Institutt for datateknologi og informatikk
Recent Submissions
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AI-Enhanced ABM Development: Facilitating Agent-based Modeling using Artificial Intelligence
(Doctoral theses at NTNU;2025:124, Doctoral thesis, 2025)Agent-based Modeling (ABM) is a multi-disciplinary micro-to-macro level simulation technique that is based on autonomous entity interaction – entities with the ability to learn, make decisions, and display random behaviors ... -
Decommissioning, Characterization and Proposed Recycling Route of a Used Na-ZnCl₂ Battery Cell
(Journal article; Peer reviewed, 2025)New battery technologies are necessary to cover the increasing demand for stationary energy storage as the green transition requires more use of renewable intermittent energy sources. The novel Na-ZnCl2 battery has been ... -
AIFAL-prosjekt: Allmennlegers perspektiv på muligheter og begrensninger ved bruk av KI på fastlegekontoret
(SINTEF AS (ISBN starter med 978-82-14-);, Research report, 2025)I prosjektet Allmennlegers perspektiv på muligheter og begrensninger ved bruk av AI på fastlegekontoret (AIFAL-prosjekt) har vi utforsket allmennlegenes perspektiv på bruk av kunstig intelligens (KI) og generative språkmodeller ... -
Evaluation of Escapade: An Engaging, Collaborative Multi-Role Learning Game on History
(Journal article; Peer reviewed, 2024)Game-based learning positively impacts learning performance, classroom dynamics, and attitudes of both students and teachers. While digital learning games have existed since the 1960s, most remain single- player. Although ... -
Exploring the Evolution of Educational Serious Games Research: A Topic Modeling Perspective
(Journal article; Peer reviewed, 2024)This study aims to reveal the dominant research interests and models in serious games research using topic modeling analysis. The dataset of this study covers a comprehensive collection of 2676 articles from the past to ... -
Using Graph Neural Networks in Reinforcement Learning with Application to Monte Carlo Simulations in Power System Reliability Analysis
(Journal article; Peer reviewed, 2024)This paper presents a novel method for power system reliability studies that combines graph neural networks with reinforcement learning. Monte Carlo methods are the backbone of probabilistic power system reliability analyses. ... -
Monitoring Fish Assemblages in Seasonal Off- Channel Habitats Using Underwater Video and Computer Vision
(Journal article; Peer reviewed, 2025)Floodplains provide suitable spawning and rearing habitats for many freshwater fishes and refugia from high flow events. Here, we study seasonal habitat use at the northern edge of the distribution for several spring-spawning ... -
Using Microsoft Copilot Chat in the Work of IT Educators: Pilot Study
(Journal article; Peer reviewed, 2024)Artificial intelligence (AI) chatbots have recently emerged in nearly all aspects of life, including education, where educators are exploring their potential. However, achieving proficiency remains a challenge due to ... -
Integrating pratical Sustainability tools in Software Process
(Master thesis, 2024)Med økende etterspørsel etter kraftig maskinvare og økt energiforbruk, er bærekraftig programvareutvikling essensiell for å minimere klimagassutslipp og redusere teknologibransjens karbonavtrykk. Dette arbeidet adresserer ... -
FOMOsim: An open-source simulator for rigorous analysis of micromobility planning problems
(Journal article; Peer reviewed, 2024)Existing simulation models for micromobility systems often face significant limitations: they are typically custom-built for specific contexts, lack generalizability, are not open-source, and undergo limited testing, which ... -
Promising microRNAs in pre-diagnostic serum associated with lung cancer up to eight years before diagnosis: a HUNT study
(Journal article; Peer reviewed, 2024)Introduction Blood biomarkers for early detection of lung cancer (LC) are in demand. There are few studies of the full microRNome in serum of asymptomatic subjects that later develop LC. Here we searched for novel microRNA ... -
Hate Speech Detection in Code-Mixed Datasets Using Pretrained Embeddings and Transformers
(International Conference on Frontiers of Information Technology (FIT);, Chapter, 2025)Social media platforms are more accessible than needed in this digital era. People are given the freedom to express their thoughts, their emotions, and their opinions. And this freedom is being exploited negatively. It has ... -
Large-scale Self-supervised Learning for Enhancing Accelerometer-based Human Activity and Sleep Recognition
(Doctoral theses at NTNU;2025:93, Doctoral thesis, 2025)Physical activity and sleep are crucial for an individual’s health and well-being, making accurate human activity recognition (HAR) and sleep-wake recognition (SWR) essential for public health and clinical research. ... -
Lost in Translation: Depression Detection in Multilingual Social Media
(Master thesis, 2024)Depresjon er blant de ledende årsakene til den globale helserelaterte byrden, og påvirker store deler av dagens samfunn. Verdens helseorganisasjon anslår at omtrent 280 millioner mennesker verden over lider av denne psykiske ... -
Lost in Translation: Depression Detection in Multilingual Social Media
(Master thesis, 2024)Depresjon er blant de ledende årsakene til den globale helserelaterte byrden, og påvirker store deler av dagens samfunn. Verdens helseorganisasjon anslår at omtrent 280 millioner mennesker verden over lider av denne psykiske ... -
Stitching from spectral filter array video sequences
(Peer reviewed; Journal article, 2024) -
Metrology-Based Statistical Framework for Monitoring Changes in Hyperspectral Datasets of Artworks
(Journal article; Peer reviewed, 2024)Hyperspectral imaging is a valuable technique for preserving and monitoring cultural heritage objects. Over time, artworks can undergo subtle changes due to environmental factors or handling during loan periods, making it ... -
Spatially Constrained Hyperspectral Pigment Mapping using Watershed Segmentation
(Peer reviewed; Journal article, 2024) -
Better and safer autonomous driving with predicted object relevance
(Chapter, 2024)Object detection in autonomous driving consists in perceiving and locating instances of objects in multi-dimensional data, such as images or LIDAR scans. Very recently, multiple works are proposing to evaluate object ...
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