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Application of Water Quality Index and Water Suitability for Drinking of the Euphrates River within Al-Anbar Province, Iraq
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In this study water quality was indicated in terms of Water Quality Index that was determined through summarizing multiple parameters of water test results. This index offers a useful representation of the overall quality of water for public or any intended
use as well as indicating pollution, which are useful in water quality management and decision making. The application of Water Quality Index (WQI) with ten physicochemical water quality parameters was performed to evaluate the quality of Euphrates River water for drinking usage. This was done by subjecting the water samples collected from seven stations within Al-Anbar province during the period 2004-2010 to comprehensive physicochemical analysis. The ten physicochemical parameters included: pH value, Alkalinity (ALK), Orthophosphate (PO4-3), Nitrate (NO3-),Sulphate (SO4-2), Chloride (Cl-), Total Hardness (TH), Calcium (Ca), Magnesium (Mg), and Total Dissolved Solids (TDS). The average annual overall WQI was found to be 107.59 through the study period. The high WQI obtained is a result of the high concentrations of Orthophosphate and Magnesium which can be attributed to the various human
activities taking place along the river banks. From this analysis the quality of the Euphrates River is classified as "very poor quality" ranging poor water at the river upstream near station (E1) and unsuitable for drinking at the river downstream near station (E7) with an annual minimum WQI of 89.34 in 2008 and maximum 112.44 in 2009. The present study demonstrated the application of WQI in estimating and understanding the water quality of Euphrates River. WQI appears to be promising in water quality management and a valuable tool in categorizing pollution sources in surface waters

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Publication Date
Wed Jun 07 2023
Journal Name
Journal Of Educational And Psychological Researches
Job Satisfaction for Educational Counselors: General Directorate of Education Rusafa II
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The current research aims to measure the job satisfaction of educational counselors in the general directorate of education of the second Rusafa in the ministry of education of Iraq. Moreover, it aims to identify the significant differences in job satisfaction according to the gender (Male-Female), the length of service (less than 15 years more than 15 years), and the relationship between these two variables. To achieve the objectives of the research, the researcher developed a scale to measure job satisfaction. This tool was applied to sample of (100) educational counselors selected randomly. The results showed that educational counselors have job satisfaction, in which males are more satisfied in their job than females. The results als

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Publication Date
Wed Nov 04 2020
Journal Name
Advances In Mobility-as-a-service Systems
Community Participation Towards Sustainability Enhancement of Transportation Sector for Baghdad City
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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)
In Situ Gelling Formulation of Naproxen for Oral Sustained Delivery System
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Naproxen is non-steroidal anti-inflammatory drug, which has antipyretic and anti-inflammatory effect. It is extensively bound to plasma albumin, and exhibits gastric toxicity, so it may be more efficient to deliver the drug in its sustained release dosage form and adequate blood level is achieved. Three liquid formulations with in situ gelling properties have been assessed for their potential for the oral sustained delivery of naproxen . The formulations were dilute solutions of: (a) pectin; (b) gellan gum and; (c) sodium alginate, all containing complexed calcium ion that form gels when these ions are released in the acidic environment of the stomach . The viscosity of the sols and drug release were measured, and was found to be depende

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Publication Date
Tue Nov 01 2016
Journal Name
Iosr Journal Of Computer Engineering
Implementation of new Secure Mechanism for Data Deduplication in Hybrid Cloud
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Cloud computing provides huge amount of area for storage of the data, but with an increase of number of users and size of their data, cloud storage environment faces earnest problem such as saving storage space, managing this large data, security and privacy of data. To save space in cloud storage one of the important methods is data deduplication, it is one of the compression technique that allows only one copy of the data to be saved and eliminate the extra copies. To offer security and privacy of the sensitive data while supporting the deduplication, In this work attacks that exploit the hybrid cloud deduplication have been identified, allowing an attacker to gain access to the files of other users based on very small hash signatures of

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Publication Date
Wed Jul 01 2026
Journal Name
Nature Communications
Structural basis for independent pore function of Vpb4 from Bacillus thuringiensis
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Abstract<p> The Bacterial_Exotoxin_B family constitutes translocating pore-forming proteins that function as the binding (B) component in the binary AB Toxin mechanism. While the two-component system of the family is consistent among well-characterised members, the single-component Vpb4 subclass from entomopathogenic <italic>Bacillus thuringiensis</italic> challenges this dogma. Here, through single-particle cryo-electron microscopy, we elucidate the inserted pore structure of a Vpb4 member, Vpb4Aa2, at 2.2 Å resolution. The structure reveals distinguishing features from other family members: missing molecular bottleneck</p> ... Show More
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Publication Date
Mon Feb 27 2023
Journal Name
Applied Sciences
Comparison of ML/DL Approaches for Detecting DDoS Attacks in SDN
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Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an

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Publication Date
Sun May 01 2022
Journal Name
Journal Of Engineering
Performance Analysis of different Machine Learning Models for Intrusion Detection Systems
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In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve

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Publication Date
Fri May 03 2024
Journal Name
Journal Of Optics
Transmission Of 10 Gb/s For Underwater Optical Wireless Communication System
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Publication Date
Thu May 18 2023
Journal Name
Journal Of Engineering
Development of Pavement Maintenance Management System for Baghdad Urban Roadway Network
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The road transportation system is considered as major component of the infrastructure in any country, it affects the developments in economy and social activities. The Asphalt Concrete which is considered as the major pavement material for the road transportation system in Baghdad is subjected to continuous deterioration with time due to traffic loading and environmental conditions, it was felt that implementing a comprehensive pavement maintenance management system (PMMS), which should be capable for preserving the functional and structural conditions of pavement layers, is essential. This work presents the development of PMMS with Visual inspection technique for evaluating the Asphalt Concrete pavement surface condition; common types o

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Publication Date
Fri Nov 15 2019
Journal Name
Journal Of Materials And Applications
Load Transfer Stiffness of Two-layer Roller Compacted Concrete for Pavements
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Roller compacted concrete (RCC) is a form of plain concrete pavement (JPCP). RCC is a zero-slump concrete consisting of well-graded aggregate, cement and water. RCC has many advantages over other pavement types, particularly cost and speed of construction. Recently, RCC has undergone many developments mostly directed towards improving quality, including smoothness and durability. RCC now has the potential to combine the performance of concrete with the low cost of asphalt installation. A two-layer system of RCC with different aggregate types and sizes was utilized in this study. This paper presents the determination of load transfer stiffness across induced joints in a two-layer RCC system based on a cyclic shear test. The test was

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