Zobrazeno 1 - 10
of 138
pro vyhledávání: '"M. Hayajneh"'
Autor:
Feras Alasali, Ali M. Hayajneh, Salah Abu Ghalyon, Naser El‐Naily, Anas AlMajali, Awni Itradat, William Holderbaume, Eyad Zaroure
Publikováno v:
IET Renewable Power Generation, Vol 18, Iss 5, Pp 837-862 (2024)
Abstract Recently, smart grids introduce significant challenges to power system protection due to the high integration with distributed energy resources (DERs) and communication systems. To effectively manage the impact of DERs on power networks, res
Externí odkaz:
https://doaj.org/article/687ee8bbc0044c689a7c9917171d16c7
Autor:
Ali M. Hayajneh, Sami A. Aldalahmeh, Feras Alasali, Haitham Al‐Obiedollah, Sayed Ali Zaidi, Des McLernon
Publikováno v:
IET Smart Cities, Vol 6, Iss 1, Pp 10-26 (2024)
Abstract Emerging technologies are continually redefining the paradigms of smart farming and opening up avenues for more precise and informed farming practices. A tiny machine learning (TinyML)‐based framework is proposed for unmanned aerial vehicl
Externí odkaz:
https://doaj.org/article/9ac18057c05f47978544f47a2dbc75e0
Publikováno v:
IEEE Open Journal of the Communications Society, Vol 5, Pp 1656-1672 (2024)
Tiny machine learning (TinyML) is a promising approach to enable intelligent applications relying on Human Activity Recognition (HAR) on resource-limited and low-power Internet of Things (IoT) edge devices. However, designing efficient TinyML models
Externí odkaz:
https://doaj.org/article/882f843ff02944dd94bdaabec6468adc
Publikováno v:
IEEE Access, Vol 12, Pp 10846-10864 (2024)
The advancement of sustainable energy sources necessitates the development of robust forecasting tools for efficient energy management. A prominent player in this domain, solar power, heavily relies on accurate energy yield predictions to optimize pr
Externí odkaz:
https://doaj.org/article/9f52c90469b44685aa6fe6be1c04aa39
Publikováno v:
AgriEngineering, Vol 5, Iss 4, Pp 2266-2283 (2023)
Machine learning (ML) within the edge internet of things (IoT) is instrumental in making significant shifts in various industrial domains, including smart farming. To increase the efficiency of farming operations and ensure ML accessibility for both
Externí odkaz:
https://doaj.org/article/c9cccec0b10d4956b624d5e478b69282
Autor:
Feras Alasali, Awni Itradat, Salah Abu Ghalyon, Mohammad Abudayyeh, Naser El-Naily, Ali M. Hayajneh, Anas AlMajali
Publikováno v:
Smart Cities, Vol 7, Iss 1, Pp 51-77 (2023)
In recent years, the integration of Distributed Energy Resources (DERs) and communication networks has presented significant challenges to power system control and protection, primarily as a result of the emergence of smart grids and cyber threats. A
Externí odkaz:
https://doaj.org/article/918e716e60404925b51566fadd47c5ad
Autor:
Abdelaziz Salama, Achilleas Stergioulis, Ali M. Hayajneh, Syed Ali Raza Zaidi, Des McLernon, Ian Robertson
Publikováno v:
IEEE Access, Vol 11, Pp 18326-18342 (2023)
Federated Learning (FL) presents a mechanism to allow decentralized training for machine learning (ML) models inherently enabling privacy preservation. The classical FL is implemented as a client-server system, which is known as Centralised Federated
Externí odkaz:
https://doaj.org/article/ddd541a5522e40d5915c76004ecfd2ab
Publikováno v:
Tropical Animal Science Journal, Vol 46, Iss 2 (2023)
This study aimed at evaluating the response to supplementation of β-Mannanase with two levels of energy on performance, carcass yield, and meat quality of 1600 1-d-old straight run Indian River broilers which were randomly allotted to 4 dietary trea
Externí odkaz:
https://doaj.org/article/84fdcce391484d11bd2c51aed36a216a
Publikováno v:
IEEE Access, Vol 10, Pp 100867-100877 (2022)
Machine Learning (ML) on the edge is key to enabling a new breed of IoT and autonomous system applications. The departure from the traditional cloud-centric architecture means that new deployments can be more power-efficient, provide better privacy a
Externí odkaz:
https://doaj.org/article/9d6644ef22db4537a228c1f19041729a
Autor:
Suhaib M. Hayajneh, Jamal Naser
Publikováno v:
Fluids, Vol 8, Iss 5, p 140 (2023)
The purpose of this paper is to investigate the fire performance in a multi-storey cross-laminated timber (CLT) structure by the computational fluid dynamics (CFD) technique using the Fire Dynamics Simulator (FDS v.6.7). The study investigates fire t
Externí odkaz:
https://doaj.org/article/cff8b05d8da4485c97b4b4223c03d225