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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
Tue Mar 30 2021
Journal Name
Baghdad Science Journal
Measurement of some Air Pollutantsin Printing Units and Copy Centers Within Baghdad City
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Emissions of particulate matter from nanopapers as well as inks and organic solvents during the printing operationand copying machines constitute a threat to human health, especially with long time exposure in closed working environments. The present study was conducted in some printing houses and copying centers of Baghdad city during February and April  .The studyproved the occurrence of an air pollution problem concerning lead and zinc contents in all the study sites. The levels of Pb, Zn and Cu were collected by low volume sampler from the air of the study sites then filter papers digested and determined the heavy metals by flame atomic spectrophotometer. Particulate matter was measured by Aerocet, Microtector  meter device was use

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Scopus (11)
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Publication Date
Thu Aug 18 2022
Journal Name
Physica Scripta
NORM and hazard indices in soil and dates of palms groves in Baghdad Governorate, Iraq
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Abstract<p>Date palm (Phoenix dactylifera) is one of the world’s oldest cultivated fruit crops and belongs to the Arecaceae family. It originated in Mesopotamia (Iraq) in 4000 BC. Large areas of palm groves in Iraq produce various types of dates for internal consumption and export. Their cultivation has spread and has become a significant crop in the Arabian Peninsula, North Africa, and the Middle East. Date fruits are widely consumed in Iraq, and radiological monitoring of this crop is necessary as activity concentrations of <sup>238</sup>U, <sup>232</sup>Th, <sup>40</sup>K, and <sup>137</sup>Cs were measured in 12 soil samples and 12 date samples from </p> ... Show More
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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Recurrent Stroke Prediction using Machine Learning Algorithms with Clinical Public Datasets: An Empirical Performance Evaluation
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Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al

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Publication Date
Wed Dec 30 2015
Journal Name
College Of Islamic Sciences
The semantics of terms in terms of inclusiveness when Imam Ibn Hajar al-Askalani (d. 852 e) in his book Fath al-Bari: Door of worship - Practical models
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Praise be to Allaah.
My research has included the following: The field of application of semantics when fundamentalists are the book and the Sunnah. Imam Ibn Hajar agreed with the majority of fundamentalists that what is meant from the year (one word denotes one side on two things onwards), and agreed that the significance of the year specific to the rest of its members is not a definite and definite formulas of the public has the singular known as (the) Astragharism, and the plural known as ( The nationality stating that dumping, pluralism is defined as (add), and nakra, if it occurs in the context of the condition, denial and prohibition, the names of the condition, the connected names, and the word (all - all). And the year in whic

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Publication Date
Tue Mar 28 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Relationship between Blood Lead Levels and Hematological Parameters in Children from Al-Fallujah City in Iraq
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Environmental exposures to lead remain a serious problem in the developing and industrializing countries. Children are the highest risk aged-group for lead poisoning. This study was designed to assess lead exposure in Al-Fallujah city by analyzing blood lead levels in children and adults and to explain the relationship between blood lead levels, hematological parameters and ferritin levels in the children. The study was performed on-(90) subjects, (65children and 25 adults).Venous blood samples were taken for estimation of hematological parameters, serum ferritin levels and blood lead levels. The children group was subdivided into four groups as: group (A) (low ferritin, low Hb), group (B) (low ferritin, normal Hb), group (C) (normal fer

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Publication Date
Thu Jan 11 2018
Journal Name
Al-khwarizmi Engineering Journal
Control on a 2-D Wing Flutter Using an Adaptive Nonlinear Neural Controller
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An adaptive nonlinear neural controller to reduce the nonlinear flutter in 2-D wing is proposed in the paper. The nonlinearities in the system come from the quasi steady aerodynamic model and torsional spring in pitch direction. Time domain simulations are used to examine the dynamic aero elastic instabilities of the system (e.g. the onset of flutter and limit cycle oscillation, LCO). The structure of the controller consists of two models :the modified Elman neural network (MENN) and the feed forward multi-layer Perceptron (MLP). The MENN model is trained with off-line and on-line stages to guarantee that the outputs of the model accurately represent the plunge and pitch motion of the wing and this neural model acts as the identifier. Th

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Publication Date
Sun Mar 31 2013
Journal Name
Inventi Impact: Artificial Intelligence
SIMULATION OF IDENTIFICATION AND CONTROL OF SCARA ROBOT USING MODIFIED RECURRENT NEURAL NETWORKS
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This paper presents a modified training method for Recurrent Neural Networks. This method depends on the Non linear Auto Regressive (NARX) model with Modified Wavelet Function as activation function (MSLOG) in the hidden layer. The modified model is known as Modified Recurrent Neural (MRN). It is used for identification Forward dynamics of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot. This model is also used in the design of Direct Inverse Control (DIC). This method is compared with Recurrent Neural Networks that used Sigmoid activation function (RS) in the hidden layer and Recurrent Neural Networks with Wavelet activation function (RW). Simulation results shows that the MRN model is bett

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Publication Date
Wed Dec 27 2017
Journal Name
Al-khwarizmi Engineering Journal
Human Face Recognition Using GABOR Filter And Different Self Organizing Maps Neural Networks
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This work implements the face recognition system based on two stages, the first stage is feature extraction stage and the second stage is the classification stage. The feature extraction stage consists of Self-Organizing Maps (SOM) in a hierarchical format in conjunction with Gabor Filters and local image sampling. Different types of SOM’s were used and a comparison between the results from these SOM’s was given.

The next stage is the classification stage, and consists of self-organizing map neural network; the goal of this stage is to find the similar image to the input image. The proposal method algorithm implemented by using C++ packages, this work is successful classifier for a face database consist of 20

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Publication Date
Sat Dec 11 2021
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Association of Age, Parity and Body mass Index with Hemoglobin and Serum Ferritin Levels in Pregnant Women in Baghdad City
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Hemogloin (Hb) and serum ferritin levels are used to assess anemia in pregnancy. Some studies referred to the influence of maternal age, body mass index (BMI) and parity on Hb and serum ferritin levels. The study aimed to examine the possible association of maternal Hb and serum ferritin with maternal age, parity, and BMI in a sample of pregnant women in Baghdad.

 Ninety healthy pregnant women, grouped in three equal groups according to the pregnancy trimester, and thirty apparently healthy non-pregnant women from Baghdad were enrolled in this observational study.  Blood and serum samples were obtained for the estimation of Hb and serum ferritin levels.

The pooled data of participants showed a n

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Publication Date
Mon Jan 01 2018
Journal Name
Communications In Computer And Information Science
Automatically Recognizing Emotions in Text Using Prediction by Partial Matching (PPM) Text Compression Method
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In this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo

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