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A comprehensive review on modelling the adsorption process for heavy metal removal from waste water using artificial neural network technique
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Publication Date
Thu Jun 23 2022
Journal Name
American Scientific Research Journal For Engineering, Technology, And Sciences
A Review of TCP Congestion Control Using Artificial Intelligence in 4G and 5G Networks
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In recent years, the field of research around the congestion problem of 4G and 5G networks has grown, especially those based on artificial intelligence (AI). Although 4G with LTE is seen as a mature technology, there is a continuous improvement in the infrastructure that led to the emergence of 5G networks. As a result of the large services provided in industries, Internet of Things (IoT) applications and smart cities, which have a large amount of exchanged data, a large number of connected devices per area, and high data rates, have brought their own problems and challenges, especially the problem of congestion. In this context, artificial intelligence (AI) models can be considered as one of the main techniques that can be used to solve ne

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Publication Date
Mon Jun 05 2023
Journal Name
Al-khwarizmi Engineering Journal
A Review of the Stereo lithography 3D Printing Process and the Effect of Parameters on Quality
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Stereo lithography (SLA) three-dimensional (3D) printing process is a type of additive manufacturing techniques that uses digital models from computer-aided design to automatically produce customized 3D objects. Around 30 years, it has been widely utilized in the manufacturing, design, engineering, industrial sectors and its applications in dentistry for manufacturing prosthodontics are very important. The stereo lithography technology is highly regarded because it can produce items with excellent precision especially when selecting the best process parameters. This review article offers a useful and scientific summary of SLA three-dimensional printing technology and its brief history. The specific type of 3D printers which is SLA type b

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Publication Date
Mon Jun 05 2023
Journal Name
Al-khwarizmi Engineering Journal
A Review of the Stereo lithography 3D Printing Process and the Effect of Parameters on Quality
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Stereo lithography (SLA) three-dimensional (3D) printing process is a type of additive manufacturing techniques that uses digital models from computer-aided design to automatically produce customized 3D objects. Around 30 years, it has been widely utilized in the manufacturing, design, engineering, industrial sectors and its applications in dentistry for manufacturing prosthodontics are very important. The stereo lithography technology is highly regarded because it can produce items with excellent precision especially when selecting the best process parameters. This review article offers a useful and scientific summary of SLA three-dimensional printing technology and its brief history. The specific type of 3D printers which is SLA t

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Publication Date
Sat Feb 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Using GIS Technique for evaluating water quality of Abu Zarag marsh during the flood season
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Abstract<p>This research deals with the most important heritage in Iraq, which are the Iraqi marshes, especially Abu Zarag marsh in Al-Nasiriyah city south of Iraq. The research is divided into two parts. The first part deals with evaluating the water quality parameters of Abu Zarag marsh for the period from December 2018 to April 2019 which is the flooding season. The parameters are Temperature, pH, Electrical Conductivity, Total Dissolved Solids, Alkalinity, Total Hardness, Turbidity, Dissolved Oxygen, Sulfate, Nitrate. The second part is a comparison between the water quality parameters during the recent period with the same period during the previous years from 2014 to 2019. The results are </p> ... Show More
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Publication Date
Mon Oct 27 2014
Journal Name
Desalination And Water Treatment
Simultaneous adsorption–precipitation characterization as mechanisms for metals removal from aqueous solutions by cement kiln dust (CKD)
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Publication Date
Wed Nov 30 2022
Journal Name
Desalination And Water Treatment
Removal of amoxicillin from wastewater by adsorption onto activated carbon prepared from sunflower seed hulls
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In this study, the potential of adsorption of amoxicillin antibiotic (AMOX) from aqueous solutions using prepared activated carbon (AC) was studied. The used AC was prepared from an inexpensive and available precursor (sunflower seed hulls (SSH)) and activated by potassium hydroxide (KOH). The prepared AC was examined for its ability to remove AMOX from aqueous contaminated solutions and characterized with the aid of N2 -adsorption/desorption isotherm Brunauer–Emmett– Teller, scanning electron microscopy, energy-dispersive X-ray spectroscopy and Fourier-transform infrared. Zeta potential of the prepared activated carbon from sunflower seed hulls (SSHAC) were studied in relation to AMOX adsorption. The physical and chemical propert

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Publication Date
Wed Dec 12 2018
Journal Name
Iop Conference Series: Materials Science And Engineering
The performance of MnO<sub>2</sub>/graphite electrode for TOC removal from wastewater by indirect electrochemical oxidation process
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Electrochemical oxidation in the presence of sodium chloride used for removal of phenol and any other organic by products formed during the electrolysis by using MnO2/graphite electrode. The performance of the electrode was evaluated in terms fraction of phenol and the formed organic by products removed during the electrolysis process. The results showed that the electrochemical oxidation process was very effective in the removal of phenol and the other organics, where the removal percentage of phenol was 97.33%, and the final value of TOC was 6.985 ppm after 4 hours and by using a speed of rotation of the MnO2 electrode equal to 200 rpm.

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Publication Date
Fri Apr 01 2022
Journal Name
Journal Of Engineering
Prediction of Shear Strength Parameters of Gypseous Soil using Artificial Neural Networks
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The shear strength of soil is one of the most important soil properties that should be identified before any foundation design. The presence of gypseous soil exacerbates foundation problems. In this research, an approach to forecasting shear strength parameters of gypseous soils based on basic soil properties was created using Artificial Neural Networks. Two models were built to forecast the cohesion and the angle of internal friction. Nine basic soil properties were used as inputs to both models for they were considered to have the most significant impact on soil shear strength, namely: depth, gypsum content, passing sieve no.200, liquid limit, plastic limit, plasticity index, water content, dry unit weight, and initial

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Publication Date
Sun Jul 31 2022
Journal Name
Iraqi Geological Journal
A Review of Historical Studies for Water Saturation Determination Techniques
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Water saturation is the most significant characteristic for reservoir characterization in order to assess oil reserves; this paper reviewed the concepts and applications of both classic and new approaches to determine water saturation. so, this work guides the reader to realize and distinguish between various strategies to obtain an appropriate water saturation value from electrical logging in both resistivity and dielectric has been studied, and the most well-known models in clean and shaly formation have been demonstrated. The Nuclear Magnetic Resonance in conventional and nonconventional reservoirs has been reviewed and understood as the major feature of this approach to estimate Water Saturation based on T2 distribution. Artific

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Publication Date
Mon Jul 18 2022
Journal Name
Ieee Access
Moderately Multispike Return Neural Network for SDN Accurate Traffic Awareness in Effective 5G Network Slicing
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Due to the huge variety of 5G services, Network slicing is promising mechanism for dividing the physical network resources in to multiple logical network slices according to the requirements of each user. Highly accurate and fast traffic classification algorithm is required to ensure better Quality of Service (QoS) and effective network slicing. Fine-grained resource allocation can be realized by Software Defined Networking (SDN) with centralized controlling of network resources. However, the relevant research activities have concentrated on the deep learning systems which consume enormous computation and storage requirements of SDN controller that results in limitations of speed and accuracy of traffic classification mechanism. To fill thi

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