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Optimization of Biochemical Treatment of Tannery Wastewater
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The present work is concerned with the finding of the optimum conditions for biochemical wastewater treatment for a local tannery. The water samples were taken from outline areas (the wastewater of the chrome and vegetable tannery) in equal volumes and subjected to sedimentation, biological treatment, and chemical and natural sedimentation treatment.
The Box-Wilson method of experimental design was adopted to find useful relationships between three operating variables that affect the treatment processes (temperature, aeration period and phosphate concentration) on the Biochemical Oxygen Demand (BOD5).
The experimental data collected by this method were successfully fitted to a second order polynomial mathematical model. The most favorable operating conditions for the treatment are;
Temperature 32.5oC,
Aeration period 10 hours and
phosphate concentration 16.8 mg/L.
On using the optimum conditions a mathematical model simulating the operation for the treatment was obtained.

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Publication Date
Tue Feb 01 2022
Journal Name
Baghdad Science Journal
Retina Based Glowworm Swarm Optimization for Random Cryptographic Key Generation
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The biometric-based keys generation represents the utilization of the extracted features from the human anatomical (physiological) traits like a fingerprint, retina, etc. or behavioral traits like a signature. The retina biometric has inherent robustness, therefore, it is capable of generating random keys with a higher security level compared to the other biometric traits. In this paper, an effective system to generate secure, robust and unique random keys based on retina features has been proposed for cryptographic applications. The retina features are extracted by using the algorithm of glowworm swarm optimization (GSO) that provides promising results through the experiments using the standard retina databases. Additionally, in order t

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Publication Date
Sat Jan 01 2022
Journal Name
Latin American Journal Of Solids And Structures
Peak Ground Acceleration Models Predictions Utilizing Two Metaheuristic Optimization Techniques
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Publication Date
Sat Nov 30 2019
Journal Name
Journal Of Engineering And Applied Sciences
Using Particle Swarm Optimization Algorithm to Address the Multicollinearity Problem
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Publication Date
Wed Jan 01 2025
Journal Name
Fusion: Practice And Applications
Enhanced EEG Signal Classification Using Machine Learning and Optimization Algorithm
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This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance

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Publication Date
Thu Oct 01 2015
Journal Name
Engineering And Technology Journal
Genetic Based Optimization Models for Enhancing Multi- Document Text Summarization
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Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
A Novel Gravity ‎Optimization Algorithm for Extractive Arabic Text Summarization
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An automatic text summarization system mimics how humans summarize by picking the most ‎significant sentences in a source text. However, the complexities of the Arabic language have become ‎challenging to obtain information quickly and effectively. The main disadvantage of the ‎traditional approaches is that they are strictly constrained (especially for the Arabic language) by the ‎accuracy of sentence feature ‎functions, weighting schemes, ‎and similarity calculations. On the other hand, the meta-heuristic search approaches have a feature tha

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Publication Date
Tue Oct 01 2019
Journal Name
Journal Of Engineering
Removal of Dissolved Organic Compounds and Contaminants from Wastewater of a Petroleum Refinery by Ion Exchange
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The efficient removal of dissolved organic compounds (DOC) from wastewater has become a major environmental concern because of its high toxicity even at low concentrations. Therefore, a technique was needed to reduce these pollutants. Ion exchange technology (IE) was used with AmberliteTM IR120 Na, AmberliteTM IR96RF, and AmberliteTM IR402, firstly by using anion and mixed bed system, where the following variables are investigated for the process of adsorption: The height of the bed in column (8,10 and 14 cm), different concentrations of (DOC) content at constant flow rate. The use of an ion exchanger unit (continuous system) with three columns (cation, anion, and mixed bed) was studied.

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Publication Date
Tue Apr 02 2019
Journal Name
Journal Of Environmental Health Science And Engineering
Adsorptive performance of a mixture of three nonliving algae classes for nickel remediation in synthesized wastewater
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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Reducing the Pollutants from Municipal Wastewater by Chlorella Vulgaris Microalgae
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In the present work, the pollutants of the municipal wastewater are reduced using Chlorella vulgaris microalgae. The pollutants that were treated are: Total organic carbon (TOC), Chemical oxygen demand (COD), Nitrate (NO3), and Phosphate (PO4). Firstly, the treatment was achieved at atmospheric conditions (Temperature = 25oC), pH 7 with time (1 – 48 h). To study the effect of other microorganisms on the reduction of pollutants, sterilized wastewater and unsterilized wastewater were used for two types of packing (cylindrical plastic and cubic polystyrene) as well as algae's broth (without packing), where the microalgae are grown on the packing then transported to the wastewater for treatment. Th

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Publication Date
Tue Nov 01 2022
Journal Name
Journal Of Engineering
Artificial Neural Network Model for Wastewater Projects Maintenance Management Plan
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Wastewater projects are one of the most important infrastructure projects, which require developing strategic plans to manage these projects. Most of the wastewater projects in Iraq don’t have a maintenance plan. This research aims to prepare the maintenance management plan (MMP) for wastewater projects. The objective of the research is to predict the cost and time of maintenance projects by building a model using ANN. The research sample included (15) completed projects in Wasit Governorate, where the researcher was able to obtain the data of these projects through the historical information of the Wasit Sewage Directorate. In this research artificial neural networks (ANN) technique was used to build two models (cost

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