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dc.contributor.authorYap, Moi Hoon*
dc.contributor.authorUgail, Hassan*
dc.contributor.authorZwiggelaar, R.*
dc.date.accessioned2016-04-22T13:43:30Z
dc.date.available2016-04-22T13:43:30Z
dc.date.issued2014-02-05
dc.identifier.citationYap MH, Ugail H and Zwiggelaar R (2014) Facial Behavioral Analysis: A Case Study in Deception Detection. British Journal of Applied Science and Technology. 4(10): 1485-1496.en_US
dc.identifier.urihttp://hdl.handle.net/10454/8168
dc.descriptionYesen_US
dc.description.abstractThe objective of every wind energy producer is to reduce operational costs associated to the production as a way to increase profits. One other issue that must be looked carefully is the equipment maintenance. Increase the availability of wind turbines by reducing the downtime associated to failures is a good strategy to achieve the main goal of increase profits. As a way to help in the definition of the best maintenance strategies, condition monitoring systems (CMS) have an important role to play. Informatics tools to make the condition monitoring of the wind turbines were developed and are now being installed as a way to help producers reducing the operational costs. There are a lot of developed systems to do the monitoring of a wind turbine or the whole wind park, in this paper will be made an overview of the most important systems.en_US
dc.language.isoenen_US
dc.relation.isreferencedbyhttp://dx.doi.org/10.9734/BJAST/2014/6369en_US
dc.rights© 2014 Yap et al. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.en_US
dc.subjectFacial behavioural analysis; Deception; FACS coding; Machine learning; Classification.en_US
dc.titleFacial Behavioral Analysis: A Case Study in Deception Detectionen_US
dc.status.refereedYesen_US
dc.date.Accepted2013-11-11
dc.typeArticleen_US
dc.type.versionpublished version paperen_US
refterms.dateFOA2018-07-25T13:58:09Z


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