Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/31228
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dc.contributor.authorLEMMENS, Marijn-
dc.contributor.authorDe Raedt, W-
dc.contributor.authorGRIETEN, Lars-
dc.contributor.authorTHOELEN, Ronald-
dc.date.accessioned2020-05-27T08:53:42Z-
dc.date.available2020-05-27T08:53:42Z-
dc.date.issued2019-
dc.date.submitted2020-04-20T19:23:26Z-
dc.identifier.citationEngineering of Functional Interfaces (EnFi 2019), Leuven, Belgium, 8 - 9 July 2019-
dc.identifier.urihttp://hdl.handle.net/1942/31228-
dc.description.abstractAt this very moment we find ourselves in the age of sensor technology, every device has an uplink to some kind of cloud-platform which will in return make the devices smart. When talking about smart devices the term Artificial Intelligence comes very quickly to mind. In this proofof-concept study a neural network is made to distinguish the throughput of fluids in real-time Having this amount of information at your disposal, processing it becomes a major challenge. However, when looking into the artificial intelligence research branch, techniques can be derived to process this data resulting into a more compact form factor of the same data with the benefit of using this derived data to classify, or even predict reoccurring patterns-
dc.description.sponsorshipThis work is funded by the BIOMAT project which is carried out under Interreg V-A grensregio Vlaanderen - Nederland and is supported by the European Union and The European Regional Development Fund and with financial support of province of Limburg - Belgium.-
dc.language.isoen-
dc.titleMulti-frequency electrical impedance analysis for monitoring aqueous solutions using an accelerated neural network approach-
dc.typeConference Material-
local.bibliographicCitation.conferencedate8 - 9 July 2019-
local.bibliographicCitation.conferencenameEngineering of Functional Interfaces (EnFi 2019)-
local.bibliographicCitation.conferenceplaceLeuven, Belgium-
local.format.pages1-
local.bibliographicCitation.jcatC2-
local.type.refereedRefereed-
local.type.specifiedConference Poster-
local.provider.typePdf-
local.uhasselt.uhpubyes-
item.contributorLEMMENS, Marijn-
item.contributorDe Raedt, W-
item.contributorGRIETEN, Lars-
item.contributorTHOELEN, Ronald-
item.fullcitationLEMMENS, Marijn; De Raedt, W; GRIETEN, Lars & THOELEN, Ronald (2019) Multi-frequency electrical impedance analysis for monitoring aqueous solutions using an accelerated neural network approach. In: Engineering of Functional Interfaces (EnFi 2019), Leuven, Belgium, 8 - 9 July 2019.-
item.accessRightsRestricted Access-
item.fulltextWith Fulltext-
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