Recent additions

  • Synthetic wavelength scanning interferometry for 3D surface profilometry with extended range of height measurement using multi-colour LED light sources 

    Mann, Priyanka; Dubey, Vishesh Kumar; Ahmad, Azeem; Butola, Ankit; Mehta, Dalip Singh (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-04-05)
    We report three-dimensional surface profilometry with extended range of height measurements using synthetic wavelength scanning interferometry without tunable filters, wavelength-tuning lasers, grating elements. We have used inexpensive multiple colour light emitting diodes (LEDs) and operate them sequentially one by one or combination of two or more colours simultaneously to visualize synthetic ...
  • D3.3 (M18) - Report on curation in core ELIXIR registries (an ELIXIR Norway ELIXIR3 deliverable) 

    Bösl, Korbinian Michael; Fatima, Nazeefa; Gundersen, Sveinung; Klemetsen, Terje; Petters, Sebastian; Åberg, Espen (Research report; Forskningsrapport, 2023-10-01)
    This report serves as an update on the progress of WP3 Task 3.4 in ELIXIR3, in support of curation efforts on content in repositories of metadata, datasets, tools, training, workflows, and other resources, in line with the ELIXIR Platforms. The report documents progress made, methods used, and plans for the near future as of month 18 of a 48-month timeline. ELIXIR Norway extends support to numerous ...
  • Biological Evaluations, NMR Analyses, Molecular Modeling Studies, and Overview of the Synthesis of the Marine Natural Product (−)-Mucosin 

    Nolsøe, Jens Mortansson Jelstrup; Underhaug, Jarl; Sørskår, Åshild Moi; Antonsen, Simen; Malterud, Karl Egil; Gani, Osman; Fan, Qiong; Hjorth, Marit; Sæther, Thomas; Hansen, Trond Vidar; H. Stenstrøm, Yngve (Journal article; Tidsskriftartikkel; Peer reviewed, 2024-02-24)
    Natural products obtained from marine organisms continue to be a rich source of novel structural architecture and of importance in drug discovery, medicine, and health. However, the success of such endeavors depends on the exact structural elucidation and access to sufficient material, often by stereoselective total synthesis, of the isolated natural product of interest. (−)-Mucosin (1), a fatty ...
  • Reliability Assessment of Computer in Design Phase Under High Censored Setting 

    Yuan, Fuqing; Lu, Jinmei (Chapter; Bokkapittel, 2023-02-01)
    Assessment of reliability of personal computer is a challenge for the developer as the lack of sufficient data. Ordinary statistical approach depending on large dataset has less convincible result for the developer to make decision. Prior to massive production, the computer manufacturer runs a life test by picking up a certain number of new computers to run to failure to enlarge the data set. ...
  • Uncertainties in Managing Atmospheric Icing on Power Lines 

    VAHHABI, MOHSEN; Barabadi, Abbas; Barabady, Javad; Nouri, Ali (Chapter; Bokkapittel, 2023)
    Icing affects the infrastructure dramatically, especially in the cold region. Therefore, applying effective ice disaster management (IDM) to provide a systematic approach to dealing with atmospheric icing on power lines is essential. It includes preparedness, response, recovery, learning, risk assessment, and prevention. Integral to this management is the accurate prediction and modeling of icing, ...
  • The Effect of LNG and Diesel Fuel Emissions of Marine Engines on GHG-Reduction Revenue Policies Under Life-Cycle Costing Analysis in Shipping 

    Taghavifar, Hadi; Perera, Lokukaluge Prasad Channa (Chapter; Bokkapittel, 2023)
    The fuel life cycle involves different phases of extraction/refinery (well to tank: WtT), transport (tank to propeller: TtP), and storage where each of these processes can add a specific amount of emissions to the overall LCCA inventory. During the extraction or operation of machinery on the raw material, the released amount of GHG components is undergoing a change in the generated emissions per ...
  • Trustworthiness Evaluation Framework for Digital Ship Navigators in Bridge Simulator Environments 

