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Artificial Neural Networks Modeling of Total Dissolved Solid in the Selected Locations on Tigris River, Iraq
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The study aims to predict Total Dissolved Solids (TDS) as a water quality indicator parameter at spatial and temporal distribution of the Tigris River, Iraq by using Artificial Neural Network (ANN) model. This study was conducted on this river between Mosul and Amarah in Iraq on five positions stretching along the river for the period from 2001to 2011. In the ANNs model calibration, a computer program of multiple linear regressions is used to obtain a set of coefficient for a linear model. The input parameters of the ANNs model were the discharge of the Tigris River, the year, the month and the distance of the sampling stations from upstream of the river. The sensitivity analysis indicated that the distance and discharge have the most significant affect on the predicted TDS concentrations. The results showed that a network with (8) hidden neurons was highly accurate in predicting TDS concentration. The correlation coefficient (r), root mean square error (RMSE) and mean absolute percentage error (MAPE) between measured data and model outputs were calculated as 0.975, 113.9 and 11.51%, respectively for testing data sets. Comparisons between final results of ANNs and multiple linear regressions (MLR) showed that the ANNs model could be successfully applied and provides high accuracy to predict TDS concentrations as a water quality parameter.

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Publication Date
Sun Jan 05 2025
Journal Name
Science Journal Of University Of Zakho
DETECTION AND RECOGNITION OF IRAQI LICENSE PLATES USING CONVOLUTIONAL NEURAL NETWORKS
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Due to the large population of motorway users in the country of Iraq, various approaches have been adopted to manage queues such as implementation of traffic lights, avoidance of illegal parking, amongst others. However, defaulters are recorded daily, hence the need to develop a mean of identifying these defaulters and bring them to book. This article discusses the development of an approach of recognizing Iraqi licence plates such that defaulters of queue management systems are identified. Multiple agencies worldwide have quickly and widely adopted the recognition of a vehicle license plate technology to expand their ability in investigative and security matters. License plate helps detect the vehicle's information automatically ra

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Publication Date
Tue Jan 01 2019
Journal Name
International Journal Of Machine Learning And Computing
Facial Emotion Recognition from Videos Using Deep Convolutional Neural Networks
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Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.

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Publication Date
Mon Jan 01 2024
Journal Name
Aims Mathematics
Solving quaternion nonsymmetric algebraic Riccati equations through zeroing neural networks
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<abstract><p>Many variations of the algebraic Riccati equation (ARE) have been used to study nonlinear system stability in the control domain in great detail. Taking the quaternion nonsymmetric ARE (QNARE) as a generalized version of ARE, the time-varying QNARE (TQNARE) is introduced. This brings us to the main objective of this work: finding the TQNARE solution. The zeroing neural network (ZNN) technique, which has demonstrated a high degree of effectiveness in handling time-varying problems, is used to do this. Specifically, the TQNARE can be solved using the high order ZNN (HZNN) design, which is a member of the family of ZNN models that correlate to hyperpower iterative techniques. As a result, a novel

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Publication Date
Thu Jun 23 2022
Journal Name
American Scientific Research Journal For Engineering, Technology, And Sciences
A Review of TCP Congestion Control Using Artificial Intelligence in 4G and 5G Networks
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In recent years, the field of research around the congestion problem of 4G and 5G networks has grown, especially those based on artificial intelligence (AI). Although 4G with LTE is seen as a mature technology, there is a continuous improvement in the infrastructure that led to the emergence of 5G networks. As a result of the large services provided in industries, Internet of Things (IoT) applications and smart cities, which have a large amount of exchanged data, a large number of connected devices per area, and high data rates, have brought their own problems and challenges, especially the problem of congestion. In this context, artificial intelligence (AI) models can be considered as one of the main techniques that can be used to solve ne

