Zobrazeno 1 - 10
of 277
pro vyhledávání: '"Norman W Paton"'
Autor:
Darren M Soanes, Intikhab Alam, Mike Cornell, Han Min Wong, Cornelia Hedeler, Norman W Paton, Magnus Rattray, Simon J Hubbard, Stephen G Oliver, Nicholas J Talbot
Publikováno v:
PLoS ONE, Vol 3, Iss 6, p e2300 (2008)
Fungi and oomycetes are the causal agents of many of the most serious diseases of plants. Here we report a detailed comparative analysis of the genome sequences of thirty-six species of fungi and oomycetes, including seven plant pathogenic species, t
Externí odkaz:
https://doaj.org/article/98ccfbf7a8454b6186f18a9a48f9776f
Autor:
Nikolaos Konstantinou, Edward Abel, Luigi Bellomarini, Alex Bogatu, Cristina Civili, Endri Irfanie, Martin Koehler, Lacramioara Mazilu, Emanuel Sallinger, Alvaro A. A. Fernandes, Georg Gottlob, John A. Keane, Norman W. Paton
Publikováno v:
Journal of Big Data, Vol 6, Iss 1, Pp 1-32 (2019)
Abstract Background Data scientists spend considerable amounts of time preparing data for analysis. Data preparation is labour intensive because the data scientist typically takes fine grained control over each aspect of each step in the process, mot
Externí odkaz:
https://doaj.org/article/5c4d22d6e26a4c9cb3649b742d929700
Publikováno v:
Journal of Data and Information Quality. 14:1-26
Machine learning can be applied in applications that take decisions that impact people’s lives. Such techniques have the potential to make decision making more objective, but there also is a risk that the decisions can discriminate against certain
Autor:
Abdelkhalik Mosa, Norman W. Paton
Publikováno v:
Journal of Cloud Computing: Advances, Systems and Applications, Vol 5, Iss 1, Pp 1-17 (2016)
Abstract Cloud computing provides on-demand access to a shared pool of computing resources, which enables organizations to outsource their IT infrastructure. Cloud providers are building data centers to handle the continuous increase in cloud users
Externí odkaz:
https://doaj.org/article/71f90f8085f34d93ab3ac0971fcc7993
Publikováno v:
2023 IEEE 17th International Conference on Semantic Computing (ICSC).
Publikováno v:
Hummaida, A R, Paton, N W & Sakellariou, R 2023, ' A hierarchical decentralized architecture to enable adaptive scalable virtual machine migration ', Concurrency and Computation: Practice and Experience, vol. 35, no. 2, e7487 . https://doi.org/10.1002/cpe.7487
Cloud computing is an established paradigm for end users to access resources. Cloud infrastructure providers seek to maximize accepted requests, meet Service Level Agreements (SLAs), and reduce operational costs by dynamically allocating Virtual Mach
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7bea562177c2ea15fdaf9a7a45d1ecbe
https://research.manchester.ac.uk/en/publications/fac7eab6-6317-4cb6-81ef-b70b9791f99d
https://research.manchester.ac.uk/en/publications/fac7eab6-6317-4cb6-81ef-b70b9791f99d
Publikováno v:
Hummaida, A R, Paton, N W & Sakellariou, R 2022, ' Scalable Virtual Machine Migration using Reinforcement Learning ', Journal of Grid Computing, vol. 20, no. 2 . https://doi.org/10.1007/s10723-022-09603-4
Heuristic approaches require fixed knowledge of how resource allocation should be carried out, and this can be limiting when managing variable cloud workloads. Solutions based on Reinforcement Learning (RL) have been presented to manage cloud infrast
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e4d40178c564c028cd3fa18ff85986a9
https://pure.manchester.ac.uk/ws/files/231290406/Scalable_Virtual_Machine_Migration_using_Reinforcement_Learning.pdf
https://pure.manchester.ac.uk/ws/files/231290406/Scalable_Virtual_Machine_Migration_using_Reinforcement_Learning.pdf
Autor:
Alvaro A. A. Fernandes, Norman W. Paton, Martin Koehler, Alex Bogatu, Edward Abel, Leonid Libkin, John A. Keane, Nikolaos Konstantinou, Lacramioara Mazilu, Cristina Civili
Publikováno v:
Koehler, M, Abel, E, Bogatu, A, Civili, C, Mazilu, L, Konstantinou, N, Fernandes, A A A, Keane, J, Libkin, L & Paton, N W 2021, ' Incorporating Data Context to Cost-Effectively Automate End-to-End Data Wrangling ', IEEE Transactions on Big Data, vol. 7, no. 1, pp. 169-186 . https://doi.org/10.1109/TBDATA.2019.2907588
Koehler, M, Abel, E, Bogatu, A, Civili, C, Mazilu, L, Konstantinou, N, Fernandes, A, Keane, J, Libkin, L & Paton, N 2019, ' Incorporating Data Context to Cost-Effectively Automate End-to-End Data Wrangling ', IEEE Transactions on Big Data, vol. 0, no. 0, pp. 1-1 . https://doi.org/10.1109/TBDATA.2019.2907588
Koehler, M, Abel, E, Bogatu, A, Civili, C, Mazilu, L, Konstantinou, N, Fernandes, A, Keane, J, Libkin, L & Paton, N 2019, ' Incorporating Data Context to Cost-Effectively Automate End-to-End Data Wrangling ', IEEE Transactions on Big Data, vol. 0, no. 0, pp. 1-1 . https://doi.org/10.1109/TBDATA.2019.2907588
The process of preparing potentially large and complex data sets for further analysis or manual examination is often called data wrangling. In classical warehousing environments, the steps in such a process are carried out using Extract-Transform-Loa
Publikováno v:
Service-Oriented and Cloud Computing ISBN: 9783031047176
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::191009bf6c681bae480c8213bac95fed
https://doi.org/10.1007/978-3-031-04718-3_2
https://doi.org/10.1007/978-3-031-04718-3_2
Autor:
Raúl García-Castro, Kostis Kyzirakos, Asunción Gómez-Pérez, Manolis Koubarakis, David De Roure, Kirk Martinez, Oscar Corcho, Alvaro A. A. Fernandes, Alex Frazer, Ixent Galpin, Kevin Page, Jean-Paul Calbimonte, Manos Karpathiotakis, Norman W. Paton, Oles Kit, Jason Sadler, Alasdair J. G. Gray
Publikováno v:
Sensors, Vol 11, Iss 9, Pp 8855-8887 (2011)
Sensing devices are increasingly being deployed to monitor the physical world around us. One class of application for which sensor data is pertinent is environmental decision support systems, e.g., flood emergency response. For these applications, th
Externí odkaz:
https://doaj.org/article/10b4f85eb38e482daf096eded836f8a4