2017
DOI: 10.1016/j.neucom.2016.05.105
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A multi-modal architecture for non-intrusive analysis of performance in the workplace

Abstract: Human performance, in all its di erent dimensions, is a very complex and interesting topic. In this paper we focus on performance in the workplace which, asides from complex is often controversial. While organizations and generally competitive working conditions push workers into increasing performance demands, this does not necessarily correlates positively to productivity. Moreover, existing performance monitoring approaches (electronic or not) are often dreaded by workers since they either threat their priv… Show more

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Cited by 10 publications
(2 citation statements)
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“…Data collection was carried out using a logger application developed in previous work [33,34] . The data collected by the logger application, characterizing the students' interaction patterns, is aggregated in a server to which the logger application connects after the student logs in.…”
Section: Methodsmentioning
confidence: 99%
“…Data collection was carried out using a logger application developed in previous work [33,34] . The data collected by the logger application, characterizing the students' interaction patterns, is aggregated in a server to which the logger application connects after the student logs in.…”
Section: Methodsmentioning
confidence: 99%
“…In the case of regression, the value to be predicted by the program follows a continuous spectrum and allows answering questions such as “how many are there” or “how much does it cost” . Decision trees (DTs), SVMs, and ANNs are some models present in this type of learning. ANNs, one of the models most used in the simulation and prediction of the performance of biological treatment in WWTP, use models composed of several artificial neurons, connected by links of variable weight, to form black box representations of pseudoneurological systems . Each neuron receives input signals from other neurons, processes them, and sends out the output, which in turn is passed on as input to subsequent neurons .…”
Section: Wastewater Treatment Modeling Using Machine Learningmentioning
confidence: 99%