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A Comparative Study of Various Intelligent Optimization Algorithms Based on Path Planning and Neural Controller for Mobile Robot
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In this paper, a cognitive system based on a nonlinear neural controller and intelligent algorithm that will guide an autonomous mobile robot during continuous path-tracking and navigate over solid obstacles with avoidance was proposed. The goal of the proposed structure is to plan and track the reference path equation for the autonomous mobile robot in the mining environment to avoid the obstacles and reach to the target position by using intelligent optimization algorithms. Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) Algorithms are used to finding the solutions of the mobile robot navigation problems in the mine by searching the optimal paths and finding the reference path equation of the optimal path. As well as, PSO algorithm is used to find and tune on-line the neural control gains values of the nonlinear neural controller to obtain the best torques actions of the wheels for the mining autonomous mobile robot. Simulation results by matlab showed that the proposed cognitive system is more accurate in terms of planning reference path to avoid obstacles and online finding and tuning parameters of the controller which generated smoothness control action without saturation state for tracking the reference path equation as well as minimize the mobile robot tracking pose error to zero value.

 

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Publication Date
Wed Dec 14 2016
Journal Name
Journal Of Baghdad College Of Dentistry
Correlation between Periodontal Health Status and Salivary Matrix Metalloproteinase-9 Levels in Smoker and Non-Smoker Chronic Periodontitis Patients (A Comparative Study)
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Background: Periodontal diseases are inflammatory diseases affecting the supporting tissues of the teeth. One of the leading environmental factors that are closely related not only to the risk but also to the prognosis of periodontitis is smoking. This study aimed to evaluate the influence of smoking on periodontal health status and to measure the levels of matrix metalloproteinase-9 in smokers and nonsmokers chronic periodontitis patients, also it aimed to test the correlation between the levels of matrix metalloproteinase-9 and the clinical periodontal parameters. Materials and Methods: Five milliliters samples of un-stimulated whole saliva and full-mouth clinical periodontal recordings (plaque index, gingival index, bleeding on probing,

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Publication Date
Thu Jun 01 2023
Journal Name
Baghdad Science Journal
Determination of essential and trace elements in various vegetables using ICP-MS
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Metal contents in vegetables are interesting because of issues related to food safety and ‎potential health risks. The availability of these metals in the human body ‎may perform many biochemical functions and some of them linked with various diseases at ‎high levels. The current study aimed to evaluate the concentration of various metals in ‎common local consumed vegetables using ICP-MS. The concentrations of metals in vegetables ‎of tarragon, Bay laurel, dill, Syrian mesquite, vine leaves, thymes, arugula, basil, common ‎purslane and parsley of this study were found to be in the range of, 76-778 for Al, 10-333 for B, 4-119 for ‎Ba, ‎2812‎-24645 for Ca, 0.1-0.32 for Co, 201-464 for Fe, 3661-46400 for K, 0.31–‎‎1.

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Publication Date
Tue Nov 01 2022
Journal Name
Journal Of Engineering
Artificial Neural Network Model for Wastewater Projects Maintenance Management Plan
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Wastewater projects are one of the most important infrastructure projects, which require developing strategic plans to manage these projects. Most of the wastewater projects in Iraq don’t have a maintenance plan. This research aims to prepare the maintenance management plan (MMP) for wastewater projects. The objective of the research is to predict the cost and time of maintenance projects by building a model using ANN. The research sample included (15) completed projects in Wasit Governorate, where the researcher was able to obtain the data of these projects through the historical information of the Wasit Sewage Directorate. In this research artificial neural networks (ANN) technique was used to build two models (cost

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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
Tue Feb 01 2022
Journal Name
Webology
Efficient Eye Recognition for Secure Systems using Convolutional Neural Network
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Publication Date
Mon Jan 28 2019
Journal Name
Soft Computing
Bio-inspired multi-objective algorithms for connected set K-covers problem in wireless sensor networks
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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
AlexNet Convolutional Neural Network Architecture with Cosine and Hamming Similarity/Distance Measures for Fingerprint Biometric Matching
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In information security, fingerprint verification is one of the most common recent approaches for verifying human identity through a distinctive pattern. The verification process works by comparing a pair of fingerprint templates and identifying the similarity/matching among them. Several research studies have utilized different techniques for the matching process such as fuzzy vault and image filtering approaches. Yet, these approaches are still suffering from the imprecise articulation of the biometrics’ interesting patterns. The emergence of deep learning architectures such as the Convolutional Neural Network (CNN) has been extensively used for image processing and object detection tasks and showed an outstanding performance compare

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Publication Date
Tue Jun 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Using the Critical Path Method (CPM) for scheduling the project (paving the Amil Sayid Al-Ayyam Street with a length of 1.25 km) In terms of Decresing the time
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The implementation of the concept of project scheduling in the organizations generally requires a set of procedures and requirements, So, most important of all is the understanding and knowledge of the tools and techniques which are called the methods of scheduling projects. Consequently, the projects of the municipality administration in the holy governorate of Karbala suffer from the problem of delaying their projects and chaos in the ways of implementation. To provide assistance to this directorate and to demonstrate how to schedule projects using one of the advanced scientific methods that proved their ability to schedule any project and its potential to accelerate the time of completion, as well as ease of use and effectiven

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Publication Date
Tue Dec 31 2024
Journal Name
Iraqi Geological Journal
Geomechanical Modeling and Artificial Neural Network Technique for Predicting Breakout Failure in Nasiriyah Oilfield
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Wellbore instability is one of the major issues observed throughout the drilling operation. Various wellbore instability issues may occur during drilling operations, including tight holes, borehole collapse, stuck pipe, and shale caving. Rock failure criteria are important in geomechanical analysis since they predict shear and tensile failures. A suitable failure criterion must match the rock failure, which a caliper log can detect to estimate the optimal mud weight. Lack of data makes certain wells' caliper logs unavailable. This makes it difficult to validate the performance of each failure criterion. This paper proposes an approach for predicting the breakout zones in the Nasiriyah oil field using an artificial neural network. It

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Publication Date
Sun Mar 01 2020
Journal Name
Sustainable Chemistry And Pharmacy
A sustainable approach to utilize olive pips for the sorption of lead ions: Numerical modeling with aid of artificial neural network
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