Now showing items 441-460 of 4870

    • Algorithms that forget: Machine unlearning and the right to erasure 

      Juliussen, Bjørn Aslak; Rui, Jon Petter; Johansen, Dag (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-09-22)
      rticle 17 of the General Data Protection Regulation (GDPR) contains a right for the data subject to obtain the erasure of personal data. The right to erasure in the GDPR gives, however, little clear guidance on how controllers processing personal data should erase the personal data to meet the requirements set out in Article 17. Machine Learning (ML) models that have been trained on personal data ...
    • Unsupervised Band Selection for Hyperspectral Datasets by Double Graph Laplacian Diagonalization 

      Khachatrian, Eduard; Chlaily, Saloua; Eltoft, Torbjørn; Gamba, Paolo; Marinoni, Andrea (Journal article; Tidsskriftartikkel, 2021)
      The vast amount of spectral information provided by hyperspectral images can be useful for different applications. However, the presence of redundant bands will negatively affect application performance. Therefore, it is crucial to select a relevant subset that preserves the information of the original set. In this paper, we present an automatic and accurate band selection method based on Graph ...
    • Explaining doping in material research (Hf substitution in ZnO films) by directly quantifying the van der Waals force 

      Lai, Chia-Yun; Santos Hernandez, Sergio; Moser, Toni; Alfakes, Boulos; Lu, Chun-Yu; Olukan, Tuza Adeyemi; Rajput, Nitul; Boström, Tobias; Chiesa, Matteo (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-02-04)
      Non-monotonic behavior has been observed in the optoelectronic properties of ZnO thin films as doped with Hf (HZO). Here we propose that two competing mechanisms are responsible for such behaviour. Specifically, we propose that provided two crystal orientations dominate film growth, only one of them might be responsible for direct Hf substitution. Nonmonotonic behaviour is expected at once by ...
    • Damage Characterisation in Composite Laminates Using Vibro-Acoustic Technique 

      Andersen, Kristian G; Jombo, Gbanaibolou; Ismail, Sikiru Oluwarotimi; Chen, Yong Kang; Dhakal, Hom Nath; Zhang, Yu (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-04-30)
      The need to characterise in-service damage in composite structures is increasingly becoming important as composites find higher utilisation in wind turbines, aerospace, automotive, marine, among others. This paper investigates the feasibility of simplifying the conventional acousto-ultrasonic technique set-up for quick and economic one-sided in-service inspection of composite structures. Acousto-ultrasonic ...
    • Structured illumination microscopy using a photonic chip 

      Helle, Øystein Ivar; Dullo, Firehun Tsige; Lahrberg, Marcel; Tinguely, Jean-Claude; Hellesø, Olav Gaute; Ahluwalia, Balpreet Singh (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-04-11)
      Structured illumination microscopy (SIM) enables live-cell super-resolution imaging of subcellular structures at high speeds. At present, linear SIM uses free-space optics to illuminate the sample with the desired light patterns; however, such arrangements are prone to misalignment and add cost and complexity to the microscope. Here, we present an alternative photonic chip-based two-dimensional SIM ...
    • Deep convolutional regression modelling for forest parameter retrieval 

      Björk, Sara Maria (Doctoral thesis; Doktorgradsavhandling, 2023-10-06)
      <p>Accurate forest monitoring is crucial as forests are major global carbon sinks. Additionally, accurate prediction of forest parameters, such as forest biomass and stem volume (SV), has economic importance. Therefore, the development of regression models for forest parameter retrieval is essential. <p>Existing forest parameter estimation methods use regression models that establish pixel-wise ...
    • Intermittent fluctuations in the boundary of magnetically confined fusion plasmas 

      Ahmed, Sajidah (Doctoral thesis; Doktorgradsavhandling, 2023-10-09)
      Fluctuation-induced transport in the form of hot and dense blob-like filaments is a profound concern for the successful operation of commercially-viable fusion reactors. These turbulent phenomena are inherent in the scrape-off layer (SOL), a region of magnetic field lines intersecting with the material surfaces. These filaments propagate radially outward leading to damaging plasma-wall interaction ...
    • Flyr piloter unfit? En spørreundersøkelse og sammenlignende studie 

