The present study develops an artificial neural network (ANN) to model an analysis and a simulation of the correlation between the average corrosion rate carbon steel and the effective parameter Reynolds number (Re), water concentration (Wc) % temperature (T o) with constant of PH 7 . The water, produced fom oil in Kirkuk oil field in Iraq from well no. k184-Depth2200ft., has been used as a corrosive media and specimen area (400 mm2) for the materials that were used as low carbon steel pipe. The pipes are supplied by Doura Refinery . The used flow system is all made of Q.V.F glass, and the circulation of the two –phase (liquid – liquid ) is affected using a Q.V.F pump .The input parameters of the model consists of Reynolds number , water concentration and temperature. The output is average corrosion rate .The performance of the two training algorithms, gradient descent with momentum and Levenberg-Marquardt, are compared to select the most suitable training algorithm for corrosion rate model. The model can be used to calculate the average corrosion rate properties of carbon steel alloy as functions of Reynolds number, water concentration and temperature. Accordingly, the combined influence of these effective parameters and the average corrosion rate is simulated. The results show that the corrosion rate increases with the increase of temperature, Reynolds number and the increase of water concentration.
In the present work, experimental tests was done to explain the effect of insulation and water level on the yield output. Linear basin, single slope solar still used to do this purpose. The test was done from May to August 2017 in Mosul City-Iraq (Latitude: Longitude: Elevation: 200 m, and South-East face). Experimental results showed that the yield output of the still increased by 20.785% and 19.864% in case of using thermal insulation at 4cm and 5cm respectively, also the yield output decrease by 15.134% as the water level increase from 4 to 5cm, with the presence of insulation and 14.147% without it. It has been conclude that the insulation and water level play important role in the process of passive
... Show MoreObjective(s): The aim of this study was to assess the severity of anemia among children under 5 years and to find
out relationship between severity of anemia in children with socio-demographic variables such as: child gender,
age, supplement diet, hookworm, pica, parent's education level, father's and mother's occupation, and family
monthly income with severity of anemia
Methodology: A descriptive cross sectional study was conducted at the primary health care centers in Alsadr city
for the period of 1
st July 2011 to the 1st November 2011.Non probability (purposive) sample of (630) children who
aged under 5 years and who attended to primary health care centers of Alsadr city. The data were collected
through using
The aim of this paper is to approximate multidimensional functions f∈C(R^s) by developing a new type of Feedforward neural networks (FFNS) which we called it Greedy ridge function neural networks (GRGFNNS). Also, we introduce a modification to the greedy algorithm which is used to train the greedy ridge function neural networks. An error bound are introduced in Sobolov space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result in [1]).
The aim of this study is to describe the leech species that are used in some of the alternative medicine clinics in Baghdad Province based on morphometric measurements and colouring pattern of the body. A collection of twenty leeches was provided from some clinics. All specimens were identified and described based on standard available keys. The morphometric characteristics and colouring patterns were recorded and the indicated that these leeches were Hirudo orientalis Utevsky & Trontelj, 2005 and H. verbana Carena, 1820.
Phase-change materials (PCMs) have a remarkable potential for use as efficient energy storage means. However, their poor response rates during energy storage and retrieval modes require the use of heat transfer enhancers to combat these limitations. This research marks the first attempt to explore the potential of dimple-shaped fins for the enhancement of PCM thermal response in a shell-and-tube casing. Fin arrays with different dimensions and diverse distribution patterns were designed and studied to assess the effect of modifying the fin geometric parameters and distribution patterns in various spatial zones of the physical domain. The results indicate that increasing the number of
Background/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the
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