<Record><identifier xmlns="http://purl.org/dc/elements/1.1/">URN:NBN:SI:DOC-5TBV80MS</identifier><date>2020</date><creator>Groznik, Vida</creator><relation>documents/doc/5/URN_NBN_SI_doc-5TBV80MS_001.pdf</relation><relation>documents/doc/5/URN_NBN_SI_doc-5TBV80MS_001.txt</relation><format format_type="issue">2</format><format format_type="volume">44</format><format format_type="type">article</format><format format_type="extent">str. 285-286</format><identifier identifier_type="ISSN">0350-5596</identifier><identifier identifier_type="DOI">10.31449/inf.v44i2.3177</identifier><identifier identifier_type="COBISSID_HOST">26990339</identifier><identifier identifier_type="URN">URN:NBN:SI:doc-5TBV80MS</identifier><language>eng</language><publisher>Slovensko društvo Informatika</publisher><source>Informatica (Ljubljana)</source><rights>BY</rights><subject language_type_id="eng">attribute visualisation</subject><subject language_type_id="eng">digital spirography</subject><subject language_type_id="slv">digitalizirana spirografija</subject><subject language_type_id="slv">izualizacija atributov</subject><subject language_type_id="slv">tremor</subject><title>Artificial intelligence methods for modelling tremor mechanisms</title></Record>