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Seismic Effects and Static Analysis for the Artificial Damped Outrigger Systems in Tall R.C Buildings
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This paper studies the combination fluid viscous dampers in the outrigger system to add supplementary damping into the structure, which purpose to remove the dependability of the structure to lower variable intrinsic damping. It works by connecting the central core, comprising either shear walls or braced frames, to the outer perimeter columns.

     The modal considered is a 36 storey square high rise reinforced concrete building. By constructing a discrete lumped mass model, and using frequency-based response function, two systems of dampers, parallel and series systems are studied. The maximum lateral load at the top of the building is calculated, and  this load  will be applied at every floor of the building, giving a conservative solution. For static study Equivalent Lateral Force (ELF) was conducted. MATLAB software, has been used in this study.

     From analysis data, it is observed that the parallel system of dampers result lower amplitude of vibration and achieved more efficiently compared to the series system, and the horizontal displacement for each configurations by using MATLAB software is less than the analytical solution using a uniformly distributed load of 36 nodal point forces that divided the total height.

 

 

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Publication Date
Sun Feb 28 2021
Journal Name
Journal Of Economics And Administrative Sciences
Effects of Macroeconomic Variables on Gross Domestic Product in Saudi Arabia using ARDL model for the period 1993-2019
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This paper analyses the relationship between selected macroeconomic variables and gross domestic product (GDP) in Saudi Arabia for the period 1993-2019. Specifically, it measures the effects of interest rate, oil price, inflation rate, budget deficit and money supply on the GDP of Saudi Arabia. The method employs in this paper is based on a descriptive analysis approach and ARDL model through the Bounds testing approach to cointegration. The results of the research reveal that the budget deficit, oil price and money supply have positive significant effects on GDP, while other variables have no effects on GDP and turned out to be insignificant. The findings suggest that both fiscal and monetary policies should be fo

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Publication Date
Sun Sep 04 2011
Journal Name
Baghdad Science Journal
Spectroscopic Study for Resonance Effects on the Carbonyl Double Bond Order in Urea Schiff Bases Which Contain Conjugated System
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In this work we prepared some schiff bases by condensation urea and benzaldehyde or its derevative ( bromo benzaldehyde or hydroxy benzaldehyde ) as ( 1 : 1 ) mole ( urea : benzaldehyde or its substitution ) to prepare compounds ( A1 , B1 , C1 , D1 , E1 , F1 , G1 ) and ( 1 : 2 ) mole ( urea : benzaldehyde or its substitution ) to prepare compounds ( A2 , B2 , C2 , D2 , E1 , F2 , G2 ) . The prepared compounds identified spectroscopic by infrared spectroscopy FT-IR and Thin layer chromotography T.L.C . The force constant calculated from the wave number for the carbonyl stretching from FT-IR chart and by using the following equation K = 4?2C2?'2? The change in double bond order for carbonyl deteremined in according with some past re

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Publication Date
Fri Apr 12 2019
Journal Name
Journal Of Economics And Administrative Sciences
Measurement and Analysis of Oil Price Fluctuations and Trends of Government Spending on the Security and Health Sectors in Iraq for the Period (2006-2016)
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The objective of the study: To diagnose the reality of the relationship between the fluctuations in world oil prices and their reflection on the trends of government spending on the various economic sectors.

The research found: that public expenditures contribute to the increase of national consumption through the purchase of consumer goods by the state for the performance of the state's duties or the payment of wages to employees in the public sector and thus have a direct impact on national consumption

The results of the standard tests showed that there is no common integration between the oil price fluctuations and the government expenditure on the security sector through the A

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Publication Date
Wed Jan 01 2025
Journal Name
International Journal Of Hydrogen Energy
A comprehensive review of battery thermal management systems for electric vehicles: Enhancing performance, sustainability, and future trends
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Publication Date
Fri Sep 15 2017
Journal Name
Journal Of Baghdad College Of Dentistry
The Effect of Artificial Saliva on The Surface Roughness of Different Esthetic Archwires (An in Vitro Study)
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Background:The demand for esthetic orthodontic appliances is increasing so that the esthetic orthodontic archwires were introduced. This in vitro study was designed to evaluate the surface roughness offiber-reinforced polymer composite (FRPC) archwires compared to coated nickel-titanium (NiTi) archwires immersed in artificial saliva. Materials and Methods:Three types of esthetic orthodontic archwires were used: FRPC (Dentaurum), Teflon coated NiTi (Dentaurum) and epoxy coated NiTi (Orthotechnology). They were round (0.018 inch) in cross section and cut into pieces of 15 mm in length.Forty pieces from each type were divided into four groups; one group was left at a dry condition and the other three groups were immersed in artificial saliva (

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Publication Date
Tue Sep 19 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Density and Approximation by Using Feed Forward Artificial Neural Networks
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I n  this  paper ,we 'viii  consider  the density  questions  associC;lted with  the single  hidden layer feed forward  model. We proved  that a FFNN   with   one   hidden   layer  can   uniformly   approximate   any continuous  function  in C(k)(where k is a compact set in R11 ) to any required accuracy.

 

However, if the set of basis function is dense then the ANN's can has al most one hidden layer. But if the set of basis function  non-dense, then we  need more  hidden layers. Also, we have shown  that there exist  localized functions and that there is no t

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Publication Date
Fri Aug 01 2008
Journal Name
2008 International Symposium On Information Technology
Generating pairwise combinatorial test set using artificial parameters and values
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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
Sun Jan 01 2023
Journal Name
Lecture Notes In Networks And Systems
Using Artificial Intelligence and Metaverse Techniques to Reduce Earning Management
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This study aims to demonstrate the role of artificial intelligence and metaverse techniques, mainly logistical Regression, in reducing earnings management in Iraqi private banks. Synthetic intelligence approaches have shown the capability to detect irregularities in financial statements and mitigate the practice of earnings management. In contrast, many privately owned banks in Iraq historically relied on manual processes involving pen and paper for recording and posting financial information in their accounting records. However, the banking sector in Iraq has undergone technological advancements, leading to the Automation of most banking operations. Conventional audit techniques have become outdated due to factors such as the accuracy of d

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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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