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Optimization of photocatalytic process with SnO2 catalyst for COD reduction from petroleum refinery wastewater using a slurry bubble photoreactor
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Publication Date
Tue Sep 30 2008
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Electrocoagulation of phenol for wastewater treatment
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Electrocoagulation is an electrochemical process of treating polluted water where sacrificial anode corrodes to produce active coagulant (usually aluminum or iron cations) into solution. Accompanying electrolytic reactions evolve gas (usually as hydrogen bubbles). The present study investigates the removal of phenol from water by this method. A glass tank with 1 liter volume and two electrodes were used to perform the experiments. The electrode connected to a D.C. power supply. The effect of various factors on the removal of phenol (initial phenol concentration, electrode size, electrodes gab, current density, pH and treatment time) were studied. The results indicated that the removal efficiency decreased as initial phenol concentration

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Publication Date
Sun Sep 07 2008
Journal Name
Baghdad Science Journal
Bioremoval of chromium from wastewater of tannery factory in Iraq
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Bioremoval of chromium from wastewater of tannery factory in Iraq was studied. The bacteria Proteus vulgaris 7E showed an enhanced capability in biosorping chromium when its concentration increased in the solution, reaching a maximum of 476,7 mg/ ml out of 492 mg/ ml under optimum conditions at pH 6 and 50°C at one hour contact time and biomass of 1 mg/ml. The present results showed that dead cells of P. vulgaris 7E biosorbed 87.41 mg/ml of chromium in comparison with91.18 mg/ml of chromium biosorbed by living cells, this indicates the insignificant effect of physiological state of cells. It was found that the above biosorption is physico-chemical process depends upon electrostatic attraction forces. The results has illustrated that the

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Publication Date
Thu Mar 06 2025
Journal Name
International Journal Of Applied Mechanics And Engineering
Evaluation of microstructure and mechanical properties resulting from gas nitriding process for different types of steel
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This work investigates the effect of the gas nitriding process on the surface layer microstructure and mechanical properties for steel 37, tool steel X155CrVMo12-1 and stainless steel 316L. Nitriding was conducted at a temperature of 550 °C for 2 hours during the first stage and at 750 °C for 4 hours during the second stage. SEM and X-ray diffraction tests were performed to evaluate the microstructural features and the major phases formed after surface treatment. SEM and X-ray diffraction tests were performed to assess the microstructural features and the primary phases formed after surface treatment. The new secondary precipitates were identified as γ′-Fe4N, ε (Fe2–3N), and α-Fe, exhibiting an uneven chain-like pattern wit

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Publication Date
Mon Jan 01 2018
Journal Name
Biochemical And Cellular Archives
Optimization of enzymatic conversion of waste office paper using response surface methodology for bioethanol production
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Publication Date
Mon Jul 11 2022
Journal Name
Aip Conference Proceedings
Gas lift optimization: A review
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Optimization of gas lift plays a substantial role in production and maximizing the net present value of the investment of oil field projects. However, the application of the optimization techniques in gas lift project is so complex because many decision variables, objective functions and constraints are involved in the gas lift optimization problem. In addition, many computational ways; traditional and modern, have been employed to optimize gas lift processes. This research aims to present the developing of the optimization techniques applied in the gas lift. Accordingly, the research classifies the applied optimization techniques, and it presents the limitations and the range of applications of each one to get an acceptable level of accura

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Publication Date
Mon Jul 11 2022
Journal Name
Aip Conference Proceedings
Well placement optimization: A review
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Optimization of well placement plays a considerable role in the production and maximizing the net present value of the investment of oil field developments. However, the application of the optimization techniques in well placement developments is so complicated because many decision variables, objective functions, and constraints are involved in the well placement optimization case. Furthermore, many computational techniques; conventional and non-conventional, have been utilized to optimize well placement operations. This study displays the advancement of the optimization methods applied in the well placement. Subsequently, the study assorted the applied optimization methods, and it demonstrates the restriction and the range of implementati

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Publication Date
Fri Dec 01 2017
Journal Name
International Journal Of Science And Research
Theoretical and Experimental Study of Nanofiltration and Reverse Osmosis Membranes for Removal of Heavy Metals from Wastewater
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The present work aimed to study the efficiency of nanofiltration (NF) and reverse osmosis (RO) membrane for heavy metal removal from wastewater and study the factors affecting the performance of these two membranes: feed concentrations for heavy metal ions, pressure, and flow rate. The experimental results showed, heavy metals concentration in permeate increase with raise in feed concentrations, decline with increase in flow rate. The raise of pressure, heavy metals concentration decreases for RO membrane, but for NF membrane the concentration decrease and then at high pressure increase. The rejection percentage for chromium in NF and RO is 99.7% and 99.9%, for copper is 98.4% and 99.3%, for zinc is 97.9% and 99.5%, for nickel is 97.2% and

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Publication Date
Sun Jan 19 2014
Journal Name
Romanian Biotechnological Letters
Optimization conditions for bioemulsifier production by local Streptomyces sp. SS20 isolated from hydrocarbon contaminated soil
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Publication Date
Mon Oct 31 2022
Journal Name
International Journal Of Intelligent Engineering And Systems
Robot Path Planning in Unknown Environments with Multi-Objectives Using an Improved COOT Optimization Algorithm
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Publication Date
Wed Oct 09 2024
Journal Name
Engineering, Technology & Applied Science Research
Improving Pre-trained CNN-LSTM Models for Image Captioning with Hyper-Parameter Optimization
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The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

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