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Prediction of sediment heavy metal at the Australian Bays using newly developed hybrid artificial intelligence models
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Publication Date
Thu Dec 01 2011
Journal Name
Journal Of Engineering
Image Reconstruction Using Modified Hybrid Transform
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In this paper, an algorithm for reconstruction of a completely lost blocks using Modified
Hybrid Transform. The algorithms examined in this paper do not require a DC estimation
method or interpolation. The reconstruction achieved using matrix manipulation based on
Modified Hybrid transform. Also adopted in this paper smart matrix (Detection Matrix) to detect
the missing blocks for the purpose of rebuilding it. We further asses the performance of the
Modified Hybrid Transform in lost block reconstruction application. Also this paper discusses
the effect of using multiwavelet and 3D Radon in lost block reconstruction.

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Publication Date
Mon May 15 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Determination of the Heavy Metals in the Contaminated Soil Zones at College of Education Ibn Al-Haitham -University of Baghdad
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  Soil is a crucial component of environment. Total soil analysis may give information about possible enrichment of the soil with heavy metals. Heavy metals, potentially contaminate soils, may have been dumped on the ground. The concentrations of soil heavy metals (Cd, As, Pb, Cr, Ni, Zn and Cu) were measured in three zones thought to be deeply contaminated at different depths (5, 25, 50 cm) at Ibn Al-Haitham College. The highest concentration of heavy metals Pb (63.3ppm), Cr (90.7ppm), Ni (124ppm) and Cu (75.7ppm) were found in zone (A) location-1, where the highest concentration of Zn (111.7ppm) was found in zone (C). Cd and As were detected in small amounts in all zones.     PH value, organic matters, carbonat

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Publication Date
Sun Jun 30 2013
Journal Name
Al-khwarizmi Engineering Journal
Efficiency Prediction and Performance Characterization of Photovoltaic Solar Panel at Baghdad Climate Conditions
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The performance of a solar cell under sun radiation is necessary to describe the electrical parameters of the cell. The Prova 200 solar panel analyzer is used for the professional testing of four solar cells at Baghdad climate conditions. Voltage -current characteristics of different area solar cells operated under solar irradiation for testing their quality and determining the optimal operational parameters for maximum electrical output were obtained. A correlation is developed between solar cell efficiency h and the corresponding solar cell parameters; solar irradiance G, maximum power Pmax, and production date P. The average absolute error of the proposed correlation is 5.5% for 40 data points. The results also show th

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Publication Date
Wed Dec 13 2017
Journal Name
Al-khwarizmi Engineering Journal
Design of a Kinematic Neural Controller for Mobile Robots based on Enhanced Hybrid Firefly-Artificial Bee Colony Algorithm
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The paper present design of a control structure that enables integration of a Kinematic neural controller for trajectory tracking of a nonholonomic differential two wheeled mobile robot, then  proposes a Kinematic neural controller to direct a National Instrument mobile robot (NI Mobile Robot). The controller is to make the actual velocity of the wheeled mobile robot close the required velocity by guarantees that the trajectory tracking mean squire error converges at minimum tracking error. The proposed tracking control system consists of two layers; The first layer is a multi-layer perceptron neural network system that controls the mobile robot to track the required path , The second layer is an optimization layer ,which is impleme

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Publication Date
Thu Jun 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Analysis of Models (NAGARCH & APGARCH) by Using Simulations
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Simulation experiments are a means of solving in many fields, and it is the process of designing a model of the real system in order to follow it and identify its behavior through certain models and formulas written according to a repeating software style with a number of iterations. The aim of this study is to build a model  that deals with the behavior suffering from the state of (heteroskedasticity) by studying the models (APGARCH & NAGARCH) using (Gaussian) and (Non-Gaussian) distributions for different sample sizes (500,1000,1500,2000) through the stage of time series analysis (identification , estimation, diagnostic checking and prediction). The data was generated using the estimations of the parameters resulting f

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Publication Date
Fri Oct 16 2020
Journal Name
Solid State Technology
Study and Investigation of Transition Rate at Metal–Organic Semiconductor Interfaces
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In this paper,we focus on the investigated and studied of transition rate in metal/organic semiconductor interface due to quantum postulate and continuum transition theory. A theoretical  model has been used to estimate  the transition rate cross the interface through estimation many parameters such that ;transition energy  ,driving electronic energy U(eV) ,Potential barrier ,electronic coupling  ,semiconductor volume ,density ,metal work function ,electronic affinity and temperature T. The transition energy  is critical facter of charge transfer through the interfaces of metal organic films device and itscontrol of charge injection and transport cross interface. However,the potential at interfa

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Publication Date
Mon Jul 01 2024
Journal Name
Journal Of Food Process Engineering
Artificial intelligence‐based modeling of novel non‐thermal milk pasteurization to achieve desirable color and predict quality parameters during storage
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Abstract<sec><label></label><p>This study proposed using color components as artificial intelligence (AI) input to predict milk moisture and fat contents. In this sense, an adaptive neuro‐fuzzy inference system (ANFIS) was applied to milk processed by moderate electrical field‐based non‐thermal (NP) and conventional pasteurization (CP). The differences between predicted and experimental data were not significant (<italic>p</italic> > 0.05) for lightness (<italic>L</italic>*), redness‐greenness (<italic>a</italic>*), yellowness‐blueness (<italic>b</italic>*), total color differences (∆<italic>E</italic>), hue angle (<italic>h</italic></p></sec> ... Show More
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Publication Date
Sat Aug 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Simulation of Sediment Transport in the Upper Reach of Al-Gharraf River
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Abstract<p>For the past few years, the sediment began to accumulate in Al-Gharraf River which reduces the flow capacity of the River. In the present research, a numerical model was developed using Hec-Ras software, version 5.0.4. to simulate the flow and sediment transport in the upper reach of the river. The hydrological and cross-section data measured by the Ministry of Water Resources, for the reach located between Kut and Hai cities and having a length of 58200 m, was used to perform calibration and verification of the model. Moreover, field sampling of suspended and bed loads was gathered for five months starting from 7/2/2019, and laboratory tests of samples were conducted to be used as in</p> ... Show More
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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
A Developed Colorimetric Assay Using Unmodified Gold Nanoparticles for the Identification of Acinetobacter baumannii Isolates from Different Clinical Samples
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  Acinetobacter baumannii (A. baumannii ) is considered a critical healthcare problem for patients in intensive care units due to its high ability to be multidrug-resistant to most commercially available antibiotics. The aim of this study is to develop a colorimetric assay to quantitatively detect the target DNA of A. baumannii based on unmodified gold nanoparticles (AuNPs) from different clinical samples (burns, surgical wounds, sputum, blood and urine). A total of thirty-six A. baumannii clinical isolates were collected from five Iraqi hospitals in Erbil and Mosul provinces within the period from September 2020 to January 2021. Bacterial isolation and biochemical identification of isolates

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Publication Date
Wed Dec 01 2021
Journal Name
Civil And Environmental Engineering
Prediction of the Delay in the Portfolio Construction Using Naïve Bayesian Classification Algorithms
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Abstract<p>Projects suspensions are between the most insistent tasks confronted by the construction field accredited to the sector’s difficulty and its essential delay risk foundations’ interdependence. Machine learning provides a perfect group of techniques, which can attack those complex systems. The study aimed to recognize and progress a wellorganized predictive data tool to examine and learn from delay sources depend on preceding data of construction projects by using decision trees and naïve Bayesian classification algorithms. An intensive review of available data has been conducted to explore the real reasons and causes of construction project delays. The results show that the postpo</p> ... Show More
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