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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
Fri Jul 01 2011
Journal Name
Journal Of Petroleum Research & Studies
Preparation of Cross Linked PVA with MA, EDTA and a mixture of MA/EDTA for water uptake membranes at different pH
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Poly (viny1 alcohol) (PVA) of 72000 g mol -1 molar mass was cross linked through cold cast esterification with different mol % of MA and EDTA (10 % , 20 % and 30 % ), and two different mol % mixture of MA l EDTA (20 %/5% and 20%/10% .

Publication Date
Wed Sep 01 2021
Journal Name
Iraqi Journal Of Physics
Study the Effect of Graphene on the Contact Angle, Water Absorption and Thermal Stability ( TGA ,DSC) for Blend (Epoxy & Repcoat ZR)
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In this study, polymeric coating was developed by incorporating nano graphene in the polymer blend with applications to oil storage tanks. The oil storage tanks samples were brought from the oil Pipeline Company / Doura refinery in Baghdad. The coating polymer was formed with a blend (epoxy resin and repcoat ZR). The proportion of mixing the mixture was 3:1:1 epoxy resin 21.06 gm: repcoat ZR 10.53 gm: hardener 10.53 gm. The blend/graphene was prepared using in stui-polymerization method with different weight percentage 1, 3, 5, and 7 wt % added to blend. The resulting solution was put in a glass tube on a magnetic stirrer for one hour at a temperature of 40 °C. The result of contact angle and wate

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Publication Date
Tue Apr 06 2021
Journal Name
Journal Of Polymers And The Environment
Novel Sorbent of Sand Coated with Humic Acid-Iron Oxide Nanoparticles for Elimination of Copper and Cadmium Ions from Contaminated Water
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Nanoparticles of humic acid and iron oxide were impregnated on the inert sand to produce sorbent for treating groundwater contained of cadmium and copper ions by technology of permeable reactive barrier (PRB). Sewage sludge was the source of the humic acid to prepare the coated sand by humic acid—iron oxide (CSHAIO) sorbent; so, this work is consistent with sustainable development. For 10 mg/L metal concentration, batch tests at speed of 200 rpm signified that the removal efficiencies are greater than 90% at sorbent dosage 0.25 g/ 50 mL, pH 6 and contact time 1 h. The kinetic data was well described by the Pseudo first-order model indicating that physicosorption is the predominant mechanism. The maximum adsorption capacities (qmax) were c

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Publication Date
Tue Oct 01 2024
Journal Name
Analytical And Bioanalytical Electrochemistry
New Electrochemical Sensors for Determination of Tamoxifen Based on Enhanced Polymer Nano Composite Deep Eutectic Solvent and Water Mixture as Ionophores
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Publication Date
Tue Jan 01 2019
Journal Name
Desalination And Water Treatment
Effect of synthesis parameters on the formation 4A zeolite crystals: characterization analysis and heavy metals uptake performance study for water treatment
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Publication Date
Mon Jan 01 2018
Journal Name
Matec Web Of Conferences
Possibility of reusing Al-Machraya River for feeding Hawizeh marsh
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Al Machraya River was considered as one of the water feeders of Hawizeh Marsh. In 1986, the outlet of this river into the marsh was blocked and the river was used as a main channel for the East Tigris Irrigation Project near Kalat Salih. This causes significant decrease in the available water supply sources, deterioration in the water quality distribution patterns and increasing the stagnation areas within the marsh. This research aims to study the possibility of reusing this river for feeding Hawizeh Marsh. A frequency analysis study was carried out to study the maximum and minimum probable water level (MMPWL) of Tigris River at the upstream of Kalat Salih Barrage. Six statistical models; Normal distribution, Log-Normal type II, Lo

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Robotics And Control (jrc)
Automated Stand-alone Surgical Safety Evaluation for Laparoscopic Cholecystectomy (LC) using Convolutional Neural Network and Constrained Local Models (CNN-CLM)
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In this golden age of rapid development surgeons realized that AI could contribute to healthcare in all aspects, especially in surgery. The aim of the study will incorporate the use of Convolutional Neural Network and Constrained Local Models (CNN-CLM) which can make improvement for the assessment of Laparoscopic Cholecystectomy (LC) surgery not only bring opportunities for surgery but also bring challenges on the way forward by using the edge cutting technology. The problem with the current method of surgery is the lack of safety and specific complications and problems associated with safety in each laparoscopic cholecystectomy procedure. When CLM is utilize into CNN models, it is effective at predicting time series tasks like iden

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Publication Date
Fri Sep 15 2017
Journal Name
Journal Of Baghdad College Of Dentistry
Comparison among pulp capping materials in: calcium ion release, pH change, solubility and water sorption (An in vitro study)
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Background: Calcium hydroxide and calcium-silicate materials used as direct pulp capping materials. The aims of this in vitro study is to compare among these materials in, the calcium ion release and pH change in soaking water after immersion of materials’ specimens in deionized water. Also Solubility and water sorption of materials’ specimens measured after soaking time. Calcium-silicate materials used were Biodentine, TheraCal and MTA Plus. Materials and methods: Four materials used in this study; Urbical lining (as control group), Biodentine, TheraCal and MTA Plus. Ten discs fabricated from each tested material, by using plastic moulds of 9 mm diameter and 1 mm thickness. Each specimen was immersed in 10 ml of d

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Deep Learning Techniques in the Cancer-Related Medical Domain: A Transfer Deep Learning Ensemble Model for Lung Cancer Prediction
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Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

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Publication Date
Thu Jun 04 2026
Journal Name
Journal Of Physical Education
The Effect of Constructive Learning Model on Cognitive Achievement and Learning dribbling Skill in Soccer for Secondary School Students
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The research aimed at identifying the effect of using constructive learning model on academic achievement and learning soccer dribbling Skill in 2nd grade secondary school students. The researcher used the experimental method on (30) secondary school students; 10 selected for pilot study, 20 were divided into two groups. The experimental group followed constructive learning model while the controlling group followed the traditional method. The experimental program lasted for eight weeks with two teaching sessions per week for each group. The data was collected and treated using SPSS to conclude the positive effect of using constructive learning model on developing academic achievement and learning soccer dribbling Skill in 2nd grade seconda

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