The Mauddud Formation was one of the important and widespread Lower Cretaceous period formations in Iraq. It has been studied in three wells (EB. 55, EB. 58, and EB. 59) within the East Baghdad Oil Field, Baghdad, central Iraq. 280 thin sections were studied by microscope to determine fauna, the formation composed of limestone and dolomitized limestone in some parts which tends to be marl in some parts, forty species and genus of benthic foraminifera have been identified beside algae and other fossils, three biozones have been identified in the range which is: Orbitolina qatarica range zone (Late Albian), Orbitolina sefini range zone (Late Albian – Early Cenomanian) and Orbitolina concava range zone (Early Cenomanian), The age of

The Quantitative high-resolution planktonic foraminiferal analysis of the subsurface section in three selected wells in the Ajeel Oil Field (Aj-8, Aj-12, and Aj-15) in Tikrit Governorate, Central Iraq has revealed that Shiranish Formation deposited in Late Campanian- Latest Maastrichtian age. This formation consists mainly of marly and marly limestone yielding diverse planktonic foraminiferal assemblages and calcareous benthic foraminifera, with a total of 46 species that belong to 23 genera, Three zones and four subzones, which cover the Late Campanian to the Latest Maastrichtian, were identified based on the recorded planktonic foraminifera and their ranges. They are as follows:1. Globotruncana aegyptiaca Zone that dated to be Lat

    Shiranish has been studied at Hijran section near Erbil city, NE Iraq. Fifty two thin-sections were prepared to study them under polarized microscope, to determine the petrographic component, organic content and digenetic processes. Rock units subdivided into four rock beds, as follows: dolostone, foraminiferal biomicrite, poorly washed biomicrite and micrite. Vertical succession of Shiranish Formation refers to off-shore quite marine environment.

Passive optical network (PON) is a point to multipoint, bidirectional, high rate optical network for data communication. Different standards of PONs are being implemented, first of all PON was ATM PON (APON) which evolved in Broadband PON (BPON). The two major types are Ethernet PON (EPON) and Gigabit passive optical network (GPON). PON with these different standards is called xPON. To have an efficient performance for the last two standards of PON, some important issues will considered. In our work we will integrate a network with different queuing models such M/M/1 and M/M/m model. After analyzing IPACT as a DBA scheme for this integrated network, we modulate cycle time, traffic load, throughput, utilization and overall delay

Imitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing co