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Detection and Removal of Polycyclic Aromatic Hydrocarbon from Selected Areas in Tigris River in Baghdad City
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Aromatic hydrocarbons present in Iraqi national surface water were believed to be raised principally from combustion of various petroleum products, industrial processes and transport output and their precipitation on surface water.
Polycyclic aromatic hydrocarbons (PAHs) were included in the priority pollutant list due to their toxic and carcinogenic nature. The concern about water contamination and the consequent human exposure have encouraged the development of new methods for
PAHs detection and removal.
PAHs, the real contaminants of petroleum matter, were detected in selected sites along Tigris River within Baghdad City in summer and winter time, using Shimadzu high performance liquid chromatography (HPLC) system.
Analysis of samples from selected sites proved that the most abundant component of aromatic hydrocarbons were phenanthrene naphthalene, and acenaphthylene, followed by fluorene, acenaphthene, fluoranthene, benzo (a) pyrene, anthracene. and pyrene were
present in low concentrations ranging in a descending order. Chrysene and benzo (a) anthracene were found in very low concentration.
A laboratory unit was designed to optimize the factors which may influence the feasibility of degradation processes of naphthalene and phenanthrene in aqueous matrices by oxidation with Fenton reagent. The study proved that 83% and 79% removal of naphthalene and phenanthrene were achieved applying optimum conditions of pH=3, temperature=40 ° C, H2O2=50 ppm and Fe2+ catalyst = 6 ppm

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Publication Date
Wed Dec 18 2019
Journal Name
Baghdad Science Journal
Detection of Nutrients and Major Ions at Al Muthanna Storage Site Soil
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In the early 90s military operations and United Nations Special Commission “UNSCOM” teams have been destroyed the past Iraqi chemical program. Both operations led an extensive number of scattered remnants of contaminated areas. The quantities of hazardous materials, incomplete destructed materials, and toxic chemicals were sealed in two bunkers. Deficiency of appropriate destruction technology led to spreading the contamination around the storage site. This paper aims to introduce the environmental detection of the contamination in the storage site area using geospatial analysis technique. The environmental contamination level of nutrients and major ions such as sulphate (SO4), potassium (K), sodium (Na), magnesi

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Publication Date
Sun Feb 03 2019
Journal Name
Iraqi Journal Of Physics
Change detection of remotely sensed image using NDVI subtractive and classification methods.
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Change detection is a technology ascertaining the changes of
specific features within a certain time Interval. The use of remotely
sensed image to detect changes in land use and land cover is widely
preferred over other conventional survey techniques because this
method is very efficient for assessing the change or degrading trends
of a region. In this research two remotely sensed image of Baghdad
city gathered by landsat -7and landsat -8 ETM+ for two time period
2000 and 2014 have been used to detect the most important changes.
Registration and rectification the two original images are the first
preprocessing steps was applied in this paper. Change detection using
NDVI subtractive has been computed, subtrac

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Publication Date
Sat Jan 31 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Depression status in relation to caries experience and salivary physiochemical characteristics among 15 years old students in Al-Swera city – Wassit Governorate-Iraq
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Background: Depression is a common mental disorder that presents with depressed mood;it can become chronic or recurrent and affect dental health .Thus this research aimed to assess the prevalence and severity of dental caries among students with different grade of depression in relation to physicochemical characteristics of stimulated whole saliva. Materials and methods: The total sample involved for depression status assessment is composed of 800 students for both gender aged 15 years old that were selected randomly , This was performed using children depression inventory (CDI) index that divided the students into four groups of depression(low or average grade, high average grade, elevated grade and very elevated grade). The diagnosis and

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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
Removal of Copper Ions onto Walnut Shells by Using Batch and Continuous Fluidized Bed
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An agricultural waste (walnut shell) was undertaken to remove Cu(II) from aqueous solutions in batch and continuous fluidized bed processes. Walnut shell was found to be effective in batch reaching 75.55% at 20 and 200 rpm, when pH of the solution adjusted to 7. The equilibrium was achieved after 6 h of contacting time. The maximum uptake was 11.94mg/g. The isotherm models indicated that the highest determination coefficient belongs to Langmuir model. Cu (II) uptake process in kinetic rate model followed the pseudo-second-order with determination coefficient of 0.9972. More than 95% of the Cu(II) were adsorbed on the walnut shells within 6 h at optimum agitation speed of 800 rpm. The main functional groups responsible for biosorption of

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Publication Date
Wed Jan 01 2025
Journal Name
E3s Web Of Conferences
The impact of military waste on Iraq’s waters: The case of the Jassim River
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This article aims to investigate how war contributes to the pollution of water bodies with harmful substances including heavy metals and toxic substances. The paper explains how these pollutants, carelessly dumped by military operations, have severely damaged the water quality of rivers and lakes all across Iraq. Based on the Jassim River as case study, the paper shows a close relationship between military operations and pollution. Shown is the effects of this pollution on local ecosystems like fish and wildlife, and human population, dependent on the river for drinking, irrigation, and other basic needs. The article reveals the problem of military waste in Iraq, focusing on the absence of satisfactory waste disposal techniques and

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Publication Date
Sat Jan 31 2026
Journal Name
Journal Of Oral And Dental Research
Prevalence of Orofacial Clefts: A Retrospective Crosssectional Analysis of Gynecology and Obstetrics Hospital Records in the City of Sulaimani, Kurdistan Region of Iraq
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Publication Date
Tue Dec 28 2021
Journal Name
2021 2nd Information Technology To Enhance E-learning And Other Application (it-ela)
Pedestrian and Objects Detection by Using Learning Complexity-Aware Cascades
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Publication Date
Mon May 11 2020
Journal Name
Baghdad Science Journal
Towards Accurate Pupil Detection Based on Morphology and Hough Transform
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 Automatic recognition of individuals is very important in modern eras. Biometric techniques have emerged as an answer to the matter of automatic individual recognition. This paper tends to give a technique to detect pupil which is a mixture of easy morphological operations and Hough Transform (HT) is presented in this paper. The circular area of the eye and pupil is divided by the morphological filter as well as the Hough Transform (HT) where the local Iris area has been converted into a rectangular block for the purpose of calculating inconsistencies in the image. This method is implemented and tested on the Chinese Academy of Sciences (CASIA V4) iris image database 249 person and the IIT Delhi (IITD) iris

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
DNA Encoding and STR Extraction for Anomaly Intrusion Detection Systems
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Publication Date
Tue Jun 23 2020
Journal Name
Baghdad Science Journal
Anomaly Detection Approach Based on Deep Neural Network and Dropout
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   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

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