Papers by Sigurdur Brynjolfsson
Applied sciences, Dec 16, 2021
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
Engineering Structures, Jul 1, 1988
Geophysical Research Letters, Sep 15, 1993
The South Iceland seismic zone is a 20-60 km-wide (north-south) and up to 70 km-long zone of nort... more The South Iceland seismic zone is a 20-60 km-wide (north-south) and up to 70 km-long zone of north and northnortheast trending Holocene arrays of en echelon tension fractures. These fracture arrays are related to dextral strikeslip faults buried by Holocene lava flows. In this zone, major destructive earthquake sequences occur at intervals of 45-112 years, the largest events reaching magnitude 7 (Ms). We propose that this seismic zone is located between overlapping rift-zone segments (spreading centers), where the eastern segment has been propagating to the south during the past 3 Ma. We made a finite element study of this configuration with the segments modeled as mode I cracks loaded in tension. The results suggest that the South Iceland seismic zone in general, and the north and northnortheast trending dextral faults in particular, develop in response to the shear stresses generated between the riftzone segments.
Diagnostics, Jun 17, 2023
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
ACS ES&T water, May 5, 2023
Journal of Cleaner Production, Aug 1, 2023
Given the Covid-19 pandemic, the retail industry shifts many business models to enable more onlin... more Given the Covid-19 pandemic, the retail industry shifts many business models to enable more online purchases that produce large transaction data quantities (i.e., big data). Data science methods infer seasonal trends about products from this data and spikes in purchases, the effectiveness of advertising campaigns, or brand loyalty but require extensive processing power leveraging High-Performance Computing to deal with large transaction datasets. This paper proposes an High-Performance Computing-based expert system architectural design tailored for ‘big data analysis’ in the retail industry, providing data science methods and tools to speed up the data analysis with conceptual interoperability to commercial cloud-based services. Our expert system leverages an innovative Modular Supercomputer Architecture to enable the fast analysis by using parallel and distributed algorithms such as association rule mining (i.e., FP-Growth) and recommender methods (i.e., collaborative filtering). It enables the seamless use of accelerators of supercomputers or cloud-based systems to perform automated product tagging (i.e., residual deep learning networks for product image analysis) to obtain colour, shapes automatically, and other product features. We validate our expert system and its enhanced knowledge representation with commercial datasets obtained from our ON4OFF research project in a retail case study in the beauty sector.
Data in Brief, Feb 1, 2019
The data presented in this article are related to the research article entitled "Sugar-stimulated... more The data presented in this article are related to the research article entitled "Sugar-stimulated CO 2 sequestration by the green microalga Chlorella vulgaris" (Fu et al., 2019) [1]. The data describe a rational design and scale-up of LED-based photobioreactors for producing value-added algal biomass while removing waste CO 2 from flu gases from power plants. The dataset were created from growth rate experiments for biomass production including direct biomass productivity data, PBR size and setup parameters, medium composition as well as indirect energy cost and overhead in Iceland. A complete economic analysis is formed through a cost breakdown as well as PBR scalability predictions.
2022 45th Jubilee International Convention on Information, Communication and Electronic Technology (MIPRO), May 23, 2022
Science of The Total Environment, Mar 1, 2019
To convert waste CO2 from flue gases of power plants into value-added products, biomitigation tec... more To convert waste CO2 from flue gases of power plants into value-added products, biomitigation technologies show promise. In this study, we cultivated a fast-growing species of green microalgae, Chlorella vulgaris, in different sizes of photobioreactors (PBRs) and developed a strategy using small doses of sugars for enhancing CO2 sequestration under light-emitting diode illumination. Glucose supplementation at low levels resulted in an increase of photoautotrophic growth-driven biomass generation as well as CO2 capture by 10% and its enhancement corresponded to an increase of supplied photon flux. The utilization of urea instead of nitrate as the sole nitrogen source increased photoautotrophic growth by 14%, but change of nitrogen source didn't compromise glucose-induced enhancement of photoautotrophic growth. The optimized biomass productivity achieved was 30.4% higher than the initial productivity of purely photoautotrophic culture. The major pigments in the obtained algal biomass were found comparable to its photoautotrophic counterpart and a high neutral lipids productivity of 516.6 mg/(L•day) was achieved after optimization. A technoeconomic model was also developed, indicating that LED-based PBRs represent a feasible strategy for converting CO2 into value-added algal biomass.
