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The use of Artificial Neural Network (ANN) for modeling of Cu (II) ion removal from aqueous solution by flotation and sorptive flotation process
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Publication Date
Wed Feb 15 2023
Journal Name
Environmental Technology
Bio-synthesis of TiO<sub>2</sub> using grape leaves extract and its application for photocatalytic degradation of ibuprofen from aqueous solution
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Publication Date
Fri Jul 01 2016
Journal Name
Journal Of Engineering
Estimation and Improvement of Routing Protocol Mobile Ad-Hoc Network Using Fuzzy Neural Network
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Ad-Hoc Networks are a generation of networks that are truly wireless, and can be easily constructed without any operator. There are protocols for management of these networks, in which the effectiveness and the important elements in these networks are the Quality of Service (QoS). In this work the evaluation of QoS performance of MANETs is done by comparing the results of using AODV, DSR, OLSR and TORA routing protocols using the Op-Net Modeler, then conduct an extensive set of performance experiments for these protocols with a wide variety of settings. The results show that the best protocol depends on QoS using two types of applications (+ve and –ve QoS in the FIS evaluation). QoS of the protocol varies from one prot

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Publication Date
Mon Nov 01 2021
Journal Name
Iop Conference Series: Earth And Environmental Science
Treatability influence of municipal sewage effluent on surface water quality assessment based on Nemerow pollution index using an artificial neural network
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Abstract<p>Assessing water quality provides a scientific foundation for the development and management of water resources. The objective of the research is to evaluate the impact treated effluent from North Rustumiyia wastewater treatment plant (WWTP) on the quality of Diyala river. The model of the artificial neural network (ANN) and factor analysis (FA) based on Nemerow pollution index (NPI). To define important water quality parameters for North Al-Rustumiyia for the line(F2), the Nemerow Pollution Index was introduced. The most important parameters of assessment of water variation quality of wastewater were the parameter used in the model: biochemical oxygen demand (BOD), chemical oxygen dem</p> ... Show More
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Publication Date
Sat Sep 30 2017
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Removal of Dyes from Synthetic Wastewater by Agriculturalwaste
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Adsorption is one of the most important technologies for the treatment of polluted water from dyes. Theaim of this study is to use a low-cost adsorbent for this purpose. A novel and economical adsorbent was used to remove methyl violet dye (MV) from aqueous solutions. This adsorbent was prepared from bean peel, which is an agricultural waste. Batch adsorption experiments were conducted to study the ability of the bean peel adsorbent (BPA) to remove the methyl violet (MV) dye. The effects of different variables, such as weight of the adsorbent, pH of the MV solution, initial concentration of MV, contact time and temperature, on the adsorption behaviour were studied. It was found experimentally that the time required to achieve equilibrium

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Publication Date
Wed Sep 01 2021
Journal Name
Journal Of Engineering
Spike neural network as a controller in SDN network
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The paper proposes a methodology for predicting packet flow at the data plane in smart SDN based on the intelligent controller of spike neural networks(SNN). This methodology is applied to predict the subsequent step of the packet flow, consequently reducing the overcrowding that might happen. The centralized controller acts as a reactive controller for managing the clustering head process in the Software Defined Network data layer in the proposed model. The simulation results show the capability of Spike Neural Network controller in SDN control layer to improve the (QoS) in the whole network in terms of minimizing the packet loss ratio and increased the buffer utilization ratio.

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Publication Date
Tue Apr 03 2018
Journal Name
International Journal Of Science And Research (ijsr)
Synthesis, Spectral of Azo Dyes Complexes with Ni (II) and Cu (II) and Their Industrial and Bacteriological Application
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Azo dye ligand was produced by coupling the diazonium salt of 4aminoantipyrine with 2, 4-dimethylphenol. The structure of 1 azo compound was someone by elemental analyses, HNMR, FT-IR and UV-Vis spectroscopic mechanics. Metal complexes of nickel (II) and copper (II) have been performed and depicted. The formation of complexes has been identified by using flame atomic absorption, (C.H.N) Analysis, FT-IR and UV-Vis spectral process as well as, conductivity and magnetic properties quantifications. The nature of the complexes formed were studied succeed the mole ratio and continuous variation methods, Beer's law followed over a concentration 4 4 scope (1×10- - 3×10- M). High molar absorbtivity of the complex solutions were observed. Analytica

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Publication Date
Tue Jan 01 2013
Journal Name
International Journal Of Application Or Innovation In Engineering & Management (ijaiem)
Probabilistic Neural Network for User Authentication Based on Keystroke Dynamics
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Computer systems and networks are increasingly used for many types of applications; as a result the security threats to computers and networks have also increased significantly. Traditionally, password user authentication is widely used to authenticate legitimate user, but this method has many loopholes such as password sharing, brute force attack, dictionary attack and more. The aim of this paper is to improve the password authentication method using Probabilistic Neural Networks (PNNs) with three types of distance include Euclidean Distance, Manhattan Distance and Euclidean Squared Distance and four features of keystroke dynamics including Dwell Time (DT), Flight Time (FT), mixture of (DT) and (FT), and finally Up-Up Time (UUT). The resul

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Publication Date
Tue Feb 01 2022
Journal Name
Webology
Efficient Eye Recognition for Secure Systems using Convolutional Neural Network
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Publication Date
Sat Jan 01 2022
Journal Name
Webology
Efficient Eye Recognition for Secure Systems Using Convolutional Neural Network
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AA Abbass, HL Hussein, WA Shukur, J Kaabi, R Tornai, Webology, 2022 Individual’s eye recognition is an important issue in applications such as security systems, credit card control and guilty identification. Using video images cause to destroy the limitation of fixed images and to be able to receive users’ image under any condition as well as doing the eye recognition. There are some challenges in these systems; changes of individual gestures, changes of light, face coverage, low quality of video images and changes of personal characteristics in each frame. There is a need for two phases in order to do the eye recognition using images; revelation and eye recognition which will use in the security systems to identify the persons. The mai

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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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