The prophet was against the monopoly . He warned the monopolies with great punishment . inspite of the high price in his time, he did not price , so did the rightely guided caliphes and the ummayads . Umar b abid al-aziz had been asked to price but he refused and said ―the prophet said ― ― God grieves ,pleases and fixes price ―
The monopoly was declard announce in the third and the fourth centuries of A.H . because of the weakness of the Islamis State and it’s failure to find the real reasons of it’s existence. Besides that they used the guaranty system in collecting the money . The guaranted shared in monopoly the food-stuff and sold it in high price .Add to that the foreign control on the executive power ,not to be menti

Bedside clinical teaching is a fundamental part of the medical education that offers invaluable opportunities for the students to build and improve their clinical and communication skills. However, there is a growing concern about the increasing refusal of patients to participate in clinical sessions, especially in certain settings where there are sensitive cultural traditions and decreased trust in institutions.

Rutting is a crucial concern impacting asphalt concrete pavements’ stability and long-term performance, negatively affecting vehicle drivers’ comfort and safety. This research aims to evaluate the permanent deformation of pavement under different traffic and environmental conditions using an Artificial Neural Network (ANN) prediction model. The model was built based on the outcomes of an experimental uniaxial repeated loading test of 306 cylindrical specimens. Twelve independent variables representing the materials’ properties, mix design parameters, loading settings, and environmental conditions were implemented in the model, resulting in a total of 3214 data points. The network accomplished high prediction accuracy with an R

The large number of failure in electrical power plant leads to the sudden stopping of work. In some cases, the necessary reserve materials are not available for maintenance which leads to interrupt of power generation in the electrical power plant unit. The present study, deals with the determination of availability aspects of generator in unit 5 of Al-Dourra electric power plant. In order to evaluate this generator's availability performance, a wide range of studies have been conducted to gather accurate information at the level of detail considered suitable to achieve the availability analysis aim. The Weibull Distribution is used to perform the reliability analysis via Minitab 17, and Artificial Neural Networks (ANNs) by approaching o

This growing interest of the international scientific specialized commissions is due to the role that the audit committee can play, as one of companies’ governance tools, to increase the accuracy and transparency of the financial information disclosed by the companies, through its oversight role on the process of preparing financial reports, its supervision on the internal audit function within the companies, and supporting its independency, as well as coordinating the efforts between the internal control unites and the external auditor represented by the (Board of Supreme Audit) to clear the observations and irregularities in order to reduce the fraud cases.

This research was built on an applied sample of audit committee works

The Estimation Of The Reliability Function Depends On The Accuracy Of The Data Used To Estimate The Parameters Of The Probability distribution, and Because Some Data Suffer from a Skew in their Data to Estimate the Parameters and Calculate the Reliability Function in light of the Presence of Some Skew in the Data, there must be a Distribution that has flexibility in dealing with that Data. As in the data of Diyala Company for Electrical Industries, as it was observed that there was a positive twisting in the data collected from the Power and Machinery Department, which required distribution that deals with those data and searches for methods that accommodate this problem and lead to accurate estimates of the reliability function,