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Predicting Potential Salinity in River Water for Irrigation Water Purposes Using Integrative Machine Learning Models
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ABSTRACT<p>Accurate prediction of river water quality parameters is essential for environmental protection and sustainable agricultural resource management. This study presents a novel framework for estimating potential salinity in river water in arid and semi‐arid regions by integrating a kernel extreme learning machine (KELM) with a boosted salp swarm algorithm based on differential evolution (KELM‐BSSADE). A dataset of 336 samples, including bicarbonate, calcium, pH, total dissolved solids and sodium adsorption ratio, was collected from the Idenak station in Iran and was used for the modelling. Results demonstrated that KELM‐BSSADE outperformed models such as deep random vector functional link (dRVFL), general regression neural network (GRNN), multivariate adaptive regression spline (MARS), online sequential extreme learning machine (OSELM) and extreme gradient boosting decision tree (XGBoost) when compared with observed river salinity data. Also, the KELM‐BSSADE model effectively identified optimal inputs through the Boruta‐XGBoost (B‐XGB) feature selection method. Four metaheuristic‐based KELM models were developed, utilizing grey wolf optimizer, whale optimization, slime mould algorithm and equilibrium optimizer, further illustrating the capability of KELM‐BSSADE in estimating potential salinity in river water. By accurately estimating potential salinity, KELM‐BSSADE can assist in optimizing irrigation practices, ensuring that agricultural demands are met while minimizing the risk of salinity‐related crop damage.</p>
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Publication Date
Mon Jul 31 2017
Journal Name
Journal Of Engineering
Assessment of Water Clarity within Dokan Lake Using Remote Sensing Techniques
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Publication Date
Tue Sep 01 2020
Journal Name
Journal Of Engineering
Stabilization of Al-Rustamiya Waste Water Treatment Plant Sludge Using Lime
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A study was performed to evaluate heavy metals removal from sewage sludge using lime. The processes of stabilization using alkaline chemicals operating on a simple principle of raising pH to 12 or higher, with sufficient mixing and suitable contact time to ensure that immobilization can reduce heavy metals. A 0.157 m3 tank was designed to treat Al-Rustemeyia wastewater treatment plant sludge. Characteristics of raw sludge were examined through two parameters: pH and heavy metal analysis. Different lime doses of (0- 25) g CaO/100 g sludge were mixed manually with raw sludge in a rotating drum. The samples were analyzed two hours after mixing. pH and heavy metals results were compared with EPA and National Iraqi Stand

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Publication Date
Fri Mar 15 2019
Journal Name
Al-khwarizmi Engineering Journal
Desalination of Highly Saline Water Using Direct Contact Membrane Distillation (DCMD)
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In this work, laboratory experiments were carried out to verify direct contact membrane distillation system’s performance in highly saline water desalination. The study included the investigation of various operating conditions, like feed flow rate, temperature and concentration of NaCl solution and their impact on the permeation flux were discussed. 16 cm2 of a flat sheet membrane module with commercial poly-tetra-fluoroethylene (PTFE) membrane, which has 0.22 μm pore size, 96 µm thickness and 78% average porosity, was used. A high salt rejection factor was obtained greater than 99.9%, and the permeation flux up to 17.27 kg/m2.h was achieved at 65°C for hot feed side and 20°C for cold side stream.

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Publication Date
Tue Mar 01 2022
Journal Name
Asian Journal Of Applied Sciences
Comparison between Expert Systems, Machine Learning, and Big Data: An Overview
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Today, the science of artificial intelligence has become one of the most important sciences in creating intelligent computer programs that simulate the human mind. The goal of artificial intelligence in the medical field is to assist doctors and health care workers in diagnosing diseases and clinical treatment, reducing the rate of medical error, and saving lives of citizens. The main and widely used technologies are expert systems, machine learning and big data. In the article, a brief overview of the three mentioned techniques will be provided to make it easier for readers to understand these techniques and their importance.

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Publication Date
Wed Feb 01 2023
Journal Name
Journal Of Engineering
An Empirical Investigation on Snort NIDS versus Supervised Machine Learning Classifiers
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With the vast usage of network services, Security became an important issue for all network types. Various techniques emerged to grant network security; among them is Network Intrusion Detection System (NIDS). Many extant NIDSs actively work against various intrusions, but there are still a number of performance issues including high false alarm rates, and numerous undetected attacks. To keep up with these attacks, some of the academic researchers turned towards machine learning (ML) techniques to create software that automatically predict intrusive and abnormal traffic, another approach is to utilize ML algorithms in enhancing Traditional NIDSs which is a more feasible solution since they are widely spread. To upgrade t

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Publication Date
Sat Aug 10 2024
Journal Name
Cureus
Machine Learning and Vision: Advancing the Frontiers of Diabetic Cataract Management
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Publication Date
Tue Oct 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
The role of drinking water quality in achieving customer satisfaction Applied research in the Directorate of water Diwaniyah
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ABSTRACT    

The purpose of the research is to identify the role of drinking water quality in achieving customer satisfaction in one of the formations of the Ministry of Construction, Housing and Public Municipalities (Diwaniyah Water Directorate), as they are important service organizations that have a fundamental role in serving the community. Faced many administrative challenges, as a result of the continuous and accelerating environmental changes, environmental pollution and immaturity of social awareness and social responsibility, as these contributed to and affected the quality of drinking water, Therefore, it is necessary to know the role of quality, specifically "drinking water and its effect o

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Evaluation of the Organic-Pollution Based on the Determination of some Polycyclic Aromatic Hydrocarbons(PAHs) in Tigris River Water in 2012 at Baghdad City , Iraq
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This study aims to predict the organic pollution produced from the presence of some polycyclic aromatic hydrocarbons (PAHs) and determination it's concentrations (µg/L , ppb) in Tigris river water by a collection twenty-seven water samples from a selected three stations with nine sampling sites and three depths of water (5 cm , 2 m and 4 m) each site for 4.6 km distance of a geographic studied area which is located between the ( Al-Senak and AL-Sarrafiah bridges ) at Baghdad city – Iraq on May, 2012. The geographic location was determined with a Global Positioning System (GPS) and Geographic Information System (GIS) software program. The concentrations of fourteen components (PAHs) were performed using the reverse phase

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
Evaluation the turbidity removal efficiency in Al-Wahda water treatment plant using statistical indicators
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Abstract<p>Most of drinking water consuming all over the world has been treated at the water treatment plant (WTP) where raw water is abstracted from reservoirs and rivers. The turbidity removal efficiency is very important to supply safe drinking water. This study is focusing on the use of multiple linear regression (MLR) and artificial neural network (ANN) models to predict the turbidity removal efficiency of Al-Wahda WTP in Baghdad city. The measured physico-chemical parameters were used to determine their effect on turbidity removal efficiency in various processes. The suitable formulation of the ANN model is examined throughout many preparations, trials, and steps of evaluation. The predict</p> ... Show More
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Publication Date
Tue Nov 01 2022
Journal Name
Energy Reports
Thermal effectiveness of solar collector using Graphene nanostructures suspended in ethylene glycol–water mixtures
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