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All Journal International Journal of Electrical and Computer Engineering Indonesian Journal of Electrical Engineering and Computer Science
Shahbaa I. Khaleel
Mosul University
Computer Science & IT Electrical & Electronics Engineering

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Image retrieval based on swarm intelligence Shahbaa I. Khaleel; Ragad W. Khaled
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i6.pp5390-5401

Abstract

To keep pace with the development of modern technology in this information technology era, and the immense image databases, whether personal or commercial, are increasing, is requiring the management of these databases to strong and accurate systems to retrieve images with high efficiency. Because of the swarm intelligence algorithms are great importance in solving difficult problems and obtaining the best solutions. Here in this research, a proposed system is designed to retrieve color images based on swarm intelligence algorithms. Where the algorithm of the ant colony optimization (ACOM) and the intelligent water drop (IWDM) was used to improve the system's work by conducting the clustering process in these two methods on the features extracted by annular color moment method (ACM) to obtain clustered data, the amount of similarity between them and the query image, is calculated to retrieve images from the database, efficiently and in a short time. In addition, improving the work of these two methods by hybridizing them with fuzzy method, fuzzy gath geva clustering algorithm (FGCA) and obtaining two new high efficiency hybrid algorithms fuzzy ant colony optimization method (FACOM) and fuzzy intelligent water drop method (FIWDM) by retrieving images whose performance values are calculated by calculating the values of precision, recall and the f-measure. It proved its efficiency by comparing it with fuzzy method, FGCA and by methods of swarm intelligence without hybridization, and its work was excellent.
A literature review for measuring maintainability of code clone Shahbaa I. Khaleel; Ghassan Khaleel Al-Khatouni
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 2: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i2.pp1118-1127

Abstract

Software organizations face constant pressure due to stakeholder requirements and the increasing complexity of software systems. This complexity, combined with defects in code quality and failures, can pose risks to software systems. To ensure code is understood before maintenance, developers must spend over 60% of their time modifying and improving code quality, which is costly. This study examines the impact of code refactoring activities on software maintainability and quality by reviewing relevant research and explaining key terms. The research finds that refactoring activities can enhance specific quality characteristics, including maintainability, understandability, and testability. The study also identifies important factors that should be considered when developing refactoring tools. Refactoring enables code improvement without altering program behavior and can be applied multiple times to source code.
Co-Authors Ghassan Khaleel Al-Khatouni Ragad W. Khaled