• Uncertainty quantification in large language models through convex hull analysis 

  Catak, Ferhat Özgur; Kuzlu, Murat (Peer reviewed; Journal article, 2024-11)

  Uncertainty quantification approaches have been more critical in large language models (LLMs), particularly high-risk applications requiring reliable outputs. However, traditional methods for uncertainty quantification, ...

• NMGrad: Advancing Histopathological Bladder Cancer Grading with Weakly Supervised Deep Learning 

  Fuster Navarro, Saul; Kiraz, Umay; Eftestøl, Trygve Christian; Janssen, Emiel; Engan, Kjersti (Peer reviewed; Journal article, 2024)

  The most prevalent form of bladder cancer is urothelial carcinoma, characterized by a high recurrence rate and substantial lifetime treatment costs for patients. Grading is a prime factor for patient risk stratification, ...

• Santa has Everything under Control: A Control Themed Advent Calendar 

  Knorn, Steffi; Visioli, Antonio; Stoica, Cristina; Lichtenberg, Gerwald; Varagnolo, Damiano; Sanchez Corrales, Helem Sabina; Rotondo, Damiano; Guzman, Jose Luis (Peer reviewed; Journal article, 2024-11)

  We describe the process of creating a control themed advent calendar quiz by means of a joint effort of researchers involved in control education from different countries, of distributing it among our students, and of ...

• Integration of Local Energy Communities in Electricity Distribution Grids: FINE project deliverable 

  Askeland, Magnus; Bjarghov, Sigurd Nikolai; Taxt, Henning; Berg, Kjersti; Morch, Andrei Z; Rana, Rubi; Degefa, Merkebu Zenebe; Crespo del Granado, Pedro Andres (SINTEF Energi. Rapport;, Research report, 2024)

  This report investigates the integration of Local Energy Communities (LECs) into electricity distribution networks, with a focus on enhancing grid flexibility, optimizing resource use, and supporting the transition to ...

• Enhancing Safety and Privacy in Industry 4.0: The ICE Laboratory Case Study 

  Cunico, Federico; Aldegheri, Stefano; Avogaro, Andrea; Boldo, Michele; Bombieri, Nicola; Capogrosso, Luigi; Caputo, Ariel; Carra, Damiano; Centomo, Stefano; Cheng, Dong Seon; Cinquetti, Ettore; Cristani, Marco; Marchi, Mirco De; Demrozi, Florenc; Emporio, Marco; Fummi, Franco; Geretti, Luca; Germiniani, Samuele; Giachetti, Andrea; Girella, Federico; Martini, Enrico; Menegaz, Gloria; Muijs, Niek; Paci, Federica; Panato, Marco; Pravadelli, Graziano; Quintarelli, Elisa; Siviero, Ilaria; Storti, Silvia Francesca; Tadiello, Carlo; Turetta, Cristian; Villa, Tiziano; Zannone, Nicola; Quaglia, Davide (Peer reviewed; Journal article, 2024)

  he revolutionary technologies behind Industry 4.0 have opened a new era for manufacturing: connected and autonomous machines, collaborative robotics, and monitoring techniques are spreading to increase productivity and ...

• Journey mapping the digital remote care services: Problems and opportunities for a large-scale implementation in China 

  Li, Hong; Grisot, Miria (Peer reviewed; Journal article, 2024)

  Digital remote care has emerged as a transformative approach in the delivery of healthcare services. This paper presents an empirical case study that investigates the utilization of digital remote care for postoperative ...

• Balancing privacy and progress in artificial intelligence : Anonymization in histopathology for biomedical research and education 

  Kanwal, Neel; Janssen, Emiel; Engan, Kjersti (Frontiers of Artificial Intelligence, Ethics and Multidisciplinary Applications;, Chapter, 2024)

  The advancement of biomedical research heavily relies on access to large amounts of medical data. In the case of histopathology, Whole Slide Images (WSI) and clinicopathological information are valuable for developing ...

• DRL-Based Availability-Aware Migration of a MEC Service 

  Sarah, Annisa; Nencioni, Gianfranco; Khan, Md Muhidul Islam (Peer reviewed; Journal article, 2024)

  Multi-access Edge Computing (MEC) allows a mobile user to access a service on a computing device called MEC Host (MEH), enabling lower latency by running the service closer to the users. When the user moves away from the ...

• Software Bill of Materials in Critical Infrastructure 

  Jaatun, Lars Andreassen; Sørlien, Silje Marie; Borgaonkar, Ravishankar Bhaskarrao; Steve, Taylor; Jaatun, Martin Gilje (Chapter, 2024)

  Critical infrastructure today is comprised of cyber-physical systems, and therefore also vulnerable to cyber threats. Many of these threats come from within, through malicious code in software updates or bugs that can be ...

