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Rigid trunk sewer deterioration prediction models using multiple discriminant and neural network models in Baghdad city, Iraq
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The deterioration of buried sewers during their lifetime can be affected by several factors leading to bad performance and can damage the infrastructure similar to other engineering structures. The Hydraulic deterioration of the buried sewers caused by sewer blockages while the structural deterioration caused by sewer collapses due to sewer specifications and the surrounding soil characteristics and the groundwater level. The main objective of this research is to develop deterioration models, which are used to predict changes in sewer condition that can provide assessment tools for determining the serviceability of sewer networks in Baghdad city. Two deterioration models were developed and tested using statistical software SPSS, the multiple discriminant model (MDM) and neural network model (NNM). Zublin trunk sewer in Baghdad city was selected as a case study. The deterioration model based on the NNDM provide the highest overall prediction efficiency which could be attributed to its inherent ability to model complex processes. The MDDM provided relatively low overall prediction efficiency, this may be due to the restrictive assumptions by this model. For the NNDM the confusion matrix gave overall prediction efficiency about 87.3% for model training and 70% for model validation, and the overall conclusion from these models may predict that Zublin trunk sewer is of a poor condition.

Publication Date
Wed Aug 26 2020
Journal Name
Journal Of Engineering
Groundwater Simulation and Wells Distribution at Qazaniyah City in Diyala Governorate
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In recent years, there is more interest in water sources availability, including groundwater due to an increase in demand for water because of the increasing population in the world, and the water recedes due to climate change also. Therefore, the study of groundwater has required more attention. The aim of the present study is to establish a MODFLOW model in the groundwater modeling system software to simulate the movement of groundwater in the Turssaq alluvial fan which is located in the Qazaniyah city, east of Diyala Governorate. The solid model was used to define the aquifer in the study area. Using the GIS software, mapping and preparing the data needed to create a conceptual model were carried out. The data of the

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Medicine And Life
An overview of neuro-ophthalmic disorders at Jenna Ophthalmic Center, Baghdad, Iraq (2021-2022)
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Neuro-ophthalmic disorders are often documented individually for each illness, with little data available on their overall incidence and pattern. The overall incidence of neuro-ophthalmic illnesses in Iraq is still not recorded. This study aimed to evaluate the clinical, demographic, and etiological features of patients seeking consultation at an Iraqi neuro-ophthalmology clinic. A prospective cross-sectional observational research was conducted at the Janna Ophthalmic Center in Baghdad, Iraq. The center serves a diverse patient population from various governorates. All newly diagnosed patients with neuro-ophthalmic disorders who visited the neuro-ophthalmological clinic, regardless of gender or age group, were included. The neuro-ophthalmo

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Publication Date
Thu Jan 01 2009
Journal Name
Computer And Information Science 2009
The Stochastic Network Calculus Methodology
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Home Computer and Information Science 2009 Chapter The Stochastic Network Calculus Methodology Deah J. Kadhim, Saba Q. Jobbar, Wei Liu & Wenqing Cheng Chapter 568 Accesses 1 Citations Part of the Studies in Computational Intelligence book series (SCI,volume 208) Abstract The stochastic network calculus is an evolving new methodology for backlog and delay analysis of networks that can account for statistical multiplexing gain. This paper advances the stochastic network calculus by deriving a network service curve, which expresses the service given to a flow by the network as a whole in terms of a probabilistic bound. The presented network service curve permits the calculation of statistical end-to-end delay and backlog bounds for broad

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Publication Date
Sat Oct 01 2011
Journal Name
Journal Of Engineering
MODIFIED TRAINING METHOD FOR FEEDFORWARD NEURAL NETWORKS AND ITS APPLICATION in 4-LINK SCARA ROBOT IDENTIFICATION
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In this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func

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Publication Date
Mon Oct 17 2011
Journal Name
Journal Of Engineering
MODIFIED TRAINING METHOD FOR FEEDFORWARD NEURAL NETWORKS AND ITS APPLICATION in 4-LINK SCARA ROBOT IDENTIFICATION
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In this research the results of applying Artificial Neural Networks with modified activation function to perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of identification strategy consists of a feed-forward neural network with a modified activation function that operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have been trained online and offline have been used, without requiring any previous knowledge about the system to be identified. The activation function that is used in the hidden layer in FFNN is a modified version of the wavelet function. This approach ha

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Publication Date
Sun Oct 05 2025
Journal Name
Mesopotamian Journal Of Computer Science
DGEN: A Dynamic Generative Encryption Network for Adaptive and Secure Image Processing
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Cyber-attacks keep growing. Because of that, we need stronger ways to protect pictures. This paper talks about DGEN, a Dynamic Generative Encryption Network. It mixes Generative Adversarial Networks with a key system that can change with context. The method may potentially mean it can adjust itself when new threats appear, instead of a fixed lock like AES. It tries to block brute‑force, statistical tricks, or quantum attacks. The design adds randomness, uses learning, and makes keys that depend on each image. That should give very good security, some flexibility, and keep compute cost low. Tests still ran on several public image sets. Results show DGEN beats AES, chaos tricks, and other GAN ideas. Entropy reached 7.99 bits per pix

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Publication Date
Thu Mar 30 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
The Safety Profile of Single Daily Dose of Aminoglycosides in Comparison with Multiple Daily Dose
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To overcome  the  problems  which  associated  with  the standard  multiple  daily  doses (MDD)

of aminoglycosides (AGs) like high incidence of toxicity(nephrotoxicity, ototoxicity)(5-25%) and high cost, an alternative approach was developed which was single daily dose (SDD).This new regimen was designed to maximize bacterial killing by optimizing the peak concentration/minimum inhibitory concentration(MIC)ratio and to reduce the potential for toxicity. The study includes 75 patients selected randomly, 50 of them received SDD regimen of age range of 17-79 years and the remaining received MDD regimen of age range of 13-71 years. The study was designed to evaluate the safety of SDD regim

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Publication Date
Sun Dec 27 2020
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn: 1683 - 3597 , E-issn : 2521 - 3512)
Estimation of Beta Two Microglobulins, Fetuin-A, Resistin Serum Level in Iraqi Multiple Myeloma Patients
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Multiple myeloma is hematological disease produces many complications in the bone, kidney, neural and other complications. The study aims to measure serum biomolecules like fetuin-A and resistin and determined the possibility to use these biomarkers as disease predictor. blood samples were isolated from 58 patients and 24 sex and age-matched control, serum then isolated, and proper ELISA kit then used to a determined level of B2 microglobulin, resistin, and fetuin-A. The result demonstrated significant increase in   B2 microglobulin, fetuin-A and resistin in patients compare to control (1.3470.714 vs. 0.9130.253), p = 0.000, (14.00310.352 vs. 9.2594.264), p= 0.005, (1.9673.595 vs. 0.6040.622), p = 0.009, respectively.   These di

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Publication Date
Thu Jul 01 2021
Journal Name
Solar Energy
A new approach for employing multiple PCMs in the passive thermal management of photovoltaic modules
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Publication Date
Wed Jan 13 2016
Journal Name
University Of Baghdad
Employ Mathematical Model and Neural Networks for Determining Rate Environmental Contamination
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