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
Life in a cold-water environment: Allometric adaptations of cetaceans in Skjálfandi Bay, Iceland
(University of Iceland, School of Engineering and Natural Sciences, Faculty of Life and Environmental Sciences, 2026-08-28) Glarou, Maria; Marianne H. Rasmussen, Fredrik Christiansen, Takashi Iwata, Arnar Pálsson; Faculty of Life and Environmental Sciences (UI); Líf- og umhverfisvísindadeild (HÍ); School of Engineering and Natural Sciences (UI); Verkfræði- og náttúruvísindasvið (HÍ)
Energy drives all biological processes and constrains how animals acquire, allocate, and expend resources to maintain fitness. This thesis investigates bioenergetic strategies in sympatric cetaceans inhabiting cold subarctic waters. Focusing on five different-sized species in Skjálfandi Bay, Iceland (harbour porpoises, white-beaked dolphins, minke whales, humpback whales, and blue whales), this study combines UAV photogrammetry and bioenergetic modelling to examine how body size influences heat loss (Article I), field metabolic rate (FMR; Article II), and energetic requirements (Article III) under shared environmental conditions. Heat loss scaled predictably with body size, with absolute heat loss increasing and volume-specific heat loss decreasing across species. Smaller cetaceans exhibited higher surface-area-to-volume ratios (SVR) and therefore higher relative heat loss, partly offset by increased blubber thickness and lower thermal conductivity. In contrast, larger species benefited from reduced SVR and lower relative heat loss. FMR also scaled with body size, with absolute FMR increasing and mass-specific FMR decreasing. Species with higher SVR exhibited higher mass-specific FMR, indicating a correlation between thermoregulatory costs and metabolic scaling. Cetacean FMR estimates were generally higher than predictions for similarly sized terrestrial mammals. Energetic requirements and prey consumption followed the same pattern, with larger species having higher absolute but lower mass-specific requirements. Smaller cetaceans required a greater proportion of their body mass in prey, whereas larger species dominated total prey removal at the population level. Overall, the findings of this thesis show that body size is a primary driver of bioenergetic strategies in cetaceans, shaping their life-history traits and ecological roles.
What Is This Skítur : Viking Authenticity in Ys X: Nordics as a Japanese Role-Playing Game
(2026) Panaro, Luca Arruns; Bjarnason, Nökkvi Jarl; Faculty of Icelandic and Comparative Cultural Studies
This article explores how viking authenticity is filtered through the media ecology of Japan by employing Ys X: Nordics (Nihon Falcom 2023) as a case study. It examines how the game constructs and engages with historical imaginaries while simultaneously being shaped by conventions and sensibilities of Japanese game development and its broader media landscape. To address this, the discussion situates Ys X within the broader history of viking representation in video games, showing how the figure of the “digital viking” has been recontextualized to meet diverse cultural and commercial demands. Particular attention is then paid to how the national and production context of Ys X inform its representations, with the game blending viking motifs with the visual, narrative, and thematic conventions of anime, manga, and Japanese role-playing games. Through close analysis, the article identifies moments of what can be termed authentic recontextualization, while also being mindful of numerous decontextualized or ornamental uses of viking imagery, names, and mythological figures. These strategies produce a selectively authentic, viking-inflected world that resonates with audience expectations while eschewing historical authenticity. Moreover, the game’s tonal orientation diverges from the “gritty” medievalism common in contemporary Western media, favoring instead the colorful optimism and narrative ethos of mainstream manga and anime, with its emphasis on friendship, perseverance, and collective victory. Ultimately, the article argues that Ys X exemplifies how Japanese popular media reworks transnational historical motifs, embedding them within its own aesthetic and narrative logics. In doing so, it highlights the culturally contingent nature of authenticity in historical games, showing that viking imagery in Japanese contexts functions less as a claim to historical accuracy than as an adaptive, stylistic device within a global media landscape.
