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Quantitative identification of phosphate using X-ray diffraction and Fourier transform infrared (FTIR) spectroscopy
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Inthisstudy,FourierTransformInfraredSpectrophotometry(FTIR),XRay Diffraction(XRD)andlossonignition(LOI),comparativelyemployedtoprovideaquick,relativelyinexpensiveandefficientmethodforidentifyingandquantifyingcalcitecontentofphosphateoresamplestakenfromAkashatsiteinIraq.Acomprehensivespectroscopicstudyofphosphate-calcitesystemwasreportedfirstintheMid-IRspectra(4004000cm-1)usingShimadzuIRAffinity-1,fordifferentcutsofphosphatefieldgradeswithsamplesbeneficiatedusingcalcinationandleachingwithorganicacidatdifferenttemperatures.Thenusingtheresultedspectratocreateacalibrationcurverelatesmaterialconcentrationstotheintensity(peaks)ofFTIRabsorbanceandappliesthiscalibrationtospecifyphosphate-calcitecontentinIraqicalcareousphosphateore.Theirpeakswereassignedtothefundamental vibration modes of PO4-3 in phosphate and CO3-2 in calcite. Thus FTIR appearstoprovideafastandreliablemethodforidentifyingcalciteconcentrationsin phosphate ore.

Publication Date
Sat Oct 01 2011
Journal Name
Journal Of Engineering
MODIFIED TRAINING METHOD FOR FEEDFORWARD NEURAL NETWORKS AND ITS APPLICATION in 4-LINK SCARA ROBOT IDENTIFICATION
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In this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func

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Publication Date
Mon Oct 17 2011
Journal Name
Journal Of Engineering
MODIFIED TRAINING METHOD FOR FEEDFORWARD NEURAL NETWORKS AND ITS APPLICATION in 4-LINK SCARA ROBOT IDENTIFICATION
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In this research the results of applying Artificial Neural Networks with modified activation function to perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of identification strategy consists of a feed-forward neural network with a modified activation function that operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have been trained online and offline have been used, without requiring any previous knowledge about the system to be identified. The activation function that is used in the hidden layer in FFNN is a modified version of the wavelet function. This approach ha

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Publication Date
Wed Feb 22 2023
Journal Name
Iraqi Journal Of Science
Isolation and Identification the Cyanobacterium: Scytonema hofmanni var. calcicolum as New Record in Iraqi Drinking Water.
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The aim of this study was to isolate and identify the cyanobacterium Scytonema hofmanni Var. calcicolum from the domestic drinking tanks as a new record in Iraqi drinking water. Scytonema hofmanni var. calcicolum, a filamentous freshwater cyanobacterium (blue-green alga). This alga was isolated from the walls of the domestic plastic water tanks in Al- karkh/ Baghdad city on July 2014. The sampling was performed by collecting three samples from this tanks, the three examined samples microscopically revealed the dominance of this cyanobacterium as unialgal in the studied samples. The results showed this alga has the ability to tolerate high temperature up to 42 Cº and very low light intensity inside the tanks which up to 10 μE/m²/s.

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Publication Date
Tue Dec 11 2018
Journal Name
Baghdad Science Journal
Isolation and identification of the Myxobacterium Myxococcus fulvus from the Farms and study the inhibitory effect of cells and filtrates against pathogenic fungi
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The study was performed to isolate and identify the Myxococcus fulvus from the one hundred samples of soils of farms. Special growth conditions had been used to support the growth of M.fulvus local isolates and suppressed the growth of other microorganisms like (Drying , High Temperature , High concentration of antibiotics and specific growth media ) M.fulvus isolates had been subjected to the morphological, cultural , biochemical examination for identification , as well as , study the inhibitory activites of cells and filtrates of localized isolates against some pathogenic fungi include (Trichophyton mentagrophytes , Microsporum gypseum , Aspergillus niger and Fusarium oxyporum ) by using three methods :- Cup assay , well diffusio

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Publication Date
Thu Aug 02 2018
Journal Name
European Journal Of Oral Sciences
Identification of key determinants in<i>Porphyromonas gingivalis</i>host-cell invasion assays
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Publication Date
Mon Apr 01 2019
Journal Name
Journal Of Engineering
Design of New Hybrid Neural Controller for Nonlinear CSTR System based on Identification
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This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

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Publication Date
Fri Jul 01 2022
Journal Name
Aip Conf. Proc. 2450, 020031 (2022)
The study of the identification and association of adiponectin and Interleukin-6 and some variables. Biochemical parameters in the Iraqi cord blood of newborns
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t. The current study was conducted on the umbilical cord blood of newborns in the Banks Hospital in Baghdad, Diyala, and Khalis in Diyala, where the study included 90 samples of blood, and samples were collected for the period from the 1st of October;2020 to The first of February;2021 AD, where the study included measuring levels of interleukin-6;Adiponectin,glucose and bilirubin in the blood, comparison study between the study variables with the child's weight (greater than 3 kg),(less or equal 3 kg),the mother's age (greater than 25 years, less or equal to 25 years),the sex of the child (male, female).The results of our study showed that there were no significant differences between the variables of the current study between the two sex

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Publication Date
Fri Jan 01 2016
Journal Name
Applied Numerical Mathematics
Multiple time-dependent coefficient identification thermal problems with a free boundary
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Publication Date
Sun Jan 01 2017
Journal Name
Iraqi Journal Of Medical Sciences
ISOLATION, IDENTIFICATION AND DETERMINATION OF ANTIFUNGAL SENSITIVITY OF FUNGI ISOLATED FROM A SAMPLE OF PATIENTS WITH RHINOSINUSITIS IN BAGHDAD CITY
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Publication Date
Sun May 01 2022
Journal Name
Songklanakarin J. Sci. Technol.
Molecular identification of three novel species of Ganoderma from different habitats in Mosul, Iraq
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Reishi Mushroom, Ganoderma, is considered one of important wood-decaying medicinal mushrooms. This study aimed to identify three samples of this genus in Mosul city in February and April 2019. Three species of Ganoderma were collected from three various trees including Eucalyptus, Morus, and Olea (olive) in Mosul City, Northern Iraq. Their identifications and their DNA sequences were genetically identified by using PCR techniques according to detect nuclear ribosomal internal transcribed spacer (ITS) regions. Results exhibited the finding of Ganoderma resinaceum, Ganoderma applanatum, and Ganoderma sp. This study is first attempt to identify Reishi Mushroom by molecular methods in Iraq. Thus, the current study is considered new good d

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