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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
Wed Dec 27 2017
Journal Name
Al-khwarizmi Engineering Journal
Human Face Recognition Using GABOR Filter And Different Self Organizing Maps Neural Networks
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This work implements the face recognition system based on two stages, the first stage is feature extraction stage and the second stage is the classification stage. The feature extraction stage consists of Self-Organizing Maps (SOM) in a hierarchical format in conjunction with Gabor Filters and local image sampling. Different types of SOM’s were used and a comparison between the results from these SOM’s was given.

The next stage is the classification stage, and consists of self-organizing map neural network; the goal of this stage is to find the similar image to the input image. The proposal method algorithm implemented by using C++ packages, this work is successful classifier for a face database consist of 20

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Publication Date
Thu Jan 11 2018
Journal Name
Al-khwarizmi Engineering Journal
Control on a 2-D Wing Flutter Using an Adaptive Nonlinear Neural Controller
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An adaptive nonlinear neural controller to reduce the nonlinear flutter in 2-D wing is proposed in the paper. The nonlinearities in the system come from the quasi steady aerodynamic model and torsional spring in pitch direction. Time domain simulations are used to examine the dynamic aero elastic instabilities of the system (e.g. the onset of flutter and limit cycle oscillation, LCO). The structure of the controller consists of two models :the modified Elman neural network (MENN) and the feed forward multi-layer Perceptron (MLP). The MENN model is trained with off-line and on-line stages to guarantee that the outputs of the model accurately represent the plunge and pitch motion of the wing and this neural model acts as the identifier. Th

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Publication Date
Tue Jan 01 2019
Journal Name
Desalination And Water Treatment
Numerical modeling of performance of olive seeds as permeable reactive barrier for containment of copper from contaminated groundwater
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Publication Date
Tue Dec 31 2019
Journal Name
Journal Of Economics And Administrative Sciences
The Reflection of the application TD-ABC approach on profits persistence Applied study in the General State of Hydraulic Industries Factory of Plastic*
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The interest of many companies has become dealing with the tools and methods that reduce the costs as one of the most important factors of successful companies, and became the subject of the attention of many economic units because of the impact on the profits of company, and since the nineties of the last century the researchers and writers gave great attention to this subject, especially in light of the large competition and rapid developments in cost management techniques, as well as the wide and significant change in production methods that have been directed towards achieving customer satisfaction, all this and more driven by economic units in all sectors whether it is service or productivity to find methods that would reduc

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Publication Date
Tue Sep 01 2026
Journal Name
International Journal Of Advances In Applied Sciences
COVID-19 infection detection using convolutional self-attention network with voting classifier
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Early and accurate detection of COVID-19 from chest computed tomography (CT) scans are becoming essential for effective clinical decision-making and disease control. This study is proposing a robust deep learning framework that integrates a convolutional self-attention network (CSAN), gamma correction for image enhancement, and a voting-based ensemble classifier to improving diagnostic performance. The model is being evaluated on a dataset of 2,271 CT images and is achieving an accuracy of 95.12%, sensitivity of 97.25%, specificity of 98.11%, F1-score of 96.46%, and area under the curve (AUC) of 0.977. Experimental results are demonstrating that the proposed method significantly surpasses baseline models, including standalone CSAN,

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Publication Date
Sat Dec 11 2021
Journal Name
Engineering, Technology & Applied Science Research
Evaluation of Rutting in Conventional and Rubberized Asphalt Mixes Using Numerical Modeling Under Repeated Loads
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This research aimed to predict the permanent deformation (rutting) in conventional and rubberized asphalt mixes under repeated load conditions using the Finite Element Method (FEM). A three-dimensional (3D) model was developed to simulate the Wheel Track Testing (WTT) loading. The study was conducted using the Abaqus/Standard finite element software. The pavement slab was simulated using a nonlinear creep (time-hardening) model at 40°C. The responses of the viscoplastic model under the influence of the trapezoidal amplitude of moving wheel loadings were determined for different speeds and numbers of cycles. The results indicated that a wheel speed increase from 0.5Km/h to 1.0Km/h decreased the rut depth by about 22% and 24% in conv

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Publication Date
Mon Dec 01 2025
Journal Name
Case Studies In Construction Materials
Optimized stress-strain modeling of eco-friendly fiber-reinforced concrete members using meta-heuristic algorithms
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Eco-friendly concrete is produced using the waste of many industries. It reduces the fears concerning energy utilization, raw materials, and mass-produced cost of common concrete. Several stress-strain models documented in the literature can be utilized to estimate the ultimate strength of concrete components reinforced with fibers. Unfortunately, there is a lack of data on how non-metallic fibers, such as polypropylene (PP), affect the properties of concrete, especially eco-friendly concrete. This study presents a novel approach to modeling the stress-strain behavior of eco-friendly polypropylene fiber-reinforced concrete (PFRC) using meta-heuristic particle swarm optimization (PSO) employing 26 PFRC various mixtures. The cement was partia

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Publication Date
Sun Mar 01 2015
Journal Name
Sust Journal Of Engineering And Computer Science (jecs)
Virtual failure influence of Roseires dam on Khartoum city using HEC-RAS Hydraulic simulation modeling
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Dam break is series phenomenon that can result in fatal consequences and loss of properties. Unfortunately, the observed consequences can only be available after the dam breaks. Therefore, it is important to anticipate what will happen prior to dam break to issue suitable warning and locate the possible risk areas. This study attempts to simulate the case of dam break in Blue Nile at Roseires dam and see its consequences downstream. Roseires dam lies at a distance of 630 km south of Khartoum, Sennar dam lies at about 260 km downstream of Roseires dam. In this study hydraulic model is developed based of Hydraulic Engineering Centre (HEC), River Analysis System (RAS), and HEC- RAS. The HEC-RAS based model is calibrated and validated usi

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
Modeling Jar Test Results Using Gene Expression to Determine the Optimal Alum Dose in Drinking Water Treatment Plants
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Coagulation is the most important process in drinking water treatment. Alum coagulant increases the aluminum residuals, which have been linked in many studies to Alzheimer's disease. Therefore, it is very important to use it with the very optimal dose. In this paper, four sets of experiments were done to determine the relationship between raw water characteristics: turbidity, pH, alkalinity, temperature, and optimum doses of alum [   .14 O] to form a mathematical equation that could replace the need for jar test experiments. The experiments were performed under different conditions and under different seasonal circumstances. The optimal dose in every set was determined, and used to build a gene expression model (GEP). The models were co

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Publication Date
Fri Sep 15 2023
Journal Name
Bionatura
Effect of Freezing On Some Morphometric Features of Planiliza Abu ( Hekel,1843)
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The present study attempts to determine the effect of freezing for different periods on preserved bodies of fish in the laboratory to keep for the research and diagnosis of taxonomic studies and not for consumption. It also endeavors to identify the effect of freezing on some morphometric features of the preserved bodies of fishes. Planiliza abu fish were used to conduct the present study. Fish were frozen by regular freezing in the home refrigerator freezer with temperatures reaching four degrees centigrade below zero. Freezing time is distributed over four months; biometric measurements of frozen fish have been taken in these periods represented by body total length, Standard length, and Head length in centimeters using a ruler ve

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