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bsj-6046
Synthesis and Characterization of New nano catalyst Mo-Ni /TiO2- γAl2O3 for Hydrodesulphurization of Iraqi Gas Oil
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   A new nano-sized NiMo/TiO2-γ-Al2O3 was prepared as a Hydrodesulphurization catalyst for Iraqi gas oil with sulfur content of 8980 ppm, supplied from Al-Dura Refinery. Sol-gel method was used to prepare TiO2- γ-Al2O3 nano catalyst support with 64% TiO2, 32% Al2O3, Ni-Mo/TiO-γ-Al2O3 catalyst was prepared under vacuum impregnation conditions to loading metals with percentage 3.8 wt.% and 14 wt.% for nickel and molybdenum respectively while the percentage for alumina, and titanium became 21.7, and 58.61 respectively. The synthesized TiO2- γ-Al2O3 nanocomposites and Ni-Mo /TiO2- γ-Al2O3 Nano catalyst were then characterized by XRD, AFM, and BET surface area, SEM, XRF, and FTIR. The performance of the synthesized catalyst for removing sulfur compounds was conducted through the pilot HDS laboratory unit, various temperatures range 275oC to 375°C, LHSV 1 h-1 were studied; moreover, the effect of LHSV 1 to 4 h-1 on the percentage of sulfur removal was also studied at the temperature of the best removal with constant pressure 35 bar and H2/HC ratio 200cm3/200cm3. The sulfur content results generally revealed that there was a substantial decrease at all operating conditions used, while the maximum sulfur removal was 87.75% in gas oil on Ni-Mo/TiO2-γ-Al2O3 catalyst at temperature 375˚C and LHSV 1h-1.

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Publication Date
Fri Jun 01 2018
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The tax planning and its effect on the investment: On sample of Iraqi Contribution Company
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The importance of the current study  lies in the  importance of the  Tax policy that  being considered one of the most important tools working on fulfilling  the  social,  financial  and economic  goals  and improving  the investment environment  in the country  to become  having the ability to  activate the  national economy. The current study  has  referred  that  (  Has  the  tax planning  practiced by  the Iraqi  contribution  companies  led to increase  the  far-term tax  outcome through  getting  benefit of   the monetary  funds  and expansion in&nbs

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Publication Date
Thu Jan 01 2015
Journal Name
International Journal Of Advanced Research
UV Photovoltaic detector based on Bi doped TiO2 Fabricated by Pulse Laser Deposition
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Pure and doped TiO 2 with Bi films are obtained by pulse laser deposition technique at RT under vacume 10-3 mbar, and the influence of Bi content on the photocvoltaic properties of TiO 2 hetrojunctions is studied. All the films display photovoltaic in the near visible region. A broad double peaks are observed around λ= 300nm for pure TiO 2 at RT in the spectral response of the photocurrent, which corresponds approximately to the absorption edge and this peak shift to higher wavelength (600 nm) when Bi content increase by 7% then decrease by 9%. The result is confirmed with the decreasing of the energy gap in optical properties. Also, the increasing is due to an increase in the amount of Bi content, and shifted to 400nm when annealed at 523

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Publication Date
Mon Nov 01 2010
Journal Name
Iraqi Journal Of Physics
New Technique for Treatment of the dust accumulation from PV solar panels surface
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One of the most important problems facing the world today is the energy problem. The solution was in finding renewable energy sources such as solar energy. The solar energy applications in Iraq is facing many problems . One of the most important problems is the accumulation of dust on the solar panels surface which causes decreasing its performance sharply. In the present work, a new technique was presented by using two-axis solar tracking system to reduce the accumulated dust on the solar panel surface and compared it with the fixed solar panels which installed at tilt angles 30° and 45°. The results indicated that the maximum losses of the output power due to accumulation of dust on the fixed solar panels is about 31.4% and 23.1% res

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Publication Date
Mon Apr 01 2019
Journal Name
Journal Of Engineering
Design of New Hybrid Neural Controller for Nonlinear CSTR System based on Identification
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This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

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Publication Date
Tue Dec 03 2013
Journal Name
Ibn Al-haitham Journal For Pure And Applied Science
New adaptive satellite image classification technique for al Habbinya region west of Iraq
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Publication Date
Mon Dec 30 2024
Journal Name
Iraqi Journal Of Science
Study of Corrosion Inhibition for Some New Schiff Bases Synthesized from Quinazolinone Derivative
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In this work, new Schiff bases of quinazolinone derivatives (Q1-Q5) were synthesized from methyl anthranilate. The synthesis involved three steps. In the first step, methyl anthranilate was reacted with isothiocyanatobenzene, producing the thiourea derivative K1. The second step entailed reacting K1 with hydrazine hydrate, synthesizing 3-amino-2-(phenylamino) quinazolin-4(3H)-one (K2). The third step involved reaction of K2 with various aromatic aldehydes, yielding the Schiff bases derivatives Q1-Q5. The chemical structures of these compounds were identified by FT-IR,1H NMR and 13C NMR spectroscopy. The newly synthesized derivatives (Q1-Q5) were subjected to rigorous evaluation to assess their efficacy as corrosion inhibitors for ca

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Publication Date
Mon Jan 01 2018
Journal Name
Image And Video Technology: 8th Pacific-rim Symposium
A New Scheme for QoE Management of Live Video Streaming in Cloud Environment
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Publication Date
Sun Aug 13 2023
Journal Name
Arpn Journal Of Engineering And Applied Sciences
A NEW APPROACH FOR MODELLING THE VIBRATION OF BEAMS UNDER MOVING LOAD EFFECT
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In this paper, a new equivalent lumped parameter model is proposed for describing the vibration of beams under the moving load effect. Also, an analytical formula for calculating such vibration for low-speed loads is presented. Furthermore, a MATLAB/Simulink model is introduced to give a simple and accurate solution that can be used to design beams subjected to any moving loads, i.e., loads of any magnitude and speed. In general, the proposed Simulink model can be used much easier than the alternative FEM software, which is usually used in designing such beams. The obtained results from the analytical formula and the proposed Simulink model were compared with those obtained from Ansys R19.0, and very good agreement has been shown. I

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Publication Date
Fri Mar 01 2024
Journal Name
Journal Of Applied Spectroscopy
Spectrophotometric Method for Determination of Cu(II) Using a New Schiff Base Ligand
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The Cu(II) was found using a quick and uncomplicated procedure that involved reacting it with a freshly synthesized ligand to create an orange complex that had an absorbance peak of 481.5 nm in an acidic solution. The best conditions for the formation of the complex were studied from the concentration of the ligand, medium, the eff ect of the addition sequence, the eff ect of temperature, and the time of complex formation. The results obtained are scatter plot extending from 0.1–9 ppm and a linear range from 0.1–7 ppm. Relative standard deviation (RSD%) for n = 8 is less than 0.5, recovery % (R%) within acceptable values, correlation coeffi cient (r) equal 0.9986, coeffi cient of determination (r2) equal to 0.9973, and percentage capita

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Publication Date
Sat Apr 15 2023
Journal Name
Journal Of Robotics
A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

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