      Enaasen, Christian Ryther; Ørsleie, Audun Angell (Master thesis; Mastergradsoppgave, 2023-06-01)
      I en verden hvor antall flybevegelser er i økning etter noen år med pandemi er piloters helse og flysikkerheten igjen blitt et tema. Piloter som går på jobb til tross for at de burde holdt seg hjemme kan potensielt utgjøre en stor sikkerhetsrisiko for seg selv og alle andre om bord på samme fly. Denne oppgaven har derfor forsket på dette temaet, med problemstillingen Flyr piloter «unfit», ...
    • Flyr piloter "unfit"? En spørreundersøkelse og sammenlignende studie 

      Ørsleie, Audun Angell; Enaasen, Christian Ryther (Master thesis; Mastergradsoppgave, 2023-06-01)
      I en verden hvor antall flybevegelser er i økning etter noen år med pandemi er piloters helse og flysikkerheten igjen blitt et tema. Piloter som går på jobb til tross for at de burde holdt seg hjemme kan potensielt utgjøre en stor sikkerhetsrisiko for seg selv og alle andre om bord på samme fly. Denne oppgaven har derfor forsket på dette temaet, med problemstillingen "Flyr piloter «unfit», og finnes ...
    • Når tiden er knapp, forholdene er tøffe, men det står liv på spill: En spørreskjemaundersøkelse om emosjonell påvirkning, beslutningstaking og CRM hos luftambulanseflygere 

      Granli, Marius Møllevik (Master thesis; Mastergradsoppgave, 2023-05-31)
      Luftambulansetjenesten HF har i dag kontrakt med Avincis Aviation Services, som opererer luftambulanseflyene i Norge. Denne delen av tjenesten hadde 109.095 oppdrag i tiårsperioden 2013-2022, hvorav 30.0% var haste- eller akuttoppdrag. Luftambulansetjenesten har blitt beskrevet av flere som en samfunnskritisk ressurs, da befolkningen i Norge har rett på lik medisinsk behandling uavhengig av ...
    • Operativ risiko i HEMS 

      Johansen, Torstein (Mastergradsoppgave; Master thesis, 2023-05-24)
      HEMS – helicopter emergency medical services – omtales i dagligtale ofte som helikopter luftambulanse. Dagens operatør Norsk Luftambulanse helikopter AS opererer alle luftambulanse helikopterbaser i Norge. Denne masteroppgaven har operativ risiko i HEMS som tema. En datainnsamling ble foretatt via elektronisk spørreskjema til samtlige operative piloter og HEMS crew members (HCM) innen HEMS i Norge, ...
    • From Waste to Value: A Practical Framework for Waste Identification and Mitigation Using Lean Management Principles 

      Barabadi, Abbas; Nouri, Ali (Chapter; Bokkapittel, 2023)
      In the complex and fast-changing marketing environment, there is a constant need to reduce costs and enhance the performance of production systems. The cost-cutting strategies need to consider the long-term effect on the company. For example, the layoff may reduce the cost in the short term, but in the long term, it may significantly affect employees' psychological safety and increase human error. ...
    • Predictive Modeling for Fair and Efficient Transaction Inclusion in Proof-of-Work Blockchain Systems 

      Tedeschi, Enrico (Doctoral thesis; Doktorgradsavhandling, 2023-10-02)
      This dissertation investigates the strategic integration of Proof-of-Work(PoW)-based blockchains and ML models to improve transaction inclusion, and consequently molding transaction fees, for clients using cryptocurrencies such as Bitcoin. The research begins with an in-depth exploration of the Bitcoin fee market, focusing on the interdependence between users and miners, and the emergence of a fee ...
    • Methods for enhanced learning using wearable technologies. A study of the maritime sector 

