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Application of Artificial Neural Network and GeographicalInformation System Models to Predict and Evaluate the Quality ofDiyala River Water, Iraq
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This research discusses application Artificial Neural Network (ANN) and Geographical InformationSystem (GIS) models on water quality of Diyala River using Water Quality Index (WQI). Fourteen water parameterswere used for estimating WQI: pH, Temperature, Dissolved Oxygen, Orthophosphate, Nitrate, Calcium, Magnesium,Total Hardness, Sodium, Sulphate, Chloride, Total Dissolved Solids, Electrical Conductivity and Total Alkalinity.These parameters were provided from the Water Resources Ministryfrom seven stations along the river for the period2011 to 2016. The results of WQI analysis revealed that Diyala River is good to poor at the north of Diyala provincewhile it is poor to very polluted at the south of Baghdad City. The selected parameters were subjected to Kruskal-Wallis test for detecting factors contributing to the degradation of water quality and for eliminating independentvariables that exhibit the highest contribution in p-value. The analysis of results revealed that ANN model was goodin predicting the WQI. The confusion matrix for Artificial Neural Model (NNM) gave almost 96% for training, 85.7%for testing and 100% for holdout. In relation to GIS, six color maps of the river have been constructed to give clearimages of the water quality along the river (PDF) Application of Artificial Neural Network and Geographical Information System Models to Predict and Evaluate the Quality of Diyala River Water, Iraq. Available from: https://www.researchgate.net/publication/346028558_Application_of_Artificial_Neural_Network_and_Geographical_Information_System_Models_to_Predict_and_Evaluate_the_Quality_of_Diyala_River_Water_Iraq [accessed Apr 07 2023].

Publication Date
Fri Apr 28 2023
Journal Name
Mathematical Modelling Of Engineering Problems
Design Optimal Neural Network for Solving Unsteady State Confined Aquifer Problem
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Publication Date
Sat Apr 30 2022
Journal Name
Iraqi Journal Of Science
A Review on Face Detection Based on Convolution Neural Network Techniques
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     Face detection is one of the important applications of biometric technology and image processing. Convolutional neural networks (CNN) have been successfully used with great results in the areas of image processing as well as pattern recognition. In the recent years, deep learning techniques specifically CNN techniques have achieved marvellous accuracy rates on face detection field. Therefore, this study provides a comprehensive analysis of face detection research and applications that use various CNN methods and algorithms. This paper presents ten of the most recent studies and illustrate the achieved performance of each method. 

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Publication Date
Mon Mar 11 2019
Journal Name
Baghdad Science Journal
Solving Mixed Volterra - Fredholm Integral Equation (MVFIE) by Designing Neural Network
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       In this paper, we focus on designing feed forward neural network (FFNN) for solving Mixed Volterra – Fredholm Integral Equations (MVFIEs) of second kind in 2–dimensions. in our method, we present a multi – layers model consisting of a hidden layer which has five hidden units (neurons) and one linear output unit. Transfer function (Log – sigmoid) and training algorithm (Levenberg – Marquardt) are used as a sigmoid activation of each unit. A comparison between the results of numerical experiment and the analytic solution of some examples has been carried out in order to justify the efficiency and the accuracy of our method.

         

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Publication Date
Thu Oct 29 2020
Journal Name
Complexity
Training and Testing Data Division Influence on Hybrid Machine Learning Model Process: Application of River Flow Forecasting
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The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

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Publication Date
Sun Oct 22 2023
Journal Name
Iraqi Journal Of Science
Morphotectonics of Shatt Al-Arab River Southern Iraq
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A morphotectonic analysis is conducted on Shatt Al-Arab drainage basin. This study aims to analysis of the river patterns of Shatt Al-Arab channel and their relationship with the development of subsurface geological structures and the neotectonic activity, as well as an attempt to determine the relative amount to this activity.
Transverse river profile analysis is derived quantifiable and comparable parameters such as neotectonic index (Eh*Ln), Eh, Ch, and Bs. These parameters are useful to detect the morphotectonic indicators of Shatt Al-Arab basin. The analysis showed the role of the subsurface structures that affecting the river cross sections shape, through channel incision, as in (Dair and NuhrUmr) cross sections, while in the ot

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Publication Date
Wed Apr 01 2015
Journal Name
Journal Of Educational And Psychological Researches
Standards and quality controls for information technology applications to serve the Holy Quran
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the research goal is preparing a list of standard criteria and quality controls for information technology applications to serve the Holy Quran.

