Iraqi Journal for Electrical and Electronic Engineering
Login
Iraqi Journal for Electrical and Electronic Engineering
  • Home
  • Articles & Issues
    • Latest Issue
    • All Issues
  • Authors
    • Submit Manuscript
    • Guide for Authors
    • Authorship
    • Article Processing Charges (APC)
    • Proofreading Service
  • Reviewers
    • Guide for Reviewers
    • Become a Reviewer
  • About
    • About Journal
    • Aims and Scope
    • Editorial Team
    • Journal Insights
    • Peer Review Process
    • Publication Ethics
    • Plagiarism
    • Allegations of Misconduct
    • Appeals and Complaints
    • Corrections and Withdrawals
    • Open Access
    • Archiving Policy
    • Abstracting and indexing
    • Announcements
    • Contact

Search Results for Zainab Khalaf

Article
A Comprehensive Review for Aircraft Detection Techniques Utilizing Deep Learning

Marwa Hameed, Zainab Khalaf

Pages: 216-236

PDF Full Text
Abstract

Aircraft detection is a vital and significant field within object detection that has garnered considerable attention from academics, particularly following the advancement of deep learning methods. Aircraft detection has recently become widely utilized in several civil and military fields. This comprehensive survey meticulously categorizes and evaluates diverse deep learning methodologies in airplane detection research. Encompassing radar-based, image-based, and multimodal approaches, the paper presents a structured framework to enhance understanding of the evolving research landscape within this domain. The survey critically identifies gaps and discerns emerging trends, offering valuable insights into standard datasets of aircraft images, performance metrics, real-world applications, and challenges and limitations encountered by aircraft detection systems. Its potential contributions are underscored as pivotal for advancing the safety and security of air travel. This research paper is the inaugural publication of its kind in the domain of aircraft detection review papers, establishing itself as an all-encompassing reference for subsequent scholars.

Article
Design and Implementation of a 3RRR Parallel Planar Robot

Ammar Aldair, Auday Al-Mayyahi, Zainab A. Khalaf, Chris Chatwin

Pages: 48-57

PDF Full Text
Abstract

Parallel manipulators have a rigid structure and can pick up the heavy objects. Therefore, a parallel manipulator has been developed based on the cooperative of three arms of a robotic system to make the whole system suitable for solving many problems such as materials handling and industrial automation. The three revolute joints are used to achieve the mechanism operation of the parallel planar robot. Those revolute joints are geometrically designed using an open-loop spatial robotic platform. In this paper, the geometric structure with three revolute joints is used to drive and analyze the inverse kinematic model for the 3RRR parallel planar robot. In the proposed design, three main variables are considered: the length of links of the 3RRR parallel planar robot, base positions of the platform, and joint angles’ geometry. Cayley-Menger determinants and bilateration are proposed to calculate these three variables to determine the final position of the platform and to move specific objects according to given desired trajectories. The proposed structure of the 3RRR parallel planar robot is simulated and different desired trajectories are tested to study the performance of the proposed stricter. Furthermore, the hardware implementation of the proposed structure is accomplished to validate the design in practical terms.

1 - 2 of 2 items

Search Parameters

Journal Logo
Iraqi Journal for Electrical and Electronic Engineering

College of Engineering, University of Basrah

  • Copyright Policy
  • Terms & Conditions
  • Privacy Policy
  • Accessibility
  • Cookie Settings
Licensing & Open Access

CC BY 4.0 Logo Licensed under CC-BY-4.0

This journal provides immediate open access to its content.

Editorial Manager Logo Elsevier Logo

Peer-review powered by Elsevier’s Editorial Manager®

Copyright © 2025 College of Engineering, University of Basrah. All rights reserved, including those for text and data mining, AI training, and similar technologies.