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Identification, Quantification, and Classification of Potential Safety Risk for Sustainable Construction in the United States
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Publication Date
Mon Oct 31 2022
Journal Name
Biodiversitas Journal Of Biological Diversity
Identification of new species record of Cyanophyceae in Diyala River, Iraq based on 16S rRNA sequence data
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Abstract. Hassan FM, Mahdi WM, Al-Haideri HH, Kamil DW. 2022. Identification of new species record of Cyanophyceae in Diyala River, Iraq based on 16S rRNA sequence data. Biodiversitas 23: 5239-5246. The biodiversity and water quality of the Diyala River require screening water in terms of biological contamination, because it is the only water source in Diyala City and is used for many purposes. This study aimed to identify a new species record of Cynaophyceae and emphasize the importance of using molecular methods beside classic morphological approaches, particularly in the water-shrinkage-aqua system. Five different sites along Diyala River were selected for Cyanophyceae identification. Morphological examination and 16S rRNA sequen

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Lactic Acid Bacteria (LAB) with Probiotic Potential from Dengke Naniura
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Dengke Naniura is a traditional food from Sumatera Utara, Indonesia, that is produced through fermenting process, and this food is believed to contain high probiotics. The objective of the current research is to determine the potential of LAB as a probiotic that has been obtained from Dengke Naniura. Dengke Naniura was traditionally prepared from Cyprinus carpio. Four LABs have been successfully isolated from Dengke Naniura, such as D7DA3, D7B3, D7DBF and D7DN3. Those four LAB isolates were identified as Lactobacillus sp. This result has been confirmed by the non-spore forming bacterium, non-motile, and Gram-positive. Also, it has been supported by biochemical test, for the example Voges Proskauer, catalase test, Methyl

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Publication Date
Mon May 20 2024
Journal Name
Iraqi Journal Of Applied Physics
Effect of Thermal Neutron Radiation Dose on Density of Local and Extended Energy States in Se<inf>55</inf>S<inf>20</inf>Sb<inf>15</inf>Sn<inf>10</inf> Alloy
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Four samples of the Se55S20Sb15Sn10 alloy were prepared using the melting point method. Samples B, C and D were irradiated with (6.04×1010, 12.08×1010 and 18.12×1010 (n.cm-2s -1 ) of thermal neutron beam from a neutron source (241Am-9Be) respectively, while sample A was left not irradiated. The electrical properties were assessed both before and after the radiation. All irradiated and non-irradiated samples show three conduction mechanisms, at low temperatures, electrical conductivity is achieved by electron hopping between local states near the Fermi level. At intermediate temperatures, conduction occurs by the jumping of electrons between local states at band tails. At high temperatures, electrons transfer between extended stat

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Publication Date
Thu Dec 01 2022
Journal Name
Microbiology And Biotechnology Letters
Production and Identification of Secondary Metabolite Gliotoxin-Like Substance Using Clinical Isolates of <i>Candida</i> spp.
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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Recognizing Different Foot Deformities Using FSR Sensors by Static Classification of Neural Networks
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Sensing insole systems are a promising technology for various applications in healthcare and sports. They can provide valuable information about the foot pressure distribution and gait patterns of different individuals. However, designing and implementing such systems poses several challenges, such as sensor selection, calibration, data processing, and interpretation. This paper proposes a sensing insole system that uses force-sensitive resistors (FSRs) to measure the pressure exerted by the foot on different regions of the insole. This system classifies four types of foot deformities: normal, flat, over-pronation, and excessive supination. The classification stage uses the differential values of pressure points as input for a feedforwar

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Oil spill classification based on satellite image using deep learning techniques
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 An oil spill is a leakage of pipelines, vessels, oil rigs, or tankers that leads to the release of petroleum products into the marine environment or on land that happened naturally or due to human action, which resulted in severe damages and financial loss. Satellite imagery is one of the powerful tools currently utilized for capturing and getting vital information from the Earth's surface. But the complexity and the vast amount of data make it challenging and time-consuming for humans to process. However, with the advancement of deep learning techniques, the processes are now computerized for finding vital information using real-time satellite images. This paper applied three deep-learning algorithms for satellite image classification

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Publication Date
Sat Oct 03 2009
Journal Name
Proceeding Of 3rd Scientific Conference Of The College Of Science
Research Address: New Multispectral Image Classification Methods Based on Scatterplot Technique
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Publication Date
Sun May 01 2016
Journal Name
2016 Al-sadeq International Conference On Multidisciplinary In It And Communication Science And Applications (aic-mitcsa)
Landsat-8 (OLI) classification method based on tasseled cap transformation features
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