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 ...

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, ...

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 ...

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 ...

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 ...

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 ...

The optimized network architectures and interconnect technologies employed in high-performance cloud computing environments introduce challenges when it comes to developing monitoring solutions that effectively capture relevant network metrics. Moreover, network monitoring often involves capturing and analyzing a large volume of network traffic data. This process can introduce additional overhead ...

Flipped Classroom (FC) approaches, which utilize video distribution via modern internet platforms, have recently gained interest as a pedagogical framework. Inquiry Based Mathematics Education (IBME) has proven to be a valid form of task design to motivate active learning and enhance classroom interactivity. This article presents a practical combination of introductory videos and inquiry-based class ...

Nearest neighbor (NN) sampling provides more semantic variations than predefined transformations for selfsupervised learning (SSL) based image recognition problems. However, its performance is restricted by the quality of the support set, which holds positive samples for the contrastive loss. In this work, we show that the quality of the support set plays a crucial role in any nearest neighbor based ...

This paper presents the design, implementation and early tests of an app that collects a comprehensive set of health-related data, as part of the EU-project WARIFA. To achieve the main aim of the project – using AI to prevent chronic conditions – a wide range of data needs to be collected and stored at a backend server for processing. The methods and elements for creating this system are presented, ...