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An Adaptive Multi-Objective Particle Swarm Optimization Algorithm for Multi-Robot Path Planning
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This paper discusses an optimal path planning algorithm based on an Adaptive Multi-Objective Particle Swarm Optimization Algorithm (AMOPSO) for two case studies. First case, single robot wants to reach a goal in the static environment that contain two obstacles and two danger source. The second one, is improving the ability for five robots to reach the shortest way. The proposed algorithm solves the optimization problems for the first case by finding the minimum distance from initial to goal position and also ensuring that the generated path has a maximum distance from the danger zones. And for the second case, finding the shortest path for every robot and without any collision between them with the shortest time. In order to evaluate the proposed algorithm in term of finding the best solution, six benchmark test functions are used to make a comparison between AMOPSO and the standard MOPSO. The results show that the AMOPSO has a better ability to get away from local optimums with a quickest convergence than the MOPSO. The simulation results using Matlab 2014a, indicate that this methodology is extremely valuable for every robot in multi-robot framework to discover its own particular proper pa‌th from the start to the destination position with minimum distance and time.

 

 

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Publication Date
Wed Oct 18 2023
Journal Name
Ieee Access
A New Imputation Technique Based a Multi-Spike Neural Network to Handle Missing Data in the Internet of Things Network (IoT)
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Publication Date
Wed Jan 19 2022
Journal Name
Iraqi Journal Of Science
Synergistic effect of biosynthesized silver nanoparticles with antibiotics against multi-drug resistance bacteria isolated from children with diarrhoea under five years
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Isolation and identification of bacterial isolates were carried out according to the morphology and biochemical characteristics on one hundred and twenty stool specimens collected from children under five years old via using biochemical tests and Api 20E compact system for further confirmation. Bacterial isolates were distributed as (34.48, 20.68, 5.17,0.86) % for Escherichia coli, Salmonella typhi ,Enterobacter aerogenos, Citrobacter freundii and Hafnia alvei respectively and 9.48 % for each Proteus mirabilis, Pseudomonas aeruginosa and Klebsiella Pneumonia. As well as, 2.58% for both Shigella sonnei and Serratia marcescens. Antibiotic susceptibility test for 116 bacterial isolates was performed towards 20 antibiotics types using disk d

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Publication Date
Sat Jun 01 2019
Journal Name
2019 Ieee International Conference On Automatic Control And Intelligent Systems (i2cacis)
Study on Solar Panel Cleaning Robot
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Publication Date
Thu Dec 29 2016
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Technique For Image De-blurring Using Adaptive Wavelet Lagrange Fuzzy Filter
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A new de-blurring technique was proposed in order to reduced or remove the blur in the images. The proposed filter was designed from the Lagrange interpolation calculation with adjusted by fuzzy rules and supported by wavelet decomposing technique. The proposed Wavelet Lagrange Fuzzy filter gives good results for fully and partially blurring region in images.
 

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Publication Date
Sat Dec 17 2022
Journal Name
Journal Of Al-ma'moon College
Simulation and Implementation of SNR Measurement processor for Adaptive Communication Systems
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Publication Date
Sat Oct 01 2011
Journal Name
Journal Of Engineering
MODIFIED TRAINING METHOD FOR FEEDFORWARD NEURAL NETWORKS AND ITS APPLICATION in 4-LINK SCARA ROBOT IDENTIFICATION
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In this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func

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Publication Date
Mon Oct 17 2011
Journal Name
Journal Of Engineering
MODIFIED TRAINING METHOD FOR FEEDFORWARD NEURAL NETWORKS AND ITS APPLICATION in 4-LINK SCARA ROBOT IDENTIFICATION
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In this research the results of applying Artificial Neural Networks with modified activation function to perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of identification strategy consists of a feed-forward neural network with a modified activation function that operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have been trained online and offline have been used, without requiring any previous knowledge about the system to be identified. The activation function that is used in the hidden layer in FFNN is a modified version of the wavelet function. This approach ha

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Publication Date
Wed Apr 05 2023
Journal Name
Journal Of Engineering
Construction Time-Cost Optimization Modeling Using Ant Colony Optimization
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In the field of construction project management, time and cost are the most important factors to be considered in planning every project, and their relationship is complex. The total cost for each project is the sum of the direct and indirect cost. Direct cost commonly represents labor, materials, equipment, etc.
Indirect cost generally represents overhead cost such as supervision, administration, consultants, and interests. Direct cost grows at an increasing rate as the project time is reduced from its original planned time. However, indirect cost continues for the life of the project and any reduction in project time means a reduction in indirect cost. Therefore, there is a trade-off between the time and cost for completing construc

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Publication Date
Sun Mar 15 2020
Journal Name
Journal Of The College Of Education For Women
Urban Security in Cities Planning
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Cities have witnessed great changes since the planning of the first cities. This is due to the increase in population and problems in services which affect urban security. As such, urban security is directed and affected by the nature of city planning and the types of services. Besides, the kind of services plays an imminent place in providing urban security at all levels. Other factors that influence urban security can be limited to the increase of population, economic and social changes. This leads to losing urban control. This study will explore the historical chronology to identify weaknesses in urban planning since its dawn and reaching solutions to protect urban security. The importance of the research lies in achieving urban secur

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Publication Date
Sat Jun 06 2020
Journal Name
Journal Of The College Of Education For Women
Urban Security in Cities Planning
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Cities have witnessed great changes since the planning of the first cities. This is due to the increase in population and problems in services that affect urban security. As such, urban security is directed and affected by the nature of city planning and the types of services. Besides, the kind of services plays an imminent place in providing urban security at all levels. Other factors that influence urban security can be limited to the increase of population, economic and social changes. This leads to losing urban control. This study will explore the historical chronology to identify weaknesses in urban planning since its dawn and reaching solutions to protect urban security. The importance of the research lies in achieving urban securi

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