Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Saleh Ghanem"'
Publikováno v:
Insects, Vol 12, Iss 10, p 863 (2021)
There are multiple feedback mechanisms involved in appetite regulation, which is an integral part of maintaining energetic homeostasis. Older forager honey bees, in comparison to newly emerged bees and nurse bees, are known to have highly fluctuating
Externí odkaz:
https://doaj.org/article/e6d9b53dd52b4d0d951e4c97d20622c0
Publikováno v:
Insects
Insects, Vol 12, Iss 863, p 863 (2021)
Volume 12
Issue 10
Insects, Vol 12, Iss 863, p 863 (2021)
Volume 12
Issue 10
Simple Summary Appetite regulation is an important function necessary to maintain energetic balance, but how honey bees accomplish this could vary as they age because they go through a number of behavioral and physiological changes during development
Autor:
Hamad Ameer Alkhal, Amal Saleh Ghanem
Publikováno v:
2018 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT).
The recent advances in cloud computing have been widely used in different domains and highly employed for designing cloud-based solutions in healthcare. With the could-based solutions, services can be accessed by patients from anywhere using their ow
Autor:
Hadeel Alobaidy, Amal Saleh Ghanem
Publikováno v:
2018 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT).
This paper proposes an approach to address the common problem of classification from educational dataset with irrelevant or redundant attributes. In particular, the paper focuses on using this approach to improve academic advising through intelligent
Publikováno v:
ICPR
The majority of multi-class pattern classification techniques are proposed for learning from balanced datasets. However, in several real-world domains, the datasets have imbalanced data distribution, where some classes of data may have few training e
Publikováno v:
AI 2009: Advances in Artificial Intelligence ISBN: 9783642104381
Australasian Conference on Artificial Intelligence
Australasian Conference on Artificial Intelligence
Real-world data are often stored as relational database systems with different numbers of significant attributes. Unfortunately, most classification techniques are proposed for learning from balanced non-relational data and mainly for classifying one
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b6d85270ac5f6ba7a8e086f54a2dc983
https://doi.org/10.1007/978-3-642-10439-8_23
https://doi.org/10.1007/978-3-642-10439-8_23
Publikováno v:
Scopus-Elsevier
ICPR
ICPR
Traditional learning techniques learn from flat data files with the assumption that each class has a similar number of examples. However, the majority of real-world data are stored as relational systems with imbalanced data distribution, where one cl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8210d7fdc65455b1f3359fc36690238e
http://www.scopus.com/inward/record.url?eid=2-s2.0-77957947784&partnerID=MN8TOARS
http://www.scopus.com/inward/record.url?eid=2-s2.0-77957947784&partnerID=MN8TOARS