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jih-1677
The Finite Element Neural Network And Its Applications To Forward And Inverse Problems
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In this paper, first we   refom1Ulated   the finite   element  model

(FEM)   into   a   neural   network   structure   using   a   simple   two   - dimensional problem. The structure of this neural network is described

, followed  by its   application   to   solving  the forward    and  inverse problems. This model is then extended to the general case and the advantages and  di sadvantages  of  this  approach  are  descri bed  along with an analysis  of  the sensi tivity   of  the algorithm  to errors  in the measurements. Consider  a typical  boundary  value  problem  with  the

govern ing  differential  equation:  Lcp  = f, where  L  is a  differential

operator,  f is the forcing function and cp  is the unknown quant ity. This

di fferential  equation  can  be  solved  in  conjunction   wi th  boundary conditi ons  on  the  boundary  r enclosing  the domain.  A commonly

used  approach  to  solve  this   problem  is  to  use  the  finite  element approach.

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Publication Date
Sun Dec 01 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Exercise the leadership of the tax administration leaders to drive away the strategic orientation And its relation to organizational excellence: Practical research in the General Authority for Taxes
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The aim of the research is to assess the practice of tax administration to diminish the strategic direction of (proactive, analytical, defensive, response) and the nature of its relationship to organizational excellence represented by (leadership, strategic planning, focus on taxpayers, information and analysis and knowledge management, focus on operations, focus on forces. The questionnaire was adopted as a main tool in collecting data and information from the sample members of the General Authority for Taxes (110) who are in the site (m.  Second Division Manager, Ms The statistical program (SPSS) was used to calculate (mean, standard deviation, difference coefficient, correlation coefficient, t-test). The research reached a number

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Publication Date
Thu Jun 01 2023
Journal Name
Baghdad Science Journal
In vitro isolation and expansion of neural stem cells NSCs
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   Neural stem cells (NSCs) are progenitor cells which have the ability to self‑renewal and potential for differentiating into neurons, oligodendrocytes, and astrocytes. The in vitro isolation, culturing, identification, cryopreservation were investigated to produce neural stem cells in culture as successful sources for further studies before using it for clinical trials. In this study, mouse bone marrow was the source of neural stem cells. The results of morphological study and immunocytochemistry of isolated cells showed that NSCs can be produced successfully and maintaining their self‑renewal and successfully forming neurosphere for multiple passages. The spheres preserved their morphology in culture and cryopreserved t

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Modeling and Control of Fuel Cell Using Artificial Neural Networks
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This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback

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Publication Date
Sun Nov 26 2017
Journal Name
Journal Of Engineering
Compression Index and Compression Ratio Prediction by Artificial Neural Networks
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Information about soil consolidation is essential in geotechnical design. Because of the time and expense involved in performing consolidation tests, equations are required to estimate compression index from soil index properties. Although many empirical equations concerning soil properties have been proposed, such equations may not be appropriate for local situations. The aim of this study is to investigate the consolidation and physical properties of the cohesive soil. Artificial Neural Network (ANN) has been adapted in this investigation to predict the compression index and compression ratio using basic index properties. One hundred and ninety five consolidation results for soils tested at different construction sites

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Publication Date
Wed Sep 01 2021
Journal Name
Journal Of Physics: Conference Series
Theory and applications of Marshall Olkin Marshall Olkin Weibull distribution
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Abstract<p>In probability theory generalizing distribution is an important area. Several distributions are inappropriate for data modeling, either symmetrical, semi-symmetrical, or heavily skewed. In this paper, a new compound distribution with four parameters called Marshall Olkin Marshall Olkin Weibull (MOMOWe) is introduced. Several important statistical properties of new distribution were studied and examined. The estimation of unknown four parameters was carried out according to the maximum likelihood estimation method. The flexibility of MOMOWe distribution is demonstrated by the adoption of two real datasets (semi-symmetric and right-skewed) with different information fitting criteria. Su</p> ... Show More
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Publication Date
Wed Jan 01 2020
Journal Name
International Conference Of Numerical Analysis And Applied Mathematics Icnaam 2019
Isolation and characterization study towards microbial improved oil recovery applications
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Publication Date
Sat Jul 01 2017
Journal Name
Energy Procedia
Epoxy/Silicone Rubber Blends for Voltage Insulators and Capacitors Applications
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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Design and Implementation of a Telemetry System for Environmental Applications
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The Environmental Data Acquisition Telemetry System is a versatile, flexible and economical means to accumulate data from multiple sensors at remote locations over an extended period of time; the data is normally transferred to the final destination and saved for further analysis.

This paper introduces the design and implementation of a simplified, economical and practical telemetry system to collect and transfer the environmental parameters (humidity, temperature, pressure etc.) from a remote location (Rural Area) to the processing and displaying unit.

To get a flexible and practical system, three data transfer methods (three systems) were proposed (including the design and implementation) for rural area services, the fi

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
synthesis of novel n-Substituted phthalimidyl esters and thier applications
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Research has included preparation of three of n Vthal acids Amec Bmentoj high of interaction vehicles Ortometta and bar aminophenol with phthalic anhydride was withdrawn water and ring closure of acids Alvthal AMEC prepared

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Publication Date
Tue Aug 02 2022
Journal Name
Journal Of Population Therapeutics & Clinical Pharmacology
A systematic review of Antimicrobial peptides and their current applications
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In present days, drug resistance is a major emerging problem in the healthcare sector. Novel antibiotics are in considerable need because present effective treatments have repeatedly failed. Antimicrobial peptides are the biologically active secondary metabolites produced by a variety of microorganisms like bacteria, fungi, and algae, which possess surface activity reduction activity along with this they are having antimicrobial, antifungal, and antioxidant antibiofilm activity. Antimicrobial peptides include a wide variety of bioactive compounds such as Bacteriocins, glycolipids, lipopeptides, polysaccharide-protein complexes, phospholipids, fatty acids, and neutral lipids. Bioactive peptides derived from various natural sources like bacte

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