English
norskArtikler, rapporter og annet (informatikk): Recent submissions
Now showing items 1-20 of 436
-
AC Microgrid Modeling and Adaptive Control Using Biomimetic Valence Learning: An AI-Based Approach
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-11-04)AC microgrids play a crucial role in integrating distributed energy resources and facilitating localized power management in contemporary power networks. Nevertheless, conventional droop control methods in these microgrids have constraints in guaranteeing precise power distribution, stability of voltage/frequency, and flexibility in response to changing operating conditions. This study introduces ... -
ANN-Based Real-Time Optimal Voltage Control In Islanded AC Microgrids
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-09-18)The purpose of this paper is to explore an innovative primary control strategy for a voltage source inverter (VSI). This strategy involves integrating an Artificial Neural Network (ANN) into the proportional resonant (PR) regulator within the inner loop of the primary control system. The primary objective is to regulate the output voltage and minimize deviations under various operating conditions, ... -
Consent Management System on Patient-Generated Health Data
(Chapter; Bokkapittel, 2024)We consent to many things in life, but sometimes we do not know what we consent to. When discussing data protection in Europe, consent has been associated with permission under the GDPR, and health data are highly sensitive. Patients cannot make an informed decision without being provided with the information they need upfront: no informed decision, no informed consent. This paper presents a consent ... -
AI-Based Cropping of Soccer Videos for Different Social Media Representations
(Chapter; Bokkapittel, 2024-01-29)The process of re-publishing soccer videos on social media often involves labor-intensive and tedious manual adjustments, particularly when altering aspect ratios while trying to maintain key visual elements. To address this issue, we have developed an AI-based automated cropping tool called SmartCrop which uses object detection, scene detection, outlier detection, and interpolation. This innovative ... -
SmartCrop-H: AI-Based Cropping of Ice Hockey Videos
(Chapter; Bokkapittel, 2024-04-17)Sports multimedia plays a central role in captivating audiences on social media platforms. However, fast-paced sports such as ice hockey pose unique challenges due to their swift gameplay and the small puck size, making object tracking-based video adaptation for social media a complex task. In this context, we introduce SmartCrop-H, an innovative ice hockey video cropping tool powered by advanced ... -
Representing Power Variability of an Idle IoT Edge Node in the Power State Model
(Chapter; Bokkapittel, 2023-05-01)Simulations can be used to efficiently predict and explore energy consumption of nodes in cyber-physical and IoT systems. The Power State Model (PSM), widely used in simulators, uses only a single value for the energy consumption, for each power state of a node. However, for a given state (including the idle state) the actual consumed energy can vary. Consequently, PSM having a single value only per ... -
Design and Evaluation of Single-Board Computer Based Power Monitoring for IoT and Edge Systems
(Chapter; Bokkapittel, 2023-05-01)Internet of Things (IoT) and edge platforms are very complex systems. They are heterogeneous in terms of hardware and software. In these systems, being able to document the energy consumed by the nodes is important. To mitigate the impact of such systems on the energy consumption and improve their energy efficiency, research experiments involving power monitoring tools are required.However, in the ... -
Compact representation for memory-efficient storage of images using genetic algorithm-guided key pixel selection
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-11-04)In the past few years, we have observed rapid growth in digital content. Even in the biological domain, the arrival of microscopic and nanoscopic images and videos captured for biological investigations increases the need for space to store them. Hence, storing these data in a storage-efficient manner is a pressing need. In this work, we have introduced a compact image representation technique with ... -
AI-Based Cropping of Ice Hockey Videos for Different Social Media Representations
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-08-23)Sports multimedia is among the most prominent types of content distributed across social media today, and the retargeting of videos for diverse aspect ratios is essential for a suitable representation on different social media platforms. In this respect, ice hockey is quite challenging due to its agile movement pattern and speed, and because the main reference point (puck) is very small. In this ... -
Validating polyp and instrument segmentation methods in colonoscopy through Medico 2020 and MedAI 2021 Challenges
(Journal article; Tidsskriftartikkel; Peer reviewed, 2025-09-05)Automatic analysis of colonoscopy images has been an active field of research motivated by the importance of early detection of precancerous polyps. However, detecting polyps during the live examination can be challenging due to various factors such as variation of skills and experience among the endoscopists, lack of attentiveness, and fatigue leading to a high polyp miss-rate. Therefore, there is ... -
A Theoretical and Empirical Analysis of 2D and 3D Virtual Environments in Training for Child Interview Skills
