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
Adopting digital government shared-services centers : A case from Iceland
(Association for Computing Machinery, 2022-10-04) Hjaltalin, Illugi T.; Amaral, Luis; Soares, Delfina; Zheng, Lei; Department of Business and Economics
The overall objective of this study is to understand how shared services adoption by governments can affect public sector reforms and public value. In this ongoing research paper, a case study involving a deployment of a government digital shared-services center is outlined. The adoption process is analyzed through a framework inspired by systems theory and public value theory. Initial results suggest that networked collaborative governance in the form of cross-sector collaborations can play an important role in public value (co)creation. However, the findings also indicate a barrier to public innovation. This involves a zero-error culture in state agencies. In this context, strong leadership skills and diverse use of relevant administrative instruments at various stages in the innovation process are found to be critical factors for the successful adoption of shared services. This study contributes empirically and theoretically to the latest research on ICT and public value by scrutinizing a successful case of a shared-services unit within central government.
Decline in Running Performance in Highest-Level Soccer : Analysis of the UEFA Champions League Matches
(2022-10) Modric, Toni; Versic, Sime; Alexe, Dan Iulian; Gilic, Barbara; Mihai, Ilie; Drid, Patrik; Radulovic, Nikola; Saavedra, Jose M.; Menjibar, Rafael Burgueño; Department of Sport Science
It is widely recognized that there is a decline in match running performance (MRP) towards the end of matches. To clarify whether it is primarily a consequence of fatigue, pacing or situational influences, this study aimed to examine MRP across 15-min match periods for players on different playing positions. Players’ MRP (n = 244) were examined from the UEFA Champions League matches (n = 20) using a semiautomatic optical tracking system. Linear mixed models for repeated measures were adjusted to analyze MRP over the six 15-min match periods while controlling the influence of situational factors. No effects of match outcome, match location, team, and opponent quality on total distance (TD) and high-intensity running (HIR) for players in all playing positions were found (F = 0.03–2.75; all p > 0.05). Significant differences in TD (F = 17.57–53.01; η2 = 0.39–0.52, all large effect sizes) and HIR (F = 3.67–7.64; η2 = 0.05–0.19, small to medium effect sizes) among six 15-minute match periods were found for players in all playing positions. In addition, players in all playing positions covered less TD (d = 1.41–2.15, large to very large effect sizes) and HIR (d = 0.16–0.6, trivial to medium effect sizes) in the last compared to the first 15-min match period. No differences in TD and HIR between the last two match periods in the second half were observed. This study confirmed that soccer players reduce MRP towards the end of matches, and suggest that the decline of MPR in highest-level soccer may be a consequence of pacing strategies.
Encodability and Separation for a Reflective Higher-Order Calculus
(2022-09-06) Lybech, Stian; Department of Computer Science
The ρ-calculus (Reflective Higher-Order Calculus) of Meredith and Radestock is a π-calculus-like language with some unusual features, notably, structured names, runtime generation of free names, and the lack of an operator for scoping visibility of names. These features pose some interesting difficulties for proofs of encodability and separation results. We describe two errors in a previously published attempt to encode the π-calculus in the ρ-calculus by Meredith and Radestock. Then we give a new encoding and prove its correctness, using a set of encodability criteria close to those proposed by Gorla, and discuss the adaptations necessary to work with a calculus with runtime generation of structured names. Lastly we prove a separation result, showing that the ρ-calculus cannot be encoded in the π-calculus.
A Generic Type System for Higher-Order Ψ-calculi
(2022-09-06) Bendixen, Alex Rønning; Bojesen, Bjarke Bredow; Hüttel, Hans; Lybech, Stian; Department of Computer Science
The Higher-Order Ψ-calculus framework (HOΨ) is a generalisation of many first- and higher-order extensions of the π-calculus. It was proposed by Parrow et al. who showed that higher-order calculi such as HOπ and CHOCS can be expressed as HOΨ-calculi. In this paper we present a generic type system for HOΨ-calculi which extends previous work by Hüttel on a generic type system for first-order Ψ-calculi. Our generic type system satisfies the usual property of subject reduction and can be instantiated to yield type systems for variants of HOπ, including the type system for termination due to Demangeon et al.. Moreover, we derive a type system for the ρ-calculus, a reflective higher-order calculus proposed by Meredith and Radestock. This establishes that our generic type system is richer than its predecessor, as the ρ-calculus cannot be encoded in the π-calculus in a way that satisfies standard criteria of encodability.
Artificial intelligence and auditing in small- and medium-sized firms : Expectations and applications
(2022-09-01) Rikhardsson, Pall; Thórisson, Kristinn R.; Bergthorsson, Gudmundur; Batt, Catherine; Department of Computer Science
Auditing is a field of expertise often mentioned as being ripe for automation using artificial intelligence methods at all levels of operations. Primarily, the application of artificial intelligence (AI) in the auditing profession is done by and for large organizations, leveraging large datasets. While AI approaches for big data are continually improving, methods for small data are scarce. Yet most firms in the world employ fewer than 50 people and can, therefore, rarely rely on big data for automation. In our study, we ask auditors, who mainly audit SMEs, about their expectations towards the impact of AI on the auditing profession and where they expect it to provide the most value when it comes to auditing SMEs. We find that these auditors expect significant improvements in their own efficiency on the job, that learning to use AI applications will not be a challenge for them, and that the use of AI in auditing firms will become mandatory in the future. They expect the performance of certain tasks to become AI-augmented, including risk assessment of individual transactions, conducting audit interviews, performing all manners of analysis, writing confirmation letters, performing the final verification of annual reports, and performing physical observations. Considering these results, we discuss the potential impact of these developments, such as how AI could make the auditing process more effective and efficient but also how AI could lead to an even higher concentration of the auditing service industry.
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