righteousness until the Day of Judgment. But after:-

Anyone who looks into the history of nations, peoples, and the conditions of human beings will see that naturalization as a person’s affiliation to a particular state is something that happened only in recent centuries. In ancient times, a person’s loyalty was to the tribe to which the person belonged, and he was integrated into it and attributed to it, and in

     Social media and news agencies are major sources for tracking news and events. With these sources' massive amounts of data, it is easy to spread false or misleading information. Given the great dangers of fake news to societies, previous studies have given great attention to detecting it and limiting its impact. As such, this work aims to use modern deep learning techniques to detect Arabic fake news. In the proposed system, the attention model is adapted with bidirectional long-short-term memory (Bi-LSTM) to identify the most informative words in the sentence. Then, a multi-layer perceptron (MLP) is applied to classify news articles as fake or real. The experiments are conducted on a newly launched Arabic dataset called the Ara

In this paper, we proposed a modified Hestenes-Stiefel (HS) conjugate
gradient method. This achieves a high order accuracy in approximating the second
order curvature information of the objective function by utilizing the modified
secant condition which is proposed by Babaie-Kafaki [1], also we derive a nonquadratic
conjugate gradient model. The important property of the suggestion
method that is satisfy the descent property and global convergence independent of
the accuracy of the line search. In addition, we prove the global convergence under
some suitable conditions, and we reported the numerical results under these
conditions.

Background: Selenium-73 with half- life of 7.15 hour emits β+ in nature and has six stable isotopes which are ( 74Se,76Se,77Se,78Se,80Se and 82Se ). Selenium-73 has many applications in technology and radioselenium compounds of metallic have found various applications in medicine. Objective:  To make a comparison between different reactions that produced cross sections of Se-73 radioisotopes. Subjects and methods: The feasibility of the production of Selenium -73 via various nuclear reactions was investigated. Excitation functions of 73Se production by the reactions of 75As (p,3n), 169Tm( d,x), 74Se, natSe, natBr (p,x) , 75As (d,4n), natGe (3He,x), 70Ge (α, n), and 72Ge (α, 3n) and neutron capture were calculated using the avail

This work, deals with Kumaraswamy distribution. Kumaraswamy (1976, 1978) showed well known probability distribution functions such as the normal, beta and log-normal but in (1980) Kumaraswamy developed a more general probability density function for double bounded random processes, which is known as Kumaraswamy’s distribution. Classical maximum likelihood and Bayes methods estimator are used to estimate the unknown shape parameter (b). Reliability function are obtained using symmetric loss functions by using three types of informative priors two single priors and one double prior. In addition, a comparison is made for the performance of these estimators with respect to the numerical solution which are found using expansion method. The