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FILTRATION MODELING USING ARTIFICIAL NEURAL NETWORK (ANN)
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In this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, with a
good degree of accuracy reaching 97.26, 95.92 and 86.43% respectively. These ANN models could be used as a support for workers in operating the filters in water treatment plants and to improve water treatment process. With the use of ANN, water systems will get more efficient, so reducing operation cost and improving the quality of the water produced.

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Publication Date
Sun Jul 06 2025
Journal Name
Jordan Medical Journal
Enhancing Adherence and Satisfaction with Disease-Modifying Therapies in Multiple Sclerosis Through Pharmacist-Led Interventions: Interventional Study
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Background: Pharmacists are essential in treating MS. Pharmacists' involvement and patient consultation may improve patient adherence and satisfaction. Aim: To evaluate the influence of pharmacist-led interventions (PLI) on medication adherence and satisfaction in patients with multiple sclerosis receiving disease-modifying therapies (DMTs). Methods: This study was conducted on patients with relapsing-remitting multiple sclerosis who were receiving DMTs and attended a neurological consultant clinic in the medical city of Baghdad. It was a pre-post-intervention study. Each patient underwent two educational sessions: the first session took place at the beginning of the study, after completing the Arabic version of the treatment satisfaction q

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Publication Date
Tue Sep 01 2020
Journal Name
Petroleum
Reversible and irreversible adsorption of bare and hybrid silica nanoparticles onto carbonate surface at reservoir condition
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Realistic implementation of nanofluids in subsurface projects including carbon geosequestration and enhanced oil recovery requires full understanding of nanoparticles (NPs) adsorption behaviour in the porous media. The physicochemical interactions between NPs and between the NP and the porous media grain surface control the adsorption behavior of NPs. This study investigates the reversible and irreversible adsorption of silica NPs onto oil-wet and water-wet carbonate surfaces at reservoir conditions. Each carbonate sample was treated with different concentrations of silica nanofluid to investigate NP adsorption in terms of nanoparticles initial size and hydrophobicity at different temperatures, and pressures. Aggregation behaviour and the

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Publication Date
Sun Dec 17 2017
Journal Name
Al-khwarizmi Engineering Journal
Formation of Compressive Residual Stress by Face Milling Steel AISI 1045
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Abstract

     Machining residual stresses correlate very closely with the cutting parameters and the tool geometries. This research work aims to investigate the effect of cutting speed, feed rate and depth of cut on the surface residual stress of steel AISI 1045 after face milling operation. After each milling test, the residual stress on the surface of the workpiece was measured by using X-ray diffraction technique. Design of Experiment (DOE) software was employed using the response surface methodology (RSM) technique with a central composite rotatable design to build a mathematical model to determine the relationship between the input variables and the response. The results showed that both

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Publication Date
Sat Aug 06 2022
Journal Name
Ijci. International Journal Of Computers And Information
Techniques for DDoS Attack in SDN: A Comparative Study
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Abstract Software-Defined Networking (commonly referred to as SDN) is a newer paradigm that develops the concept of a software-driven network by separating data and control planes. It can handle the traditional network problems. However, this excellent architecture is subjected to various security threats. One of these issues is the distributed denial of service (DDoS) attack, which is difficult to contain in this kind of software-based network. Several security solutions have been proposed recently to secure SDN against DDoS attacks. This paper aims to analyze and discuss machine learning-based systems for SDN security networks from DDoS attack. The results have indicated that the algorithms for machine learning can be used to detect DDoS

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Publication Date
Tue Oct 30 2018
Journal Name
Journal Of Engineering
Accuracy Assessment of Stonex X-300 Laser Scanner Cameras
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Assessment the actual accuracy of laboratory devices prior to first use is very important to know the capabilities of such devices and employ them in multiple domains. As the manual of the device provides information and values in laboratory conditions for the accuracy of these devices, thus the actual evaluation process is necessary.

