Iraqi crude Atmospheric residual fraction supplied from al-Dura refinery was treated to remove metals contaminants by solvent extraction method, with various hydrocarbon solvents and concentrations. The extraction method using three different type solvent (n-hexane, n-heptane, and light naphtha) were found to be effective for removal of oil-soluble metals from heavy atmospheric residual fraction. Different solvents with using three different hydrocarbon solvents (n-hexane, n-heptane, and light naphtha) .different variables were studied solvent/oil ratios (4/1, 8/1, 10/1, 12/1, and 15/1), different intervals of perceptual (15, 30-60, 90 and 120 min) and different temperature (30, 45, 60 and 90 °C) were used. The metals removal perce

Iraqi crude Atmospheric residual fraction supplied from al-Dura refinery was treated to remove metals contaminants by solvent extraction method, with various hydrocarbon solvents and concentrations. The extraction method using three different type solvent (n-hexane, n-heptane, and light naphtha) were found to be effective for removal of oil-soluble metals from heavy atmospheric residual fraction. Different solvents with using three different hydrocarbon solvents (n-hexane, n-heptane, and light naphtha) .different variables were studied solvent/oil ratios (4/1, 8/1, 10/1, 12/1, and 15/1), different intervals of perceptual (15, 30-60, 90 and 120 min) and different temperature (30, 45, 60 and 90 °C) were used. The metals removal percent we

Iron oxide(Fe3O4) nanoparticles of different sizes and shapes were synthesized by solve-hydrothermal reaction assisted by microwave irradiation using ferrous ammonium sulfate as a metal precursor, oleic acid as dispersing agent, ethanol as reducing agent and NaOH as precipitating agent at pH=12. The synthesized Fe3O4 nano particles were characterized by X-ray diffraction (XRD), FTIR and thermal analysis TG-DTG. Sizes and shapes of Fe3O4 nanoparticles were characterized by Scanning Electron Microscopy (SEM), and atomic force microscopy (AFM).

Roller compacted concrete (RCC) is a special type of concrete with zero or even negative slump consistency. In this work, it had aimed to produce an RCC mix suitable for roads paving with minimum cost and better engineering properties so, different RCC mixes had prepared i.e. (M1, M2, M3, and M4) using specified percentages of micro natural silica sand powder (SSP) as partial replacement of (0%, 5%, 10%, and 20%) by weight of sulfate resistant Portland cement. Additionally, M-sand, crushed stone, filler, and water had been used. The results had obtained after 28 days of water curing. The control mix (M1) had satisfied the required f ‘c with accepted results for the other tests. M2 mix with SSP of 5% had

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]).

As material flow cost accounting technology focuses on the most efficient use of resources like energy and materials while minimizing negative environmental effects, the research aims to show how this technology can be applied to promote green productivity and its reflection in attaining sustainable development. In addition to studying sustainability, which helps to reduce environmental impacts and increase green productivity, the research aims to demonstrate the knowledge bases for accounting for the costs of material flow and green productivity. It also studies the technology of accounting for the costs of material flow in achieving sustainable development and the role of green productivity in achieving sustainable development. According

This research a study model of linear regression problem of autocorrelation of random error is spread when a normal distribution as used in linear regression analysis for relationship between variables and through this relationship can predict the value of a variable with the values of other variables, and was comparing methods (method of least squares, method of the average un-weighted, Thiel method and Laplace method) using the mean square error (MSE) boxes and simulation and the study included fore sizes of samples (15, 30, 60, 100). The results showed that the least-squares method is best, applying the fore methods of buckwheat production data and the cultivated area of the provinces of Iraq for years (2010), (2011), (2012),

Time and space are indispensable basics in cinematic art. They contain the characters, their actions and the nature of events, as well as their expressive abilities to express many ideas and information. However, the process of collecting space and time in one term is space-time, and it is one of Einstein’s theoretical propositions, who sees that Time is an added dimension within the place, so the study here differs from the previous one, and this is what the researcher determined in the topic of his research, which was titled (The Dramatic Function of Space-Time Variables in the Narrative Film), Which included the following: The research problem, which crystallized in the following question: What is the dramatic function of the tempor

This paper discusses reliability R of the (2+1) Cascade model of inverse Weibull distribution. Reliability is to be found when strength-stress distributed is inverse Weibull random variables with unknown scale parameter and known shape parameter. Six estimation methods (Maximum likelihood, Moment, Least Square, Weighted Least Square, Regression and Percentile) are used to estimate reliability. There is a comparison between six different estimation methods by the simulation study by MATLAB 2016, using two statistical criteria Mean square error and Mean Absolute Percentage Error, where it is found that best estimator between the six estimators is Maximum likelihood estimation method.