Recent Submissions

  • Digital Significance 

    Sanchez Laws, Ana Luisa (Chapter, 2023)
    This chapter proposes the idea of ‘digital significance’ as a governance and decision- making process for assessing the value of digital collections. This concept is inspired by Australian approaches to valuing heritage, ...
  • A Multi-channel EEG Data Analysis for Poor Neuro-prognostication in Comatose Patients with Self and Cross-channel Attention Mechanism 

    Qadir, Hemin Ali; Nesaragi, Naimahmed; Halvorsen, Per Steinar; Balasingham, Ilangko (Chapter, 2023)
  • Exploring the Role of UX Influencing Factors in Virtual Reality for Natural Hazards Prepardness: A Disign-Based Approach 

    Irshad, Shafaq (Doctoral theses at NTNU;2024:152, Doctoral thesis, 2024)
    Climate change is one of the major challenges of our time, and its complexity makes finding innovative solutions challenging. One of the ways that climate change poses a challenge is by reshaping the earth’s natural ecosystem ...
  • Distributed Detection and Localization 

    Tabella, Gianluca (Doctoral theses at NTNU;2024:84, Doctoral thesis, 2024)
    This thesis delves into the detection and localization aspects of distributed Wireless Sensor Networks (WSNs). Specifically, the research concentrates on WSNs in which sensors autonomously carry out detection tasks and ...
  • NIRCA MkII DevKit Firmware Development 

    Øfsti, Gjermund Sollien (Master thesis, 2024)
    NIRCA MkII Development Board(NM2DB) er en PCB med NIRCA MkII(NM2), en ASIC brukt til kontroll og utlesning av infrarøde sensorer. PCBen har også en Trenz FPGA "system-på-modul" brukt til kontroll av ASICen, LDOer og for ...
  • Computationally-Efficient Structural Health Monitoring using Graph Signal Processing 

    Cheema, Muhammad Asaad; Sarwar, Muhammad Zohaib; Gogineni, Vinay Chakravarthi; Cantero Lauer, Daniel; Salvo Rossi, Pierluigi (Peer reviewed; Journal article, 2024)
    Structural health monitoring (SHM) of bridges is crucial for ensuring safety and long-term durability, however, standard damage-detection algorithms are computationally intensive. This article proposes a computationally ...
  • Optimization of Extracellular Vesicle Release for Targeted Drug Delivery 

    Damrath, Martin; Veletic, Mladen; Rudsari, Hamid Khoshfekr; Balasingham, Ilangko Sellappah (Journal article, 2023)
    Targeted drug delivery is a promising approach for many serious diseases, such as glioblastoma multiforme, one of the most common and devastating brain tumor. In this context, this work addresses the optimization of the ...
  • Classification of Kidney Tumor Grading on Preoperative Computed Tomography Scans 

    Mahootiha, Maryamalsadat; Qadir, Hemin Ali; Bergsland, Jacob; Balasingham, Ilangko Sellappah (Chapter, 2023)
    Deep learning (DL) has proven itself as a powerful tool to capture patterns that human eyes may not be able to perceive when looking at high-dimensional data such as radiological data (volumetric data). For example, the ...
  • Fish Monitoring in Aquaculture Using Multibeam Echosounders and Machine Learning 

    Kristmundsson, Johannus; Patursson, Oystein; Potter, John Robert; Xin, Qin (Peer reviewed; Journal article, 2023)
    Offshore salmon aquaculture is a growing industry that faces challenges such as sea lice infestations and varying environmental conditions, necessitating the development of new monitoring systems to improve fish welfare ...
  • Experimental assessment of a JANUS-based consensus protocol 

    Wengle, Johan Emil Hugo; Erstorp, Elias Strandell; Lidström, Viktor; Varagnolo, Damiano; Dong, Hefeng (Journal article; Peer reviewed, 2024)
    This paper proposes a distributed, JANUS-based protocol that enables an underwater acoustic network to reach consensus on arbitrary local opinions as numeric state variables. An envisioned scenario where nodes shall agree ...
  • Bayesian Fault Detection and Localization Through Wireless Sensor Networks in Industrial Plants 