Sustainable horizons, Mar 1, 2022
Transfusion, Aug 21, 2017
Journal of water process engineering, Aug 1, 2020
This study compared the membrane performances and water quality of gravity-driven membrane (GDM) ... more This study compared the membrane performances and water quality of gravity-driven membrane (GDM) systems in treating algae-polluted lake water under different operation conditions (microfiltration (MF) vs. ultrafiltration (UF); Chlorella vulgaris (green algae) vs. Phaeodactylum tricornutum (diatom); different algal amounts in the lake water). The results showed the cake layer fouling was predominant in the UF-GDM systems, while irreversible fouling contributed majorly to the MF-GDM fouling. As a result, the UF-GDM systems achieved > 1.5 time higher permeate flux compared to the MF-GDM systems in treating algae-polluted lake water. Compared to the green algae, the presence of the diatom cells in the feed water had more negative impacts on the UF permeate flux (increasing the cake layer resistance) and water quality (containing more low molecule weight neutrals). The analysis of cake layer foulants revealed that more aromatic protein-based biopolymers were accumulated on the membranes during filtration of algae-polluted lake water and the biopolymer amounts were almost linearly associated with membrane fouling potential of the GDM systems.
Vox Sanguinis, Mar 31, 2017
Planta Medica, Dec 14, 2016
Methods in molecular biology, 2018
In order to produce natural pigments with competitive prices, algal strains employed in industria... more In order to produce natural pigments with competitive prices, algal strains employed in industrial production need to be improved for increasing the productivity of valuable metabolites, thereby reducing the overall production cost. Adaptive laboratory evolution (ALE) is a traditional method for strain improvement, which has been effectively utilized in bacteria and fungi. With the growing interest in algal biotechnology, attempts have recently been put forward to improve microalgal strains with ALE approach. This chapter describes a stepwise adaptive evolution strategy that enhances carotenoid yield from microalgae.
Tectonophysics, Apr 1, 1993
Abstract On the north coast of Iceland, the rift zone in North Iceland is shifted about 120 km to... more Abstract On the north coast of Iceland, the rift zone in North Iceland is shifted about 120 km to the west where it meets with, and joins, the mid-ocean Kolbeinsey ridge. This shift occurs along the Tjörnes fracture zone, an 80-km-wide zone of high seismicity, which is an oblique (non-perpendicular) transform fault. There are two main seismic lineaments within the Tjörnes fracture zone, one of which continues on land as a 25-km-long WNW-trending strike-slip fault. This fault, referred to as the Husavik fault, meets with, and joins, north-trending ...
An increasing number of data science approaches that take advantage of deep learning in computati... more An increasing number of data science approaches that take advantage of deep learning in computational medicine and biomedical engineering require parallel and scalable algorithms using High-Performance Computing systems. Especially computational methods for analysing clinical datasets that consist of multivariate time series data can benefit from High-Performance Computing when applying computing-intensive Recurrent Neural Networks. This paper proposes a dynamic data science platform consisting of modular High-Performance Computing systems using accelerators for innovative Deep Learning algorithms to speed-up medical applications that take advantage of large biomedical scientific databases. This platform's core idea is to train a set of Deep Learning models very fast to easily combine and compare the different Deep Learning models' forecast (out-of-sample) performance to their past (in-sample) performance. Considering that this enables a better understanding of what Deep Learning models can be useful to apply to specific medical datasets, our case study leverages the three data science methods Gated Recurrent Units, one-dimensional convolutional layers, and their combination. We validate our approach using the open MIMIC-III database in a case study that assists in understanding, diagnosing, and treating a specific condition that affects Intensive Care Unit patients, namely Acute Respiratory Distress Syndrome.
The International Journal of Advanced Manufacturing Technology, May 1, 1990
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Papers by Sigurdur Brynjolfsson