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Application of multivariate statistical techniques in the evaluation of large-scale water treatment plants in Baghdad.
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Abstract<p>This paper aims to evaluate large-scale water treatment plants’ performance and demonstrate that it can produce high-level effluent water. Raw water and treated water parameters of a large monitoring databank from 2016 to 2019, from eight water treatment plants located at different parts in Baghdad city, were analyzed using nonparametric and multivariate statistical tools such as principal component analysis (PCA) and hierarchical cluster analysis (HCA). The plants are Al-Karkh, Sharq-Dijlah, Al-Wathba, Al-Qadisiya Al-Karama, Al-Dora, Al-Rasheed, Al-Wehda. PCA extracted six factors as the most significant water quality parameters that can be used to evaluate the variation in drinking water quality and responsible for 73.389% of the variance in the data set. Based on this selection criterion, the most significant water quality parameters that can be used to evaluate the variation in drinking water quality parameters are the mineral-related parameters (e.g., Ca<sup>+2</sup>, Mg<sup>+2</sup>, salinity, hardness), the nutrient parameters (i.e., dissolved nitrate and nitrite and orthophosphate), and a physical parameter. HCA analysis was able to group water treatment plants with similar raw water and treated water quality based on the water quality data from eight WTPs into three clusters.</p>
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Publication Date
Tue Dec 30 2025
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
Deep Spoof Face Detection Techniques in React Native
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The rapid rise in the use of artificially generated faces has significantly increased the risk of identity theft in biometric authentication systems. Modern facial recognition technologies are now vulnerable to sophisticated attacks using printed images, replayed videos, and highly realistic 3D masks. This creates an urgent need for advanced, reliable, and mobile-compatible fake face detection systems. Research indicates that while deep learning models have demonstrated strong performance in detecting artificially generated faces, deploying these models on consumer mobile devices remains challenging due to limitations in computing power, memory, privacy, and processing speed. This paper highlights several key challenges: (1) optimiz

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Publication Date
Fri Mar 19 2021
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
New cost control techniques in mega construction projects
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Publication Date
Tue Oct 08 2024
Journal Name
Technology In Agronomy
Harnessing automation techniques for supporting sustainability in agriculture
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Automation is one of the key systems in modern agriculture, providing potential solutions to the challenges related to the growing world population, demographic shifts, and economic situation. The present article aims to highlight the importance of precision agriculture (PA) and smart agriculture (SA) in increasing agricultural production and the importance of environmental protection in increasing production and reducing traditional production. For this purpose, different types of automation systems in the field of agricultural operations are discussed, as well as smart agriculture technologies including the Internet of Things (IoT), artificial intelligence (AI), machine learning (ML), big data analysis, in addition to agricultural robots,

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Publication Date
Tue Dec 30 2025
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
Deep Spoof Face Detection Techniques in React Native
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The rapid rise in the use of artificially generated faces has significantly increased the risk of identity theft in biometric authentication systems. Modern facial recognition technologies are now vulnerable to sophisticated attacks using printed images, replayed videos, and highly realistic 3D masks. This creates an urgent need for advanced, reliable, and mobile-compatible fake face detection systems. Research indicates that while deep learning models have demonstrated strong performance in detecting artificially generated faces, deploying these models on consumer mobile devices remains challenging due to limitations in computing power, memory, privacy, and processing speed. This paper highlights several key challenges: (1) optimiz

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Publication Date
Thu Jul 01 2010
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
NOTES ON SOME ARMORED SCALE INSECTS (HEMIPTERA:DIASPIDIDAE) OF IRAQ
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Sixteen species of Armored Scale insects were recorded from Baghdad city during 2001-2005. Three of these are reported here for the first time Abgrallaspis cyanophylli (Signoret, 1869), Aonidiella citrina (Craw,1870) and Chrysomphalus aonidium (Linnaeus,1758). The other thirteen species were recorded earlier Aonidiella aurantii (Maskell), Aonidiella orientalis (Newstead), Chrysomphalus dictyospermi (Morgan), Diaspidiotus ostreaeformis (Curtis), Diaspidiotu perniciosus (Comctock), Hemiberlesia lataniae (Signoret), Lepidosaphes beckii (Newman), Lepidosaphes conchiformis (Gmelin), Lepidosaphes ulmi (Linnaeus), Mercetaspis halli

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Publication Date
Thu Apr 25 2019
Journal Name
Engineering And Technology Journal
Improvement of Harris Algorithm Based on Gaussian Scale Space
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Features is the description of the image contents which could be corner, blob or edge. Corners are one of the most important feature to describe image, therefore there are many algorithms to detect corners such as Harris, FAST, SUSAN, etc. Harris is a method for corner detection and it is an efficient and accurate feature detection method. Harris corner detection is rotation invariant but it isn’t scale invariant. This paper presents an efficient harris corner detector invariant to scale, this improvement done by using gaussian function with different scales. The experimental results illustrate that it is very useful to use Gaussian linear equation to deal with harris weakness.

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Publication Date
Tue May 07 2024
Journal Name
Hayati Journal Of Biosciences
Histological and Molecular Evaluation of the Antiproliferative Activity of Allium ampeloprasum Water Extract Against Oral Mucosa Cell Line (Gingival Cancer)
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Gingival carcinoma is a malignant neoplasm affecting the oral mucosa and is associated with significant morbidity and mortality. Allium ampeloprasum var. porrum water extracts have gotten a lot of attention because of their bioactive components, such as polyphenols, flavonoids, and alkaloids, which have a variety of pharmacological activities, including antiproliferative actions. This study aimed to evaluate the histological and molecular effects of Allium ampeloprasum (leek) water extract on the proliferation of the murine gingival cancer cell line. Histological evaluation was conducted to examine morphological changes induced by extract treatment. Molecular mechanisms underlying the observed histological changes were investigated

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Publication Date
Tue Jan 01 2019
Journal Name
Plant Archives
The seasonal effect on the water bodies in Iraqi marshlands
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Publication Date
Sat Oct 19 2019
Journal Name
Geotechnical And Geological Engineering
Local Scale Displacement Fields in Grains–Structure Interactions Under Cyclic Loading: Experiments and Simulations
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Abstract<p>Soils encounter cyclic loading conditions in situ, for example during the earthquakes and in the construction sequences of pavements. Investigations on the local scale displacements of the soil grain and their failure patterns under the cyclic loading conditions are relatively scarce in the literature. In this study, the local displacement fields of a dense sand layer interacting with a rigid footing under the plane-strain condition are examined using both experiments and simulations. Three commonly used types of cyclic loading conditions were applied on the footing. Digital particle image velocimetry (DPIV) is used to measure the local scale displacement fields in the soil, and to understand the ev</p> ... Show More
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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
STATISTICAL ANALYSIS OF PATIENTS INFECTED WITH CORONAVIRUS USING MANOVA
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Scopus