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Publication Date
Sun Dec 06 2009
Journal Name
Baghdad Science Journal
THE EFFECT OF RAMADI SEWAGE TREATMENT PLANT ON THE PHYTOPLANKTON AND SOME PHYSICO – CHEMICAL CHARACTERS IN EUPHRATES RIVER , IRAQ
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Four localities were selected in Euphrates River and Ramadi sewage treatment plant to collect water samples monthly during the period between October 2001 to July 2002 . Total cell count of phytoplankton and its physico- chemical concentrations were determined . The study aimed to demonstrate the effect of Ramadi sewage treatment plant on Euhprates River . It is concluded that the sewage had an dilution effect for the total hardness , total alkalinity , electrical conductivity and salinity of Euphrates River , but it is also caused in the presence of a contaminated area . This was cleared from the depletion of dissolved oxygen and high values of biological oxygen demand with lower valuse of pH in this area . The water of Euphrates

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Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
Application of GIS technique in the studies on fish assemblages in Shatt Al-Arab River, Basrah, Iraq
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The present study has examined the spatiotemporal varieties of the demographics of the Shatt Al-Arab River fishes and their relation to some ecological components. The aim is to forecast these groups in the unexplored parts of the waterway with an emphasis on environmental indices of diversity. Three sites in the river were selected as an observation and study of these species, which lasted from March 2019 to February 2020, the study dealt with factors affecting fishes, as Water Temperature (WT), Dissolved Oxygen (DO), Potential Hydrogen Ion (pH), Salinity (Sal), and Transparency (Tra). Gill nets, cast nets, hooks, and hand nets were adopted to collecting fish. The results indicated that the fish population comprises 60 species represent

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Publication Date
Wed Jan 01 2014
Journal Name
Infection And Drug Resistance
Virulence and antimicrobial resistance of Escherichia coli isolated from Tigris River and children diarrhea
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Publication Date
Sun Jan 01 2017
Journal Name
Journal Of Engineering
Two – Dimensional Mathematical Model to Study Erosion Problem of Tigris River Banks at Nu’maniyah
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The high and low water levels in Tigris River threaten the banks of the river. The study area is located on the main stream of Tigris River at Nu’maniyah City and the length of the considered reach is 5.4 km, especially the region from 400 m upstream Nu’maniyah Bridge and downstream of the bridge up to 1250 mwhich increased the risk ofthe problemthat itheading towardsthe streetand causingdanger tonearbyareas.

The aim of this research is to identify the reason of slope collapse and find proper treatments for erosion problem in the river banks with the least cost. The modeling approach consisted of several steps, the first of which  is by using “mini” JET (Jet Erosion Test) d

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Publication Date
Tue Aug 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Estimate Raw Water Salinity for the Tigris River for a Long Time Using a Mathematical Model
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Abstract<p>The measurement data of the raw water quality of Tigris River were statistically analyzed to measure the salinity value in relation to the selected raw water quality parameters. The analyzed data were collected from five water treatment plants (WTPs) assembled alongside of the Tigris River in Baghdad: Al-Karkh, Al-Karama, Al-Qadisiya, Al-Dora, and Al-Wihda for the period from 2015 to 2021. The selected parameters are total dissolved solid (TDS), electrical conductivity (EC), pH and temperature. The main objective of this research is to predicate a mathematical model using SPSS software to calculate the value of salinity along the river, in addition, the effect of electrical conductivi</p> ... Show More
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Publication Date
Thu Jun 01 2023
Journal Name
Baghdad Science Journal
Modeling The Power Grid Network Of Iraq
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Recently, the theory of Complex Networks gives a modern insight into a variety of applications in our life. Complex Networks are used to form complex phenomena into graph-based models that include nodes and edges connecting them. This representation can be analyzed by using network metrics such as node degree, clustering coefficient, path length, closeness, betweenness, density, and diameter, to mention a few. The topology of the complex interconnections of power grids is considered one of the challenges that can be faced in terms of understanding and analyzing them. Therefore, some countries use Complex Networks concepts to model their power grid networks. In this work, the Iraqi Power Grid network (IPG) has been modeled, visua

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