Integrity of data is important in today as more of societies structure today are distributed and becomes vulnerable to dishonest entities on their edge devices. Using provenance to prove integrity over edge devices and distributed networks is difficult, as it often produces big amounts of data which fills up storage without having a need to be used. Comm2Prov seeks to fix this by combining the ...

In contemporary football, advanced analysis techniques are increasingly important, enhancing clubs’ capabilities to make strategic in-game adjustments. Central to this advancement is the availability of real-time analytics, which relies heavily on accurate player and ball tracking technologies. While real-time player tracking has become more accessible, automatic and reliable real-time ball ...

Studies have shown that the Sami culture of communicating about health can often be indirect and reliant on implications and hints rather than clear unambiguous statements. The style is described as “roundabout”, circling around a topic before closing in on it. Modern medicine typically values directness and unambiguousness in its mission of effective anamnesis and diagnosis. Due to these differing ...

In recent years, there has been considerable effort to promote gender balance in the academic environment of Computer Science (CS). However, there is still a gender gap at all CS academic levels: from students, to PhD candidates, to faculty members. This general trend is followed by the Department of Computer Science at UiT The Arctic University of Norway. To combat this trend within the CS environment ...

Digitalization of lithium-ion batteries can significantly advance the performance improvement of lithium-ion batteries by enabling smarter controlling strategies during operation and reducing risk and expenses in the design and development phase. Accurate physics-based models play a crucial role in the digitalization of lithium-ion batteries by providing an in-depth understanding of the system. ...

This Master’s thesis investigates the application of Machine Learning (ML) in predicting blast-induced ground vibrations in mining, with the aim of sur- passing the precision of the current industry-standard model that utilizes an empirical, regression-based method. The study applied a Deep Neural Network (DNN) model, selected for its capability to consider a broader range of variables than the ...

This study discusses the methods and challenges of deidentifying and pseudonymizing Norwegian clinical text for research purposes. The results of the NorDeid tool for deidentification and pseudonymization on different types of protected health information were evaluated and discussed, as well as the extension of its functionality with regular expressions to identify specific types of sensitive ...

Virtual care comprising virtual visits and monitoring via audio or video has the potential to reduce access barriers to care and has been successfully implemented in prenatal care. It reduces the frequency of in-person visits and increases self-care skills. However, the knowledge and competence in handling monitoring equipment at home directly influences satisfaction and engagement with the ...

Many real-world applications based on online learning produce streaming data that is haphazard in nature, i.e., contains missing features, features becoming obsolete in time, the appearance of new features at later points in time and a lack of clarity on the total number of input features. These challenges make it hard to build a learnable system for such applications, and almost no work exists in ...

Scanning Acoustic Microscopy (SAM) uses high-frequency acoustic waves to generate non-ionizing, label-free images of the surface and internal structures of industrial objects and biological specimens. The resolution of SAM images is limited by several factors such as the frequency of excitation signals, the signal-to-noise ratio, and the pixel size. We propose to use a hypergraphs image inpainting ...