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Application of Artificial Neural Network for Predicting Iron Concentration in the Location of Al-Wahda Water Treatment Plant in Baghdad City
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Iron is one of the abundant elements on earth that is an essential element for humans and may be a troublesome element in water supplies.  In this research an AAN model was developed to predict iron concentrations in the location of Al- Wahda water treatment plant in Baghdad city by water quality assessment of iron concentrations at seven WTPs up stream Tigris River. SPSS software was used to build the ANN model. The input data were iron concentrations in the raw water for the period 2004-2011. The results indicated the best model predicted Iron concentrations at Al-Wahda WTP with a coefficient of determination 0.9142. The model used one hidden layer with two nodes and the testing error was 0.834. The ANN model could be used to predict future iron concentrations as the results from the verification of the ANN model for years 2012 and 2013 indicated good accuracy with a coefficient of determination R2 = 0.8965.

 

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Publication Date
Thu Dec 28 2017
Journal Name
Al-khwarizmi Engineering Journal
Simulation Study of Mass Transfer Coefficient in Slurry Bubble Column Reactor Using Neural Network
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The objective of this study was to develop neural network algorithm, (Multilayer Perceptron), based correlations for the prediction overall volumetric mass-transfer coefficient (kLa), in slurry bubble column for gas-liquid-solid systems. The Multilayer Perceptron is a novel technique based on the feature generation approach using back propagation neural network. Measurements of overall volumetric mass transfer coefficient were made with the air - Water, air - Glycerin and air - Alcohol systems as the liquid phase in bubble column of 0.15 m diameter. For operation with gas velocity in the range 0-20 cm/sec, the overall volumetric mass transfer coefficient was found to decrease w

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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Diagnosing COVID-19 Infection in Chest X-Ray Images Using Neural Network
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With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  T

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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Performance evaluation of sewage treatment plant for Abu Ghraib Dairy Factory, Iraq
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The objective of this study is to verify the overall performance and evaluate the wastewater quality of the wastewater treatment plant at the Abu Ghraib Dairy Factory and compare the results with the Iraqi Quality Standards (IQS) for effluent disposal and with the national determinants of treated water use. Agricultural irrigation wastewater, which included daily assessment records of the main parameters affecting wastewater [five-day biochemical oxygen demand (BOD5), chemical oxygen demand (COD), total dissolved solids (T.D.S), total suspended solids (TSS), phosphate (PO4), nitrate (NO3), hydrogen ion concentration (pH)] obtained from the quality control department of Abu Ghraib dairy plant registered from January 2017 to December 2020. Th

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Publication Date
Wed Mar 18 2020
Journal Name
Baghdad Science Journal
Effect of Temperature and Alcohol on the Determination of Critical Micelle Concentration of Non- Ionic Surfactants in Magnetic Water
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The determination of critical micelle concentration of selected non-ionic surfactants (Tween 20,40 and 80) have been investigated using magnetic water(MW)as an aqueous medium.Conductometry technique is used to determine critical micelle concentration.The effect of alcohol addition and temperature variation at the range(293.15 -303.15K) are also pursued. It is concluded that the process of micellization is spontaneous and endothermic because of the observed free energy of micellization (ΔGom) , enthalpy change of micellization  (ΔHom), and entropy change of micellization (ΔSom) for the system was also studied.The properties of the non-ionic surfactants were studied, both in absence and presence of

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Publication Date
Thu Sep 28 2023
Journal Name
Iraqi Journal Of Computer, Communication, Control And System Engineering
Distinct Architectures of Feed Forward Neural Network for Implementing A Human Swing Leg System
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The artificial intelligence techniques such as neural networks and fuzzy systems play an important role to disconnect flexion & expansion of the swing leg, the earth response force of the other foot has been redesigned. Under that paper, we think the fuzzy controller plan issue for yield following flawed genuine investigation of nonlinear systems. For examination, an essential fuzzy control plot has been bristly developed dependent on a current methodology delegate under the field. In this paper, the Feedforward Neural Network has been implemented with integer, fixed point and floating point data representations. Additionally, The Fuzzy Logic Controllers in both analog and digital forms has been implemented in hardware. Both designs use les

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Publication Date
Sun Nov 01 2020
Journal Name
Journal Of Engineering
Convolutional Multi-Spike Neural Network as Intelligent System Prediction for Control Systems
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The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed

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Publication Date
Sat Jan 01 2022
Journal Name
Computers, Materials & Continua
An Optimal Method for Supply Chain Logistics Management Based on Neural Network
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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
PDCNN: FRAMEWORK for Potato Diseases Classification Based on Feed Foreword Neural Network
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         The economy is exceptionally reliant on agricultural productivity. Therefore, in domain of agriculture, plant infection discovery is a vital job because it gives promising advance towards the development of agricultural production. In this work, a framework for potato diseases classification based on feed foreword neural network is proposed. The objective of this work  is presenting a system that can detect and classify four kinds of potato tubers diseases; black dot, common scab, potato virus Y and early blight based on their images. The presented PDCNN framework comprises three levels: the pre-processing is first level, which is based on K-means clustering algorithm to detect the infected area from potato image. The s

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Publication Date
Wed Jan 01 2025
Journal Name
E3s Web Of Conferences
Spatial analysis of air pollution concentration (radon, humidity, VOCS) in the homes of the Mitham Al-Tammar neighborhood in Kufa
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The study aims to determine the concentrations of radon, humidity, and CO2 in residences within the Mitham Al-Tammar neighbourhood of Kufa, utilising an Airthings 2960 Wave Plus device in the living rooms of each household. The concentration of radon varied, with a minimum value of 13 ± 3.9 Bq/m3 and a maximum value of 90 ± 5.8 Bq/m3, yielding an average rate of 35.8 ± 4.889 Bq/m3. The concentrations of total VOCs in residences ranged from 69.26 ppb to 810.14 ppb, with a mean of 321.4855 ± 40.4. The humidity percentages exhibited a minimum concentration of 51.68% and a maximum of 122.97%, averaging 76.594 ± 4.298. The concentrations of volatile organic compounds and

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Publication Date
Sat Feb 27 2021
Journal Name
Journal Of Engineering
Using Geographic Information Systems (GIS) Program and Water Quality Index (WQI) to Assess and Manage Groundwater Quality in the City of Baghdad
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Groundwater is an essential source because of its high quality and continuous availability characterize this water resource. Therefore, the study of groundwater has required more attention. The present study aims to assess and manage groundwater quality's suitability for various purposes through the Geographical Information System GIS and the Water Quality Index WQI. The study area is located in the city of Baghdad in central Iraq, with an approximate area of ​​900 , data were collected from the relevant official departments representing the locations of 97 wells of groundwater in the study area for the year 2019, as it included physicochemical parameters such as  pH, EC, TDS, Na, K, Mg, Ca, Cl,  , and &nbs

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