Opin vísindi
Opin vísindi er varðveislusafn vísindaefnis og doktorsritgerða í opnum aðgangi á vegum íslenskra háskóla og Landsbókasafns Íslands - Háskólabókasafns.
Opinn aðgangur að rannsóknaniðurstöðum er í samræmi við 10. gr. laga nr. 3/2003 um opinberan stuðning við vísindarannsóknir sem og kröfur innlendra og erlendra rannsóknasjóða. Markmiðið með opnum aðgangi er að niðurstöður rannsókna séu aðgengilegar sem flestum óhindrað og án endurgjalds á rafrænu formi. Vistun í varðveislusafninu er varanleg og ætlað að tryggja aðgang að vísindaefni íslenskra háskóla í opnum aðgangi um ókomna tíð. Varðveislusafnið Opin vísindi er tengt við rannsóknagáttina IRIS og rannsóknaniðurstöður í opnum aðgangi sem eru skráðar í IRIS eru um leið vistaðar og gerðar aðgengilegar til framtíðar í varðveislusafninu. Með því að safna þessu efni saman í eitt safn verður aðgangur að því einfaldur og þægilegur fyrir alla sem vilja kynna sér það og geta þannig notið þess öfluga vísindastarfs sem fram fer í háskólum landsins.
Varðveislusafnið er OpenAIRE / OpenAIREplus samhæft og samrýmist kröfum sem gerðar eru um birtingu rannsóknaniðurstaðna úr verkefnum sem styrkt eru úr evrópsku rannsóknaáætlununum FP7 og H2020.
Varðveislusafnið notar opna hugbúnaðinn DSpace.
Opinn aðgangur að rannsóknaniðurstöðum er í samræmi við 10. gr. laga nr. 3/2003 um opinberan stuðning við vísindarannsóknir sem og kröfur innlendra og erlendra rannsóknasjóða. Markmiðið með opnum aðgangi er að niðurstöður rannsókna séu aðgengilegar sem flestum óhindrað og án endurgjalds á rafrænu formi. Vistun í varðveislusafninu er varanleg og ætlað að tryggja aðgang að vísindaefni íslenskra háskóla í opnum aðgangi um ókomna tíð. Varðveislusafnið Opin vísindi er tengt við rannsóknagáttina IRIS og rannsóknaniðurstöður í opnum aðgangi sem eru skráðar í IRIS eru um leið vistaðar og gerðar aðgengilegar til framtíðar í varðveislusafninu. Með því að safna þessu efni saman í eitt safn verður aðgangur að því einfaldur og þægilegur fyrir alla sem vilja kynna sér það og geta þannig notið þess öfluga vísindastarfs sem fram fer í háskólum landsins.
Varðveislusafnið er OpenAIRE / OpenAIREplus samhæft og samrýmist kröfum sem gerðar eru um birtingu rannsóknaniðurstaðna úr verkefnum sem styrkt eru úr evrópsku rannsóknaáætlununum FP7 og H2020.
Varðveislusafnið notar opna hugbúnaðinn DSpace.
Nýlega bætt við
Using a Stack to Find an AI Needle : Topic Modeling for Cyber Threat Intelligence
(2025-12-15) Schröer, Saskia Laura; Seideman, Jeremy D.; Luo, Shoufu; Apruzzese, Giovanni; Dietrich, Sven; Laskov, Pavel; Department of Computer Science
Cyber Threat Intelligence (CTI) is a fundamental activity to ensure the protection of modern organizations against sophisticated cyberattackers. A large body of literature has addressed problems related to CTI. Despite the scientific validity of such results, the reality is that CTI practitioners rarely deploy advanced CTI methods proposed by the research community and mostly rely on manual processes. We seek to facilitate the manual analyses typical for CTI practice by proposing a novel topic modeling technique that enables analysts to identify specific topics in CTI data sources. We demonstrate how our method, released as an open source tool, can be used to investigate three case studies revolving around the research question whether attackers are deploying AI for malicious purposes “in the wild,” and, if so, what features of AI interest them the most. We analyzed 7 million discussions from 18 underground forums. Our findings reveal that attackers may favor easy-to-use AI toolkits over the sophisticated AI techniques envisioned in research papers. Our contributions are further validated by a user study (N = 24) with CTI experts, confirming the relevance of our research. Ultimately, we advocate future endeavors to account for the opinion of CTI practitioners—who should, in turn, try to cooperate.
