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Lactic acid-based deep eutectic solvents and activated carbon for soap removal from crude biodiesel
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Publication Date
Wed Jul 05 2017
Journal Name
Chemical Engineering Communications
Microwave-assisted preparation of mesoporous-activated carbon from coconut (<i>Cocos nucifera</i>) leaf by H<sub>3</sub>PO<sub>4</sub>activation for methylene blue adsorption
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Publication Date
Fri Nov 30 2018
Journal Name
Iop Conference Series: Materials Science And Engineering
Estimating the PVT Properties for Crude Oil from a Southern Iraqi Oil Field
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Publication Date
Tue Jun 30 2015
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Preparation and Characterization of Nay Zeolite for Biodiesel Production
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Iraqi kaolin was used for the preparation and characterization of NaY zeolite for biodiesel production via esterification reaction. Oleic acid was used usually as a typical simulated feedstock of high acid number for the esterification reaction.

   The chemical composition for the prepared Nay zeolite is as following:  (Ca2.6Na1.K0.1)(Al6.3Si17.7)O48.16H2O, the silica to alumina ratio in the prepared catalyst was found equal to 2.6 and Na2O content was 12.26 wt. %, with relative crystallinity equal to 147.4 % obtained by the X-ray diffraction. The surface area result shows that the prepared catalyst has 330 m2

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Publication Date
Wed Jan 15 2025
Journal Name
International Journal Of Cloud Computing And Database Management
Deep video understanding based on language generation
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Vol. 6, Issue 1 (2025)

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Publication Date
Sat Aug 02 2025
Journal Name
Engineering, Technology &amp; Applied Science Research
A New Method for Face-Based Recognition Using a Fuzzy Face Deep Model
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Face recognition is a crucial biometric technology used in various security and identification applications. Ensuring accuracy and reliability in facial recognition systems requires robust feature extraction and secure processing methods. This study presents an accurate facial recognition model using a feature extraction approach within a cloud environment. First, the facial images undergo preprocessing, including grayscale conversion, histogram equalization, Viola-Jones face detection, and resizing. Then, features are extracted using a hybrid approach that combines Linear Discriminant Analysis (LDA) and Gray-Level Co-occurrence Matrix (GLCM). The extracted features are encrypted using the Data Encryption Standard (DES) for security

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Publication Date
Tue Jun 23 2020
Journal Name
Baghdad Science Journal
Anomaly Detection Approach Based on Deep Neural Network and Dropout
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   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

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Publication Date
Thu Dec 16 2021
Journal Name
Translational Vision Science &amp; Technology
A Hybrid Deep Learning Construct for Detecting Keratoconus From Corneal Maps
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Publication Date
Tue Aug 22 2023
Journal Name
Karbala International Journal Of Modern Science
Biogenesis Synthesis of ZnO NPs: Its adsorption and photocatalytic activity for removal of acid black 210 dye
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Abstract This study investigated the treatment of textile wastewater contaminated with Acid Black 210 dye (AB210) using zinc oxide nanoparticles (ZnO NPs) through adsorption and photocatalytic techniques. ZnO NPs were synthesized using a green synthesis process involving eucalyptus leaves as reducing and capping agents. The synthesized ZnO NPs were characterized using UV-Vis spectroscopy, SEM, EDAX, XRD, BET, Zeta potential, and FTIR techniques. The BET analysis revealed a specific surface area and total pore volume of 26.318 m2/g. SEM images confirmed the crystalline and spherical nature of the particles, with a particle size of 73.4 nm. A photoreactor was designed to facilitate the photo-degradation process. The study investigated the inf

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Publication Date
Sun Jun 05 2016
Journal Name
Baghdad Science Journal
Prevalence of Tonsillitis caused by Streptococcus spp. Among children and the effect of some Lactic acid bacterial (LAB) strain on it
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In this study 100 samples were collected from infected children with acute and chronic tonsillitis who attended to Al-Yarmook Teaching Hospital (ENT consultation clinic) from 5/12/2013 to 1/3/2014. The result of laboratory culture was positive in 67 samples. Depending on their cultural, morphological and biochemical characterization of bacterial isolate of them were identified as (37.31%) belonged to Streptococcus pyogenes and the diagnosis is confirmed by the use of Remel Rapid STR System, (34.32%) belonged to S.parasanguinis, (11.94%) S.mitis, (11.94%) S.oralis and (4.47%) S.thoraltensis . Results confirmed that cup assay gave highest inhibition zone after 24 hrs compare with well diffusion methods for suspension of L.

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Publication Date
Mon Mar 30 2026
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Ciprofloxacin adsorption via compressed wood activated carbon with ZnCl&lt;sub&gt;2&lt;/sub&gt; activating agent from simulated wastewater: Mechanism studying
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      The current study objective is to synthesize activated carbon (AC) from compressed wood using the ZnCl2 activating agent and to assess the ciprofloxacin (CIP) elimination efficiency in simulated wastewater. The produced AC was characterized using multiple techniques, including SEM, BET, FTIR, AFM, and XRD. The adsorbent demonstrates high adsorption performance, achieving 91% removal of CIP within 5 hours at an initial pollutant concentration of 100 mg/L with an AC dose of 2 g/L. Experimental data correspond to the Freundlich isotherm model (R² = 0.995) as well as the Langmuir competitive fitting (R² = 0.99), while the root mean square error (RMSE) equation best fits the Langmuir model. Moreover, the pseudo-second-order

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