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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
Tue Apr 30 2024
Journal Name
Iraqi Journal Of Science
Crescent Moon Visibility: A New Criterion using Deep learned Artificial Neural-Network
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     Many authors investigated the problem of the early visibility of the new crescent moon after the conjunction and proposed many criteria addressing this issue in the literature. This article presented a proposed criterion for early crescent moon sighting based on a deep-learned pattern recognizer artificial neural network (ANN) performance. Moon sight datasets were collected from various sources and used to learn the ANN. The new criterion relied on the crescent width and the arc of vision from the edge of the crescent bright limb. The result of that criterion was a control value indicating the moon's visibility condition, which separated the datasets into four regions: invisible, telescope only, probably visible, and certai

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Arabic Speech Classification Method Based on Padding and Deep Learning Neural Network
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Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to

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Publication Date
Mon Nov 21 2022
Journal Name
Sensors
Deep Learning-Based Computer-Aided Diagnosis (CAD): Applications for Medical Image Datasets
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Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

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Publication Date
Tue Jul 01 2025
Journal Name
Ain Shams Engineering Journal
Deep neural networks for speech enhancement and speech recognition: A systematic review
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Publication Date
Tue Jul 01 2025
Journal Name
Ain Shams Engineering Journal
Deep neural networks for speech enhancement and speech recognition: A systematic review
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Publication Date
Wed May 10 2023
Journal Name
Journal Of Engineering
DOUBLE DIFFUSIVE FREE CONVECTION IN A PACKED BED SQUARE ENCLOSURE BY USING LOCAL THERMAL NON-EQUILIBRIUM (LTNE) MODEL
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In the present study, free convection heat and mass transfer of fluid in a square packed bed enclosure is numerically investigated. For the considered geometrical shape, the left vertical wall of enclosure was assumed to be kept at high temperature and concentration while the opposite wall was kept at low temperature and concentration with insulating both the top and bottom walls of enclosure. The Brinkman– Forchheimer extended Darcy model was used to solve the momentum equations, while the energy equations for fluid and solid phases were solved by using the local thermal non-equilibrium (LTNE) model.Computations are performed for a range of the Darcy number from 10-5 to 10-1, the porosity from 0.5 to 0.9, and buoyancy ratio from -15 t

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Publication Date
Thu Jun 30 2011
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
CRACKING ACTIVITY OF PREPARED Y-ZEOLITE CATALYST USING CUMENE ON FLUIDIZED BED REACTOR
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The catalytic activity of faujasite type NaY catalysts prepared from local clay (kaolin) with different Si/Al ratio was studied using cumene cracking as a model for catalytic cracking process in the temperature range of 450-525° C, weight hourly space velocity (WHSV) of 5-20 h1, particle size ≤75μm and atmospheric pressure. The catalytic activity was investigated using experimental laboratory plant scale of fluidized bed reactor.
It was found that the cumene conversion increases with increasing temperature and decreasing WHSV. At 525° C and WHSV 5 h-1, the conversion was 42.36 and 35.43 mol% for catalyst with 3.54 Si/Al ratio and Catalyst with 5.75 Si/Al ratio, respectively, while at 450° C and at the same WHSV, the conversion w

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Publication Date
Fri Mar 31 2017
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Equilibrium, Kinetic and Thermodynamic Study of Aniline Adsorption over Prepared ZSM-5 Zeolite
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Aniline and its derivatives are common contaminants in various wastewaters and represent a serious worry for societies health and a challenge to ecologists due to their dangers effects on to the human health.

ZSM-5 zeolite was prepared from locally available materials (kaolin and rice husk) for adsorption of aniline from synthetic wastewater. Characterization of the prepared zsm-5, kinetics and thermodynamic of the adsorption process were investigated.

The characterization results of the prepared zsm-5 zeolite showed that the surface area was 270.1 m2/g and pore volume 0.21828 cm3/g. The silica to alumina ratio (Si/Al) was 166. 47 and the sodium content was 11 wt. %. The atomic force microscope (AFM)

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Isotherms and Thermodynamic Parameters of Metoprolol Drug Adsorption on the Prepared Mesoporous Silica
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In this study, mesoporous silica (MPS) is made using the sol-gel method from a cheap source (Na2SiO3) using the surfactant hydroxycetyl hydroxyethyl dimonium chloride as a template. The task is the adsorption-based removal of the medication metoprolol (MP) at concentrations between 10 and 50 ppm. Variables such as: contact time, dose of adsorbent, starting concentration of adsorbate, and adsorption temperature were studied which show the equilibrium time and adsorbent dose are 40 min and 0.05 g respectively. The Langmuir, Freundlich, Temkin, and Dubinin-Radushkevich isotherm models were fitted to the data obtained from the experiments. Comparing the outcomes showed that, of the four investigated isotherm models, the Freundlich equation m

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Publication Date
Thu Oct 01 2009
Journal Name
Iraqi Journal Of Physics
Gray-Scale Image Brightness/Contrast Enhancement with Multi-Model Histogram linear Contrast Stretching (MMHLCS) method
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Gray-Scale Image Brightness/Contrast Enhancement with Multi-Model
Histogram linear Contrast Stretching (MMHLCS) method

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