Zobrazeno 1 - 10
of 86
pro vyhledávání: '"Feras A. Batarseh"'
Publikováno v:
Water Practice and Technology, Vol 18, Iss 12, Pp 3399-3418 (2023)
This manuscript presents a novel state-of-the-art cyber-physical water testbed, namely the AI and Cyber for Water and Agriculture testbed (ACWA). ACWA is motivated by the aim to advance water resources' management using AI and cybersecurity experimen
Externí odkaz:
https://doaj.org/article/253b9b04df14412cbc6b6500eca12a95
Publikováno v:
Data & Policy, Vol 6 (2024)
Precision healthcare is an emerging field of science that utilizes an individual’s health information, context, and genetics to provide more personalized diagnostics and treatments. In this manuscript, we leverage that concept and present a group o
Externí odkaz:
https://doaj.org/article/d8349e05854b4e839cd268ad75ad90a8
Publikováno v:
Frontiers in Water, Vol 5 (2023)
Flood events have the potential to impact every aspect of life, economic loss and casualties can quickly be coupled with damages to agricultural land, infrastructure, and water quality. Creating flood susceptibility maps is an effective manner that e
Externí odkaz:
https://doaj.org/article/8345b3d4e0f2472297cf9f13a2b6556d
Publikováno v:
Frontiers in Artificial Intelligence, Vol 6 (2023)
Recent advances in deep learning have improved the performance of many Natural Language Processing (NLP) tasks such as translation, question-answering, and text classification. However, this improvement comes at the expense of model explainability. B
Externí odkaz:
https://doaj.org/article/2a5ae2ba3cf24cd28c52398fc232bd8e
Publikováno v:
Journal of Big Data, Vol 8, Iss 1, Pp 1-30 (2021)
Abstract Artificial Intelligence (AI) algorithms are increasingly providing decision making and operational support across multiple domains. AI includes a wide (and growing) library of algorithms that could be applied for different problems. One impo
Externí odkaz:
https://doaj.org/article/70ef07f53cda44c7bed3084532268a3f
Publikováno v:
Journal of Big Data, Vol 7, Iss 1, Pp 1-25 (2020)
Abstract Data-driven healthcare policy discussions are gaining traction after the Covid-19 outbreak and ahead of the 2020 US presidential elections. The US has a hybrid healthcare structure; it is a system that does not provide universal coverage, al
Externí odkaz:
https://doaj.org/article/b1b510e1ea1f4b31852ca123f28541be
Publikováno v:
Machine Learning with Applications, Vol 5, Iss , Pp 100046- (2021)
International economics has a long history of improving our understanding of factors causing trade, and the consequences of free flow of goods and services across countries. The recent shocks to the free-trade regime, especially trade disputes among
Externí odkaz:
https://doaj.org/article/26464e8b41f14a82b5f2437d6b409072
Publikováno v:
Data & Policy, Vol 3 (2021)
The quality of service in healthcare is constantly challenged by outlier events such as pandemics (i.e., Covid-19) and natural disasters (such as hurricanes and earthquakes). In most cases, such events lead to critical uncertainties in decision-makin
Externí odkaz:
https://doaj.org/article/3237332f19d84adeaa84b979b5b62ca5
Publikováno v:
Data & Policy, Vol 3 (2021)
Focusing on seven major agricultural commodities with a long history of trade, this study employs data-driven analytics to decipher patterns of trade, namely using supervised machine learning (ML), as well as neural networks. The supervised ML and ne
Externí odkaz:
https://doaj.org/article/d95eb65bc7624742af12d1e5b81da55a
Publikováno v:
Social Sciences, Vol 10, Iss 9, p 322 (2021)
The wide scale adoption of Artificial Intelligence (AI) will require that AI engineers and developers can provide assurances to the user base that an algorithm will perform as intended and without failure. Assurance is the safety valve for reliable,
Externí odkaz:
https://doaj.org/article/e75970e6cca840f5ab94629bedf11c4e