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Evolutionary Feature Optimization for Plant Leaf Disease Detection by Deep Neural Networks
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Publication Date
Sun Aug 01 2021
Journal Name
Telkomnika
Proposed different relay selection schemes for improving the performance of cooperative wireless networks
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Publication Date
Thu Jun 20 2024
Journal Name
Ingénierie Des Systèmes D Information
Enabling Technologies for Ultra-Low Latency and High-Reliability Communication in 6G Networks
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Publication Date
Fri Jan 01 2021
Journal Name
Journal Of Intelligent Systems
Void-hole aware and reliable data forwarding strategy for underwater wireless sensor networks
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Abstract<p>Reliable data transfer and energy efficiency are the essential considerations for network performance in resource-constrained underwater environments. One of the efficient approaches for data routing in underwater wireless sensor networks (UWSNs) is clustering, in which the data packets are transferred from sensor nodes to the cluster head (CH). Data packets are then forwarded to a sink node in a single or multiple hops manners, which can possibly increase energy depletion of the CH as compared to other nodes. While several mechanisms have been proposed for cluster formation and CH selection to ensure efficient delivery of data packets, less attention has been given to massive data co</p> ... Show More
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Publication Date
Mon Jan 01 2024
Journal Name
Computer Modeling In Engineering &amp; Sciences
A Review and Bibliometric Analysis of the Current Studies for the 6G Networks
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Publication Date
Tue Jan 01 2019
Journal Name
Wireless Communications And Mobile Computing
Corrigendum to “Developing a Video Buffer Framework for Video Streaming in Cellular Networks”
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Publication Date
Fri Jan 01 2016
Journal Name
Ieee Access
Towards an Applicability of Current Network Forensics for Cloud Networks: A SWOT Analysis
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In recent years, the migration of the computational workload to computational clouds has attracted intruders to target and exploit cloud networks internally and externally. The investigation of such hazardous network attacks in the cloud network requires comprehensive network forensics methods (NFM) to identify the source of the attack. However, cloud computing lacks NFM to identify the network attacks that affect various cloud resources by disseminating through cloud networks. In this paper, the study is motivated by the need to find the applicability of current (C-NFMs) for cloud networks of the cloud computing. The applicability is evaluated based on strengths, weaknesses, opportunities, and threats (SWOT) to outlook the cloud network. T

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Publication Date
Tue Apr 30 2024
Journal Name
Iraqi Geological Journal
Wellbore Instability Analysis to Determine the Safe Mud Weight Window for Deep Well, Halfaya Oilfield
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Wellbore instability is one of the most common issues encountered during drilling operations. This problem becomes enormous when drilling deep wells that are passing through many different formations. The purpose of this study is to evaluate wellbore failure criteria by constructing a one-dimensional mechanical earth model (1D-MEM) that will help to predict a safe mud-weight window for deep wells. An integrated log measurement has been used to compute MEM components for nine formations along the studied well. Repeated formation pressure and laboratory core testing are used to validate the calculated results. The prediction of mud weight along the nine studied formations shows that for Ahmadi, Nahr Umr, Shuaiba, and Zubair formations

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Publication Date
Wed May 10 2023
Journal Name
Biomass Conversion And Biorefinery
Lactic acid-based deep eutectic solvents and activated carbon for soap removal from crude biodiesel
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Publication Date
Wed Dec 01 2021
Journal Name
Computers &amp; Electrical Engineering
Utilizing different types of deep learning models for classification of series arc in photovoltaics systems
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Publication Date
Thu Jul 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Synthesis of Manganese Dioxide Nanoparticles by Plant Extract Mediated and their Effect on Biofilm Formation
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In the current work, Punica granatum L. peel, Artemisia herba-alba Asso., Matricaria chamomilla L., and Camellia sinensis extracts were used to prepare manganese dioxide (MnO2) nanoparticles utilizing a green method. Energy-dispersive X-ray (EDX) analysis, Fourier Transform Infrared Spectroscopy (FTIR) analysis, and Filed emission-scanning electron microscopy (FE-SEM) analysis were used to evaluate the produced MnO2 NPs. FE-SEM pictures demonstrated how agglomerated nanoparticles formed. According to FE-SEM calculations, the particle size ranged from 18.7-91.5 nm. FTIR spectra show that pure Mn-O is formed, while EDX results show that Mn and O are present. The ability to suppress biofilm growth in the produced MnO

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