Rodyti trumpą aprašą

dc.contributor.authorKaklauskas, Artūras
dc.date.accessioned2023-09-18T17:06:47Z
dc.date.available2023-09-18T17:06:47Z
dc.date.issued2018
dc.identifier.issn1877-7058
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/119768
dc.description.abstractThe EU RTD stresses the Europe 2020 objective that it “aims to support the development of a strong and sustainable industrial base able to innovate and compete globally”. University-industry partnerships should be sustained for inspiring up-to-date RTD, and industry-driven antecedences should be reinforced. The positioning by these authors had a solid accent on university-industry partnerships over the entire course of the ASCENT project to increase societal resilience to disasters. Collaboration appointments can appear in numerous forms and dimensions (career fairs, business advisors and affiliates, placements, conferences and meetings, project and university initiative support, program improvement, scholar fellowships, joint life cycle collaboration, RTD projects and product/service development). The forms and stages of partnership will fluctuate depending on the micro-, meso- and macro-levels of the environment. A founder of behavioral economics, Nobel Prize laureate Daniel Kahneman, asserts that two categories describe our thinking: fast thinking (first system) and slow thinking (second system). The foundation of the first system consists of emotions, impulses and exaggerated optimism. The first system does not require any great efforts; it operates practically automatically. Meanwhile the second thinking system is slow and analytical with an ability to control behavior and thoughts. Based on this idea, the author of this article developed the Neuro Multiple Criteria Analysis System for University-Industry Partnerships.eng
dc.formatPDF
dc.format.extentp. 93-100
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.relation.ispartofseriesProcedia Engineering Vol. 212 1877-7058
dc.relation.isreferencedbyScienceDirect
dc.relation.isreferencedbyScopus
dc.relation.isreferencedbyKnovel
dc.relation.isreferencedbyReaxys
dc.relation.isreferencedbyElsevier Biobase
dc.source.urihttps://doi.org/10.1016/j.proeng.2018.01.013
dc.subjectSD04 - Tvarus statinių gyvavimo ciklas / Sustainable lifecycle of the buildings
dc.titleNeuro multiple criteria analysis system for university-industry partnerships
dc.typeStraipsnis konferencijos darbų leidinyje Scopus DB / Paper in conference publication in Scopus DB
dcterms.accessRightsUnder a Creative Commons license
dcterms.references38
dc.type.pubtypeP1b - Straipsnis konferencijos darbų leidinyje Scopus DB / Article in conference proceedings Scopus DB
dc.contributor.institutionVilniaus Gedimino technikos universitetas
dc.contributor.facultyStatybos fakultetas / Faculty of Civil Engineering
dc.subject.researchfieldT 002 - Statybos inžinerija / Construction and engineering
dc.subject.researchfieldS 003 - Vadyba / Management
dc.subject.researchfieldT 007 - Informatikos inžinerija / Informatics engineering
dc.subject.ltspecializationsL102 - Energetika ir tvari aplinka / Energy and a sustainable environment
dc.subject.enUniversity-industry partnerships
dc.subject.enMultiple criteria analysis
dc.subject.enAffective computing
dc.subject.enNeuro decision matrix
dcterms.sourcetitleProcedia Engineering. 7th International Conference on Building Resilience; Using scientific knowledge to inform policy and practice in disaster risk reduction, ICBR 2017, 27-29 November 2017, Bangkok, Thailand
dc.description.volumeVol. 212
dc.publisher.nameElsevier
dc.publisher.cityAmsterdam
dc.identifier.doi2-s2.0-85043383438
dc.identifier.doi10.1016/j.proeng.2018.01.013
dc.identifier.elaba26411643


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