We believe the underutilization of clinically validated algorithms for heart health assessment in current medical platforms undermines patient confidence in using associated screening instruments. The importance of earlier detection and improved health outcomes in heart disease motivated the development of these screening instruments. Available risk assessment tools are stand-alone online apps or ...

Artificial Intelligence (AI) and the underlying Machine Learning (ML) technology is experiencing increased applications in various areas. The training of ML models requires significant amounts of data, and data might contain restrictions regarding their permitted usage. High-performant models are often called black-boxes because of their complex decision-making process. Thus, ML applications threaten ...

Federated Learning (FL) is a privacy-preserving approach to train machine learning models on distributed datasets across different organizations. This is particularly beneficial for domains like healthcare and finance, where user data is often sensitive and tabular (e.g., hospital records and financial transactions). However, recent research like Tableak highlighted vulnerabilities that can exploit ...

For people with Type 1 Diabetes Mellitus (T1DM), engaging in physical activities (PA) presents unique challenges. The aim of this thesis was to improve the prediction of blood glucose (BG) levels for individuals with T1DM during and after PA. The study began with a literature review to guide the research direction and understand existing prediction models. Then particular emphasis was placed on ...

The advancement in the field of Artificial Intelligence (AI) has brought revolution in almost every field of life, and Journalism is also one of them. Which includes prospective use in Investigating reports and uncovering information. This project explores the avenue of integrating technologies such as Large Language Model (LLM) with the Vector Databases. At the same time, the motive is to address ...

Advanced analysis tools leveraging invasive tracking technologies such as gps and manual event tagging has become a global staple in top-tier soccer clubs for enhancing their strategical decision making and insight. These tools rely on precise coordinate data, with their effectiveness significantly enhanced when this data is produced in real-time. With the rapid advancement in computer vision and ...

Parid-GO A Personalised Augmented Reality Game to Reinforce Outdoor Physical Activity for People with Intellectual Disabilities. This project aims to develope a dynamic content solution that are user centric. The rationale is that by allowing the participants to customize and use other themes, colors, etc., the participant will be more engaged and use the application more. Which in turn will increase ...

The Arctic Tundra is an extremely cold desert-like environment. It is the home to many different species of animals and plants. With the oncoming threat of climate change, this biome is at risk of losing its biodiversity. This disruption of the Arctic Tundra caused by climate change, is what researchers at COAT with the assistance of UiT’s DAO project is trying to monitor. To be able to achieve this ...

At the one end of the spectrum, locally installed applications allow users to work offline and at their convenience but do not support collaboration among multiple users or devices. At the other end, cloud-based applications offer collaboration and data synchronization but require an uninterrupted internet connection. To address these limitations, Local-First software was introduced to merge the ...

This master’s thesis evaluates the scalability and cost-effectiveness of the AWS cloud platform used to collect and utilize data generated by the 87 digitally equipped trams. The SL-18 Cloud Platform was developed before the trams arrived, and resource configuration estimates were made to handle the data generated by the trams. However, with a few trams currently operational, it is crucial to evaluate ...