Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Yazan Aljeroudi"'
Autor:
Haitham Q. Ghadhban, Muhaini Othman, Noor Samsudin, Shahreen Kasim, Aisyah Mohamed, Yazan Aljeroudi
Publikováno v:
IEEE Access, Vol 9, Pp 73482-73494 (2021)
In the last few years, deep learning-based models have made significant inroads into the field of handwriting recognition. However, deep learning requires the availability of massive labelled data and considerable computation for training or automati
Externí odkaz:
https://doaj.org/article/e7683c6142fb418b9077f295858b9a5d
Publikováno v:
IEEE Access, Vol 7, Pp 10196-10207 (2019)
Multi-objective optimization (MOO) is widely used for solving various engineering real-life problems. Meta-heuristic optimization has been regarded as an effective solution for such problems because it enables the successful examination of a broad ra
Externí odkaz:
https://doaj.org/article/538c1ce9edb04b4e98f45bc2b0e02671
Publikováno v:
IEEE Access, Vol 7, Pp 132374-132383 (2019)
Vehicular ad hoc networks (VANETs) provide alternative technology solutions to various transportation problems, and they provide a communication solution in intelligent transportation systems. However, the reliability and connectivity of VANET networ
Externí odkaz:
https://doaj.org/article/554aa8521b3b488dbf77c90dc418546b
Autor:
Ahmed Salih Al-Khaleefa, Mohd Riduan Ahmad, Azmi Awang Md Isa, Mona Riza Mohd Esa, Ahmed Al-Saffar, Yazan Aljeroudi
Publikováno v:
IEEE Access, Vol 6, Pp 54769-54785 (2018)
Wi-Fi localization is an active research topic, and various challenges are not yet resolved in this field. Researchers develop models and use benchmark datasets for Wi-Fi or fingerprinting to create a quantitative comparative evaluation. These benchm
Externí odkaz:
https://doaj.org/article/83dcf9d293314fe28dc398fb880508c1
Autor:
Hayfaa Abdulzahra Atee, Robiah Ahmad, Norliza Mohd Noor, Abdul Monem S Rahma, Yazan Aljeroudi
Publikováno v:
PLoS ONE, Vol 12, Iss 2, p e0170329 (2017)
In image steganography, determining the optimum location for embedding the secret message precisely with minimum distortion of the host medium remains a challenging issue. Yet, an effective approach for the selection of the best embedding location wi
Externí odkaz:
https://doaj.org/article/625f091c377d403f8621d26b89a376bb
Autor:
Ahmed Salih AL-Khaleefa, Mohd Riduan Ahmad, Azmi Awang Md Isa, Mona Riza Mohd Esa, Yazan Aljeroudi, Mohammed Ahmed Jubair, Reza Firsandaya Malik
Publikováno v:
Sensors, Vol 19, Iss 10, p 2397 (2019)
Wi-Fi has shown enormous potential for indoor localization because of its wide utilization and availability. Enabling the use of Wi-Fi for indoor localization necessitates the construction of a fingerprint and the adoption of a learning algorithm. Th
Externí odkaz:
https://doaj.org/article/09b3b13ef3e949fd90994a2010113fa4
Autor:
Sheeba Memon, Jiawei Huang, Hussain Saajid, Naadiya Khuda Bux, Arshad Saleem, Yazan Aljeroudi
Publikováno v:
Symmetry, Vol 11, Iss 2, p 145 (2019)
Typically, the production data centers function with various risk factors, such as for instance the network dynamicity, topological asymmetry, and switch failures. Hence, the load-balancing schemes should consider the sensing accurate path circumstan
Externí odkaz:
https://doaj.org/article/3e0b14c9902d400fb89411cd7e335580
Publikováno v:
Symmetry, Vol 10, Iss 11, p 576 (2018)
In today’s world, millions of transactions are connected to online businesses, and the main challenging task is ensuring the privacy of sensitive information. Sensitive association rules hiding (SARH) is an important goal of privacy protection algo
Externí odkaz:
https://doaj.org/article/2a1977d8609343aaa8d410a0a4a70fd1
Publikováno v:
IEEE Access, Vol 7, Pp 10196-10207 (2019)
Multi-objective optimization (MOO) is widely used for solving various engineering real-life problems. Meta-heuristic optimization has been regarded as an effective solution for such problems because it enables the successful examination of a broad ra
Publikováno v:
IOP Conference Series: Materials Science and Engineering. 1244:012007
WiFi indoor localization is regarded as the most promising reliable technology for indoor localization. Its concept is based on building fingerprint and training a ma-chine learning model on it, then using it for predicting the location based on the