In this paper, the accuracy of laser scanner (stonex X-300) cameras were evaluated, so that those cameras attached to the device and lead supporting role in it. This is particularly because the device manual did not contain sufficient information about those cameras.

To know the accuracy when using these cameras in close range photogrammetry, laser scanning (stonex X-300) de

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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Iraqi stock market structure analysis based on minimum spanning tree
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tock markets changed up and down during time. Some companies’ affect others due to dependency on each other . In this work, the network model of the stock market is discribed as a complete weighted graph. This paper aims to investigate the Iraqi stock markets using graph theory tools. The vertices of this graph correspond to the Iraqi markets companies, and the weights of the edges are set ulrametric distance of minimum spanning tree.

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Publication Date
Fri Nov 01 2024
Journal Name
Egyptian Journal Of Aquatic Biology And Fisheries
Heavy Metals Levels in the Al-Shamiyah River: A Lotic Ecosystem Case Study
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Monitoring lotic ecosystems is vital for addressing sustainability issues. The Al-Shamiyah River is the primary source of water for various daily activities in the Al-Shamiyah district. This study assessed the pollution levels of the river by measuring the concentration and distribution of heavy metals—specifically chromium, cadmium, manganese, copper, zinc, and lead—in both the river's water and sediments. The concentrations of heavy metals in the water ranged from 0.05 to 1.44µg/ L for copper (Cu), 1.57 to 7.25µg/ L for manganese (Mn), 0 to 1.7µg/ L for cadmium (Cd), 0.02 to 1.33µg/ L for lead (Pb), 0.08 to 2.74µg/ L for zinc (Zn), and 0.44 to 1.84µg/ L for chromium (Cr). In the particulate phase, the concentrations ranged from

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Engineering
Mathematical Model for BOD in Waste Water Discharges from Al Dora Refinery in Baghdad
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This research consists of two parts, the first part concern with analyzing the collected data of BOD and COD values in discharge waste water from Al-Dora refinery during 2010 to find the relationship between these two variables The results indicates that there is a high correlation between BOD and COD when using a natural logarithm model (0.86 ln(COD)) with correlation coefficient of 0.98. This relationship is useful in predicting the BOD value using the COD value. The second part includes analyzing collected data from the same site in order to find a relationsip between BOD and other parameters COD, Phenol(phe), Temperature(T), Oil, Sulphat(SO4),pH and Total dissolved solids( TDS) discharged from the refinery. The results indicated that th

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Engineering
The Effects of Different Water Types on the Dissolution, Physical Appearance, and Compressive Strength of Gypsum Rock
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Dissolution of gypsum rock in water is significant, which may result in hydrocarbon reservoir formation and evaporate deposits. However, the complexity of the gypsum dissolution process is still of interest because of its uncleanness that requires more critical analysis. The objectives of this experimental study are emphasis on the dissolution characteristics of gypsum rock under room temperature and by various types of water; namely: deionized, tap, fresh, acidic, well, and normal rainwatre. In addition, the influences of dissolution on gypsum rock's mechanical and physical characteristics. Gypsum rock was obtained from Agjalar area, in the southwest of Sulaymaniyah city, Northern Iraq. Experimental results show that we

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Publication Date
Tue Jan 08 2019
Journal Name
Lubricants
Influence of Sample Mixing Techniques on Engine Oil Contamination Analysis by Infrared Spectroscopy
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For the most reliable and reproducible results for calibration or general testing purposes of two immiscible liquids, such as water in engine oil, good emulsification is vital. This study explores the impact of emulsion quality on the Fourier transform infrared (FT-IR) spectroscopy calibration standards for measuring water contamination in used or in-service engine oil, in an attempt to strengthen the specific guidelines of ASTM International standards for sample preparation. By using different emulsification techniques and readily available laboratory equipment, this work is an attempt to establish the ideal sample preparation technique for reliability, repeatability, and reproducibility for FT-IR analysis while still considering t

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