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Bionics-Based Approach for Object Tracking to Implement in Robot Applications
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In this paper, an approach for object tracking that is inspired from human oculomotor system is proposed and verified experimentally. The developed approach divided into two phases, fast tracking or saccadic phase and smooth pursuit phase. In the first phase, the field of the view is segmented into four regions that are analogue to retinal periphery in the oculomotor system. When the object of interest is entering these regions, the developed vision system responds by changing the values of the pan and tilt angles to allow the object lies in the fovea area and then the second phase will activate. A fuzzy logic method is implemented in the saccadic phase as an intelligent decision maker to select the values of the pan and tilt angle based on suggested logical rules. In smooth pursuit phase, the object is kept in the center area of the field of the view by smooth adjusting the values of the pan and tilt angles where this stage is analogue to putting the observing object in the fovea centralis of the oculomotor system. The proposed approach was implemented by using (Camera-Pan / Tilt) configuration and showed good results to improve the vision capability of the humanoid robots.

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Publication Date
Wed Jun 01 2022
Journal Name
Baghdad Science Journal
Advanced GIS-based Multi-Function Support System for Identifying the Best Route
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Geographic Information Systems (GIS) are obtaining a significant role in handling strategic applications in which data are organized as records of multiple layers in a database. Furthermore, GIS provide multi-functions like data collection, analysis, and presentation. Geographic information systems have assured their competence in diverse fields of study via handling various problems for numerous applications. However, handling a large volume of data in the GIS remains an important issue. The biggest obstacle is designing a spatial decision-making framework focused on GIS that manages a broad range of specific data to achieve the right performance. It is very useful to support decision-makers by providing GIS-based decision support syste

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Publication Date
Mon Jan 28 2013
Journal Name
Spie Proceedings
Enhancement of security for free space optics based on reconfigurable chaotic technique
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Free Space Optical (FSO) technology offers highly directional, high bandwidth communication channels. This technology can provide fiber-like data rate over short distances. In order to improve security associated with data transmission in FSO networks, a secure communication method based on chaotic technique is presented. In this paper, we have turned our focus on a specific class of piece wise linear one-dimensional chaotic maps. Simulation results indicate that this approach has the advantage of possessing excellent correlation property. In this paper we examine the security vulnerabilities of single FSO links and propose a solution to this problem by implementing the chaotic signal generator “reconfigurable tent map”. As synchronizat

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Publication Date
Wed Jul 01 2020
Journal Name
Journal Of Engineering
Bat Algorithm Based an Adaptive PID Controller Design for Buck Converter Model
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The aim of this paper is to design a PID controller based on an on-line tuning bat optimization algorithm for the step-down DC/DC buck converter system which is used in the battery operation of the mobile applications. In this paper, the bat optimization algorithm has been utilized to obtain the optimal parameters of the PID controller as a simple and fast on-line tuning technique to get the best control action for the system. The simulation results using (Matlab Package) show the robustness and the effectiveness of the proposed control system in terms of obtaining a suitable voltage control action as a smooth and unsaturated state of the buck converter input voltage of ( ) volt that will stabilize the buck converter sys

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Publication Date
Sun Aug 01 2021
Journal Name
International Journal Of Mechanical Engineering And Robotics Research
Adaptive Approximation-Based Feedback Linearization Control for a Nonlinear Smart Thin Plate
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This paper proposes feedback linearization control (FBLC) based on function approximation technique (FAT) to regulate the vibrational motion of a smart thin plate considering the effect of axial stretching. The FBLC includes designing a nonlinear control law for the stabilization of the target dynamic system while the closedloop dynamics are linear with ensured stability. The objective of the FAT is to estimate the cubic nonlinear restoring force vector using the linear parameterization of weighting and orthogonal basis function matrices. Orthogonal Chebyshev polynomials are used as strong approximators for adaptive schemes. The proposed control architecture is applied to a thin plate with a large deflection that stimulates the axial loadin

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Publication Date
Mon Nov 01 2010
Journal Name
Journal Of Systems And Software
Development of Java based RFID application programmable interface for heterogeneous RFID system
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Publication Date
Tue Feb 28 2023
Journal Name
Applied System Innovation
Earthquake Hazard Mitigation for Uncertain Building Systems Based on Adaptive Synergetic Control
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This study presents an adaptive control scheme based on synergetic control theory for suppressing the vibration of building structures due to earthquake. The control key for the proposed controller is based on a magneto-rheological (MR) damper, which supports the building. According to Lyapunov-based stability analysis, an adaptive synergetic control (ASC) strategy was established under variation of the stiffness and viscosity coefficients in the vibrated building. The control and adaptive laws of the ASC were developed to ensure the stability of the controlled structure. The proposed controller addresses the suppression problem of a single-degree-of-freedom (SDOF) building model, and an earthquake control scenario was conducted and simulat

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Publication Date
Sun Jul 01 2012
Journal Name
Applied Soft Computing
A new evolutionary based routing protocol for clustered heterogeneous wireless sensor networks
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Publication Date
Wed Sep 30 2020
Journal Name
Association Of Arab Universities Journal Of Engineering Sciences
Estimation of Minimum Miscibility Pressure for Hydrocarbon Gas Injection Based on EOS
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The important parameter used for determining the probable application of miscible displacement is the MMP (minimum miscibility pressure). In enhanced oil recovery, the injection of hydrocarbon gases can be a highly efficient method to improve the productivity of the well especially if miscibility developed through the displacement process. There are a lot of experiments for measuring the value of the miscibility pressure, but they are expensive and take a lot of time, so it's better to use the mathematical equations because of it inexpensive and fast. This study focused on calculating MMP required to inject hydrocarbon gases into two reservoirs namely Sadi and Tanomaa/ East Baghdad field. Modified Peng Robenson Equation of State was

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Publication Date
Mon Feb 21 2022
Journal Name
Iraqi Journal For Computer Science And Mathematics
Fuzzy C means Based Evaluation Algorithms For Cancer Gene Expression Data Clustering
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The influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, whic

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
PDCNN: FRAMEWORK for Potato Diseases Classification Based on Feed Foreword Neural Network
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         The economy is exceptionally reliant on agricultural productivity. Therefore, in domain of agriculture, plant infection discovery is a vital job because it gives promising advance towards the development of agricultural production. In this work, a framework for potato diseases classification based on feed foreword neural network is proposed. The objective of this work  is presenting a system that can detect and classify four kinds of potato tubers diseases; black dot, common scab, potato virus Y and early blight based on their images. The presented PDCNN framework comprises three levels: the pre-processing is first level, which is based on K-means clustering algorithm to detect the infected area from potato image. The s

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