    Namazi Rabati, Hosna; Perera, Lokukaluge Prasad Channa (Chapter; Bokkapittel, 2023)
    The maritime industry is going towards implementing digital navigators, i.e., AI created by machine learning algorithms, on autonomous vessels in the future. Digital navigators can be developed by utilizing machine learning algorithms, e.g., deep learning type neural networks trained by data sets from human navigators. Even though there is significant importance in studying the trustworthiness of ...
  • Multiple Model Adaptive Estimation Coupled With Nonlinear Function Approximation and Gaussian Mixture Models for Predicting Fuel Consumption in Marine Engines 

    Taghavi, Mahmood; Perera, Lokukaluge Prasad Channa (Chapter; Bokkapittel, 2023)
    Digital twin type models can be developed for physical systems that are complex nonlinear a system of systems (SoS). However, such models are usually difficult to represent by linear equations. Therefore, an adequate linearization technique should be introduced. Therefore, linear models as digital twins can be interpreted easily and need much less computational power when applied to various industrial ...
  • Preventing E. coli Biofilm Formation with Antimicrobial Peptide-Functionalized Surface Coatings: Recognizing the Dependence on the Bacterial Binding Mode Using Live-Cell Microscopy 

    Hansson, Adam; Karlsen, Eskil André; Stensen, Wenche Gunvor B; Svendsen, John Sigurd Mjøen; Berglin, Mattias; Lundgren, Anders (Journal article; Tidsskriftartikkel; Peer reviewed, 2024-01-31)
    Antimicrobial peptides (AMPs) can kill bacteria by destabilizing their membranes, yet translating these molecules’ properties into a covalently attached antibacterial coating is challenging. Rational design efforts are obstructed by the fact that standard microbiology methods are ill-designed for the evaluation of coatings, disclosing few details about why grafted AMPs function or do not ...
  • Unpacking uncertainty in regional avalanche forecasting: A quantitative case study of uncertainty in forecasting regional avalanche danger 

    Karlsen, Kristoffer (Master thesis; Mastergradsoppgave, 2023-12-10)
    When assessing a risk, a future event, uncertainty is vital as we cannot know what will happen. Having an active relationship to uncertainty can reduce it and help the decision-makers make informed decisions. Avalanche forecasting is widely used by outdoor recreational and local authorities for emergency preparedness use. Therefore, an additional focus on uncertainty in this field benefits people ...
  • Power availability of PV plus thermal batteries in real-world electric power grids 

    Foldvik Eikeland, Odin; Kelsall, Colin C.; Buznitsky, Kyle; Verma, Shomik; Bianchi, Filippo Maria; Chiesa, Matteo; Henry, Asegun (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-07-25)
    As variable renewable energy sources comprise a growing share of total electricity generation, energy storage technologies are becoming increasingly critical for balancing energy generation and demand.<p> <p>In this study, a real-world electricity system was modeled rather than modeling hypothetical future electric power systems where the existing electricity infrastructure are neglected. In ...
  • The expressive power of pooling in Graph Neural Networks 

    Bianchi, Filippo Maria; Lachi, Veronica (Journal article; Tidsskriftartikkel; Peer reviewed, 2023)
    In Graph Neural Networks (GNNs), hierarchical pooling operators generate local summaries of the data by coarsening the graph structure and the vertex features. While considerable attention has been devoted to analyzing the expressive power of message-passing (MP) layers in GNNs, a study on how graph pooling affects the expressiveness of a GNN is still lacking. Additionally, despite the recent advances ...
  • Total Variation Graph Neural Networks 

    Hansen, Jonas Berg; Bianchi, Filippo Maria (Journal article; Tidsskriftartikkel, 2023-07)
    Recently proposed Graph Neural Networks (GNNs) for vertex clustering are trained with an unsupervised minimum cut objective, approximated by a Spectral Clustering (SC) relaxation. However, the SC relaxation is loose and, while it offers a closed-form solution, it also yields overly smooth cluster assignments that poorly separate the vertices. In this paper, we propose a GNN model that computes cluster ...
  • Advanced data cluster analyses in digital twin development for marine engines towards ship performance quantification 

