Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Bulletin of Electrical Engineering and Informatics
Chamseddine Zaki
American University of the Middle East
Computer Science & IT Electrical & Electronics Engineering Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
A comparative study of Arabic morphological analyzers Omar Saadiyeh; Alaaeddine Ramadan; Chamseddine Zaki; Mohamad Hajjar; Gilles Bernard
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 15, No 2: April 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v15.i2.pp1876-1890

Abstract

The field of Arabic natural language processing (NLP) has witnessed significant advancements, driven by the development of various morphological analyzers. This paper compares several major Arabic morphological analyzers and examines their ability to handle word ambiguities, process dialects, operate efficiently, and support downstream NLP tasks. By reviewing previous studies, we identify key gaps, including the limited resources for dialects, the shortage of annotated corpora, and challenges related to system scalability. The study also highlights future directions, such as building larger and more diverse corpora, adapting neural models for dialects, and developing analyzers that are more interpretable and trustworthy. Overall, this comparative overview aims to provide a clearer understanding of the current state of Arabic morphological analyzers, synthesize existing research, and offer practical recommendations for future work in this area.
Two-way differential strategy for wireless sensor networks Samer Alabed; Amer Alsaraira; Nour Mostafa; Mohammad Al-Rabayah; Ahmed Shdefat; Chamseddine Zaki; Omar A. Saraereh; Zakwan Al-Arnaout
Bulletin of Electrical Engineering and Informatics Vol 12, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i6.6121

Abstract

In this paper, a novel optimal two-way amplify and forward (AF) differential beamforming method for wireless sensor network is proposed. The proposed method is an advanced signal processing technique used to enhance the performance and reliability of the communication link by exploiting the diversity provided by multiple antennas. Unlike current state-of-the-art methods which require the knowledge of channel state information (CSI) at both transmitting and receiving antennas or at least at the receiving antennas, the suggested method does not need CSI at any transmitting or receiving antenna. Moreover, the proposed method enjoys high error performance with high diversity and coding gain and has a very low encoding and decoding complexity. Through our simulations, the proposed method is proved to outperform the best known non-coherent multi-antenna methods.
Co-Authors Ahmed Shdefat Alaaeddine Ramadan Amer Alsaraira Gilles Bernard Mohamad Hajjar Mohammad Al-Rabayah Nour Mostafa Omar A. Saraereh Omar Saadiyeh Samer Alabed Zakwan Al-Arnaout