• Improving predictive models for rate of penetration in real drilling operations through transfer learning 

  Pacis, Felix James Cardano; Ambrus, Adrian; Alyaev, Sergey; Khosravanian, Rasool; Kristiansen, Tron Golder; Wiktorski, Tomasz (Peer reviewed; Journal article, 2023-09)

  The rate of penetration (ROP) is a key performance indicator in the oil and gas drilling industry as it directly translates to cost savings and emission reductions. A prerequisite for a drilling optimization algorithm is ...

• Building Precision: Efficient Encoder-Decoder Networks for Remote Sensing Based on Aerial RGB and LiDAR Data 

  Sulaiman, Muhammad; Finnesand, Erik; Farmanbar, Mina; Belbachir, Ahmed Nabil; Rong, Chunming (Peer reviewed; Journal article, 2024-04)

  Precision in building delineation plays a pivotal role in population data analysis, city management, policy making, and disaster management. Leveraging computer vision technologies, particularly deep learning models for ...

• SHPIA 2.0: An Easily Scalable, Low-Cost, Multi-purpose Smart Home Platform for Intelligent Applications 

  Demrozi, Florenc; Turetta, Cristian; Pravadelli, Graziano (Peer reviewed; Journal article, 2023-11)

  Sensors, electronic devices, and smart systems have invaded the market and our daily lives. As a result, their utility in smart home contexts to improve the quality of life, especially for the elderly and people with special ...

• Adaptive Methods for Revenue Model learning of a Slice Broker in the Presence of Adversaries 

  Khan, Md Muhidul Islam; Nencioni, Gianfranco (Peer reviewed; Journal article, 2024)

  In the fifth-generation (5G) of mobile networks, Multi-Access Edge Computing (MEC) refers to the deployment of computing resources closer to the end-users for improved service delivery. In the context of 5G MEC, the slice ...

• Artificial Intelligence in Digital Pathology for Bladder Cancer: Hype or Hope? A Systematic Review 

  Khoraminia, Farbod; Fuster Navarro, Saul; Kanwal, Neel; Olislagers, Mitchell; Engan, Kjersti; Leenders, Geet J.L.H. Van; Stubbs, Andrew P; Akram, Farhan; Zuiverloon, Tahlita C.M. (Peer reviewed; Journal article, 2023)

  Bladder cancer (BC) diagnosis and prediction of prognosis are hindered by subjective pathological evaluation, which may cause misdiagnosis and under-/over-treatment. Computational pathology (CPATH) can identify clinical ...

• Field Telemetry Drilling Dataset Modeling with Multivariable Regression, Group Method Data Handling, Artificial Neural Network, and the Proposed Group-Method-Data-Handling-Featured Artificial Neural Network 

  Amir, Mohammad; Agonafir, Mesfin Belayneh (Peer reviewed; Journal article, 2024)

  This paper presents data-driven modeling and a results analysis. Group method data handling (GMDH), multivariable regression (MVR), artificial neuron network (ANN), and new proposed GMDH-featured ANN machine learning ...

• Investigation of the Effect of Fracturing Fluids on Shale Pore Structure by Nuclear Magnetic Resonance 

  Zhu, Xiulan; Wang, Zhiguo; You, Yang; Zhang, Chuang; Gao, Hui; Zhang, Nan; Li, Teng; Wang, Chen; Cheng, Zhilin (Peer reviewed; Journal article, 2023)

  Hydraulic fracturing technology significantly enhances the productivity of shale oil and gas reservoirs. Nonetheless, the infiltration of fracturing fluid into shale formations can detrimentally affect the microscopic pore ...

• RiskTUN: An ICT-based Concept for a Risk-aware Decision Support System for Tunnel Safety 

  Khademi, Naeem; Bjelland, Henrik; Nilsson, Erik Gøsta; Boletsis, Costas (Chapter, 2023)

  Safety in road tunnels are of utmost importance for the public notion of safety within the road system. In recent years, there has been significant progress in multiple areas of artificial intelligence, sensor fusion and ...

• Virtual Actuator and Sensor Fault Tolerant Consensus for Homogeneous Linear Multi-Agent Systems 

  Rotondo, Damiano; Theilliol, Didier; Ponsart, Jean-Christophe (Peer reviewed; Journal article, 2023)

  This paper presents a fault tolerant consensus protocol for homogeneous linear multi-agent systems using virtual actuators and virtual sensors. By means of the virtual actuators/sensors, the faulty system is reconfigured ...

• From Baseline to Top Performer: A Reproducibility Study of Approaches at the TREC 2021 Conversational Assistance Track 

  Lajewska, Weronika; Balog, Krisztian (Chapter, 2023)

  This paper reports on an effort of reproducing the organizers’ baseline as well as the top performing participant submission at the 2021 edition of the TREC Conversational Assistance track. TREC systems are commonly regarded ...

• Modeling and identification of the Quanser Aero using a detailed description of friction and centripetal forces 

  Dyvik, Mathias; Fjereide, Didrik Efjestad; Rotondo, Damiano (Chapter, 2023)

  This paper deals with the modeling and identification of the Quanser Aero. The Quanser Aero is an aerospace laboratory setup designed for teaching aerospace concepts. Two propellers generate thrust and allow the user to ...

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