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

Reservoir study has been developed in order to get a full interesting of the Nahr Umr formation in Ratawi oil field. Oil in place has been calculated for Nahr Umr which was 2981.37 MM BBL. Several runs have been performed to get matching between measured and calculated of oil production data and well test pressure. In order to get the optimum performance of Nahr Umr many strategies have been proposed in this study where vertical and horizontal wells were involved in addition to different production rates. The reservoir was first assumed to be developed with vertical wells only using production rate of (80000–125000) STB/day. The reservoir is also proposed to produce using horizontal wells besides vertical wells with production rat

Bentonite is widely used in industrial applications. The present study reports the effect of adding different weights of ZnO to the Iraqi bentonite, on surface area, pore volume and real density. These surface properties were evaluated for pure and modified bentonite. The modification was made by adding different ZnO weights such as; ( 0.5%, 1%, 5%, 10% ). The effect of heat exposing for all modified clay samples at 500 ?C have been also evaluated. The results show that the addition of 0.5% ZnO leads to increase the surface area percentage about 36%, increase pore volume percentage about 5.48% and increase the real density percentage about 27.116%. When the samples exposed to 500 ?C, their surface area and pore volumes have been decreased a

One of the most frightening to children ages pre-school entry , Are those concerns about natural phenomena such as (The darkness, the sound of thunder, lightning and light, and rainfall, and storms) These natural phenomena are not familiar to the child , It may have a surprise when he/ she sees , And others intimidated , The affects of panic and fears that may lead him some psychological injury symptoms.

The fear of the dark, of the most common concerns associated with the child in his daily life , As the children's fear of the dark is reasonably fear that makes him a natural to live in the unknown  , We can not identify what around him and is afraid of something collision,  Or injury from somet

A piezoelectric cantilever beam with a tip mass at its free end is a common energy harvester configuration. This article introduces a new principle of designing such a harvester that increases the generated power without changing the resonance frequency of the harvester: the attraction force between two permanent magnets is used to add stiffness to the system. This magnetic stiffening counters the effect of the tip mass on the efficient operation frequency. Five set-ups incorporating piezoelectric bimorph cantilevers of the same type in different mechanical configurations are compared theoretically and experimentally to investigate the feasibility of this principle: theoretical and experimental results show that magnetically stiffened harve

The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm