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Enhanced Performance of Consensus Wireless Sensor Controlled System via Particle Swarm Optimization Algorithm
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     This paper describes the application of consensus optimization for Wireless Sensor Network (WSN) system. Consensus algorithm is usually conducted within a certain number of iterations for a given graph topology. Nevertheless, the best Number of Iterations (NOI) to reach consensus is varied in accordance with any change in number of nodes or other parameters of . graph topology. As a result, a time consuming trial and error procedure will necessary be applied
to obtain best NOI. The implementation of an intellig ent optimization can effectively help to get the optimal NOI. The performance of the consensus algorithm has considerably been improved by the inclusion of Particle Swarm Optimization (PSO). As a case study, variable number of nodes in a network with a random graph topology has been considered. Simulation results show that significant reduction in the NOI and power consumption has been achieved, where it decreased the NOI about 40 iteration; when using PSO for different number of nodes in the specified network.
 

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Publication Date
Wed Apr 30 2025
Journal Name
Iraqi Journal Of Science
Electrochemical Synthesis of Fe-doped TiO2 Nanotube for Gas Sensor Application
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Titanium dioxide (TiO2) nanotubes have gained particular interest as a material for gas sensors because of their vertical arrays, prepared by the anodization procedure. The presence of several oxygen vacancies in these nanotubes facilitates gas diffusion and provides additional active sites. This study examined the impact of voltages on the process of depositing iron nanoparticles onto arrays of TiO2 nanotubes (TNTs) for use as a gas sensor. The TNTs are manufactured using a straightforward and economical electrochemical anodization technique, specifically for gas sensor applications. By varying the deposition voltage (2-6 volts), ordered Fe-TNTs were efficiently manufactured using a simple two-step electrochemical process. It utili

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Publication Date
Thu Feb 15 2018
Journal Name
Iraqi Journal Of Laser
Characterization of Gold Coating on Nanostructured CR39 Polymer as SERS Sensor
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Abstract: The development of highly sensitive sensors has become an efficient field of research. In this work, an ArF Excimer laser of 193 nm with a maximum pulse energy of 275 mJ, 15 ns pulse duration and a repetition rate of 1 Hz is utilized to form a Laser Induced Periodic Surface Structures (LIPSS) of three different morphologies (nanochains, contours, grooves) on surface of CR39 polymer at a fluence range above the ablation threshold (250 mJ/cm2). The laser ablated polymer surface is then Surface Enhanced Raman Scattering (SERS) activated by deposition of a gold layer of 30 nm thickness. The capability of the produced substrate for surface enhanced Raman scattering is evaluated through thiophenol as an analyte molecule. It is observ

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Publication Date
Mon Jan 01 2024
Journal Name
Recent Research On Geotechnical Engineering, Remote Sensing, Geophysics And Earthquake Seismology
Evaluating the Accuracy of iPhone Lidar Sensor for Building Façades Conservation
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Publication Date
Sat Sep 30 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Optimization of Gas Lifting Design in Mishrif Formation of Halfaya Oil Field
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The optimization of artificial gas lift techniques plays a crucial role in the advancement of oil field development. This study focuses on investigating the impact of gas lift design and optimization on production outcomes within the Mishrif formation of the Halfaya oil field. A comprehensive production network nodal analysis model was formulated using a PIPESIM Optimizer-based Genetic Algorithm and meticulously calibrated utilizing field-collected data from a network comprising seven wells. This well group encompasses three directional wells currently employing gas lift and four naturally producing vertical wells. To augment productivity and optimize network performance, a novel gas lift design strategy was proposed. The optimization of

