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FACE IDENTIFICATION USING BACK-PROPAGATION ADAPTIVE MULTIWAVENET
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Face Identification is an important research topic in the field of computer vision and pattern recognition and has become a very active research area in recent decades. Recently multiwavelet-based neural networks (multiwavenets) have been used for function approximation and recognition, but to our best knowledge it has not been used for face Identification. This paper presents a novel approach for the Identification of human faces using Back-Propagation Adaptive Multiwavenet. The proposed multiwavenet has a structure similar to a multilayer perceptron (MLP) neural network with three layers, but the activation function of hidden layer is replaced with multiscaling functions. In experiments performed on the ORL face database it achieved a recognition rate of 97.75% in the presence of facial expression, lighting and pose variations. Results are compared with its wavelet-based counterpart where it obtained a recognition rate of 10.4%. The proposed multiwavenet demonstrated very good recognition rate in the presence of variations in facial expression, lighting and pose and outperformed its wavelet-based counterpart.

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Publication Date
Tue Sep 06 2022
Journal Name
Methods And Objects Of Chemical Analysis
Spectrophotometric Analysis of Quaternary Drug Mixtures using Artificial Neural network model
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A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twenty four samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

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Scopus
Publication Date
Mon Feb 18 2019
Journal Name
Iraqi Journal Of Physics
Drought assessment in Iraq using analysis of Standardized precipitation index (SPI)
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The Present study investigated the drought in Iraq, by using the rainfall data which obtained from 39 meteorological stations for the past 30 years (1980-2010). The drought coefficient calculated on basis of the standard precipitation index (SPI) and then characteristics of drought magnitude, duration and intensity were analyzed. The correlation and regression between magnitude and duration of drought were obtained according the (SPI) index. The result shows that drought magnitude values were greater in the northeast region of Iraq. 

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Publication Date
Mon Jul 10 2023
Journal Name
Journal Of Engineering
3-D Map Producing for Groundwater Level using Kriging Interpolation Method
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The effect of the initial pressure upon the laminar flame speed, for a methane-air mixtures, has been detected paractically, for a wide range of equivalence ratio. In this work, a measurement system is designed in order to measure the laminar flame speed using a constant volume method with a thermocouples technique. The laminar  burning velocity is measured, by using the density ratio method. The comparison of the present work results and the previous ones show good agreement between them. This indicates that the measurements and the calculations employed in the present work are successful and precise

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Publication Date
Sat Sep 30 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Accurate Petrophysical Interpretation of Carbonate using the Elemental Capture Spectroscopy (ECS)
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Elemental capture spectroscopy (ECS) is an important tool in the petroleum industry for determining the composition and properties of rock formations in a reservoir. Knowledge of the types and abundance of different minerals in the reservoir is crucial for accurate petrophysical interpretation, reservoir engineering practices, and stratigraphic correlation. ECS measures the elemental content of the rock, which directly impacts several physical properties that are essential for reservoir characterization, such as porosity, fluid saturation, permeability, and matrix density. The ability to accurately determine these properties leads to better reservoir mapping, improved production, and more effective resource management. Accurately determi

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Publication Date
Tue Jun 30 2015
Journal Name
Al-khwarizmi Engineering Journal
Laser Peening on Aluminum Alloy 7049 Using Black Paint Surface Coating
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Abstract

Black paint laser peening (bPLP) technique is currently applied for many engineering materials , especially for aluminum alloys due to high improvement in fatigue life and strength . Constant and variable   bending fatigue tests have been performed at RT and stress ratio R= -1 . The results of the present  work observed that the significance of the surface work hardening which generated high negative residual stresses in bPLP specimens .The fatigue life  improvement factor (FLIF)  for bPLP constant fatigue behavior was from 2.543 to 3.3 compared to untreated  fatigue and the increase in fatigue strength at 107 cycle was 21% . The bPLP cumulative fatigue life behav

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Publication Date
Mon Feb 25 2019
Journal Name
Iraqi Journal Of Physics
Nuclear level density with proton resonance using Gaussian orthogonal ensemble theory
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The Gaussian orthogonal ensemble (GOE) version of the random matrix theory (RMT) has been used to study the level density following up the proton interaction with 44Ca, 48Ti and 56Fe.

A promising analysis method has been implemented based on the available data of the resonance spacing, where widths are associated with Porter Thomas distribution. The calculated level density for the compound nuclei 45Sc,49Vand 57Co shows a parity and spin dependence, where for Sc a discrepancy in level density distinguished from this analysis probably due to the spin  misassignment .The present results show an acceptable agreement with the combinatorial method of level density.

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Publication Date
Wed Jan 01 2020
Journal Name
Periodicals Of Engineering And Natural Sciences
Estimation of return stock rate by using wavelet and kernel smoothers
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This article aim to estimate the Return Stock Rate of the private banking sector, with two banks, by adopting a Partial Linear Model based on the Arbitrage Pricing Model (APT) theory, using Wavelet and Kernel Smoothers. The results have proved that the wavelet method is the best. Also, the results of the market portfolio impact and inflation rate have proved an adversely effectiveness on the rate of return, and direct impact of the money supply.

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Scopus
Publication Date
Tue Mar 31 2015
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Extraction of Aromatic Hydrocarbons from Lube Oil Using Different Co-Solvent
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An investigation was conducted effect of addition co- solvent on solvent extraction process for two types of a lubricating oil fraction (spindle) and (SAE-30) obtained from vacuum distillation unit of lube oil plant of Daura Refinery. In this study two types of co-solvents ( formamide and N-methyl, 2, pyrrolidone) were blended with furfural to extract aromatic hydrocarbons which are the undesirable materials in raw lubricating oil, in order to improve the viscosity index, viscosity and yield of produced lubricating oil. The studied operating condition are extraction temperature range from 70 to 110 °C for formamide and 80 to 120 °C for N-methyl, 2, pyrrolidone, solvent to oil ratio range from 1:1 to 2:1 (wt./wt.) for furfural with form

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Publication Date
Sat Jun 30 2001
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Extraction of Iron from Al-Hussainyat Iron Ore using Acid Leaching
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Publication Date
Fri Jun 01 2018
Journal Name
International Journal Of Computer Science Trends And Technology
Secure Video Data Deduplication in the Cloud Storage Using Compressive Sensing
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Cloud storage provides scalable and low cost resources featuring economies of scale based on cross-user architecture. As the amount of data outsourced grows explosively, data deduplication, a technique that eliminates data redundancy, becomes essential. The most important cloud service is data storage. In order to protect the privacy of data owner, data are stored in cloud in an encrypted form. However, encrypted data introduce new challenges for cloud data deduplication, which becomes crucial for data storage. Traditional deduplication schemes cannot work on encrypted data. Existing solutions of encrypted data deduplication suffer from security weakness. This paper proposes a combined compressive sensing and video deduplication to maximize

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