Ahmad M. Khasawneh

Dr. Ahmad M. Khasawneh

Information Technology, Amman Arab University, Amman, Al ‘Āşimah, Jordan
orcid

Research Focus & Metrics

Academic Career Length

12Years (2015-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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31 October 2019 in Neural Computing and Applications
Verified
Journal Article
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MSMohammad Shehab
Mohammad Shehab
Laith AbualigahLaith Abualigah
Laith Abualigah
HHHusam Al Hamad
Husam Al Hamad
HAHamzeh Alabool
Hamzeh Alabool
MAMohammad alshinwan
Mohammad alshinwan
Ahmad M. KhasawnehAhmad M. Khasawneh
Ahmad M. Khasawneh

16 January 2022 in Neural Computing and Applications
Verified
Journal Article
Closed access
PDF file
Laith AbualigahLaith Abualigah
Laith Abualigah
Mohamed Abd ElazizMohamed Abd Elaziz
Mohamed Abd Elaziz
Ahmad M. KhasawnehAhmad M. Khasawneh
Ahmad M. Khasawneh
MAMohammad alshinwan
Mohammad alshinwan
RIRehab Ali Ibrahim
Rehab Ali Ibrahim
Amir H GandomiAmir H Gandomi
Amir H Gandomi

18 April 2021 in Neural Computing and Applications
Verified
Journal Article
Closed access
PDF file
Mohamed Abd ElazizMohamed Abd Elaziz
Mohamed Abd Elaziz
ADAbdelghani Dahou
Abdelghani Dahou
Laith AbualigahLaith Abualigah
Laith Abualigah
YLyu liyang
yu liyang
MAMohammad alshinwan
Mohammad alshinwan
SLSongfeng Lu
Songfeng Lu

6 January 2021 in Electronics
Verified
Journal Article
Open access
PDF file
Laith AbualigahLaith Abualigah
Laith Abualigah
Amir H GandomiAmir H Gandomi
Amir H Gandomi
Mohamed Abd ElazizMohamed Abd Elaziz
Mohamed Abd Elaziz
HHHusam Hamad
Husam Hamad
MOMahmoud Omari
Mahmoud Omari
Ahmad M. KhasawnehAhmad M. Khasawneh
Ahmad M. Khasawneh
This paper presents a comprehensive survey of the meta-heuristic optimization algorithms on the text clustering applications and highlights its main procedures. These Artificial Intelligence (AI) algorithms are recognized as promising swarm intelligence methods due to their successful ability to solve machine learning problems, especially text clustering problems. This paper reviews all of the relevant literature on meta-heuristic-based text clustering applications, including many variants, such as basic, modified, hybridized, and multi-objective methods. As well, the main procedures of text clustering and critical discussions are given. Hence, this review reports its advantages and disadvantages and recommends potential future research paths. The main keywords that have been considered in this paper are text, clustering, meta-heuristic, optimization, and algorithm.

19 January 2021 in Electronics
Verified
Journal Article
Open access
PDF file
Ala KhalifehAla Khalifeh
Ala Khalifeh
KDKhalid A. Darabkh
Khalid A. Darabkh
Ahmad M. KhasawnehAhmad M. Khasawneh
Ahmad M. Khasawneh
IAISSA ALQAISIEH
ISSA ALQAISIEH
MSMohammad Salameh
Mohammad Salameh
KRKishore Rajendiran
Kishore Rajendiran
The advent of various wireless technologies has paved the way for the realization of new infrastructures and applications for smart cities. Wireless Sensor Networks (WSNs) are one of the most important among these technologies. WSNs are widely used in various applications in our daily lives. Due to their cost effectiveness and rapid deployment, WSNs can be used for securing smart cities by providing remote monitoring and sensing for many critical scenarios including hostile environments, battlefields, or areas subject to natural disasters such as earthquakes, volcano eruptions, and floods or to large-scale accidents such as nuclear plants explosions or chemical plumes. The purpose of this paper is to propose a new framework where WSNs are adopted for remote sensing and monitoring in smart city applications. We propose using Unmanned Aerial Vehicles to act as a data mule to offload the sensor nodes and transfer the monitoring data securely to the remote control center for further analysis and decision making. Furthermore, the paper provides insight about implementation challenges in the realization of the proposed framework. In addition, the paper provides an experimental evaluation of the proposed design in outdoor environments, in the presence of different types of obstacles, common to typical outdoor fields. The experimental evaluation revealed several inconsistencies between the performance metrics advertised in the hardware-specific data-sheets. In particular, we found mismatches between the advertised coverage distance and signal strength with our experimental measurements. Therefore, it is crucial that network designers and developers conduct field tests and device performance assessment before designing and implementing the WSN for application in a real field setting.

6 February 2017 in Wireless Networks
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Journal Article
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Ahmad M. KhasawnehAhmad M. Khasawneh
Ahmad M. Khasawneh
MLMuhammad Shafie Bin Abd Latiff
Muhammad Shafie Bin Abd Latiff
Omprakash KaiwartyaOmprakash Kaiwartya
Omprakash Kaiwartya
HCHassan Chizari
Hassan Chizari