About: Mobile Sensor Data Classification Using GM-SOM

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An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	The paper uses a previously-introduced modification of standard Kohonen network (SOM), called GM-SOM. This approach uses partitioning the problem in case of insufficient resources (memory, disc space, etc.) and parallel processing of input data set to process all input vectors at once, with the use of modern multi-core GPUs to achieve massive parallelism. The algorithm pre-selects potential centroids of data clusters in the first step and uses them as weight vectors in the final calculation. In this paper, the algorithm has been demonstrated on a new UCI HAR dataset, representing activities recorded by smartphone sensors, which are prone to random noise due to the sensor behavior. Moreover the separation of classes is not linear, which introduces additional complexity and makes it hard to process the data by linear algebra methods. The paper uses a previously-introduced modification of standard Kohonen network (SOM), called GM-SOM. This approach uses partitioning the problem in case of insufficient resources (memory, disc space, etc.) and parallel processing of input data set to process all input vectors at once, with the use of modern multi-core GPUs to achieve massive parallelism. The algorithm pre-selects potential centroids of data clusters in the first step and uses them as weight vectors in the final calculation. In this paper, the algorithm has been demonstrated on a new UCI HAR dataset, representing activities recorded by smartphone sensors, which are prone to random noise due to the sensor behavior. Moreover the separation of classes is not linear, which introduces additional complexity and makes it hard to process the data by linear algebra methods. (en)
Title	Mobile Sensor Data Classification Using GM-SOM Mobile Sensor Data Classification Using GM-SOM (en)
skos:prefLabel	Mobile Sensor Data Classification Using GM-SOM Mobile Sensor Data Classification Using GM-SOM (en)
skos:notation	RIV/61989100:27740/13:86088507!RIV14-MSM-27740___
http://linked.open...avai/riv/aktivita	P
http://linked.open...avai/riv/aktivity	P(ED1.1.00/02.0070), P(EE.2.3.20.0073)
http://linked.open...iv/cisloPeriodika	12
http://linked.open...vai/riv/dodaniDat	2014
http://linked.open...aciTvurceVysledku	Gajdoš, Petr Dohnálek, Pavel Moravec, Pavel Peterek, Tomáš
http://linked.open.../riv/druhVysledku	J - Článek v odborném periodiku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Vysoká škola báňská - Technická univerzita Ostrava / IT4Innovations
http://linked.open...dnocenehoVysledku	88659
http://linked.open...ai/riv/idVysledku	RIV/61989100:27740/13:86088507
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	parallel calculation; KohonenNetwork; gyroscope; activity recognition; accelerometer (en)
http://linked.open.../riv/klicoveSlovo	gyroscope accelerometer KohonenNetwork activity recognition parallel calculation
http://linked.open...odStatuVydavatele	DE - Spolková republika Německo
http://linked.open...ontrolniKodProRIV	[D1339B4AEC85]
http://linked.open...i/riv/nazevZdroje	Advances in Intelligent Systems and Computing. Volume 210
http://linked.open...in/vavai/riv/obor	IN
http://linked.open...ichTvurcuVysledku	4 (xsd:int)
http://linked.open...cetTvurcuVysledku	4 (xsd:int)
http://linked.open...vavai/riv/projekt	Bio-Inspired Methods: research, development and knowledge transfer IT4Innovations Centre of Excellence
http://linked.open...UplatneniVysledku	2013
http://linked.open...v/svazekPeriodika	210
http://linked.open...iv/tvurceVysledku	Moravec, Pavel Gajdoš, Petr Peterek, Tomáš Dohnálek, Pavel
issn	2194-5357
number of pages	10 (xsd:int)
http://bibframe.org/vocab/doi	10.1007/978-3-319-00542-3_48
http://localhost/t...ganizacniJednotka	27740

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