Zobrazeno 1 - 10
of 38
pro vyhledávání: '"Safaa O. Al-Mamory"'
Autor:
zahraa ali, Safaa O. Al-mamory
Publikováno v:
Iraqi Journal for Computers and Informatics, Vol 50, Iss 1, Pp 34-45 (2024)
Researchers' interests and academic journals are crucial for advancing scientific inquiry. Journals serve as platforms for sharing and validating discoveries, fostering a symbiotic relationship that advances our collective understanding and pushes th
Externí odkaz:
https://doaj.org/article/31e8d2db9c8c470ea1ca69f7986f384b
Publikováno v:
ARO-The Scientific Journal of Koya University, Vol 12, Iss 2 (2024)
Flexible job shop scheduling problem (FJSSP) is a complex and challenging problem that plays a crucial role in industrial and manufacturing production. FJSSP is an expansion of the standard job shop scheduling problem (JSSP). One of FJSSP’s objecti
Externí odkaz:
https://doaj.org/article/239ffb1c5f284a29ac136fdf7bf60b39
Publikováno v:
IET Networks, Vol 12, Iss 5, Pp 197-228 (2023)
Abstract Within Edge and Fog computing, edge and fog nodes must be optimally located at the network edge to minimise the network's overall latency. This survey addresses all aspects of these nodes' placement problems. Literature on edge and fog nodes
Externí odkaz:
https://doaj.org/article/75011f5fab63420ca1025d7e1d1311cc
Autor:
Raad Al-azawi, Safaa O. AL-mamory
Publikováno v:
Inteligencia Artificial, Vol 25, Iss 69 (2022)
Abstract Automated or semiautomated computer programs that imitate humans and/or human behavior in online social networks are known as social bots. Users can be attacked by social bots to achieve several hidden aims, such as spreading information or
Externí odkaz:
https://doaj.org/article/b41bb42c5ae6440da1447e62cee6488c
Autor:
Safaa O. Al-mamory
Publikováno v:
Inteligencia Artificial, Vol 22, Iss 64 (2019)
Classification algorithms' performance could be enhanced by selecting many representative points to be included in the training sample. In this paper, a new border and rare biased sampling (BRBS) scheme is proposed by assigning each point in the data
Externí odkaz:
https://doaj.org/article/025121df6a554f9582802d7be923f24a
Autor:
Safaa O. Al-Mamory, Israa S. Kamil
Publikováno v:
Materials Today: Proceedings. 80:2625-2630
Density-Based clustering are the main clustering algorithms because they can cluster data with different shapes and densities, but some of these algorithms have high time complexity like OPTICS (Ordering Points to Identify Clustering Structure) and D
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bf232903040da43f84cecd75e0fd0dea
https://doi.org/10.1016/j.matpr.2021.06.441
https://doi.org/10.1016/j.matpr.2021.06.441
Publikováno v:
Webology. 19:341-366
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d3d8b331e2bbca92c6c068596b7112de
https://doi.org/10.14704/web/v19i1/web19026
https://doi.org/10.14704/web/v19i1/web19026
Autor:
Israa S. Kamil, Safaa O. Al-Mamory
Publikováno v:
Malaysian Journal of Computer Science. 32:315-327
DBSCAN is one of the efficient density-based clustering algorithms. It is characterized by its ability to discover clusters with different shapes and sizes, and to separate noise and outliers. However, when the dataset contain different densities, DB
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fd25d12784a0b5df0ed6430f01b8d367
https://doi.org/10.22452/mjcs.vol32no4.5
https://doi.org/10.22452/mjcs.vol32no4.5
Autor:
Abbas M. Al-Bakry, Mouayad A. Sahib, Safaa O. Al-Mamory, Jaafar A. Aldhaibani, Ali N. Al-Shuwaili, Haitham S. Hasan, Rula A. Hamid, Ali K. Idrees
This book constitutes the refereed proceedings of the 7th National Conference on New Trends in Information and Communications Technology Applications, NTICT 2023, held in Baghdad, Iraq, during December 20–21, 2023. The 28 full papers included in th
Publikováno v:
Communications in Computer and Information Science ISBN: 9783030934163
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5eb7a2158b8c9898ec26f2b33e893850
https://doi.org/10.1007/978-3-030-93417-0_12
https://doi.org/10.1007/978-3-030-93417-0_12