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TitleNon-intrusive quantification of performance and its relationship to mood
Author(s)Carneiro, Davide Rua
Pimenta, André
Neves, José
Novais, Paulo
KeywordsWorker Performance
Statistical Analysis
Distributed Intelligence
Issue date2017
JournalSoft Computing
CitationCarneiro D., Pimenta A., Neves J., Novais P., Non-intrusive Quantification of Performance and its Relationship to Mood, Soft Computing, Springer, ISSN: 1432-7643, vol. 21, Issue nº 17, pp 4917-4923, 2017.
Abstract(s)The number of jobs that takes place entirely or partially in a computer is nowadays very signi cant. These workplaces, as many others, often o er the key ingredients for the emergence of stress and the performance drop of its long-term e ects: long hours sitting, sustained cognitive e ort, pressure from competitiveness, among others. This has a toll on productivity and work quality, with signi cant costs for both organizations and workers. Moreover, a tired workforce is generally more susceptible to negative feelings and mood, which results in a negative environment. This paper contributes to the current need for the development of non-intrusive methods for monitoring and managing worker performance in real time. We propose a framework that assesses worker performance and a case study in which this approach was validated. We also show the relationship between performance and mood.
AccessOpen access
Appears in Collections:CAlg - Artigos em revistas internacionais/Papers in international journals

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