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http://bura.brunel.ac.uk/handle/2438/29547
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DC Field | Value | Language |
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dc.contributor.author | Groen, D | - |
dc.contributor.author | Khullar, S | - |
dc.contributor.author | Groen-Xu, M | - |
dc.contributor.author | Neykova, R | - |
dc.contributor.editor | Franco, L | - |
dc.contributor.editor | de Mulatier, C | - |
dc.contributor.editor | Paszynski, M | - |
dc.contributor.editor | Krzhizhanovskaya, VV | - |
dc.contributor.editor | Dongarra, JJ | - |
dc.contributor.editor | Sloot, PMA | - |
dc.date.accessioned | 2024-08-13T15:50:53Z | - |
dc.date.available | 2024-08-13T15:50:53Z | - |
dc.date.issued | 2024-06-29 | - |
dc.identifier | ORCiD: Derek Groen https://orcid.org/0000-0001-7463-3765 | - |
dc.identifier | ORCiD: Rumyana Neykova https://orcid.org/0000-0002-2755-7728 | - |
dc.identifier | 30 | - |
dc.identifier.citation | Groen, D. et al. (2024) 'A Working Week Simulation Approach to Forecast Personal Well-Being', in Franco, L. et al. (eds.) Computational Science – ICCS 2024. ICCS 2024: 24th International Conference, Malaga, Spain, July 2–4, 2024, Proceedings, Part III. (14834 LNCS) Cham: Springer Nature, pp. 246 - 253. doi: 10.1007/978-3-031-63759-9_30. | en_US |
dc.identifier.isbn | 978-3-031-63758-2 (pbk) | - |
dc.identifier.isbn | 978-3-031-63759-9 (ebk) | - |
dc.identifier.issn | 0302-9743 | - |
dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/29547 | - |
dc.description.abstract | Billions of people work every week. Forecasting which tasks gets done in a working week is important because it could help workers understand (i) whether their workload is manageable and (ii) which task scheduling approach helps to maximize the amount of work done and/or minimize the negative consequences of unfinished work. Here we present a working week simulation prototype, R2, and showcase how it can be used to forecast the working week for three archetypical workers. We show that R2 forecasts are sensitive to different task loads, task scheduling strategies and different levels of emerging work complications. We also highlight how R2 supports a new type of validation setting, namely that of user self-validation, and discuss the advantages and drawbacks of this new validation approach. We provide R2 as an online platform to allow users to create their own worker profile and task lists, and believe the tool could serve as a starting point for more in-depth research efforts on user-centric working week modelling. | en_US |
dc.format.extent | 246 - 253 | - |
dc.format.medium | Print-Electronic | - |
dc.language | English | - |
dc.language.iso | en_US | en_US |
dc.publisher | Springer Nature | en_US |
dc.relation.ispartofseries | Lecture Notes in Computer Science;vol 14834 | - |
dc.rights | Copyright © 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG. This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/978-3-031-63759-9_30 (see: https://www.springernature.com/gp/open-science/policies/book-policies). | - |
dc.rights.uri | https://www.springernature.com/gp/open-science/policies/book-policies | - |
dc.subject | simulation | en_US |
dc.subject | task management | en_US |
dc.subject | working week | en_US |
dc.subject | simulation development approach | en_US |
dc.title | A Working Week Simulation Approach to Forecast Personal Well-Being | en_US |
dc.type | Conference Paper | en_US |
dc.date.dateAccepted | 2024-04-01 | - |
dc.identifier.doi | https://doi.org/10.1007/978-3-031-63759-9_30 | - |
dc.relation.isPartOf | Computational Science – ICCS 2024. ICCS 2024 | - |
pubs.place-of-publication | Cham | - |
pubs.publication-status | Published | - |
pubs.volume | 14834 LNCS | - |
dc.identifier.eissn | 1611-3349 | - |
dc.rights.holder | The Author(s), under exclusive license to Springer Nature Switzerland AG | - |
Appears in Collections: | Dept of Computer Science Embargoed Research Papers |
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FullText.pdf | Embargoed until 29 June 2025 | 446.78 kB | Adobe PDF | View/Open |
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