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Deep Oxidative Desulfurization of Model fuels by Prepared Nano TiO2 with Phosphotungstic acid
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In this study, nano TiO2 was prepared with titanium isopropoxide (TTIP) as a resource to titanium oxide. The catalyst was synthesized using phosphotungstic acid (PTA) and, stearyl trimethyl ammonium bromide (STAB) was used as the structure-directing material. Characterization of the product was done by the X-ray diffraction (XRD), X-ray fluorescent spectroscopy (XRF), nitrogen adsorption/desorption measurements, Atomic Force Microscope (AFM) and Fourier transform infrared (FTIR) spectra, were used to characterize the calcined TiO2 nanoparticles by STAB and PWA. The TiO2 nanomaterials were prepared in three crystalline forms (amorphous, anatase, anatase-rutile). The results showed that the nanoparticles of anatase TiO2 have good catalytic oxidative activity. This is because of the conversions of 100% within 90 sec from 300 ppm of dibenzothiophene. This is compared to conversion rates for anatase–rutile nanoparticles and amorphous nanoparticles which reached 52% and 31 %, respectively. The influence of the temperature of reaction, catalyst amount, H2O2 concentration, and initial DBT concentration on the oxidation of DBT was investigated.  

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Publication Date
Fri Mar 01 2019
Journal Name
Iraqi Journal Of Physics
Structural and optical properties of Fe- doped ZnO thin films prepared by Sol–Gel spin coating process and their photocatalytic activities
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Pure and Fe-doped zinc oxide nanocrystalline films were prepared
via a sol–gel method using -
C for 2 h.
The thin films were prepared and characterized by X-ray diffraction
(XRD), atomic force microscopy (AFM), field emission scanning
electron microscopy (FE-SEM) and UV- visible spectroscopy. The
XRD results showed that ZnO has hexagonal wurtzite structure and
the Fe ions were well incorporated into the ZnO structure. As the Fe
level increased from 2 wt% to 8 wt%, the crystallite size reduced in
comparison with the pure ZnO. The transmittance spectra were then
recorded at wavelengths ranging from 300 nm to 1000 nm. The
optical band gap energy of spin-coated films also decreased as Fe
doping concentra

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Publication Date
Sat Apr 15 2023
Journal Name
Iraqi Journal Of Science
Preparation and Characterization of Yttrium Oxide Nanoparticles at Different Calcination Temperatures from Yttrium Hydroxide Prepared by Hydrothermal and Hydrothermal microwave Methods
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The Synthesis of yttrium oxide nanoparticles have been achieved via calcination
of yttrium hydroxide produced from the reaction of aqueous solutions of yttrium
nitrate and sodium hydroxide at pH = 13 using hydrothermal and hydrothermal
microwave methods. Effect of heat treatment of the resulted yttrium hydroxide
powder on the morphology and crystallinity of the resulting oxide was studied at
calcination 500, 700 and 1000°C to obtain. The resulted products were
characterized by means of X-ray diffraction (XRD), scanning electron microscope
(SEM), atomic force microscope (AFM), Fourier transform infrared spectrometer
(FTIR) and thermal analyses (TG).

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Publication Date
Sun Mar 03 2019
Journal Name
Diyala Journal For Pure Scince
Study influence of thickness and electrode mater on some electrical properties for ZnSe thin films prepared by thermal evaporation in vacuum
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Thin films of Zinc Selenide ZnSe have been prepared by using thermal evaporation in vacuum technique (10-5Torr) with thickness (1000, 2700, 4000) A0 and change electrode material and deposited on glass substrates with temperature (373K) and study some electrical properties at this temperature . The graphs shows linear relation between current and voltage and the results have shown increases in the value of current and electrical conductivity with increase thickness and change electrode material from Aluminum to Copper

Publication Date
Wed Jan 02 2019
Journal Name
International Journal Of Agricultural & Statistical Sciences
RESPONSE OF OLIVE SEEDLINGS TO HUMIC ACID AND INOCULATION BY FUNGI (TRICHODERMA SSP) AND THE INTERACTION OF THEM AND IRRIGATION BY SALT WATER ON VEGETATIVE GROWTH.
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Publication Date
Sat Dec 03 2022
Journal Name
Al-kut University College Of Humanities
Deep understanding skills in chemistry among middle school students
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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
3D scenes semantic segmentation using deep learning based Survey
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Abstract<p>Semantic segmentation realization and understanding is a stringent task not just for computer vision but also in the researches of the sciences of earth, semantic segmentation decompose compound architectures in one elements, the most mutual object in a civil outside or inside senses must classified then reinforced with information meaning of all object, it’s a method for labeling and clustering point cloud automatically. Three dimensions natural scenes classification need a point cloud dataset to representation data format as input, many challenge appeared with working of 3d data like: little number, resolution and accurate of three Dimensional dataset . Deep learning now is the po</p> ... Show More
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Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Science
A Review for Arabic Sentiment Analysis Using Deep Learning
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     Sentiment Analysis is a research field that studies human opinion, sentiment, evaluation, and emotions towards entities such as products, services, organizations, events, topics, and their attributes. It is also a task of natural language processing. However, sentiment analysis research has mainly been carried out for the English language. Although the Arabic language is one of the most used languages on the Internet, only a few studies have focused on Arabic language sentiment analysis.

     In this paper, a review of the most important research works in the field of Arabic text sentiment analysis using deep learning algorithms is presented. This review illustrates the main steps used in these studies, which include

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Publication Date
Thu Mar 30 2023
Journal Name
Iraqi Journal Of Science
Facial Expression Recognition Based on Deep Learning: An Overview
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      Recognizing facial expressions and emotions is a basic skill that is learned at an early age and it is important for human social interaction. Facial expressions are one of the most powerful natural and immediate means that humans use to express their feelings and intentions. Therefore, automatic emotion recognition based on facial expressions become an interesting area in research, which had been introduced and applied in many areas such as security, safety health, and human machine interface (HMI). Facial expression recognition transition from controlled environmental conditions and their improvement and succession of recent deep learning approaches from different areas made facial expression representation mostly based on u

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Publication Date
Fri Jun 30 2023
Journal Name
Iraqi Journal Of Science
Satellite Image Classification using Spectral Signature and Deep Learning
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    When images are customized to identify changes that have occurred using techniques such as spectral signature, which can be used to extract features, they can be of great value. In this paper, it was proposed to use the spectral signature to extract information from satellite images and then classify them into four categories. Here it is based on a set of data from the Kaggle satellite imagery website that represents different categories such as clouds, deserts, water, and green areas. After preprocessing these images, the data is transformed into a spectral signature using the Fast Fourier Transform (FFT) algorithm. Then the data of each image is reduced by selecting the top 20 features and transforming them from a two-dimensiona

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Publication Date
Mon Jan 01 2024
Journal Name
Computers, Materials &amp; Continua
Credit Card Fraud Detection Using Improved Deep Learning Models
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