    Taghavi, Mahmood; Perera, Lokukaluge Prasad Channa (Journal article; Tidsskriftartikkel; Peer reviewed, 2024-02-24)
    Due to the growing rate of energy consumption, it is necessary to develop frameworks for enhancing ship energy efficiency. This paper proposes a solution for this issue by introducing a digital twin framework for quantifying ship performance. For this purpose, extensive low-level clustering is performed using Gaussian Mixture Models (GMM) with the Expectation Maximization algorithm on a dataset ...
  • On C-class equations 

    Čap, Andreas; Doubrov, Boris; The, Dennis (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-09-29)
    The concept of a C-class of differential equations goes back to E. Cartan with the upshot that generic equations in a C-class can be solved without integration. While Cartan’s definition was in terms of differential invariants being first integrals, all results exhibiting C-classes that we are aware of are based on the fact that a canonical Cartan geometry associated to the equations in the class ...
  • Energy-Efficient Marine Engine and Dynamic Wing Evaluation Under Laboratory Conditions to Achieve Emission Reduction Targets in Shipping 

    Perera, Lokukaluge Prasad Channa; Belibassakis, Kostas (Chapter; Bokkapittel, 2023-09-22)
    There is a requirement to comply with the forthcoming IMO & EU requirements to reduce ship emissions by at least 40% in 2030 compared to the 2008 levels. Such medium-term emission reduction targets can only be achieved by introducing novel technologies into the shipping industry. The SeaTech H2020 project (seatech2020.eu) introduces two main innovations that can support the same emission reduction ...
  • Data Augmentation for SAR Sea Ice and Water Classification Based on Per-Class Backscatter Variation With Incidence Angle 

    WANG, QIANG; Lohse, Johannes; Doulgeris, Anthony Paul; Eltoft, Torbjørn (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-07-03)
    Monitoring sea ice in polar regions is critical for understanding global climate change and supporting marine navigation. Recently, researchers started to utilize machine/deep learning methodologies to automate the separation of sea ice and open water in synthetic aperture radar imagery. However, this requires a large amount of reliably labeled training data. We here propose an augmentation routine ...
  • Airborne Investigation of Quasi-Specular Ku-Band Radar Scattering for Satellite Altimetry Over Snow-Covered Arctic Sea Ice 

    de Rijke Thomas, Claude; Landy, Jack Christopher; Mallett, Robbie; Willatt, Rosemary; Tsamados, Michel; King, Joshua (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-09-22)
    Surface-based Ku-band radar altimetry investigations indicate that the radar signal is typically backscattered from well above the snow–sea ice interface. However, this would induce a bias in satellite altimeter sea ice thickness retrievals not reflected by buoy validation. Our study presents a mechanism to potentially explain this paradox: probabilistic quasi-specular radar scattering from the ...
  • Conceptualizing AMR as a creeping disaster in terms of pace and space 

    Staupe-Delgado, Reidar; Engstrom, Alina; Cadiz, Sebastian Andres Frugone (Chapter; Bokkapittel, 2023)
    Traditionally defined, disasters are understood as relatively limited in duration. Yet we also know that some disasters are of a creeping and indeed perpetual nature – their onsets do not seize to advance. One example is AMR. In theory, it should be easier to respond to such creeping disasters as a result of their slow build up. In reality, however, swift response to creeping disasters rarely ...
  • The challenges experts face during creeping crises: the curse of complacency 

    Zaman, Ahmad Wesal; Rubin, Olivier; Staupe, Reidar (Journal article; Tidsskriftartikkel; Peer reviewed, 2024-01-05)
    The policy literature has generally conceptualised crises as urgent public threats with clearly demarcated ‘focusing events’. Consequently, most studies have identified the main challenges faced by expert agencies involved in evidence-based policymaking as managing uncertainty, time pressure and communication. However, less focus has been devoted to analysing the concrete challenges faced by expert ...

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