To enhance Situation Awareness (SA) in the context of autonomous ship navigation within a complex navigation environment, the Advanced Ship Predictor (ASP) is proposed as a solution framework aimed at predicting ship maneuvers. This can be used to identify potential ship close encounters and collision scenarios in advance, where appropriate collision avoidance actions should be taken. The implementation ...

As the Arctic undergoes ‘Atlantification’ and warms at a faster rate than lower latitudes, dramatic physical and biological changes are occurring in the ocean, atmosphere and cryosphere systems. This project focusses on fjord environments connected to the Greenland Ice Sheet, which has recently experienced a significant and rapid loss of ice attributed primarily to changes in the surface mass balance ...

The Antarctic Ice Sheet (AIS) is one of the climate tipping elements on Earth and the largest potential contributor to sea level rise. While the consequences of ice sheet collapse on oceanic and atmospheric changes are well documented, its impact on the global carbon cycle remains critically ignored in the current global carbon budget. This is particularly important because the Antarctic Sedimentary ...

This open access book compiles state-of-the-art research on the development and implementation of advanced learning technologies and AI-assisted tools, showing how they can transform the educational landscape and learning processes in various domains. Covering topics ranging from immersive learning environments to personalized education, it offers insights and practical applications that are shaping ...

Learning assistants are assigned a diverse set of tasks in the Norwegian higher educational system, particularly in facilitating student-centered teaching in the natural sciences. The present work is an investigation into the experiences of learning assistants in science at a Norwegian university through a thematic analysis of ten interviews with undergraduate and graduate learning assistants. The ...

Polyps are well-known cancer precursors identified by colonoscopy. However, variability in their size, appearance, and location makes the detection of polyps challenging. Moreover, colonoscopy surveillance and removal of polyps are highly operator-dependent procedures and occur in a highly complex organ topology. There exists a high missed detection rate and incomplete removal of colonic polyps. To ...

This paper explores the innovative application of multi-modal data analysis for nautical skill development process. By examining the potential of integrating diverse data sources e.g., ship motion, visual, auditory and sensor data, the possibility of obtaining performance insights could be enhanced, and the decision-making processes in complex navigational environments can be made more transparent. ...

The adoption of decentralized energy market models facilitates the exchange of surplus power among local nodes in peer-to-peer settings. However, decentralized energy transactions within untrusted and non-transparent energy markets in modern Smart Grids expose vulnerabilities and are susceptible to attacks. One such attack is the False Data Injection Attack, where malicious entities intentionally ...

Predicting sea ice concentration (SIC) is an important task in climate analysis. The recently proposed deep learning system IceNet is the state-of-the-art sea ice prediction model. IceNet takes high-dimensional climate simulations and observational data as input features and forecasts SIC for the next 6 months over a spatial grid over the northern hemisphere. The model has proven to be particularly ...

In the rapidly evolving landscape of digital platforms, the need for optimizing media representations to cater to various aspect ratios is palpable. In this paper, we pioneer an approach that utilizes object detection, scene detection, outlier detection, and interpolation for smart cropping. Using soccer as a case study, our primary goal is to capture the frame salience using object (player and ball) ...