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Discrete Fracture Network and Fractured Reservoir Characterization in Khabaz Field-Tertiary Formation
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Publication Date
Fri Apr 28 2023
Journal Name
Mathematical Modelling Of Engineering Problems
Design Optimal Neural Network for Solving Unsteady State Confined Aquifer Problem
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Publication Date
Tue Jun 30 2015
Journal Name
Al-khwarizmi Engineering Journal
Wavelength Division Multiplexing Passive Optical Network modeling Using Optical System Simulator
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Abstract

Due to the continuing demand for larger bandwidth, the optical transport becoming general in the access network. Using optical fiber technologies, the communications infrastructure becomes powerful, providing very high speeds to transfer a high capacity of data. Existing telecommunications infrastructures is currently widely used Passive Optical Network that apply Wavelength Division Multiplexing (WDM) and is awaited to play an important role in the future Internet supporting a large diversity of services and next generation networks. This paper presents a design of WDM-PON network, the simulation and analysis of transmission parameters in the Optisystem 7.0 environment for bidirectional traffic. The sim

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
An Effective Hybrid Deep Neural Network for Arabic Fake News Detection
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Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural

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Publication Date
Mon Dec 02 2024
Journal Name
Engineering, Technology & Applied Science Research
An Artificial Neural Network Prediction Model of GFRP Residual Tensile Strength
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This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
Offline Signature Biometric Verification with Length Normalization using Convolution Neural Network
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Offline handwritten signature is a type of behavioral biometric-based on an image. Its problem is the accuracy of the verification because once an individual signs, he/she seldom signs the same signature. This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. The proposed method is presented by using both signature length normalization and histogram orientation gradient (HOG) for the reason of accuracy improving. In terms of verification, a deep-learning technique using a convolution neural network (CNN) is exploited for building the reference model for a future prediction. Experiments are conducted by utilizing 4,000 genuine as well as 2,000 skilled forged signatu

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Publication Date
Sat Jun 15 2019
Journal Name
Drug Invention Today
Mucoadhesive oral in situ gel of itraconazole using pH-sensitive polymers: Preparation, and in vitro characterization, release and rheology study
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Publication Date
Wed Jan 31 2024
Journal Name
Iraqi Geological Journal
Estimation of Rock Mechanical Properties of the Hartha Formation and their Relationship to Porosity Using Well-Log Data
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The physical and elastic characteristics of rocks determine rock strengths in general. Rock strength is frequently assessed using porosity well logs such as neutron and sonic logs. The essential criteria for estimating rock mechanic parameters in petroleum engineering research are uniaxial compressive strength and elastic modulus. Indirect estimation using well-log data is necessary to measure these variables. This study attempts to create a single regression model that can accurately forecast rock mechanic characteristics for the Harth Carbonate Formation in the Fauqi oil field. According to the findings of this study, petrophysical parameters are reliable indexes for determining rock mechanical properties having good performance p

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Publication Date
Mon Aug 26 2019
Journal Name
Iraqi Journal Of Science
Reconstruction of Paleo depth and Paleo temperature from C- O stable isotope records of Mishrif Formation, southern Iraq
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Stable isotopes 18O/16O and 13C/12C in the carbonate rocks of the Mishrif Formation are examined here to define the depositional characters in the basin includes paleo temperatures and paleo depth.      The Mishrif formation (Cenomanian – Early Turonian) has extensive distribution in Iraq and Middle East. Mishrif Formation composed of organic detrital limestone. Four boreholes in four oilfields, Noor – well (11), Amarah – well (14), Buzurgan – well (24), Halfaya – well (8), in south east of Iraq have been studied. The studied samples have negative δ18O isotope values studied well, with Average (-4.11‰), (-4.47‰), (-4.48‰), (-4.18‰) in the studied wells res

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Publication Date
Fri Sep 01 2023
Journal Name
Migration Letters
Organizational Machiavellianism and Its Impact on Employees’ Passion: A Field Study on a Sample of Electronic Payment Companies in Iraq
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Publication Date
Sun Jul 01 2001
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
FIELD EFFICACY OF THREE TYPES OF INSECTICIDES AGAINST LARVAE OF MUSCADOMESTICABREEDING IN EQUINE MANURE AND THEIR EFFECTS ON PREDATORY MITES
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The field efficacy of Actellic (organophosphate), Neporex (insect growth regulator) and
Ficam (carbamate), at the application rates of 2-4, 0.4-0.8 and 0.1-0.2 g AI/m2 respectively,
was studied against the larvae of Musca domestica L. Results of treatments involving horse
manure indicated that Actellic and Neporex produced sharp decrease of larval numbers (close
to zero) for 21d. But there was a slight recovery in larval numbers 14 d following treatment
with Ficam. The populations of predator mites were not affected due to insecticidal
applications.

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