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FILTRATION MODELING USING ARTIFICIAL NEURAL NETWORK (ANN)
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In this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, with a
good degree of accuracy reaching 97.26, 95.92 and 86.43% respectively. These ANN models could be used as a support for workers in operating the filters in water treatment plants and to improve water treatment process. With the use of ANN, water systems will get more efficient, so reducing operation cost and improving the quality of the water produced.

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Publication Date
Tue Dec 26 2017
Journal Name
Al-khwarizmi Engineering Journal
Fuzzy Wavenet (FWN) classifier for medical images
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    The combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet networks are feed-forward neural networks using wavelets as activation function. Wavelets networks have been used in classification and identification problems with some success.

  In this work we proposed a fuzzy wavenet network (FWN), which learns by common back-propagation algorithm to classify medical images. The library of medical image has been analyzed, first. Second, Two experimental tables’ rules provide an excellent opportunity to test the ability of fuzzy wavenet network due to the high level of information variability often experienced with this type of images.

&n

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Publication Date
Tue Dec 26 2017
Journal Name
Al-khwarizmi Engineering Journal
Optimization of Wear Parameters in AISI 4340 Steel
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Abstract

 This study investigated the optimization of wear behavior of AISI 4340 steel based on the Taguchi method under various testing conditions. In this paper, a neural network and the Taguchi design method have been implemented for minimizing the wear rate in 4340 steel. A back-propagation neural network (BPNN) was developed to predict the wear rate. In the development of a predictive model, wear parameters like sliding speed, applying load and sliding distance were considered as the input model variables of the AISI 4340 steel. An analysis of variance (ANOVA) was used to determine the significant parameter affecting the wear rate. Finally, the Taguchi approach was applied to determine

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Publication Date
Tue Jun 01 2021
Journal Name
Https://www.researchgate.net/journal/iop-conference-series-materials-science-and-engineering-1757-899x
Application of multivariate statistical techniques in the evaluation of large-scale water treatment plants in Baghdad.
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Abstract<p>This paper aims to evaluate large-scale water treatment plants’ performance and demonstrate that it can produce high-level effluent water. Raw water and treated water parameters of a large monitoring databank from 2016 to 2019, from eight water treatment plants located at different parts in Baghdad city, were analyzed using nonparametric and multivariate statistical tools such as principal component analysis (PCA) and hierarchical cluster analysis (HCA). The plants are Al-Karkh, Sharq-Dijlah, Al-Wathba, Al-Qadisiya Al-Karama, Al-Dora, Al-Rasheed, Al-Wehda. PCA extracted six factors as the most significant water quality parameters that can be used to evaluate the variation in drinkin</p> ... Show More
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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Medicinal And Chemical Sciences
An Evaluation of Activity of Prepared Zinc Nanoparticles with Extract Green Plant in Treatments of Diclofenac, Levofloxacin, and Tetracycline in Water
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Myrtle plant was washed, dried, and powdered after harvesting to produce a fine powder used in water treatment. An alcoholic extract was created from the myrtle plant using ethanol, which was then analyzed using GC-Mass, Fourier Transform Infrared spectroscopy, and ultraviolet-visible spectroscopy to identify the active components. Zinc nanoparticles were created using alcoholic extract. FT-IR, UV-Vis, SEM, EDX, and TEM were used to characterize zinc nanoparticles. Using a continuous processing procedure, zinc nanoparticles with myrtle extract and powder were employed to clean polluted water containing pesticides and antibiotic. First, 2 g of zinc nanoparticles was mixed with 20 ml of polluted water and the result was (Tetra 44%, Levo 32%),

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Publication Date
Thu Jan 30 2020
Journal Name
Journal Of Engineering
Calculation of Pressure Loss of Two Drilling Muds in Noor Oil Field
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In this work, calculation of pressure losses in circulating system for two drilling muds is evaluated in Noor oil field. Two types of drilling muds that were used for drilling section 12 1/4" and 8 3/4" which are Salt saturated mud and Ferro Chrome Lignosulfonate-Chrome Lignite mud. These calculations are based on field data that were gathered from the drilling site of well Noor-15, which are included, rheological data, flow data and specification of drill string. Based on the obtained results, the best rheological model that fit their data is the Herschel-Bulkley model according to correlation coefficient value for their two drilling mud. Also, the difference between the calculated pressure lo

