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Integration of deep eutectic solvent and activated carbon in emulsion liquid membrane system for soap removal from crude biodiesel
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Publication Date
Mon Apr 01 2019
Journal Name
Journal Of Engineering
Removal of Methyl Orange from Aqueous Solutions by Adsorption Using Corn Leaves as Adsorbent Material
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A comparative study was done on the adsorption of methyl orange dye (MO) using non-activated and activated corn leaves with hydrochloric acid as an adsorbent material. Scanning electron microscopy (SEM) and Fourier Transform Infrared spectroscopy (FTIR) were utilized to specify the properties of adsorbent material. The effect of several variables (pH, initial dye concentration, temperature, amount of adsorbent and contact time) on the removal efficiency was studied and the results indicated that the adsorption efficiency increases with the increase in the concentration of dye, adsorbent dosage and contact time, while inversely proportional to the increase in pH and temperature for both the treated and untreated corn leaves. The equi

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Publication Date
Mon Jun 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Removal of COD from Petroleum refinery Wastewater by Electro-Coagulation Process Using SS/Al electrodes
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Abstract<p>In the present study, the effectiveness of a procedure of electrocoagulation for removing chemical oxygen demand (COD) from the wastewater of petroleum refinery has been evaluated. Aluminum and stainless steel electrodes were used as a sacrificial anode and cathode respectively. The effect of current density (4-20mAcm<sup>−2</sup>), pH (3-11), and NaCl concentration (0-4g/l) on efficiency of removal of chemical oxygen demand was investigated. The results have shown that increasing of current density led to increase the efficiency of COD removal while increasing NaCl concentration resulted in decreasing of COD removal efficiency. Effect of pH was found to be lowering COD re</p> ... Show More
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Publication Date
Wed Sep 24 2014
Journal Name
International Journal Of Environmental Science And Technology
Removal of copper ions from contaminated groundwater using waste foundry sand as permeable reactive barrier
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Publication Date
Thu Jul 31 2025
Journal Name
Lecture Notes In Networks And Systems
Integration Between Network Analysis and Business Process Reengineering and Their Role in Reduce Project Costs/Applied Research in the Oil Projects Company
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Publication Date
Wed Dec 10 2025
Journal Name
Diyala Journal Of Engineering Sciences
Frankincense Extract as Eco-Friendly Corrosion Inhibitor for Carbon Steel in 1M HCl Solution
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Steel corrosion in acidic environments is a critical industrial challenge, necessitating effective yet eco-friendly inhibitors. This study aims to address this problem by introducing a novel, green alternative: frankincense extract (FE). The distinctive contribution of this work lies in the comprehensive investigation of FE natural, sustainable, and economically viable resin as an effective corrosion inhibitor for carbon steel in 1 M HCl. The research employs an integrated methodology, including electrochemical techniques (potentiodynamic polarization (PDP) and electrochemical impedance spectroscopy (EIS)), adsorption isotherm modeling, surface analysis (FT-IR and FESEM/EDX), and density functional theory (DFT) calculations. Key res

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Publication Date
Sat Dec 16 2023
Journal Name
2023 14th International Renewable Energy Congress (irec)
Utilizing the Controlled Hydropower System to Harness the Collected Water in Drainage System for Power Generation
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The variety of clean energy sources has risen, involving many resources, although their fundamental principles remain consistent in terms of energy generation and pollution reduction. The using of hydropower system for energy production also has a dynamic impact in which it utilizes to harness the water for the purpose of energy production. As it is important to overcome the problem of accidents in the highway and rural areas in the case of server rainfall and flood by implementation a smart system that used for energy production. This paper aims to develop a controlled hydropower system installed in the drainage sinks allocated in highway roads used for producing. The proposed system consists of storage unit represented by pipes used for t

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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Computational Intelligence Systems
Evolutionary Feature Optimization for Plant Leaf Disease Detection by Deep Neural Networks
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Publication Date
Thu Nov 17 2022
Journal Name
Journal Of Information And Optimization Sciences
Hybrid deep learning model for Arabic text classification based on mutual information
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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 Dec 30 2025
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
Deep Spoof Face Detection Techniques in React Native
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The rapid rise in the use of artificially generated faces has significantly increased the risk of identity theft in biometric authentication systems. Modern facial recognition technologies are now vulnerable to sophisticated attacks using printed images, replayed videos, and highly realistic 3D masks. This creates an urgent need for advanced, reliable, and mobile-compatible fake face detection systems. Research indicates that while deep learning models have demonstrated strong performance in detecting artificially generated faces, deploying these models on consumer mobile devices remains challenging due to limitations in computing power, memory, privacy, and processing speed. This paper highlights several key challenges: (1) optimiz

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