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Water quality assessment and total dissolved solids prediction using artificial neural network in Al-Hawizeh marsh south of Iraq
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The Iraqi marshes are considered the most extensive wetland ecosystem in the Middle East and are located in the middle and lower basin of the Tigris and Euphrates Rivers which create a wetlands network and comprise some shallow freshwater lakes that seasonally swamped floodplains. Al-Hawizeh marsh is a major marsh located east of Tigris River south of Iraq. This study aims to assess water quality through water quality index (WQI) and predict Total Dissolved Solids (TDS) concentrations in Al-Hawizeh marsh based on artificial neural network (ANN). Results showed that the WQI was more than 300 for years 2013 and 2014 (Water is unsuitable for drinking) and decreased within the range 200-300 in years 2015 and 2016 (Very poor water). The developed ANN mode gave a high correlation coefficient reaching 0.927 for the prediction of TDS from the model and showed high levels of TDS in Al-Hawizeh marsh that pose threats to people using the marsh for drinking and other uses. The dissolved Oxygen concentration has the highest importance of 100% in the model because the water of the marsh is fresh water, while Turbidity had the lowest importance.

Publication Date
Mon Nov 11 2019
Journal Name
Day 3 Wed, November 13, 2019
Drill Bit Selection Optimization Based on Rate of Penetration: Application of Artificial Neural Networks and Genetic Algorithms
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Abstract<p>The drill bit is the most essential tool in drilling operation and optimum bit selection is one of the main challenges in planning and designing new wells. Conventional bit selections are mostly based on the historical performance of similar bits from offset wells. In addition, it is done by different techniques based on offset well logs. However, these methods are time consuming and they are not dependent on actual drilling parameters. The main objective of this study is to optimize bit selection in order to achieve maximum rate of penetration (ROP). In this work, a model that predicts the ROP was developed using artificial neural networks (ANNs) based on 19 input parameters. For the</p> ... Show More
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Publication Date
Sun Apr 02 2023
Journal Name
Mathematical Modelling Of Engineering Problems
Traffic Classification of IoT Devices by Utilizing Spike Neural Network Learning Approach
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Whenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model bas

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Publication Date
Sun Dec 29 2019
Journal Name
Iraqi Journal Of Science
Evaluation of the Hydrochemical Characteristics of Groundwater and its Suitability for Desalination to Product Potable Water in Tolul Al-Baj, Salahaldin, Iraq
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The study area, Tlul Al-Baj, suffers from a shortage of fresh water and most people depend on groundwater for different uses (drinking, domestic, irrigation, etc.).

The present research aims to select the most suitable wells for desalination and production of potable water in Tlul Al-Baj area.

Twenty-two samples of groundwater were collected to evaluate the hydrochemical properties of groundwater in the shallow aquifer in the area and to determine their suitability for desalination purposes. The study included measuring the physicochemical characteristics of groundwater, such as total hardness (TH), total dissolved solids(TDS), sodium adsorption ratio (SAR), sodium ratio (Na%), turbidity (Tur), pH…etc. Chemical anal

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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
Sun Jul 09 2023
Journal Name
Journal Of Engineering
Comparison between Linear and Non-linear ANN Models for Predicting Water Quality Parameters at Tigris River
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In this research, Artificial Neural Networks (ANNs) technique was applied in an attempt to predict the water levels and some of the water quality parameters at Tigris River in Wasit Government for five different sites. These predictions are useful in the planning, management, evaluation of the water resources in the area. Spatial data along a river system or area at different locations in a catchment area usually have missing measurements, hence an accurate prediction. model to fill these missing values is essential.
The selected sites for water quality data prediction were Sewera, Numania , Kut u/s, Kut d/s, Garaf observation sites. In these five sites models were built for prediction of the water level and water quality parameters.

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Publication Date
Tue Mar 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
The effect of intellectual capital on the Total quality management of higher education and scientific research institutions in Baghdad
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         The purpose and goal of the research revolve around the diagnosis of intellectual capital as the logical indicator to study an effective human resource management practice and its influential role in determining the overall quality management of higher education institutions and scientific research in Baghdad.

       To achieve the purpose of the research, an upgraded standard questionnaire was used to collect data and distribute it to the selected sample in a statistical manner from the study population of (5) institutions affiliated with the Ministry of Higher Education and Scientific Resear

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Publication Date
Sat Jul 28 2018
Journal Name
Journal Of Engineering
GIS Approach for Spatial Distribution Analysis of Groundwater Quality at South-West Part of Basrah
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Water is necessary for sustainable development and healthy society.  Groundwater, often, is not sufficient and protected for direct human consumption. Due to increase in the density of population the requirement of water is increasing.  In this work, the assessment of groundwater quality was conducted in the south-west part of Basrah province. Spatial variations in the quality of groundwater in the study area have been analyzed utilizing GIS technique. The geochemical parameters of groundwater samples including pH, EC, TDS, Ca, Mg, Na, Cl, HCO3, SO4, and NO3 were assessed in this study. Information maps of the study area have been actually prepared to make use of the GIS spatial

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Publication Date
Fri Jul 19 2019
Journal Name
Iraqi Journal Of Science
Quality of Experience Measurement for Video Streaming Based On Adaptive Neural Fuzzy Inference System
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Technological development in recent years leads to increase the access speed in the networks that allow a huge number of users watching videos online. Video streaming is one of the most popular applications in networking systems. Quality of Experience (QoE) measurement for transmitted video streaming may deal with data transmission problems such as packet loss and delay. This may affect video quality and leads to time consuming. We have developed an objective video quality measurement algorithm that uses different features, which affect video quality. The proposed algorithm has been estimated the subjective video quality with suitable accuracy. In this work, a video QoE estimation metric for video strea

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Publication Date
Fri Nov 24 2023
Journal Name
Iraqi Journal Of Science
Neotectonics of Al-Thirthar, Al-Habbaniya , Al-Razzazah Depressions, Central Iraq, by using Remote Sensing Data.
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The object of this research is to reveal the neotectonics of Al-Thirthar, Al-Habbaniya, and Al-Razzazah depressions by using remote sensing data. The age of the exposed rocks ranges from Early Miocene to Holocene. The depressions represent the west margin of the Mesopotamia Zone along its boundary with Al-Salman Zone. The lineament map contains three major groups of lineaments. Two of them are trending east-west and northeast-southwest parallel to the transversal fault systems of Iraq territory. The third group is trending northwest-southeast. The lineament groups reveal the tectonic and structural effects to the extension and the shape of the depressions. The intersection of the lineaments divided the area into small fragments which con

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Publication Date
Sat Apr 15 2023
Journal Name
Iraqi Journal Of Science
Building A 3D Geological model Using Petrel Software for Asmari Reservoir, South Eastern Iraq
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Building a 3D geological model from field and subsurface data is a typical task in
geological studies involving natural resource evaluation and hazard assessment. In
this paper a 3D geological model for Asmari Reservoir in Fauqi oil field has been
built using petrel software. Asmari Reservoir belongs to (Oligocene- Lower
Miocene), it represents the second reservoir products after Mishrif Reservoir in Fauqi
field. Five wells namely FQ6, FQ7, FQ15, FQ20, FQ21 have been selected lying in
Missan governorate in order to build Structural and petrophysical (porosity and water
saturation) models represented by a 3D static geological model in three directions
.Structural model shows that Fauqi oil field represents un cylin

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