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Oxidation Desulphurization of Heavy Naphtha Improved by Ultrasound Waves
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The oxidation desulphurization assisted by ultrasound waves was applied to the desulphurization of heavy naphtha. Hydrogen peroxide and acetic acid were used as oxidants, ultrasound waves as phase dispersion, and activated carbon as solid adsorbent. When the oxidation desulphurization (ODS) process was followed by a solid adsorption step, the performance of overall Sulphur removal was 89% for heavy naphtha at the normal condition of pressure and temperature. The process of (ODS) converts the compounds of Sulphur to sulfoxides/ sulfones, and these oxidizing compounds can be removed by activated carbon to produce fuel with low Sulphur content. The absence of any components (hydrogen peroxide, acetic acid, ultrasound waves and activated carbon) from the ODS process leading to reduce the performance of removal, hydrogen peroxide was the most crucial factor. The ultrasound waves increase the dispersion of carbon, water and oil phase, promotes the interfacial mass transfer, and this leads to accelerates the reaction. The ultrasound waves did not affect the chemical or physical properties of the fuel. The chemical analysis of treated fuel oil showed that <1% of the hydrocarbon fuel compounds were oxidized in the ODS process. In this work, desulphurization by oxidation is the main mechanism was tested with several parameters that effects desulphurization efficiency such as sonication time (5-40) min, activated carbon (0.01-0.5) gm, hydrogen peroxide (1-30) ml, and acetic acid (1-15) ml. It was found that the hydrogen peroxide amounts lead to increase oxidation rates of Sulphur compounds so, the desulphurization efficiency increases. The optimum amounts of oxidants are 10 ml hydrogen peroxide per 100 ml of heavy naphtha. Increasing the amount of acid catalyst lead to increase Sulphur removal, it was found that7.5 ml acid per 10 ml oxidant was the optimum amount. Activated carbon as a solid adsorbent and reaction enhancer with 0.1gm weight was found as the optimum amount for 100 ml heavy naphtha. Increasing sonication time lead to increase desulphurization rate, it was found that (10 min) is the optimum period. By applying the optimum parameters 89% of sulfur can be removed from heavy naphtha with 598.4 ppm Sulphur content.

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Publication Date
Fri May 01 2020
Journal Name
International Journal Of Advanced Science And Technology
Improved Merging Multi Convolutional Neural Networks Framework of Image Indexing and Retrieval
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Background/Objectives: The purpose of current research aims to a modified image representation framework for Content-Based Image Retrieval (CBIR) through gray scale input image, Zernike Moments (ZMs) properties, Local Binary Pattern (LBP), Y Color Space, Slantlet Transform (SLT), and Discrete Wavelet Transform (DWT). Methods/Statistical analysis: This study surveyed and analysed three standard datasets WANG V1.0, WANG V2.0, and Caltech 101. The features an image of objects in this sets that belong to 101 classes-with approximately 40-800 images for every category. The suggested infrastructure within the study seeks to present a description and operationalization of the CBIR system through automated attribute extraction system premised on CN

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Publication Date
Mon Oct 05 2020
Journal Name
International Journal Of Advanced Science And Technology
Improved Merging Multi Convolutional Neural Networks Framework of Image Indexing and Retrieval
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Improved Merging Multi Convolutional Neural Networks Framework of Image Indexing and Retrieval

Publication Date
Wed Jun 16 2021
Journal Name
Cognitive Computation
Deep Transfer Learning for Improved Detection of Keratoconus using Corneal Topographic Maps
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Abstract <p>Clinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision b</p> ... Show More
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Publication Date
Tue Jun 01 2021
Journal Name
Baghdad Science Journal
Improved Image Security in Internet of Thing (IOT) Using Multiple Key AES
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Image is an important digital information that used in many internet of things (IoT) applications such as transport, healthcare, agriculture, military, vehicles and wildlife. etc. Also, any image has very important characteristic such as large size, strong correlation and huge redundancy, therefore, encrypting it by using single key Advanced Encryption Standard (AES) through IoT communication technologies makes it vulnerable to many threats, thus, the pixels that have the same values will be encrypted to another pixels that have same values when they use the same key. The contribution of this work is to increase the security of transferred image. This paper proposed multiple key AES algorithm (MECCAES) to improve the security of the tran

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Publication Date
Fri Dec 30 2011
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Improved Method to Correlate and Predict Isothermal VLE Data of Binary Mixtures
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Accurate predictive tools for VLE calculation are always needed. A new method is introduced for VLE calculation which is very simple to apply with very good results compared with previously used methods. It does not need any physical property except each binary system need tow constants only. Also, this method can be applied to calculate VLE data for any binary system at any polarity or from any group family. But the system binary should not confirm an azeotrope. This new method is expanding in application to cover a range of temperature. This expansion does not need anything except the application of the new proposed form with the system of two constants. This method with its development is applied to 56 binary mixtures with 1120 equili

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Publication Date
Tue Mar 01 2022
Journal Name
Journal Of Engineering
Comparison of Seepage Trough Zoned Earth dam Using Improved Light-Textured Soils
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Seepage through earth dams is one of the most popular causes for earth dam collapse due to internal granule movement and seepage transfer. In earthen dams, the core plays a vital function in decreasing seepage through the dam body and lowering the phreatic line. In this research, an alternative soil to the clay soil used in the dam core has been proposed by conducting multiple experiments to test the permeability of silty and sandy soil with different additives materials. Then the selected sandy soil model was used to represent the dam experimentally, employing a permeability device to measure the amount of water that seeps through the dam's body and to represent the seepage line. A numerical model was adopted using Geo-Studio software i

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Publication Date
Tue Jan 01 2019
Journal Name
Energy Procedia
Improved thermal and mechanical properties of CdBa2-x SrxCa2Cu3O8+δ superconducting compounds
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Publication Date
Wed May 10 2023
Journal Name
Diagnostics
A Deep Feature Fusion of Improved Suspected Keratoconus Detection with Deep Learning
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Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with

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Publication Date
Sun Mar 01 2015
Journal Name
Baghdad Science Journal
Terrestrial Invertebrates as a Bioindicators of Heavy Metals Pollution
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Bioaccumulation of heavy metals in the terrestrial invertebrates in Al-Jadriyia district Baghdad- Iraq were investigated. Forth terrestrial invertebrates snails, slug, isopods, and diplopods , were selected for this study. The results showed that all invertebrate groups have the ability in accumulate considerable amounts of heavy metals. Higher levels of zinc and copper were observed in the isopods specimens, it's about ( 60.50±0.58 ) and ( 96.00±0.58 ) ppm respectively , while higher levels of lead were observed in the diplopods specimens ,it's about ( 23.00±1.15 ) ppm ,but the higher levels of both iron and cadmium were observed in snail specimens , it's about ( 590.00±1.15 ) and ( 9.50±1.15 ) ppm respectively .but the

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Publication Date
Tue Jan 01 2019
Journal Name
Journal Of Radiation Research And Applied Sciences
Determination of muon absorption coefficients in heavy metal elements
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