This research was one of the terms that used by Al-Bazzar  in his musnad and this term was  (Al-azza) who launched on some ways and hadiths and I collected those narration, and I have graduated and studied it to access to the meaning which Al-Bazzar want that from this description. In the introduction of the research, I have mention the importance of the subject and the reasons for his selection and also my plan,  a preface where I mentioned the definition of Al-Bazzar and his musnad, then in the first section I defined Al-azza linguistically and idiomatically , the second section I studied the hadiths that Al-Bazzar described them with azza ,and then I conclude it with my results that I have reach

The aim of this research is to estimate the parameters of the linear regression model with errors following ARFIMA model by using wavelet method depending on maximum likelihood and approaching general least square as well as ordinary least square. We use the estimators in practical application on real data, which were the monthly data of Inflation and Dollar exchange rate obtained from the (CSO) Central Statistical organization for the period from 1/2005 to 12/2015. The results proved that (WML) was the most reliable and efficient from the other estimators, also the results provide that the changing of fractional difference parameter (d) doesn’t effect on the results.

       In this paper, a fixed point theorem of nonexpansive mapping is established to study the existence and sufficient conditions for the controllability of nonlinear fractional control systems in reflexive Banach spaces. The result so obtained have been modified and developed in arbitrary space having Opial’s condition by using fixed point theorem deals with nonexpansive mapping defined on a set has normal structure. An application is provided to show the effectiveness of the obtained result.

The current study aimed to adopt a method for inducing callus cells and regenerating the important common red bean using different types of growth regulators such as N6-benzylaminopurine (BAP), Naphthalene acetic acid (NAA), and Thidiazuron (TDZ). Different types of common bean pinto cultivar explants, such as internodes, cotyledons and roots, were inoculated on Murashige and Skoog medium (MS) provided with different combinations of plant growth regulators, including 1- BAP (5 mg/l) 2-BAP (4.5 mg/l) NAA (0.5 mg/l), 3- BAP (4.5 mg/l), and TDZ (0.1mg/l). Callus was initiated on MS culture medium supplied with 5 mg/l BAP for all explants (internodes, cotyledons, and roots) at 50, 20, and 10% respectively, while adding NAA with 0.5mg/l showed

Wireless sensor networks (WSNs) are emerging in various application like military, area monitoring, health monitoring, industry monitoring and many more. The challenges of the successful WSN application are the energy consumption problem. since the small, portable batteries integrated into the sensor chips cannot be re-charged easily from an economical point of view. This work focusses on prolonging the network lifetime of WSNs by reducing and balancing energy consumption during routing process from hop number point of view. In this paper, performance simulation was done between two types of protocols LEACH that uses single hop path and MODLEACH that uses multi hop path by using Intel Care i3 CPU (2.13GHz) laptop with MATLAB (R2014a). Th

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