Zobrazeno 1 - 10 of 25 pro vyhledávání: '"Ammar ElHassan"'
1
Akademický článek
An optimal control model for Covid-19 spread with impacts of vaccination and facemask
Autor: Ammar ElHassan, Yousef AbuHour, Ashraf Ahmad
Publikováno v: Heliyon, Vol 9, Iss 9, Pp e19848- (2023)
A non-linear system of differential equations was used to explain the spread of the COVID-19 virus and a SEIQR model was developed and tested to provide insights into the spread of the pandemic. This article, which is related to the aforementioned wo
Externí odkaz: https://doaj.org/article/c1113a2017114d749921f8a418312614
Zobrazit plný text záznamu
2
Akademický článek
ILA4: Overcoming missing values in machine learning datasets – An inductive learning approach
Autor: Ammar Elhassan, Saleh M. Abu-Soud, Firas Alghanim, Walid Salameh
Publikováno v: Journal of King Saud University: Computer and Information Sciences, Vol 34, Iss 7, Pp 4284-4295 (2022)
This article introduces ILA4: A new algorithm designed to handle datasets with missing values. ILA4 is inspired by a series of ILA algorithms which also handle missing data with further enhancements. ILA4 is applied to datasets with varying completen
Externí odkaz: https://doaj.org/article/00f335c13fd242b2b36a0618cc47021e
Zobrazit plný text záznamu
3
Akademický článek
DFT-MF: Enhanced deepfake detection using mouth movement and transfer learning
Autor: Ammar Elhassan, Mohammad Al-Fawa'reh, Mousa Tayseer Jafar, Mohammad Ababneh, Shifaa Tayseer Jafar
Publikováno v: SoftwareX, Vol 19, Iss , Pp 101115- (2022)
Deepfake technology presents serious cybersecurity challenges that have become more prevalent with the availability of easily accessible applications. An effective method for detection and prevention of this is necessary. This paper introduces a robu
Externí odkaz: https://doaj.org/article/4427a5f38a23479f8d9f990c93002a2a
Zobrazit plný text záznamu
5
ILA4: Overcoming missing values in machine learning datasets – An inductive learning approach
Autor: Firas Alghanim, Saleh M. Abu-Soud, Walid A. Salameh, Ammar Elhassan
Publikováno v: Journal of King Saud University - Computer and Information Sciences. 34:4284-4295
This article introduces ILA4: A new algorithm designed to handle datasets with missing values. ILA4 is inspired by a series of ILA algorithms which also handle missing data with further enhancements. ILA4 is applied to datasets with varying completen
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d7bf7b1f54f0dc5a4a3fbddc8172ee6b
https://doi.org/10.1016/j.jksuci.2021.02.011
Zobrazit plný text záznamu
6
Business Intelligence Framework Design and Implementation: A Real-estate Market Case Study
Autor: Maisa Asasfeh, Walid A. Salameh, Bushra Abu Tahoun, Ammar Elhassan, Salam Fraihat
Publikováno v: Journal of Data and Information Quality. 13:1-16
This article builds on previous work in the area of real-world applications of Business Intelligence (BI) technology. It illustrates the analysis, modeling, and framework design of a BI solution with high data quality to provide reliable analytics an
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::506e48ad04db2d3952ab904ba474c255
https://doi.org/10.1145/3422669
Zobrazit plný text záznamu
7
A novel possibilistic artificial immune-based classifier for course learning outcome enhancement
Autor: Ammar Elhassan, Ghassen Ben Brahim, Ilyes Jenhani
Publikováno v: Knowledge and Information Systems. 62:3535-3563
In this paper, we propose PAIRS3: a possibilistic classification approach based on artificial immune recognition system (AIRS) and the possibility theory. PAIRS3 is applied to address shortcomings in student attainment rates of course learning outcom
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::57c4163d4914480b9bfdc3da88871f3c
https://doi.org/10.1007/s10115-020-01465-0
Zobrazit plný text záznamu
10
Malware Detection by Eating a Whole APK
Autor: Mohammad Al-Fawa'reh, Mousa Tayseer Jafar, Ammar Elhassan, Amal Saif
Publikováno v: ICITST
As Android is one of the most popular and widely used open-source mobile platforms, the security and privacy of Android apps are very critical, especially that over 6000 apps are added to the Google Play Store every day. This makes Android a prime ta
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::c58f38022533ccbf7550fa9023a039ea
https://doi.org/10.23919/icitst51030.2020.9351333
Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání

Omezení vyhledávání
Plný text Recenzováno Digitální knihovna AV ČR
Zdroje