To achieve this goal, the researcher has built a list of criteria according to the following steps:

First - identify the key areas covered by the whole list which are:

1 – Standards of system building and implementing with the operating screens.

2 – Standards of display forms including audio and video presentation.

3 – Standards which are related to the program philosophy.

4 - Standards which are related to the program objectives.

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Publication Date
Sat Oct 01 2016
Journal Name
I-manager’s Journal On Communication Engineering And Systems
SOLVING NETWORK CONGESTION PROBLEM BY QUALITY OF SERVICE ANALYSIS USING OPNET
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Among many problems that reduced the performance of the network, especially Wide Area Network, congestion is one of these, which is caused when traffic request reaches or exceeds the available capacity of a route, resulting in blocking and less throughput per unit time. Congestion management attributes try to manage such cases. The work presented in this paper deals with an important issue that is the Quality of Service (QoS) techniques. QoS is the combination effect on service level, which locates the user's degree of contentment of the service. In this paper, packet schedulers (FIFO, WFQ, CQ and PQ) were implemented and evaluated under different applications with different priorities. The results show that WFQ scheduler gives acceptable r

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Publication Date
Mon Dec 28 2020
Journal Name
Journal Of The College Of Education For Women
Evaluating the Indicators and Quality of Potable Water Networks in Al-Shatrah City: سميع جلاب منسي السهلاني
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The present paper aims at evaluating the vailability quality and future horizons of potable water in the city of Shatra as a model. This is done in accordance with certain subjective and objective factors alongside the classification map of Shatra as a residential area. This system follows geographical studies specialized in urban construction. The problem of the present paper as well as the data approaching that problem have been chosen from the records of 2018. The researcher offered (919) questionnaire forms to be answered by a sample of dwellers in that area. Besides, the researcher also followed lab analysis of water samples collected from districts in the city of Shatra. GIS technology was also used to arrive at the real water shar

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Publication Date
Sat Apr 30 2022
Journal Name
Iraqi Journal Of Science
Impact of Tharthar Arm on the Composition and Diversity of Rotifera in Tigris River North of Baghdad, Iraq
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      This study was conducted to evaluate the effects of Tharthar Arm on the composition and diversity of Rotifera in Tigris River. Six sampling sites were selected, two on Tharthar Arm and four along the Tigris River, one before the confluence as a control site and the others downstream of the confluence. Seventy-seven species of Rotifera were identified in Tigris, whereas, 60 in the arm. The results showed that low density of Rotifera in Tharthr Arm decreased the density in Tigris from 239812.4 upstream of the confluence to 223315.5 at immediate downstream of the confluence. It also declined the mean values of richness, evenness and Shannon diversity indices from 5.19, 0.69 and 2.14 bit/Ind., before the confluence to 3.97, 0.73 a

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Publication Date
Fri Aug 28 2020
Journal Name
Iraqi Journal Of Science
The hydrochemistry of Tigris River in Baghdad city, Iraq
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The primary objective of this study was to investigate the current status of water-quality conditions and assessment it in the Tigris River, Baghdad, Iraq, and to determine how those conditions are changing over time of pollution if any. A series of Hydrochemical tests were carried out to ascertain the influence of major Cations and Anions, Total Dissolved Solids (TDS), Electrical Conductivity (EC) and Potential of hydrogen (pH) on the quality of water. To assess the environmental pollution of the study area: 34 water samples were collected along Tigris River from north to south Baghdad City; 17 on January 2019 and 17 on April 2019. Result of the test were compared with the World Health Organization standards, and showed that all the

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