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Publication Date
Fri Dec 01 2023
Journal Name
Bulletin Of Electrical Engineering And Informatics
A comparative study of Gaussian mixture algorithm and K-means algorithm for efficient energy clustering in MWSN
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Wireless sensor networks (WSNs) represent one of the key technologies in internet of things (IoTs) networks. Since WSNs have finite energy sources, there is ongoing research work to develop new strategies for minimizing power consumption or enhancing traditional techniques. In this paper, a novel Gaussian mixture models (GMMs) algorithm is proposed for mobile wireless sensor networks (MWSNs) for energy saving. Performance evaluation of the clustering process with the GMM algorithm shows a remarkable energy saving in the network of up to 92%. In addition, a comparison with another clustering strategy that uses the K-means algorithm has been made, and the developed method has outperformed K-means with superior performance, saving ener

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Publication Date
Fri Aug 01 2008
Journal Name
2008 First International Conference On The Applications Of Digital Information And Web Technologies (icadiwt)
Hybrid canonical genetic algorithm and steepest descent algorithm for optimizing likelihood estimators of ARMA (1, 1) model
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This paper presents a hybrid genetic algorithm (hGA) for optimizing the maximum likelihood function ln(L(phi(1),theta(1)))of the mixed model ARMA(1,1). The presented hybrid genetic algorithm (hGA) couples two processes: the canonical genetic algorithm (cGA) composed of three main steps: selection, local recombination and mutation, with the local search algorithm represent by steepest descent algorithm (sDA) which is defined by three basic parameters: frequency, probability, and number of local search iterations. The experimental design is based on simulating the cGA, hGA, and sDA algorithms with different values of model parameters, and sample size(n). The study contains comparison among these algorithms depending on MSE value. One can conc

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Publication Date
Tue Mar 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
Using Iterative Reweighting Algorithm and Genetic Algorithm to Calculate The Estimation of The Parameters Of The Maximum Likelihood of The Skew Normal Distribution
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Excessive skewness which occurs sometimes in the data is represented as an obstacle against normal distribution. So, recent studies have witnessed activity in studying the skew-normal distribution (SND) that matches the skewness data which is regarded as a special case of the normal distribution with additional skewness parameter (α), which gives more flexibility to the normal distribution. When estimating the parameters of (SND), we face the problem of the non-linear equation and by using the method of Maximum Likelihood estimation (ML) their solutions will be inaccurate and unreliable. To solve this problem, two methods can be used that are: the genetic algorithm (GA) and the iterative reweighting algorithm (IR) based on the M

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Publication Date
Fri Dec 30 2022
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Optimization of Drilling Well Design: A Review
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Drilling well design optimization reduces total Authorization for Expenditures (AFE) by decreasing well constructing time and expense. Well design is not a constant pattern during the life cycle of the field. It should be optimized by continuous improvements for all aspects of redesigning the well depending on the actual field conditions and problems. The core objective of this study is to deliver a general review of the well design optimization processes and the available studies and applications to employ the well design optimization to solve problems encountered with well design so that cost effectiveness and perfect drilling well performance are achievable. Well design optimization processes include unconventional design(slimhole) co

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Publication Date
Sat Apr 01 2023
Journal Name
Full Text Book Of Minar Congress8
REGULARITY VIA PRE- GENERALIZED OPEN SETS
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By use the notions pre-g-closedness and pre-g-openness we have generalized a class of separation axioms in topological spaces. In particular, we presented in this paper new types of regulαrities, which we named ρg­regulαrity and Sρg­regulαrity. Many results and properties of both types have been investigated and have illustrated by examples.

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Publication Date
Tue Apr 24 2018
Journal Name
International Journal Of Engineering Technologies And Management Research
MODELING CITY PULSATION VIA MOBILE DATA
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In this study, the mobile phone traces concern an ephemeral event which represents important densities of people. This research aims to study city pulse and human mobility evolution that would be arise during specific event (Armada festival), by modelling and simulating human mobility of the observed region, depending on CDRs (Call Detail Records) data. The most pivot questions of this research are: Why human mobility studied? What are the human life patterns in the observed region inside Rouen city during Armada festival? How life patterns and individuals' mobility could be extracted for this region from mobile DB (CDRs)? The radius of gyration parameter has been applied to elaborate human life patterns with regards to (work, off) days for

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