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Multi-Sites Multi-Variables Forecasting Model for Hydrological Data using Genetic Algorithm Modeling
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A two time step stochastic multi-variables multi-sites hydrological data forecasting model was developed and verified using a case study. The philosophy of this model is to use the cross-variables correlations, cross-sites correlations and the two steps time lag correlations simultaneously, for estimating the parameters of the model which then are modified using the mutation process of the genetic algorithm optimization model. The objective function that to be minimized is the Akiake test value. The case study is of four variables and three sites. The variables are the monthly air temperature, humidity, precipitation, and evaporation; the sites are Sulaimania, Chwarta, and Penjwin, which are located north Iraq. The model performance was checked by comparing it's results with the results of six forecasting models developed for the same data by Al-Suhili and khanbilvardi, 2014.The check of the performance of the new developed model was made for three forecasted series for each variable, using the Akaike test which indicates that the developed model is more successful, since it gave the minimum (AIC) values for (91.67 %) of the forecasted series. This indicates that the developed model had improved the forecasting performance. For the rest of cases (8.33%), other models gave the lowest AIC value, however it is slightly lower than that given by the developed model. Moreover the t-test for monthly means comparison between the models indicates that the developed model has the highest percent of succeed (100%).

 

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Publication Date
Thu Feb 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
The technique of converting multi-choice mathematical programming into linear mathematical programming to find the optimal solution
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The study deals with the issue of multi-choice linear mathematical programming. The right side of the constraints will be multi-choice. However, the issue of multi-purpose mathematical programming can not be solved directly through linear or nonlinear techniques. The idea is to transform this matter into a normal linear problem and solve it In this research, a simple technique is introduced that enables us to deal with this issue as regular linear programming. The idea is to introduce a number of binary variables And its use to create a linear combination gives one parameter was used multiple. As well as the options of linear programming model to maximize profits to the General Company for Plastic Industries product irrigation sy

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Publication Date
Tue Jan 20 2026
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Effects of a Chelated Multi-Micronutrient Nanofertilizer on the Liver ofAlbino Rats: A Biochemical and Histopathological Assessment
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Nanofertilizers offer a promising solution to increase crop yields amid increasing population pressure. Yet  there have been safety concerns about their use, particularly in challenging conditions. This work was designed to assess the toxicological effects of a chelated multi-micronutrient nanofertilizer on albino rats (Rattus norvegicus) as non-target organisms, focusing on the liver, which has important metabolic functions. Thirty-five animals were weighed and randomly divided into 5 groups (n=7). A negative control group was included, and four experimental groups (C1-C4) were given the test item. The dosing regimen for the experimental groups was 15 oral doses of nanofertilizer every other day for 29 days. All the groups were

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Publication Date
Tue Mar 31 2026
Journal Name
Al-zahraa Journal For Health And Medical Sciences
Molecular Genetics Innovations in Diagnosis of Metabolic Disorders: Integration with Multi-Omics and Computational Approaches (Review Article)
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Inherited metabolic disorders (IMDs) are a diverse group of hereditary abnormalities that leads to a defect in metabolic pathway. Its diagnosis has been transformed by the innovations of molecular genetics and computational biology. Conventionally, diagnosis of IMDs is dependent on clinical findings and biochemical tests. Yet, these methods are limited due to a heterogeneity of such disorders and a large number of genes involved. The main objective of this review is to highlight the role of next-generation sequencing (NGS), including targeted gene panels, whole-exome sequencing (WES), and whole-genome sequencing (WGS), in the diagnosis of IMDs and providing reliable information in identifying genetic causes, and to explore the integrated an

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Publication Date
Tue Apr 16 2024
Journal Name
Ecancermedicalscience
Prostate cancer across four countries in the Middle East: a multi-centre, observational, retrospective and prognostic study
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Publication Date
Tue Jan 19 2021
Journal Name
Isprs International Journal Of Geo-information
The Potential of LiDAR and UAV-Photogrammetric Data Analysis to Interpret Archaeological Sites: A Case Study of Chun Castle in South-West England
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With the increasing demands to use remote sensing approaches, such as aerial photography, satellite imagery, and LiDAR in archaeological applications, there is still a limited number of studies assessing the differences between remote sensing methods in extracting new archaeological finds. Therefore, this work aims to critically compare two types of fine-scale remotely sensed data: LiDAR and an Unmanned Aerial Vehicle (UAV) derived Structure from Motion (SfM) photogrammetry. To achieve this, aerial imagery and airborne LiDAR datasets of Chun Castle were acquired, processed, analyzed, and interpreted. Chun Castle is one of the most remarkable ancient sites in Cornwall County (Southwest England) that had not been surveyed and explored

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Publication Date
Fri Nov 26 2021
Journal Name
Nanomaterials
Solidification Enhancement in a Multi-Tube Latent Heat Storage System for Efficient and Economical Production: Effect of Number, Position and Temperature of the Tubes
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Thermal energy storage is an important component in energy units to decrease the gap between energy supply and demand. Free convection and the locations of the tubes carrying the heat-transfer fluid (HTF) have a significant influence on both the energy discharging potential and the buoyancy effect during the solidification mode. In the present study, the impact of the tube position was examined during the discharging process. Liquid-fraction evolution and energy removal rate with thermo-fluid contour profiles were used to examine the performance of the unit. Heat exchanger tubes are proposed with different numbers and positions in the unit for various cases including uniform and non-uniform tubes distribution. The results show that

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Publication Date
Mon Oct 11 2021
Journal Name
Nano Hybrids And Composites
Far Infrared Laser Detector Based on Multi-Walled Carbon Nanotubes and Blend of (Polyaniline - Polymethyl Methacrylate) Polymers with Methyl Blue Dye for Photoconductive Applications
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Infrared photoconductive detectors working in the far-infrared region and room temperature were fabricated. The detectors were fabricated using three types of carbon nanotubes (CNTs); MWCNTs, COOH-MWCNTs, and short-MWCNTs. The carbon nontubes suspension is deposited by dip coating and drop–casting techniques to prepare thin films of CNTs. These films were deposited on porous silicon (PSi) substrates of n-type Si. The I-V characteristics and the figures of merit of the fabricated detectors were measured at a forward bias voltage of 3 and 5 volts as well as at dark and under illumination by IR radiation from a CO2 laser of 10.6 μm wavelengths and power of 2.2 W. The responsivity and figures of merit of the photoconductive detector

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Publication Date
Fri Jan 01 2016
Journal Name
Wuhaib, K.m. , Hadi, B.h. , Hassan, W.a. Iraqi Journal Of Agricultural Sciences, 2016, 47(5), Pp. 1151–1165
Some genetic parameter in maize using full diallel crosses
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Publication Date
Sat Jan 01 2011
Journal Name
Journal Of Engineering
FILTRATION MODELING USING ARTIFICIAL NEURAL NETWORK (ANN)
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In this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, wi

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Publication Date
Sun Sep 07 2014
Journal Name
Baghdad Science Journal
An Algorithm for nth Order Intgro-Differential Equations by Using Hermite Wavelets Functions
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In this paper, the construction of Hermite wavelets functions and their operational matrix of integration is presented. The Hermite wavelets method is applied to solve nth order Volterra integro diferential equations (VIDE) by expanding the unknown functions, as series in terms of Hermite wavelets with unknown coefficients. Finally, two examples are given

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