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Publication Date
Tue Apr 22 2025
Journal Name
Bulgarian Journal Of Agricultural Science
The economic impacts of the post-harvest losses of tangerines and Seville oranges crops in Iraq (Baghdad Governorate: As a case study)
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This study aims to calculate the percentage of loss and its causes of the horticultural crops tangerines and Seville oranges in Baghdad governorate for the 2020 agricultural season and estimate the economic impacts of losses both crops tangerines and Seville oranges at the study samples level. The research followed both methods descriptive and the quantitative mathematical in estimating the loss of horticultural crops from tangerines and Seville oranges trees and calculating the economic impact of this loss. The results showed that the percentage of losses of tangerines and Seville oranges crops on the level of wholesalers was about 12% and 13% respectively; causing economic losses estimated at about 3184.41 Euro. The results also displayed

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Publication Date
Tue Dec 30 2014
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Heat Transfer Efficiency of Different Composite Insulators
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This research aims to investigate the thermal performance of different thermal composite insulators, wrapped around a closed-loop copper pipe (CLP). To achieve this aim a system was designed and manufactured. It is consisted of closed water tank insulated by Rock Wool, and supplied with two electric heaters, two thermostat, a flow meter, a water pump, digital temperature scales, and four series of (CLP).
Six insulators were prepared namely; composites of Impregnated Fiberglass with Elastoclad and foaming Rubber (FER), Impregnated Fiberglass with Elastoclad resin and Polymeric Membrane (FEM), Impregnated Fiberglass with Polyurethane thermoset resin and Foaming Rubber (FUR), Impregnated Fiberglass with Polyurethane thermoset resin and P

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Publication Date
Tue Mar 01 2016
Journal Name
International Journal Of Engineering Research And Advanced Technology (ijerat)
Speeding Up Back-Propagation Learning (SUBPL) Algorithm: A New Modified Back_Propagation Algorithm
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The convergence speed is the most important feature of Back-Propagation (BP) algorithm. A lot of improvements were proposed to this algorithm since its presentation, in order to speed up the convergence phase. In this paper, a new modified BP algorithm called Speeding up Back-Propagation Learning (SUBPL) algorithm is proposed and compared to the standard BP. Different data sets were implemented and experimented to verify the improvement in SUBPL.

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Publication Date
Sat Jun 01 2024
Journal Name
Al-rafidain Journal Of Computer Sciences And Mathematics
Braille Character Recognition System: Review
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The Braille Recognition System is the process of capturing a Braille document image and turning its content into its equivalent natural language characters. The Braille Recognition System's cell transcription and Braille cell recognition are the two basic phases that follow one another. The Braille Recognition System is a technique for locating and recognizing a Braille document stored as an image, such as a jpeg, jpg, tiff, or gif image, and converting the text into a machine-readable format, such as a text file. BCR translates an image's pixel representation into its character representation. As workers at visually impaired schools and institutes, we profit from Braille recognition in a variety of ways. The Braille Recognition S

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Publication Date
Sun Dec 30 2018
Journal Name
Journal Of Engineering
A Cognition Path Planning with a Nonlinear Controller Design for Wheeled Mobile Robot Based on an Intelligent Algorithm
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This paper presents a cognition path planning with control algorithm design for a nonholonomic wheeled mobile robot based on Particle Swarm Optimization (PSO) algorithm. The aim of this work is to propose the circular roadmap (CRM) method to plan and generate optimal path with free navigation as well as to propose a nonlinear MIMO-PID-MENN controller in order to track the wheeled mobile robot on the reference path. The PSO is used to find an online tune the control parameters of the proposed controller to get the best torques actions for the wheeled mobile robot. The numerical simulation results based on the Matlab package show that the proposed structure has a precise and highly accurate distance of the generated refere

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