    Tabella, Gianluca; Ciuonzo, Domenico; Paltrinieri, Nicola; Salvo Rossi, Pierluigi (Peer reviewed; Journal article, 2024)
    This work proposes a data fusion approach for quickest fault detection and localization within industrial plants via wireless sensor networks. Two approaches are proposed, each exploiting different network architectures. ...
  • On Enabling Scalable, Personalized, and Private Federated Learning 

    Gauthier, François (Doctoral theses at NTNU;2024:92, Doctoral thesis, 2024)
    This thesis investigates distributed machine learning for emerging Internet of Things (IoT) and Cyber-Physical Systems (CPS) applications. These applications involve large-scale data collection from distributed, often ...
  • Multi-Period Hybrid AC/DC-OPF Model for Flexibility Market Clearing With Seamless TSO-DSO Coordination 

    Sierazewski, Damian; Olsen, Ole Kjærland; Ivanko, Dmytro; Oleinikova, Irina; Farahmand, Hossein (Journal article; Peer reviewed, 2023)
    Unlocking flexibility assets from the consumer side and developing a well-functioning flexibility market (FM) is crucial to address the oncoming challenges in the EU power grid. In these conditions, the coordination between ...
  • Onboard Hyperspectral Classification Enables Georeferencing 

    Langer, Dennis David; Garrett, Joseph Landon; Birkeland, Roger; Berg, Simen; Orlandic, Milica (Journal article; Peer reviewed, 2023)
    The Norwegian University of Science and Technology (NTNU) has been building a system composed of multiple remote sensing agents for ocean observations. NTNU launched the first HYPerspectral Smallsat for Ocean observation ...
  • Multimodal deep learning for personalized renal cell carcinoma prognosis: Integrating CT imaging and clinical data 

    Mahootiha, Maryamalsadat; Qadir, Hemin Ali; Bergsland, Jacob; Balasingham, Ilangko (Peer reviewed; Journal article, 2023)
    Background and Objective: Renal cell carcinoma represents a significant global health challenge with a low survival rate. The aim of this research was to devise a comprehensive deep-learning model capable of predicting ...
  • Designing of an Enhanced Fuzzy Logic Controller of an Interior Permanent Magnet Synchronous Generator under Variable Wind Speed 

    Masoud, Uossif Mohamed Matoug; Tiwari, Pratibha; Gupta, Nishu (Journal article; Peer reviewed, 2023)
    On account of active governmental stimulation operations in many countries, the residential production of electricity from renewable resources has increased considerably. Due to high efficiency and reliability, a recommended ...
  • Lens Flare Attenuation Accelerator Design with Deep Learning and High-Level Synthesis 

    Gamarra, David Fosca; Kjeldsberg, Per Gunnar; Sundbeck, Henrik Valø (Chapter; Conference object, 2023)
    Lens flare artifacts are undesired visual distortions caused by stray light, which can negatively impact the integrity and quality of an image. These artifacts pose a significant challenge in industrial applications like ...
  • rockphypy: An extensive Python library for rock physics modeling 

    Yu, Junbo; Mukerji, Tapan; Avseth, Per Åge (Peer reviewed; Journal article, 2023)
    Rock physics aims to understand the relationship between the physical properties of rocks and geophysical observables under various conditions. The generic knowledge provides valuable insights into the behavior of subsurface ...
  • Performance Evaluation of an Open Source Implementation of a 5G Standalone Platform 

    Håkegård, Jan Erik; Lundkvist, Henrik Nils Oskar; Rauniyar, Ashish; Morris, Peter Keenan (Peer reviewed; Journal article, 2024)
    Fifth-generation (5G) mobile communication systems are currently implemented worldwide. Moreover, the diversity between different deployments is growing, from operator-deployed macro networks to local private networks. The ...
  • Diving-wave time-lapse delay for CO2 thin layer detection 

    Martinez Guzman, Ricardo Jose; Vinje, Vetle; Stovas, Alexei; Mispel, Joachim; Ringrose, Philip Stefan; Duffaut, Kenneth; Landrø, Martin (Peer reviewed; Journal article, 2024)
    We have derived an analytical approximate expression to estimate the delay in diving seismic waves due to thin layers of CO2. The expression is valid for high frequencies and can be used to estimate the delay in diving ...

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