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Optimization conditions for bioemulsifier production by local Streptomyces sp. SS20 isolated from hydrocarbon contaminated soil
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Publication Date
Sun Jan 01 2017
Journal Name
Lecture Notes In Computer Science
Constrained Differential Evolution for Cost and Energy Efficiency Optimization in 5G Wireless Networks
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The majority of real-world problems involve not only finding the optimal solution, but also this solution must satisfy one or more constraints. Differential evolution (DE) algorithm with constraints handling has been proposed to solve one of the most fundamental problems in cellular network design. This proposed method has been applied to solve the radio network planning (RNP) in the forthcoming 5G Long Term Evolution (5G LTE) wireless cellular network, that satisfies both deployment cost and energy savings by reducing the number of deployed micro base stations (BSs) in an area of interest. Practically, this has been implemented using constrained strategy that must guarantee good coverage for the users as well. Three differential evolution

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Scopus (2)
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Publication Date
Sun Jun 30 2024
Journal Name
Malaysian Journal Of Science
SIMPLEX OPTIMIZATION FOR THE SPECTROPHOTOMETRIC DETERMINATION OF AZITHROMYCIN DRUG VIA ION-PAIR FORMATION
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A spectrophotometric determination of azithromycin was optimized using the simplex model. The approach has been proven to be accurate and sensitive. The analyte has been reacted with bromothymol blue (BTB) to form a colored ion pair which has been extracted in chloroform in a buffer medium of pH=4 of potassium phthalate. The extracted colored product was assayed at 415 nm and exhibited a linear quantification range over (1 - 20) g/ml. The excipients did not exhibit any interferences with the proposed approach for assaying azithromycin in pharmaceutical formulations.

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Scopus
Publication Date
Fri Jul 01 2016
Journal Name
Journal Of Engineering
An Adaptive Multi-Objective Particle Swarm Optimization Algorithm for Multi-Robot Path Planning
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This paper discusses an optimal path planning algorithm based on an Adaptive Multi-Objective Particle Swarm Optimization Algorithm (AMOPSO) for two case studies. First case, single robot wants to reach a goal in the static environment that contain two obstacles and two danger source. The second one, is improving the ability for five robots to reach the shortest way. The proposed algorithm solves the optimization problems for the first case by finding the minimum distance from initial to goal position and also ensuring that the generated path has a maximum distance from the danger zones. And for the second case, finding the shortest path for every robot and without any collision between them with the shortest time. In ord

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Publication Date
Wed Oct 09 2024
Journal Name
Engineering, Technology & Applied Science Research
Improving Pre-trained CNN-LSTM Models for Image Captioning with Hyper-Parameter Optimization
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The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

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Scopus (11)
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Publication Date
Fri Apr 24 2026
Journal Name
F1000research
Machine Learning Assisted Hybrid Cuckoo Search for Predictive Optimization in Renewable Energy Systems
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Background Due to the intermittent, nonlinear, and uncertain behavior of renewable energy sources (res) such as solar and wind, grid stability and reliability require very high forecasting and optimization skills as widely reported in the literature. Traditional optimization methods work very well in small or static systems but are suffer difficulty on large-scale, dynamic and stochastic renewable environment due to their NP-hard nature. Methods The framework introduces the concept of a Machine Learning-Assisted Hybrid Cuckoo Search (ML-HCS) that combines CS with a hybrid metaheuristic and integrates Long Short-Term Memory (LSTM) networks for forecasting based on both regression models of LSTMs and hybrid optimization algorithm

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Publication Date
Mon Dec 05 2022
Journal Name
Baghdad Science Journal
Electron lens Optimization for Beam Physics Research using the Integrated Optics Test Accelerator
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This study proposed control system that has been presented to control the electron lens resistance in order to obtain a stabilized electron lens power. This study will layout the fundamental challenges, hypothetical plan arrangements and development condition for the Integrable Optics Test Accelerator (IOTA) in progress at Fermilab. Thus, an effective automatic gain  control (AGC) unit has been introduced which prevents fluctuations in the internal resistance of the electronic lens caused by environmental influences to affect the system's current and power values ​​and keep them in stable amounts. Utilizing this unit has obtained level balanced out system un impacted with electronic lens surrounding natural varieties.

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Publication Date
Fri Jun 30 2017
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Comparative Study for Removal of Zn+2 Ions from Aqueous Solutions by Adsorption and Forward Osmosis
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The aim of this paper was to investigate the removal efficiencies of Zn+2 ions from wastewater by adsorption (using tobacco leaves) and forward osmosis (using cellulose triacetate (CTA) membrane). Various experimental parameters were investigated in adsorption experiment such as: effect of pH (3 - 7), contact time (0  - 220) min, solute concentration (10 - 100) mg/l, and adsorbent dose (0.2 - 5)g. Whereas for forward osmosis the operating parameters studied were: draw solution concentration (10 - 150) g/l, pH of feed solution (4 - 7), feed solution concentration (10 - 100) mg/l. The result showed that the removal efficiency by using adsorption was 70% and the removal efficiency by using forward osmosis was 96.2 %. 

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Publication Date
Fri Feb 25 2022
Journal Name
Heat And Mass Transfer
Optimization, equilibrium, kinetics and thermodynamic study of congo red dye adsorption from aqueous solutions using iraqi porcelanite rocks
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Publication Date
Sun Jun 07 2009
Journal Name
Baghdad Science Journal
Synbiotic Effect of Probiotic ( Bifidobacterium sp ) and Prebiotics (Chicory and Inulin ) aganist some pathogenic bacteria
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The Antimicrobial activity of Probiotic Bifidobacterium sp and Prebiotics : chicory roots ( Hot water extract ) and Inulin ( 10 % ) against some Pathogenic bacteria (Esherichia coli , Proteus mirabilis , Klebsiella sp , Pseudomonas aeruginosa , Serratia marcescens was studied . The combination of Probiotic and Prebiotics (Synbiotic) (Bifidobacterium sp + chicory ) and (Bifidobacterium sp + Inulin ) also tested for their antimicrobial activity against Pathogenic bacteria . Results showed that Bifidobacterium sp had good antimicrobial activity against all the Pathogenic bacteria tested , followed by chicory and inulin . The synergistic inhibitory effect of Synbiotic (Bifidobacterium sp + chicory ) and ( Bifidobacterium sp + inuli

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Publication Date
Wed Dec 30 2015
Journal Name
College Of Islamic Sciences
Making up missed fasts Terms and conditions
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The obligatory duty must be fulfilled for attachment to the discharge, whatever the reasons for the missingness, whether it is left by mistake or omission or deliberate, whether with or without excuse. What is likely in this research to spend Ramadan on laxity.
The one who delayed making up Ramadaan fasts until he realized another Ramadaan, fasted the second and spent the first after him, and no ransom on him, either with an excuse or without an excuse.

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