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
Iterative Learning Robust PD-SDRE Control for Active Transfemoral Prostheses
(Science and Technology Publications, Lda, 2025) Bavarsad, Anna; August, Elias; Gislason, Magnus Kjartan; Yang, Xin-She; Drogoul, Alexis; Wagner, Gerd; Department of Engineering
In this paper, we present a novel control strategy for active prosthetic legs. The approach uses an intelligent robust Proportional-Derivative State-Dependent Riccati Equation controller to reduce the use of biomechanical energy, enhance performance and robustness. We include an Iterative Learning Control algorithm, to minimise control errors and allow the controller gains to adapt over time, and robust Sliding Mode Control to specifically address potential parametric and non-parametric uncertainties, disturbances, and noise. We conduct tests to demonstrate that the proposed controller not only maintains stability but also outperforms existing methods in terms of energy efficiency and tracking. Application of the proposed method in simulations shows significant improvements when compared to other methods from the literature, with up to 98.3% reduction in position tracking error and up to 91.9% reduction in control cost. Furthermore, for angular tracking of the hip and knee, improvements of up to 32.6% and 44.9%, along with torque reductions of up to 67.5% and 87.5%, are observed. This study represents a step forward in providing an effective solution for controlling active prosthetic devices.
Iterative Learning Robust PD-SDRE Control for Active Transfemoral Prostheses
(Science and Technology Publications, Lda, 2025) Bavarsad, Anna; August, Elias; Gislason, Magnus Kjartan; Yang, Xin-She; Drogoul, Alexis; Wagner, Gerd; Department of Engineering
In this paper, we present a novel control strategy for active prosthetic legs. The approach uses an intelligent robust Proportional-Derivative State-Dependent Riccati Equation controller to reduce the use of biomechanical energy, enhance performance and robustness. We include an Iterative Learning Control algorithm, to minimise control errors and allow the controller gains to adapt over time, and robust Sliding Mode Control to specifically address potential parametric and non-parametric uncertainties, disturbances, and noise. We conduct tests to demonstrate that the proposed controller not only maintains stability but also outperforms existing methods in terms of energy efficiency and tracking. Application of the proposed method in simulations shows significant improvements when compared to other methods from the literature, with up to 98.3% reduction in position tracking error and up to 91.9% reduction in control cost. Furthermore, for angular tracking of the hip and knee, improvements of up to 32.6% and 44.9%, along with torque reductions of up to 67.5% and 87.5%, are observed. This study represents a step forward in providing an effective solution for controlling active prosthetic devices.
INTERNAL FACTORS INFLUENCING CURRICULUM TRANSFORMATION IN HIGHER ENGINEERING EDUCATION
(European Society for Engineering Education (SEFI), 2025) Gerwel Proches, C.; James, A.; Kanyangale, M.; Audunsson, H.; Dagienė, V.; Liem, I.; Jasutė, E.; Rouvrais, S.; Matthiasdottir; Kangaslampi, Riikka; Langie, Greet; J�rvinen, Hannu-Matti; Nagy, Bal�zs; Department of Engineering; Department of Sport Science
In many countries in the world, there is growing scholarly interest in higher education curriculum transformation. However, there is a lack of clarity and consensus on the factors, e.g. enablers and inhibitors, which influence curriculum transformation. The aim of this study was to explore factors influencing curriculum transformation in higher engineering education, according to the views of higher education faculty, programme leaders, and departmental heads. The study drew on the qualitative research approach, using data from an international hybrid workshop. Data were analysed using thematic analysis. The findings revealed eight key factors identified as influencing curriculum transformation: conceptual clarity in curriculum transformation; urgency and need for rapid transformation in a changing landscape; curriculum adaptability and epistemological access; resource constraints; stakeholder engagement, diversity and inclusion; bureaucratic inefficiencies and slow decision making; higher education leadership; and professional development. By fostering an adaptive and forward-thinking approach, higher education can overcome systemic barriers and create inclusive, responsive, and future-oriented learning environments that prepare engineering students to navigate complex global challenges.
How well can graphs represent wireless interference?
(Association for Computing Machinery, 2015-06-14) Halldórsson, Magnús M.; Tonoyan, Tigran; Department of Computer Science
Efficient use of a wireless network requires that transmissions be grouped into feasible sets, where feasibility means that each transmission can be successfully decoded in spite of the interference caused by simultaneous transmissions. Feasibility is most closely modeled by a signal-to-interference-plus-noise (SINR) formula, which unfortunately is conceptually complicated, being an asymmetric, cumulative, many-to-one relationship. We re-examine how well graphs can capture wireless receptions as encoded in SINR relationships, placing them in a framework in order to understand the limits of such modelling. We seek for each wireless instance a pair of graphs that provide upper and lower bounds on the feasibility relation, while aiming to minimize the gap between the two graphs. The cost of a graph formulation is the worst gap over all instances, and the price of (graph) abstraction is the smallest cost of a graph formulation. We propose a family of conflict graphs that is parameterized by a non-decreasing sub-linear function, and show that with a judicious choice of functions, the graphs can capture feasibility with a cost of O(log∗Δ), where Δ is the ratio between the longest and the shortest link length. This holds on the plane and more generally in doubling metrics. We use this to give greatly improved O(logΔ)-approximation for fundamental link scheduling problems with arbitrary power control. We also explore the limits of graph representations and find that our upper bound is tight: the price of graph abstraction is Ω(logΔ). In addition, we give strong impossibility results for general metrics, and for approximations in terms of the number of links.
EXAMINING BEST PRACTICES IN CURRICULUM DESIGN : INSIGHTS FOR ENGINEERING EDUCATION
(European Society for Engineering Education (SEFI), 2024) Matthiasdottir, A.; Audunson, H.; Dagienė, V.; Rouvrais, S.; Barus, A.; Gerwel, C.; Zufferey, Jessica Dehler; Langie, Greet; Tormey, Roland; Nagy, Balazs Vince; Department of Sport Science
Higher education must be prepared for the ever-changing needs of the world to ensure that future engineers receive extensive training and are equipped to provide significant contributions to both the workforce and society. It is important for higher education leaders to be aware of the need for regularly reviewing curriculum and take part in development to ensure quality improvement. Engineering education needs to be up to date and driven by the need to prepare graduates for the challenges posed by rapidly changing technology, industry, and society. This paper specifically aims to identify best practices for curriculum design in engineering education. Data was collected through the exchange of engineering and business curricula among members participating in the DECART project (DECART 2022). The shared curricula underwent critical examination based on key features related to curriculum components. The analysis included reflection and feedback from project partners. The findings hold significance for engineering educators in various contexts, offering insights into curriculum transformation, agility, and resilience amidst increasingly Volatile, Uncertain, Complex, and Ambiguous (VUCA) environments, which continue to influence engineering education and higher education.
Flokkar í Opnum vísindum
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- 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