Zobrazeno 1 - 10
of 117
pro vyhledávání: '"Khalid Zine-dine"'
Publikováno v:
IEEE Access, Vol 12, Pp 158854-158865 (2024)
Cloud computing is a critical component in the success of 5G and 6G networks, particularly given the computation-intensive nature of emerging applications. Despite all it advantages, cloud computing faces limitations in meeting the strict latency and
Externí odkaz:
https://doaj.org/article/65ebd04a18404ca5ae5ef7e26c0b2494
Publikováno v:
IEEE Access, Vol 10, Pp 69264-69302 (2022)
With the increasing stringent QoS constraints (e.g., latency, bandwidth, jitter) imposed by novel applications (e.g., e-Health, autonomous vehicles, smart cities, etc.), as well as the rapidly increasing number of connected IoT (Internet of Things) d
Externí odkaz:
https://doaj.org/article/d6949e0de0df4e8897e648da1b483f82
Publikováno v:
Energy Reports, Vol 6, Iss , Pp 288-293 (2020)
The integration of Combined Heat and Power (CHP) systems, especially fuel cell systems, into buildings have attracted a lot of interest these last years. It is due to their higher efficiency, cleanliness and their capability for producing both valuab
Externí odkaz:
https://doaj.org/article/3fecab15a4bb474aad01270d40ac8a82
Publikováno v:
Applied Sciences, Vol 11, Iss 22, p 10981 (2021)
Increases in power demand and consumption are very noticeable. This increase presents a number of challenges to the traditional grid systems. Thus, there is the need to come up with a new solution that copes with the stringent demand on energy and pr
Externí odkaz:
https://doaj.org/article/5cde14527d274273a4f513a76db8ecaa
Publikováno v:
International Journal of Information Security and Privacy. 16:1-16
Recently, Deep Neural Networks have shown great deal of reliability and applicability as its applications spread in different areas. This paper proposes a cryptanalysis model based on Deep Neural Network, the neural network takes in plaintexts and th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::714add8ae3a77c22dcb850d025048b59
https://doi.org/10.4018/ijisp.300325
https://doi.org/10.4018/ijisp.300325
Autor:
Abdellatif Elmouatamid, Radouane Ouladsine, Mohamed Bakhouya, Najib El Kamoun, Mohammed Khaidar, Khalid Zine-Dine
Publikováno v:
Energies, Vol 14, Iss 1, p 168 (2020)
The demand for electricity is increased due to the development of the industry, the electrification of transport, the rise of household demand, and the increase in demand for digitally connected devices and air conditioning systems. For that, solutio
Externí odkaz:
https://doaj.org/article/cbdf5661896242028d9a43cbf9c8229f
Autor:
Sofia Boulmrharj, Youssef NaitMalek, Abdellatif Elmouatamid, Mohamed Bakhouya, Radouane Ouladsine, Khalid Zine-Dine, Mohammed Khaidar, Mostapha Siniti
Publikováno v:
Energies, Vol 12, Iss 7, p 1305 (2019)
Micro-Grid (MG) systems have been extensively studied and deployed to lower the power consumption while reducing the greenhouse gas emissions. Although, the challenge with Renewable Energy Sources (RES) is their uncertain and intermittent nature, thi
Externí odkaz:
https://doaj.org/article/e49bb2cb160f4fdca068f4dbc00b7c90
Publikováno v:
Advances in Science, Technology and Engineering Systems Journal. 5:1598-1608
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4a2e9348b5122ef7cef3d57387cbfeaa
https://doi.org/10.25046/aj0506191
https://doi.org/10.25046/aj0506191
Publikováno v:
Advances in Science, Technology and Engineering Systems Journal. 5:419-431
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9fd7679484da49f170fd415417134998
https://doi.org/10.25046/aj050353
https://doi.org/10.25046/aj050353
Publikováno v:
Sn Computer Science
In this paper, we are interested to forecast and predict the time evolution of the Covid-19 in Morocco based on two different time series forecasting models. We used Auto-Regressive Integrated Moving Average (ARIMA) and Long short-term memory (LSTM)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6825328aedac0c80d6ba27d773d697e1
https://doi.org/10.1007/s42979-022-01019-x
https://doi.org/10.1007/s42979-022-01019-x