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Theoretical Model for Spectroscopic Study of Cu+2, Co+2, and Fe+3 Dissolved in Ethanol with A Different Concentrations
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The absorption spectrum for three types of metal ions in different concentrations has been studying experimentally and theoretically. The examination model is by Gaius model in order to find the best fitting curve and the equation controlled with this behavior. The three metal ions are (Copper chloride Cu+2, Iron chloride Fe+3, and Cobalt chloride Co+2) with different concentrations (10-4, 10-5, 10-6, 10-7) gm/m3. The spectroscopic study included UV-visible and fluorescence spectrum for all different concentrations sample. The results refer to several peaks that appear from the absorption spectrum in the high concentration of all metal ions solution. The multiple absorption peaks continued even at the lowest concentration in the iron ion solution. Fluorescence spectrum shows intensive stimulating of the radiation strength was perceived in the manifestation of Cu+2, Co+2 and Fe+3. From modeling investigation, there are converge between experimental and theoretical results of the fluorescence spectrum for metal ions. Furthermore, identity and convergence which defined as (r2), are on average (0.995).

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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
Tue Jan 01 2019
Journal Name
Indian Journal Of Public Health Research & Development
Anticardiolipin Antibodies in Comparison to B-HCG Titer and Serum Progesterone as Indicator for Ectopic Pregnancies
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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Planner And Development
Mapping Paddy Rice Fields Using Landsat and Sentinel Radar Images in Urban Areas for Agriculture Planning
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     This research develops a new method based on spectral indices and random forest classifier to detect paddy rice areas and then assess their distributions regarding to urban areas. The classification will be conducted on Landsat OLI images and Landsat OLI/Sentinel 1 SAR data. Consequently, developing a new spectral index by analyzing the relative importance of Landsat bands will be calculated by the random forest. The new spectral index has improved depending on the most three important bands, then two additional indices including the normalized difference vegetation index (NDVI), and standardized difference built-up index (NDBI) have been used to extract paddy rice fields from the data. Several experiments being

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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
Mon Dec 05 2022
Journal Name
Baghdad Science Journal
Proposed Framework for Official Document Sharing and Verification in E-government Environment Based on Blockchain Technology
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Progression in Computer networks and emerging of new technologies in this field helps to find out new protocols and frameworks that provides new computer network-based services. E-government services, a modernized version of conventional government, are created through the steady evolution of technology in addition to the growing need of societies for numerous services. Government services are deeply related to citizens’ daily lives; therefore, it is important to evolve with technological developments—it is necessary to move from the traditional methods of managing government work to cutting-edge technical approaches that improve the effectiveness of government systems for providing services to citizens. Blockchain technology is amon

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Publication Date
Thu Sep 08 2022
Journal Name
Al-khwarizmi Engineering Journal
Performance Prediction in EDM Process for Al 6061 Alloy Using Response Surface Methodology and Genetic Algorithm
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The Electric Discharge (EDM) method is a novel thermoelectric manufacturing technique in which materials are removed by a controlled spark erosion process between two electrodes immersed in a dielectric medium. Because of the difficulties of EDM, determining the optimum cutting parameters to improve cutting performance is extremely tough. As a result, optimizing operating parameters is a critical processing step, particularly for non-traditional machining process like EDM. Adequate selection of processing parameters for the EDM process does not provide ideal conditions, due to the unpredictable processing time required for a given function. Models of Multiple Regression and Genetic Algorithm are considered as effective methods for determ

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Publication Date
Fri Sep 26 2025
Journal Name
Applied Data Science And Analysis
Deep Learning in Genomic Sequencing: Advanced Algorithms for HIV/AIDS Strain Prediction and Drug Resistance Analysis
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Genome sequencing has significantly improved the understanding of HIV and AIDS through accurate data on viral transmission, evolution and anti-therapeutic processes. Deep learning algorithms, like the Fined-Tuned Gradient Descent Fused Multi-Kernal Convolutional Neural Network (FGD-MCNN), can predict strain behaviour and evaluate complex patterns. Using genotypic-phenotypic data obtained from the Stanford University HIV Drug Resistance Database, the FGD-MCNN created three files covering various antiretroviral medications for HIV predictions and drug resistance. These files include PIs, NRTIs and NNRTIs. FGD-MCNNs classify genetic sequences as vulnerable or resistant to antiretroviral drugs by analyzing chromosomal information and id

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Publication Date
Mon Mar 15 2021
Journal Name
Journal Of Baghdad College Of Dentistry
Efficacy of arthrocentesis with injection of hyaluronic acid in the treatment of inflammatory-degenerative disease of temporomandibular joint
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Background:Temporomandibular joint (TMJ) problems refer to a group of heterogeneous pain and dysfunction conditions involving the mastication, reducing life quality of the patients. Arthrocentesis is a simple and less invasive surgical method for the treatment of inflammatory-degenerative disease than other conservative procedures and better than arthroscope. This clinical study aimed at evaluating the benefit of arthrocentesis with injection of hyaluronic acid in the management of inflammatory-degenerative disease of the TMJ. Material and methods: Eighty consecutive patients were enrolled in this study with pain symptoms of TMJ, insufficient masticatory efficiency during function and limitation of mouth opening; they were assessed with

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Publication Date
Wed Jun 19 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Accounting information system and its role in enhancing competitivness in the public industrial sector companies in iraq, from the standpoint of the auditors at the federal supeme audit board field study
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In a world of fierce competition companies of different activities strive to strengthen their competitiveness in order to be able to deliver greater value to their customers and gain a distinct sites in competition with other companies in the market at the local and international levels. Every company seeks to focus on one or more of the competitive capabilities in order to turn it into an obvious advantage or a number of competitive advantages to contribute in improving the performance and superiority over its competitors. Therefore, the management of companies no longer need only useful information for the internal aspects of the environment, but also need to include the external environment that includes various and constantly changin

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Publication Date
Tue Mar 28 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Evaluation of Rosuvastatin Effect as Adjuvant Therapy to Methotrexate on Lipid Profile and the Possibility of its Cardioprotective Effect in Iraqi Patients with Active Rheumatoid Arthritis
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Rheumatoid arthritis (RA) is a common inflammatory disease that associated with increased morbidity and mortality due to accelerated atherosclerosis. Rosuvastatin is a unique hydroxy methyl glutaryl Co A (HMGCoA) reductase inhibitor that has anti inflammatory effects.

The aim of this study was to evaluate the effect of rosuvastatin as adjuvant therapy to methotrexate (MTX) on lipid profile and its possible cardioprotective effect in RA patients. A double blinded placebo controlled clinical trial with 8 weeks follow up periods at which 40 patients with active RA using MTX were randomized into 2 groups to receive either rosuvastatin 10mg or placebo as adjuvant therapy to MTX. In addition to twenty healthy subjects as control group.

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