World of ScoreCraft : Novel Multi-Scorer Experiment on the Impact of a Decision Support System in Sleep Staging
(2026-02) Holm, Benedikt; Óskarsson, Arnar; Þorleifsson, Björn Elvar; Hafsteinsson, Hörður Þór; Sigurðardóttir, Sigríður; Grétarsdóttir, Heiður; Hoelke, Kenan; Jouan, Gabriel Marc Marie; Penzel, Thomas; Arnardottir, Erna Sif; Óskarsdóttir, María; Department of Engineering; Department of Computer Science
Manual scoring of polysomnography (PSG) is a time-intensive task, prone to inter-scorer variability that can impact diagnostic reliability. This study investigates the integration of decision support systems (DSS) into PSG scoring workflows, focusing on their effects on accuracy, scoring time and potential biases toward recommendations from artificial intelligence (AI) compared to human-generated recommendations. Using a novel online scoring platform, we conducted a repeated-measures study with sleep technologists, who scored traditional and self-applied PSGs. Participants were occasionally presented with recommendations labelled as either human- or AI-generated. As the goal of this study was to isolate the effect of perceived recommendation sources on scorer behaviour, all recommendations were human-generated. We found that traditional PSGs tended to be scored slightly more accurately than self-applied PSGs, but this difference was not statistically significant. Correct recommendations significantly improved scoring accuracy for both PSG types, while incorrect recommendations reduced accuracy. No significant bias was observed toward or against AI-generated recommendations compared to human-generated recommendations. These findings highlight the potential of DSSs to enhance PSG scoring reliability. However, ensuring the accuracy of the suggestions is critical to maximising its benefits. Future research should explore the long-term impacts of DSS on scoring workflows and strategies for integrating AI in clinical practice.
An optimized framework for processing multicentric polysomnographic data incorporating expert human oversight
(2024) Holm, Benedikt; Jouan, Gabriel; Hardarson, Emil; Sigurðardottir, Sigríður; Hoelke, Kenan; Murphy, Conor; Arnardóttir, Erna Sif; Óskarsdóttir, María; Islind, Anna Sigríður; Department of Engineering; Department of Computer Science
Introduction: Polysomnographic recordings are essential for diagnosing many sleep disorders, yet their detailed analysis presents considerable challenges. With the rise of machine learning methodologies, researchers have created various algorithms to automatically score and extract clinically relevant features from polysomnography, but less research has been devoted to how exactly the algorithms should be incorporated into the workflow of sleep technologists. This paper presents a sophisticated data collection platform developed under the Sleep Revolution project, to harness polysomnographic data from multiple European centers. Methods: A tripartite platform is presented: a user-friendly web platform for uploading three-night polysomnographic recordings, a dedicated splitter that segments these into individual one-night recordings, and an advanced processor that enhances the one-night polysomnography with contemporary automatic scoring algorithms. The platform is evaluated using real-life data and human scorers, whereby scoring time, accuracy, and trust are quantified. Additionally, the scorers were interviewed about their trust in the platform, along with the impact of its integration into their workflow. Results: We found that incorporating AI into the workflow of sleep technologists both decreased the time to score by up to 65 min and increased the agreement between technologists by as much as 0.17 κ. Discussion: We conclude that while the inclusion of AI into the workflow of sleep technologists can have a positive impact in terms of speed and agreement, there is a need for trust in the algorithms.
Deep learning for sleep analysis on children with sleep-disordered breathing : Automatic detection of mouth breathing events
(2023) Sturludóttir, Jóna Elísabet; Sigurðardóttir, Sigríður; Serwatko, Marta; Arnardóttir, Erna S.; Hrubos-Strøm, Harald; Clausen, Michael Valur; Sigurðardóttir, Sigurveig; Óskarsdóttir, María; Islind, Anna Sigridur; Department of Engineering; Department of Computer Science
Introduction: Sleep-disordered breathing (SDB) can range from habitual snoring to severe obstructive sleep apnea (OSA). A common characteristic of SDB in children is mouth breathing, yet it is commonly overlooked and inconsistently diagnosed. The primary aim of this study is to construct a deep learning algorithm in order to automatically detect mouth breathing events in children from polysomnography (PSG) recordings. Methods: The PSG of 20 subjects aged 10–13 years were used, 15 of which had reported snoring or presented high snoring and/or high OSA values by scoring conducted by a sleep technologist, including mouth breathing events. The separately measured mouth and nasal pressure signals from the PSG were fed through convolutional neural networks to identify mouth breathing events. Results: The finalized model presented 93.5% accuracy, 97.8% precision, 89% true positive rate, and 2% false positive rate when applied to the validation data that was set aside from the training data. The model's performance decreased when applied to a second validation data set, indicating a need for a larger training set. Conclusion: The results show the potential of deep neural networks in the analysis and classification of biological signals, and illustrates the usefulness of machine learning in sleep analysis.
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