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Experimental and numerical investigation on the behavior of reinforced reactive powder concrete two-way slabs under static load
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This paper studied the behaviour of reinforced reactive powder concrete (RPC) two-way slabs under static load. The experimental program included testing three simply supported slabs of 1000 mm length, 1000 mm width, and 70 mm thickness. Tested specimens were of identical properties except their steel fibers volume ratio (0.5 %, 1 %, and 1.5 %). Static test results revealed that, increasing steel fibers volume ratio from 0.5% to 1% and from 1% to 1.5%, led to an increase in: first crack load by (32.2 % and 52.3 %), ultimate load by (36.1 % and 17.0 %), ultimate deflection by (33.6 % and 3.4 %), absorbed energy by (128 % and 20.2 %), and the ultimate strain by (1.1 % and 6.73 %). The stiffness and ductility of the specimens also increased. A numerical analysis was performed using ANSYS 14.5 software. The FE analysis overestimated the ultimate load capacity of all specimens by (6–28) %, and underestimated the ultimate deflection by (22-44) %. The deflected shape and crack patterns of the FE models were similar to that of the corresponding experimental specimens. It was found out that the optimum values of steel fibers volume fraction are 1.5 % and 1.6%.

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Publication Date
Sun Sep 01 2019
Journal Name
Baghdad Science Journal
The Effect of MHD on a Longitudinal Flow of a Fractional Maxwell Fluid between Two Coaxial Cylinders
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      In this paper fractional Maxwell fluid equation has been solved. The solution is in the Mettag-Leffler form. For  the corresponding solutions for ordinary Maxwell fluid are obtained as limiting case of general solutions. Finally, the effects of different parameters on the velocity and shear stress profile are analyzed through plotting the velocity and shear stress profile.

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Publication Date
Fri Feb 05 2010
Journal Name
Etri Journal
MC-MIPOG: A Parallel t-Way Test Generation Strategy for Multicore Systems
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Publication Date
Tue Mar 21 2023
Journal Name
International Journal Of Interactive Mobile Technologies (ijim)
Study the Effect of Using Google Classroom on the Academic Performance Under the Covid19 Pandemic Using Data Mining Technique
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— In light of the pandemic that has swept the world, the use of e-learning in educational institutions has become an urgent necessity for continued knowledge communication with students. Educational institutions can benefit from the free tools that Google provide and from these applications, Google classroom which is characterized by ease of use, but the efficiency of using Google classroom is affected by several variables not studied in previous studies Clearly, this study aimed to identify the use of Google classroom as a system for managing e-learning and the factors affecting the performance of students and lecturer. The data of this study were collected from 219 members of the faculty and students at the College of Administra

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Publication Date
Thu Nov 15 2018
Journal Name
Pakistan Journal Of Biological Sciences
Immunomodulation of Zerumbone via Decreasing the Production of Reactive Oxygen Species from Immune Cells
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Publication Date
Tue May 01 2018
Journal Name
Journal Of Engineering
Prediction of the Effect of Using Stone Column in Clayey Soil on the Behavior of Circular Footing by ANN Model
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Shallow foundations are usually used for structures with light to moderate loads where the soil underneath can carry them. In some cases, soil strength and/or other properties are not adequate and require improvement using one of the ground improvement techniques. Stone column is one of the common improvement techniques in which a column of stone is installed vertically in clayey soils. Stone columns are usually used to increase soil strength and to accelerate soil consolidation by acting as vertical drains. Many researches have been done to estimate the behavior of the improved soil. However, none of them considered the effect of stone column geometry on the behavior of the circular footing. In this research, finite ele

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Publication Date
Sun Jun 21 2020
Journal Name
Baghdad Science Journal
Structural and Thermal Unusual Properties in Invar Behavior of Ni-Mn Alloys
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The Invar effect in 3D transition metal such as Ni and Mn, were prepared on a series composition of binary Ni1-xMnx system with x=0.3, 0.5, 0.8 by using powder metallurgy technique. In this work, the characterization of structural and thermal properties have been investigated experimentally by X-ray diffraction, thermal expansion coefficient and vibrating sample magnetometer (VSM) techniques. The results show that anonymously negative thermal expansion coefficient are changeable in the structure. The results were explained due to the instability relation between magnetic spins with lattice distortion on some of ferromagnetic metals.    

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
Toxicity of Nanomulsion of Castor Oil on the Fourth larval stage of Culex quinquefsciatus under Laboratory Conditions
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Mosquitoes like Culex quinquefasciatus are the primary vector that transmits many causes of diseases such as filariasis, Japanese encephalitis, and West Nile virus, in many countries around the world. The development in the scientific fields, such as nanotechnology, leads to use this technique in control programs of insects including mosquitoes through the use of green synthesis of nanoemulsions based on plant products such as castor oil.  Castor oil nanoemulsion was formulated in various ratios comprising of castor oil, ethanol, tween 80, and deionized water by ultrasonication. Thermodynamic assay improved that the formula of (10 ml) of castor oil, ethanol (5ml), tween 80 (14 ml) and deionized water (71ml)   was mor

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Engineering
A Prediction Formula for The Estimation of Sediment Load in The Upper Reach of Al-Gharraf River
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The presence of deposition in the river decreases the river flow capability's efficiency due to the absence of maintenance along the river. In This research, a new formula to evaluate the sediment capacity in the upstream part of Al-Gharraf River will be developed. The current study reach lies in Wasit province with a distance equal to 58 km. The selected reach of the river was divided into thirteen stations. At each station, the suspended load and the bedload were collected from the river during a sampling period extended from February 2019 till July 2019. The samples were examined in the laboratory with a different set of sample tests. The formula was developed using data of ten stations, and the other three s

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Publication Date
Thu Dec 31 2015
Journal Name
Al-khwarizmi Engineering Journal
Experimental Study on the Effect of Insertion of Copper Lessing Rings in Phase Change Material (PCM) on the Performance of Thermal Energy Storage Unit
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Abstract

One of the most suitable materials to be used in latent heat thermal energy storage system (LHTES) are Phase change materials, but a problem of slow melting and solidification processes made many researchers focusing on how to improve their thermal properties. This experimental work concerned with the enhancing of thermal conductivity of phase change material. The enhancing method was by the addition of copper Lessing rings in phase change material (paraffin wax). The effect of diameter for the used rings was studied by using two different diameters (0.5 cm and 1cm). Also, three volumetric percentages of rings addition (3%, 6% and 10%) were tested for each diameter. The discharging process was done with

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Publication Date
Fri Mar 29 2024
Journal Name
Iraqi Journal Of Science
Evaluating the Performance and Behavior of CNN, LSTM, and GRU for Classification and Prediction Tasks
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     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

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Scopus (9)
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