      Xue, Hui (Doctoral thesis; Doktorgradsavhandling, 2023-10-04)
      Maritime safety is a critical concern due to the potential for serious consequences or accidents for the crew, passengers, environment, and assets resulting from navigation errors or unsafe acts. Traditional training methods face challenges in the rapidly evolving maritime industry, and innovative training methods are being explored. This study explores the use of wearable sensors with biosignal ...
    • Postural Stability Variables for Dynamic Equilibrium 

      Dutt-Mazumder, Aviroop; Dhar, Sushmit; Dutt-Mazumder, Courtney (Journal article; Tidsskriftartikkel; Peer reviewed, 2018)
      Experiments on the maintenance of postural stability on flat stationary support surfaces (quiet standing) that show only limited modes of the potential configurations of balance stability have dominated investigations of balance in quiet upright standing. Recent studies have revealed coordination properties of the whole body in maintaining dynamic postural stability with the application of moving ...
    • Mind the gap – Relevant design for laboratory oil exposure of fish as informed by a numerical impact assessment model 

      Frøysa, Håvard Guldbrandsen; Nepstad, Raymond; Meier, Sonnich; Donald, Carey; Sørhus, Elin; Bockwoldt, Mathias; Carroll, JoLynn; Vikebø, Frode Bendiksen (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-09-09)
      Laboratory experiments provide knowledge of species-specific effects thresholds that are used to parameterize impact assessment models of oil contamination on marine ecosystems. Such experiments typically place individuals of species and life stages in tanks with different contaminant concentrations. Exposure concentrations are usually fixed, and the individuals experience a shock treatment being ...
    • Seismicity of the western-Svalbard margin and its relationship with near surface fluid flow and seepage systems - A study using ocean bottom seismometers 

      Domel, Przemyslaw (Doctoral thesis; Doktorgradsavhandling, 2023-09-28)
      Methane, a high potential greenhouse gas, travels as a fluid and releases as a gas in large quantities from the seafloor. This seepage impacts marine ecosystems and in specific cases, it has potential to reach the atmosphere, and therefore affect the climate. Gas seepage is documented worldwide, but there are still large unknowns regarding seepage dynamics, faulting/fracturing of the sediments and ...
    • Alignment of Multifrequency SAR Images Acquired over Sea Ice Using Drift Compensation 

      Demchev, Denis; Eriksson, Leif E.B.; Hildeman, Anders; Dierking, Wolfgang Fritz Otto (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-08-07)
      In this article, we investigate the feasibility to align synthetic aperture radar (SAR) imagery based on a compensation for sea ice drift occurring between temporally shifted image acquisitions. The image alignment is a requirement for improving sea ice classification by combining multifrequency SAR images acquired at different times. Images obtained at different radar frequencies provide ...
    • Hvordan skape mening av det usynlige - Et teoretisk rammeverk for sensemaking under dataangrep 

      Bjøru, Einar Lohne (Master thesis; Mastergradsoppgave, 2023-05-31)
      Dataangrep er en økende trussel blant organisasjoner og virksomheter i Norge. Et ekstra element i dette er at trusselen er vanskelig å se og forstå for aktører som ikke er utdannet eller har kompetanse på det tekniske fagfeltet. Problemstillingen for denne studien tar for seg hva som er viktig for at offentlige organisasjoner skal kunne forstå og formidle omstendighetene under et dataangrep. Studien ...
    • Cross-Domain Transfer Learning for Natural Scene Classification of Remote-Sensing Imagery 

      Akhtar, Muhammad; Murtza, Iqbal; Adnan, Muhammad; Saadia, Ayesha (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-07-05)
      Natural scene classification, which has potential applications in precision agriculture, environmental monitoring, and disaster management, poses significant challenges due to variations in the spatial resolution, spectral resolution, texture, and size of remotely sensed images of natural scenes on Earth. For such challenging problems, deep-learning-based algorithms have demonstrated amazing ...