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Modified Optimization Algorithms for Infinite Integro-Differential Equations via Generalized Laguerre Polynomials
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This study emphasizes the infinite-boundary integro-differential equation. To examine the approximate solution of the problem, two modified optimization algorithms are proposed based on generalized Laguerre functions. In the first technique, the proposed method is applied to the original problem by approximating the solution using the truncated generalized Laguerre polynomial of the unknown function, optimizing coefficients through error minimization, and transforming the integro-differential equation into an algebraic equation. In contrast, the second approach incorporates a penalty term into the objective function to effectively enforce boundary and integral constraints. This technique reduces the original problem to a mathematical optimization problem, making it easier to manage. The proposed methods are examined through various experiments, including numerical applications such as thermal, pharmacokinetic, oscillatory, aerodynamic, and ecological models, to demonstrate the validity, efficiency, and applicability of the techniques. Error analysis indicates that the approximation becomes more accurate as the number of generalized Laguerre basis functions increases.

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Recurrent Stroke Prediction using Machine Learning Algorithms with Clinical Public Datasets: An Empirical Performance Evaluation
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Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al

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Publication Date
Sun Aug 25 2019
Journal Name
Civil Engineering Journal
Optimum Efficiency of PV Panel Using Genetic Algorithms to Touch Proximate Zero Energy House (NZEH)
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By optimizing the efficiency of a modular simulation model of the PV module structure by genetic algorithm, under several weather conditions, as a portion of recognizing the ideal plan of a Near Zero Energy Household (NZEH), an ideal life cycle cost can be performed. The optimum design from combinations of NZEH-variable designs, are construction positioning, window-to-wall proportion, and glazing categories, which will help maximize the energy created by photovoltaic panels. Comprehensive simulation technique and modeling are utilized in the solar module I-V and for P-V output power. Both of them are constructed on the famous five-parameter model.  In addition, the efficiency of the PV panel is established by the genetic algorithm

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Publication Date
Wed Oct 01 2025
Journal Name
Journal Of Economics And Administrative Sciences
A Modified Fama-MacBeth Model based on the Single-Index Model
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The aim of this essay is to use a single-index model in developing and adjusting Fama-MacBeth.  Penalized smoothing spline regression technique (SIMPLS) foresaw this adjustment.  Two generalized cross-validation techniques, Generalized Cross Validation Grid (GGCV) and Generalized Cross Validation Fast (FGCV), anticipated the regular value of smoothing covered under this technique. Due to the two-steps nature of the Fama-MacBeth model, this estimation generated four estimates: SIMPLS(FGCV) - SIMPLS(FGCV), SIMPLS(FGCV) - SIM PLS(GGCV), SIMPLS(GGCV) - SIMPLS(FGCV), SIM PLS(GGCV) - SIM PLS(GGCV). Three-factor Fama-French model—market risk premium, size factor, value factor, and their implication for excess stock returns and portfolio return

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Publication Date
Sat Jun 01 2024
Journal Name
Case Studies In Chemical And Environmental Engineering
Optimization of photocatalytic process with SnO2 catalyst for COD reduction from petroleum refinery wastewater using a slurry bubble photoreactor
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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Optimization of Fenton process for removal of chemical oxygen demand (COD) from hospital wastewater using response surface methodology (RSM)
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Publication Date
Fri Jul 12 2024
Journal Name
Biomass Conversion And Biorefinery
Chitosan-triphosphate/food grade algae/montmorillonite clay for adsorptive removal of methyl violet 2B dye removal: Behnken design optimization
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Publication Date
Wed Dec 15 2021
Journal Name
Journal Of Physics: Conference Series
Pretreated Fishbone as Low Cost-Adsorbent for Cationic Dye Adsorption from Aqueous Solutions: Equilibrium, Optimization, Kinetic and Thermodynamic Study
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The present study investigated the use of pretreated fish bone (PTFB) as a new surface, natural waste and low-cost adsorbent for the adsorption of Methyl green (MG, as model toxic basic dye) from aqueous solutions. The functional groups and surface morphology of the untreated fish bone (FB) and pretreated fish bone were characterized using Fourier transform infrared (FTIR), scanning electron microscopy (SEM) and Energy dispersive X-ray spectroscopy (EDS),respectively. The effect of operating parameters including contact time, pH, adsorbent dose, temperature, and inorganic salt was evaluated. Langmuir, Freundlich and Temkin adsorption isotherm models were studied and the results showed that the adsorption of basic dye followed Freundlich iso

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Publication Date
Tue May 28 2019
Journal Name
Al-khwarizmi Engineering Journal
Heuristic D* Algorithm Based on Particle Swarm Optimization for Path Planning of Two-Link Robot Arm in Dynamic Environment
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 Finding a path solution in a dynamic environment represents a challenge for the robotics researchers, furthermore, it is the main issue for autonomous robots and manipulators since nowadays the world is looking forward to this challenge. The collision free path for robot in an environment with moving obstacles such as different objects, humans, animals or other robots is considered as an actual problem that needs to be solved.  In addition, the local minima and sharp edges are the most common problems in all path planning algorithms. The main objective of this work is to overcome these problems by demonstrating the robot path planning and obstacle avoidance using D star (D*) algorithm based on Particle Swarm Optimization (PSO)

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
Pretreated Fishbone as Low Cost-Adsorbent for Cationic Dye Adsorption from Aqueous Solutions: Equilibrium, Optimization, Kinetic and Thermodynamic Study
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Abstract<p>The present study investigated the use of pretreated fish bone (PTFB) as a new surface, natural waste and low-cost adsorbent for the adsorption of Methyl green (MG, as model toxic basic dye) from aqueous solutions. The functional groups and surface morphology of the untreated fish bone (FB) and pretreated fish bone were characterized using Fourier transform infrared (FTIR), scanning electron microscopy (SEM) and Energy dispersive X-ray spectroscopy (EDS), respectively. The effect of operating parameters including contact time, pH, adsorbent dose, temperature, and inorganic salt was evaluated. Langmuir, Freundlich and Temkin adsorption isotherm models were studied and the results showe</p> ... Show More
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Scopus (7)
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Publication Date
Sat Sep 30 2017
Journal Name
Al-khwarizmi Engineering Journal
Delignification of Date Palm Fronds using Modified Organosolv Technique
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Abstract

  In this study, modified organic solvent (organosolv) method was applied to remove high lignin content in the date palm fronds (type Al-Zahdi) which was taken from the Iraqi gardens. In modified organosolv, lignocellulosic material is fractionated into its constituents (lignin, cellulose and hemicellulose). In this process, solvent (organic)-water is brought into contact with the lignocellulosic biomass at high temperature, using stainless steel reactor (digester). Therefor; most of hemicellulose will remove from the biomass, while the solid residue (mainly cellulose) can be used in various industrial fields. Three variables were studied in this process: temperature, ratio of ethano

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