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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 conductivity on the salinity value was estimated. Multiple linear regression (MLR) and artificial neural network (ANN) models were used to estimate the mathematical models for calculating water salinity value in Tigris River and to present the highest effective parameter that effect on water salinity. In general, the results showed an increase in the water salinity level downstream of the Tigris River towards the south of Baghdad and the EC is the most significant effect on water salinity, and MLR and ANN analyses present a good indication of the mathematical models with highest coefficient of correlation (R<sup>2</sup>) as (0.999 and 0.998), respectively. In addition, the regression equations proved good performance in predicting the salinity value with error percentage less than 10% for all WTPs.</p>
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Publication Date
Sat Jul 15 2023
Journal Name
2023 6th International Conference On Engineering Technology And Its Applications (iiceta)
Methodology for the Design and Programming Methods for a Smart Home
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Publication Date
Fri Nov 01 2024
Journal Name
Egyptian Journal Of Aquatic Biology And Fisheries
Heavy Metals Levels in the Al-Shamiyah River: A Lotic Ecosystem Case Study
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Monitoring lotic ecosystems is vital for addressing sustainability issues. The Al-Shamiyah River is the primary source of water for various daily activities in the Al-Shamiyah district. This study assessed the pollution levels of the river by measuring the concentration and distribution of heavy metals—specifically chromium, cadmium, manganese, copper, zinc, and lead—in both the river's water and sediments. The concentrations of heavy metals in the water ranged from 0.05 to 1.44µg/ L for copper (Cu), 1.57 to 7.25µg/ L for manganese (Mn), 0 to 1.7µg/ L for cadmium (Cd), 0.02 to 1.33µg/ L for lead (Pb), 0.08 to 2.74µg/ L for zinc (Zn), and 0.44 to 1.84µg/ L for chromium (Cr). In the particulate phase, the concentrations ranged from

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Publication Date
Wed Dec 01 2021
Journal Name
Journal Of Engineering
Controlling the Salt Wedge Intrusion in Shatt Al-Arab River by a Barrage
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Shatt Al-Arab River in Al Basrah, Iraq, has recently recorded massive levels of TDS values (Total Dissolved Solids) in the water as a result of reduced fresh water discharge from sources, causing the river to become salinized due to salt wedge intrusion. Therefore, a block dam in the south reach is required to salt intrusion prevention. The main objective of this research is to simulate the hydraulic impact of a suggested barrage in Ras Al Besha on the Shatt Al-Arab River. The HEC-RAS (5.0.7) model was used to develop a one-dimensional unsteady model to gaining an understanding of the proposed barrage's influence on river behaviour. The daily discharges of the Tigris River provided as the upstream boundary conditions, wh

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Publication Date
Tue Aug 31 2021
Journal Name
Inmateh Agricultural Engineering
DETERMINING THE EFFICIENCY OF A SMART SPRAYING ROBOT FOR CROP PROTECTION USING IMAGE PROCESSING TECHNOLOGY
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A system was used to detect injuries in plant leaves by combining machine learning and the principles of image processing. A small agricultural robot was implemented for fine spraying by identifying infected leaves using image processing technology with four different forward speeds (35, 46, 63 and 80 cm/s). The results revealed that increasing the speed of the agricultural robot led to a decrease in the mount of supplements spraying and a detection percentage of infected plants. They also revealed a decrease in the percentage of supplements spraying by 46.89, 52.94, 63.07 and 76% with different forward speeds compared to the traditional method.

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Intelligent Systems
Trip generation modeling for a selected sector in Baghdad city using the artificial neural network
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Abstract<p>This study is planned with the aim of constructing models that can be used to forecast trip production in the Al-Karada region in Baghdad city incorporating the socioeconomic features, through the use of various statistical approaches to the modeling of trip generation, such as artificial neural network (ANN) and multiple linear regression (MLR). The research region was split into 11 zones to accomplish the study aim. Forms were issued based on the needed sample size of 1,170. Only 1,050 forms with responses were received, giving a response rate of 89.74% for the research region. The collected data were processed using the ANN technique in MATLAB v20. The same database was utilized to</p> ... Show More
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Publication Date
Sun Mar 03 2013
Journal Name
Baghdad Science Journal
Naididae (Clitellata : Oligochaeta) and Aeolosomatidae ( Polychaeta : Aphanoneura) Species associated with aquatic plants in Tigris River/ Baghdad / Iraq
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339 individuals , were sorted from 22 samples collected from three sites in Tigris River including , Al- Sarafiya district (S1), Al- Jaderiyah district (S2) and Al-Za'afaraniya district (S3), in addition to one site in the irrigation canal of the Al- Jaderiyah campus of the University of Baghdad (S4) , and in Al- Jeish canal(S5) east Baghdad. The sorting results revealed that the highest number of individuals of 102 was recorded at S4, whereas the lowest number of 24 individuals was recorded at S2. Regarding the sites, site S4 was the richest site with 30% of the total number represented 16 species, while each of S3 and S5 had 8 species only with 17.11% and 28.60% of the total individuals number respectively. The values of Jaccared Sim

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Publication Date
Wed Dec 18 2019
Journal Name
Baghdad Science Journal
Molecular and Immunological Methods to Confirm Toxiginicity (Microcystin Production) of Westiellopsis Prolifica Isolated from Tigris River – Iraq
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Several toxigenic cyanobacteria produce the cyanotoxin (microcystin). Being a health and environmental hazard, screening of water sources for the presence of microcystin is increasingly becoming a recommended environmental procedure in many countries of the world. This study was conducted to assess the ability of freshwater cyanobacterial species Westiellopsis prolifica to produce microcystins in Iraqi freshwaters via using molecular and immunological tools. The toxigenicity of W. prolifica was compared via laboratory experiments with other dominant bloom-forming cyanobacteria isolated from the Tigris River: Microcystis aeruginosa, Chroococcus turigidus, Nostoc carneum, and Lyngbya sp. signifi

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Publication Date
Thu Nov 21 2019
Journal Name
Journal Of Engineering
A Neural Networks based Predictive Voltage-Tracking Controller Design for Proton Exchange Membrane Fuel Cell Model
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In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de

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Publication Date
Fri Apr 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
A Comparison Between Classic Local Least Estimatop And Bayesian Methoid For Estimating Semiparametric Logistic Regression Model
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Semi-parametric models analysis is one of the most interesting subjects in recent studies due to give an efficient model estimation. The problem when the response variable has one of two values either 0 ( no response) or one – with response which is called the logistic regression model.

We compare two methods Bayesian and . Then the results were compared using MSe criteria.

A simulation had been used to study the empirical behavior for the Logistic model , with  different sample sizes and variances. The results using represent that the Bayesian method is better than the   at small samples sizes.

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Publication Date
Thu Jun 01 2017
Journal Name
Nuclear Physics A
Alpha-cluster preformation factor within cluster-formation model for odd-A and odd–odd heavy nuclei
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