You Mohammed, you're prophet of God and I'm Gabriel)). With this heavenly call which Mohammed, the messenger of God (may God's mercies be on him), got and when he left Hiraa cave and after getting the aye ((read with your God's name)), a new period of mankind's history started. From that time, the greatest state was established. There was no public treasury and no public financial resources at that time. Abu Baker (God bless him) spent a lot of money to support the costs of the new mission. After Al-Hijra, the bases of establishing the Islamic state were available but it lacked administrative and financial organizing. Therefore the prophet was very keen to find Islamic system which ensures justice and availability of

The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed

In this research, we find the Bayesian formulas and the estimation of Bayesian expectation for product system of Atlas Company.  The units of the system have been examined by helping the technical staff at the company and by providing a real data the company which manufacturer the system.  This real data include the failed units for each drawn sample, which represents the total number of the manufacturer units by the company system.  We calculate the range for each estimator by using the Maximum Likelihood estimator.  We obtain that the expectation-Bayesian estimation is better than the Bayesian estimator of the different partially samples which were drawn from the product system after  it checked by the

Abstract

The term public budget defects became nowadays a chronic, economical phenomenon, almost all the countries weather advanced or development country suffered from it, despite the different visions to economic schools of a thought to accept or reject the deficit in public budget but the prevailed opinion that is needed to rule the role of the state by reducing the public spending which led to continuous deficits in public budget and the consequent upon increase in government borrowing, increase taxes on income and wealth, thus weakening the in contrive for private investment which contributed to the increase of in flationary stagnation, it became a duty to state covered by the lack of financial sources

This study employs evolutionary optimization and Artificial Intelligence algorithms to determine an individual’s age using a single-faced image as the basis for the identification process. Additionally, we used the WIKI dataset, widely considered the most comprehensive collection of facial images to date, including descriptions of age and gender attributes. However, estimating age from facial images is a recent topic of study, even though much research has been undertaken on establishing chronological age from facial photographs. Retrained artificial neural networks are used for classification after applying reprocessing and optimization techniques to achieve this goal. It is possible that the difficulty of determining age could be reduce

<p><span>A Botnet is one of many attacks that can execute malicious tasks and develop continuously. Therefore, current research introduces a comparison framework, called BotDetectorFW, with classification and complexity improvements for the detection of Botnet attack using CICIDS2017 dataset. It is a free online dataset consist of several attacks with high-dimensions features. The process of feature selection is a significant step to obtain the least features by eliminating irrelated features and consequently reduces the detection time. This process implemented inside BotDetectorFW using two steps; data clustering and five distance measure formulas (cosine, dice, driver &amp; kroeber, overlap, and pearson correlation