Screening and Assessment of Gambling in Military Populations : A Systematic Review and Gap Analysis
(2025-12) Rayner, Chloe; Treacy, Samantha; Dighton, Glen; Champion, Hannah; Dymond, Simon; Department of Psychology
Purpose of Review: This review evaluates the use of assessment and screening tools for gambling behaviour in military populations. Although military personnel and veterans face elevated risks, most available tools were developed for general populations and may not account for military-specific factors. The review identifies the screening and assessment measures used in military population studies, assesses their psychometric properties, and highlights key methodological gaps through a structured gap analysis. Recent Findings: Across 46 studies, 28 screening or assessment tools were identified, including commonly used measures such as the PGSI, SOGS, BBGS, GRCS, MAGS, and NODS-CLiP. While these tools vary in length and purpose, none were specifically designed or validated for use with military populations. Validation studies showed inconsistent reliability, sensitivity, and specificity. Notably, no tools adequately reflected military-relevant issues such as deployment stress, occupational impact, or co-occurring mental health conditions. Barriers to accurate screening, including stigma and underreporting, further complicate assessment in this context. Summary: There is a critical need for the development of validated, military-specific screening and assessment tools that address the unique experiences and risks within this population. Existing measures may underestimate or misclassify gambling-related harm, limiting early identification and effective intervention. Future research should prioritise the design and validation of tailored tools that can support accurate screening and assessment, reduce stigma, and inform better-targeted prevention and treatment strategies for military personnel and veterans.
The future of learning : how artificial intelligence and other new technologies revolutionize project management education and foster Project Learning Intelligence
(2025-12) Mariani, Costanza; Aaltonen, Kirsi; Ingason, Helgi þor; Mancini, Mauro; Huemann, Martina; Department of Engineering
Personalised learning in project management education : Insights from an artificial intelligence-driven chatbot
(2025-12) Ingason, Helgi Thor; Aaltonen, Kirsi; Asmundarson, Atli Snaer; Fridgeirsson, Thordur Vikingur; Huemann, Daniel; Huemann, Martina; Kujala, Jaakko; Lampela, Hannele; Mancini, Mauro; Mariani, Costanza; Ringhofer, Claudia; Department of Engineering
The increasing complexity of project-based work in contemporary organisations calls for a transformation in how project management is taught. Traditional teaching approaches struggle to support self-directed, context-sensitive, and motivationally engaging learning experiences—skills that are critical for preparing future project leaders. In this context, there is growing interest in the potential of artificial intelligence-powered tools to enhance the quality and adaptability of educating future project managers. This paper explores the application of artificial intelligence-driven chatbots in university-level project management education through the lens of the two-year international project ”ChatLearn” conducted across four European countries. Using an action design research methodology, the project iteratively developed and tested a chatbot in three versions, progressively integrating feedback from students and educators. The study suggests that artificial intelligence-based chatbots hold significant promise for supporting personalised learning journeys and increasing student motivation; however, their integration requires careful design, ongoing dialogue within the teaching community, and a strong alignment with pedagogical objectives.
Optimal field-free magnetization switching via spin-orbit torque on the surface of a topological insulator
(2025-12) Miranda, Ivan P.; Kwiatkowski, Grzegorz J.; Holmqvist, Cecilia M.; Canali, Carlo M.; Lobanov, Igor S.; Uzdin, Valery M.; Manolescu, Andrei; Bessarab, Pavel F.; Erlingsson, Sigurdur I.; Department of Engineering
We present an optimal field-free protocol for current-induced switching of a perpendicularly magnetized ferromagnetic insulator nanoelement on the surface of a topological insulator. The time dependence of in-plane components of the surface current, which drives the magnetization reversal via the Dirac spin-orbit torque with minimal Joule heating, is derived analytically as a function of the switching time and material properties. Our analysis identifies that energy-efficient switching is achieved for vanishing damping-like torque. The optimal reversal time that balances switching speed and energy efficiency is determined. When we compare topological insulators to heavy-metal systems, we find similar switching costs for the optimal ratio between the spin-orbit torque coefficients. However, topological insulators offer the advantage of tunable material properties. Finally, we propose a robust and efficient simplified switching protocol using a down-chirped rotating current pulse, tailored to realistic ferromagnetic/topological insulator systems.
Flokkar í Opnum vísindum
Veldu flokk til að skoða.
- University of Iceland
- University of Akureyri
- Bifröst University
- Hólar University College
- IRIS
- Agricultural University of Iceland
- National and University Library of Iceland
- Iceland University of the Arts