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-08-12)This paper presents a detailed study of an AI-driven platform designed for the training of child welfare and law enforcement professionals in conducting investigative interviews with maltreated children. It achieves a subjective simulation of interview situation through the integration of fine-tuned GPT-3 models within the Unity framework. The study recruited participants from a range of backgrounds, ... -
Machine learning based prognostics and statistical optimization of the performance of biogas-biodiesel blends powered engine
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-09-12)In this study, waste biomass-derived biogas was employed as the main fuel while the biodiesel-diesel blend was used as pilot fuel. This paper describes the development of a Decision Tree and Response Surface methodology-based statistical framework for prediction modeling and optimization. The compression ratio, fuel injection time, fuel injection pressure, and biogas flow rate were employed as ... -
Leveraging explainable artificial intelligence for early prediction of bloodstream infections using historical electronic health records
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-11-14)Bloodstream infections (BSIs) are a severe public health threat due to their rapid progression into critical conditions like sepsis. This study presents a novel eXplainable Artificial Intelligence (XAI) framework to predict BSIs using historical electronic health records (EHRs). Leveraging a dataset from St. Olavs Hospital in Trondheim, Norway, encompassing 35,591 patients, the framework integrates ... -
Enhancing Medical Image Quality Using Fractional Order Denoising Integrated with Transfer Learning
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-08-29)In medical imaging, noise can significantly obscure critical details, complicating diagnosis and treatment. Traditional denoising techniques often struggle to maintain a balance between noise reduction and detail preservation. To address this challenge, we propose an “Efficient Transfer-Learning-Based Fractional Order Image Denoising Approach in Medical Image Analysis (ETLFOD)” method. Our approach ... -
AI-Based Cropping of Ice Hockey Videos for Different Social Media Representations
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-08-23)Sports multimedia is among the most prominent types of content distributed across social media today, and the retargeting of videos for diverse aspect ratios is essential for a suitable representation on different social media platforms. In this respect, ice hockey is quite challenging due to its agile movement pattern and speed, and because the main reference point (puck) is very small. In this ... -
Variation in Accelerometer-Derived Instantaneous Acceleration Distribution Curves of Elite Male Soccer Players According to Playing Position: A Pilot Study
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-09-23)The incorporation of triaxial accelerometers into Global Positioning Systems (GPS) has significantly advanced our understanding of accelerations in sports. However, inter-positional differences are unknown. This study aimed to explore the variability of acceleration and deceleration (Acc) distribution curves according to players’ positions during soccer matches. Thirty-seven male players from a ... -
Using power system modelling outputs to identify weather-induced extreme events in highly renewable systems
(Journal article; Tidsskriftartikkel, 2024-04-26)In highly renewable power systems the increased weather dependence can result in new resilience challenges, such as renewable energy droughts, or a lack of sufficient renewable generation at times of high demand. The weather conditions responsible for these challenges have been well-studied in the literature. However, in reality multi-day resilience challenges are triggered by complex interactions ... -
A Theoretical and Empirical Analysis of 2D and 3D Virtual Environments in Training for Child Interview Skills
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-08-12)This paper presents a detailed study of an AI-driven platform designed for the training of child welfare and law enforcement professionals in conducting investigative interviews with maltreated children. It achieves a subjective simulation of interview situation through the integration of fine-tuned GPT-3 models within the Unity framework. The study recruited participants from a range of backgrounds, ... -
Propagating Transparency: A Deep Dive into the Interpretability of Neural Networks
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-08-19)In the rapidly evolving landscape of deep learning (DL), understanding the inner workings of neural networks remains a significant challenge. The need for transparency and accountability in DL models grows in importance as they become more prevalent in decision-making processes. Interpreting these models is key to addressing this challenge. This paper offers a comprehensive overview of interpretable ... -
Breast Cancer Detection and Analytics Using Hybrid CNN and Extreme Learning Machine
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-07-26)Early detection of breast cancer is essential for increasing survival rates, as it is one of the primary causes of death for women globally. Mammograms are extensively used by physicians for diagnosis, but selecting appropriate algorithms for image enhancement, segmentation, feature extraction, and classification remains a significant research challenge. This paper presents a computer-aided diagnosis ...
