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INFLUENCE OF A RIVER WATER QUALITY ON THE EFFICIENCY OF WATER TREATMENT USING ARTIFICIAL NEURAL NETWORK
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Publication Date
Sat Jan 01 2022
Journal Name
Geotechnical Engineering And Sustainable Construction
Determine the Most Common Geotechnical Risks and Their Impacts on the Cost and Time Schedule for Implementing Water Treatment Plants in Iraq
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Publication Date
Thu Nov 03 2022
Journal Name
Sensors
A Novel Application of Deep Learning (Convolutional Neural Network) for Traumatic Spinal Cord Injury Classification Using Automatically Learned Features of EMG Signal
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In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification system and a classical classification method (k-nearest neighbors, kNN) is also presented. Developing such an NHP model with a suitable assessment tool (i.e., classifier) is a crucial step in detecting the effect of TSCI using EMG, which is expected to be essential in the evaluation of the efficacy of new TSCI treatments. Intramuscular EMG data were collected from an agonist/antagonist tail muscle pair for the pre- and post-spinal cord lesi

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Publication Date
Sun Jan 14 2018
Journal Name
Journal Of Engineering
The effect of Laser Shock Peening on Fatigue Life Using Pure Water and Hydrofluoric Acid As a Confining Layer of Al – Alloy 7075-T6
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Laser shock peening (LSP) is deemed as a deep-rooted technology for stimulating compressive residual stresses below the surface of metallic elements. As a result, fatigue lifespan is improved, and the substance properties become further resistant to wear and corrosion. The LSP provides more unfailing surface treatment and a potential decrease in microstructural damage. Laser shock peening is a well-organized method measured up to the mechanical shoot peening. This kind of surface handling can be fulfilled via an intense laser pulse focused on a substantial surface in extremely shorter intervals. In this work, Hydrofluoric Acid (HF) and pure water as a coating layer were utilized as a new technique to improve the properti

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Publication Date
Mon Aug 01 2011
Journal Name
Journal Of Engineering
Preservation of Required Chlorine Concentration in Baghdad Water Supply Networks using On-Site Chlorine Injection
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The chlorine concentration variation in Baghdad water networks was studied. The
chlorine data were collected from Mayoralty of Baghdad and Ministry of Environment
(MOE) for the networks for both sides of the city Karkh and Rasafa for (2008-2009). The
study of these data indicates that there are no systematic testing program .Classified GIS
maps showed that the areas far from the treatment plants have almost always low
chlorine concentration .This indicates that the problem of the low chlorine concentration
in the far areas is due to cracks of pipe along the conveyance path ,as expected. The area's
most frequently have low concentration are Al-sadir,Al-Kadhimya, and Al-Amiria . It
was found also that the chlorine c

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Publication Date
Sun Dec 09 2018
Journal Name
Baghdad Science Journal
Anticorrosion Behavior of Deposited Magnetite on Galvanized Steel in Saline Water Using RF-Magnetron Sputtering
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Thin films of Magnetite have been deposited on Galvanized Steel (G-S) alloy using RF-reactive magnetron sputtering technique and protection efficiency of the corrosion of G-S. A Three-Electrodes Cell was used in saline water (3.5 % NaCl) solution at different temperatures (298, 308, 318 & 328K) using potentiostatic techniques with. Electrochemical Impedance Spectroscopy (EIS) and fitting impedance data via Frequency Response Analysis (FRA) were applied to G-S alloy with Fe3O4 and tested in 3.5 % NaCl solution at 298K.Results taken from Nyquist and Bode plots were analyzed using software provided with the instrument. The results obtained show that the rate of corrosion of G.S alloy increased with increasing the temperatures from 298 t

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Publication Date
Sun Jun 30 2013
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Extraction of Oil from Eucalyptus Camadulensis Using Water Distillation Method
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This work was conducted to study the extraction of eucalyptus oil from natural plants (Eucalyptus camaldulensis leaves) using water distillation method by Clevenger apparatus. The effects of main operating parameters were studied: time to reach equilibrium, temperature (70 to100°C), solvent to solid ratio (4:1 to 8:1 (v/w)), agitation speed (0 to 900 rpm), and particle size (0.5 to 2.5 cm) of the fresh leaves, to find the best processing conditions for achieving maximum oil yield. The results showed that the agitation speed of 900 rpm, temperature 100° C, with solvent to solid ratio 5:1 (v/w) of particle size 0.5 cm for 160 minute give the highest percentage of oil (46.25 wt.%). The extracted oil was examined by HPLC.

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Publication Date
Tue Jan 01 2019
Journal Name
Plant Archives
The seasonal effect on the water bodies in Iraqi marshlands
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Publication Date
Sat Apr 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering
Intrusion detection method for internet of things based on the spiking neural network and decision tree method
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The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices

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Publication Date
Sat Apr 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Intrusion detection method for internet of things based on the spiking neural network and decision tree method
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The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices

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Scopus (25)
Crossref (12)
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Publication Date
Sat Dec 01 2018
Journal Name
Al-khwarizmi Engineering Journal
Numerical Simulation of Unsaturated Soil Water Flow from a Trickle Point System, Considering Evaporation and Root Water Uptake
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This research was carried out to study the effect of plants on the wetted area for two soil types in Iraq and predict an equation to determine the wetted radius and depth for two different soil types cultivated with different types of plants, the wetting patterns for the soils were predicted at every thirty minute for a total irrigation time equal to 3 hr. Five defferent discharges of emitter and five initial volumetric soil moisture contents were used ranged between field capacity and wilting point were utilized to simulate the wetting patterns. The simulation of the water flow from a single point emitter was completed by utilized HYDRUS-2D/3D software, version 2.05. Two methods were used in developing equations to predict the domains o

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