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Modeling BOD of the Effluent from Abu-Ghraib Diary Factory using Artificial Neural Network October 2018
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The proper operation, and control of wastewater treatment plants, is receiving an increasing attention, because of the rising concern about environmental issues. In this research a mathematical model was developed to predict biochemical oxygen demand in the waste water discharged from Abu-Ghraib diary factory in Baghdad using Artificial Neural Network (ANN).In this study the best selection of the input data were selected from the recorded parameters of the wastewater from the factory. The ANN model developed was built up with the following parameters: Chemical oxygen demand, Dissolved oxygen, pH, Total dissolved solids, Total suspended solids, Sulphate, Phosphate, Chloride and Influent flow rate. The results indicated that the constructed ANN model to predict BOD of the effluent gave a high degree of correlation reaching 93.5% with seven input parameters. This model can be queried to determine the best combination of operating conditions needed in the wastewater treatment plant to achieve the desired effluent disposal limits.

Publication Date
Sat Mar 30 2019
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Adsorption of Phenol from Aqueous Solution using Paper Waste
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The exploitation of obsolete recyclable resources including paper waste has the advantages of saving resources and environment protection. This study has been conducted to study utilizing paper waste to adsorb phenol which is one of the harmful organic compound byproducts deposited in the environment. The influence of different agitation methods, pH of the solution (3-11), initial phenol concentration (30-120ppm), adsorbent dose (0.5-2.5 g) and contact time (30-150 min) were studied. The highest phenol removal efficiency obtained was 86% with an adsorption capacity of 5.1 mg /g at optimization conditions (pH of 9, initial phenol concentration of 30 mg/L, an adsorbent dose of 2 g and contact time of 120min and at room temperature).

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Publication Date
Mon Dec 01 2008
Journal Name
Al-khwarizmi Engineering Journal
Extraction of Phenol From Industrial Water Using Different Solvents
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The analysis and efficiency of phenol extraction from the industrial water using different solvents, were investigated. To our knowledge, the experimental information available in the literature for liquid-liquid equilibria of ternary mixtures containing the pair phenol-water is limited. Therefore the purpose of the present investigation is to generate the data for the water-phenol with different solvents to aid the correlation of liquid-liquid equilibria, including phase diagrams, distribution coefficients of phenol, tie-lines data and selectivity of the solvents for the aqueous phenol system.

                The ternary equilibrium diagrams and tie-lines

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Publication Date
Wed Sep 30 2020
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Removal of Tetracycline from Wastewater Using Circulating Fluidized Bed
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   In this study, the circulating fluidized bed was used to remove the Tetracycline from wastewater utilizing a pistachio shell coated with ZnO nanoparticles. Several parameters including, Tetracycline solution flowrate, initial static bed height, Tetracycline initial concentration and airflow rate were systematically examined to show their effect on the breakthrough curve and the required time to reach the adsorption capacity and thus draw the fully saturated curve of the adsorbent. Results showed that using ZnO nanoparticles will increase the adsorbent surface area and pores and as a result the adsorption increased, also the required time for adsorbent saturation increased and thus the removal efficiency may be achieved at mi

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Publication Date
Mon Sep 30 2019
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Adsorption of Methyl Orange from Wastewater by using Biochar
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The biochar prepared from sawdust raw material was applied in this study for the treatment of wastewater polluted with methyl orange dye. The effect of pH (2-11), initial concertation (50-250 mg/L) and time were studied. The isotherm of Langmuir, Frendluch and temkin models studied. The Langmuir model was the best to explain the adsorption process, maximum uptake was 136.67 mg/g at 25Co of methyl orange dye. Equilibrium reached after four hours of contact for most adsorbents.The values of thermodynamic parameters ∆G were negative at various temperatures, so the process spontaneous, while ∆H values were 16683 j/mol and ∆S values was 60.82 j/mol.k.

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Publication Date
Tue Aug 03 2021
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Accounting disclosure of social responsibility and its impact on achieving sustainable development goals: (Applied research in the State Company for Food Industries- Diwaniyah Dairy Factory)
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The researchers seek to shed light on the importance of accounting disclosure on social responsibility, and the research aims to provide a theoretical approach to social accounting and its disclosure, identify the concept of sustainable development, highlight the theoretical foundations of sustainable development and employ disclosure of social responsibility towards achieving the goals of sustainable development, and identify the impact of The accounting disclosure on social responsibility in achieving sustainable development goals, and the research problem can be reviewed by asking the following question (Does the accounting disclosure of the social responsibility of economic units contribute to achieving sustainable developmen

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Publication Date
Mon Dec 30 2024
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Reservoir permeability prediction based artificial intelligence techniques
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   Predicting permeability is a cornerstone of petroleum reservoir engineering, playing a vital role in optimizing hydrocarbon recovery strategies. This paper explores the application of neural networks to predict permeability in oil reservoirs, underscoring their growing importance in addressing traditional prediction challenges. Conventional techniques often struggle with the complexities of subsurface conditions, making innovative approaches essential. Neural networks, with their ability to uncover complicated patterns within large datasets, emerge as a powerful alternative. The Quanti-Elan model was used in this study to combine several well logs for mineral volumes, porosity and water saturation estimation. This model goes be

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Publication Date
Fri Jun 01 2007
Journal Name
Journal Of Al-nahrain University Science
ON THE GREEDY RADIAL BASIS FUNCTION NEURAL NETWORKS FOR APPROXIMATION MULTIDIMENSIONAL FUNCTIONS
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The aim of this paper is to approximate multidimensional functions by using the type of Feedforward neural networks (FFNNs) which is called Greedy radial basis function neural networks (GRBFNNs). Also, we introduce a modification to the greedy algorithm which is used to train the greedy radial basis function neural networks. An error bound are introduced in Sobolev space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result is published in [16]).

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Publication Date
Sun Sep 04 2016
Journal Name
Baghdad Science Journal
Bioadsorption of Heavy Metals From Industrial Wastewater Using Some Species of Bacteria
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Three isolated bacteria were examined to remove heavy metals from the industrial wastewater of the Diala State Company of Electrical Industries, Diyala-Iraq. The isolated bacteria were identified as Pseudomonas aeruginosa, Escherichia coli and Sulfate Reducing Bacteria (SRB). The three isolates were used as an adsorption factor for different concentrations of Lead and Copper (100, 150, and 200 ppm.), in order to examine the adsorption efficiency of these isolates. In addition, the effect of three factors on heavy metals adsorption were examined; temperature (25, 30, and 37 ?C), pH (3 and 4.5) and contact time (2 and 24 hrs). The results showed that the highest level of lead adsorption was obtained at 37 ?C by E. coli, P, aerugenosa and

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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
FINITE ELEMENT ANALYSIS OF HUMAN AND ARTIFICIAL ARTICULAR CARTILAGE
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Joint diseases, such as osteoarthritis, induce pain and loss of mobility to millions of people around the world. Current clinical methods for the diagnosis of osteoarthritis include X-ray, magnetic resonance imaging, and arthroscopy. These methods may be insensitive to the earliest signs of osteoarthritis. This study investigates a new procedure that was developed and validated numerically for use in the evaluation of cartilage quality. This finite element model of the human articular cartilage could be helpful in providing insight into mechanisms of injury, effects of treatment, and the role of mechanical factors in degenerative
conditions, this three-dimensional finite element model is a useful tool for understanding of the stress d

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Publication Date
Sun Dec 01 2019
Journal Name
Journal Of Ecological Engineering
Biosorption of Heavy Metals from Synthetic Wastewater by Using Macro Algae Collected from Iraqi Marshlands
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