New digital technologies like activity trackers, nudge concepts, and approaches can inspire and improve personal health. There is increasing interest in employing such devices to monitor people’s health and well-being. These devices can continually gather and examine health-related information from people and groups in their familiar surroundings. Context-aware nudges can assist people in self-managing ...

The arctic tundra is considered the terrestrial biome expected to be most impacted by climate change, with temperatures projected to increase as much as 10 °C by the turn of the century. The Climate-ecological Observatory for Arctic Tundra (COAT) project monitors the climate and ecosystems using several sensor types. We report on results from projects that automate image annotations from two of the ...

Segmenting medical images accurately and reliably is crucial for disease diagnosis and treatment. Due to the wide assortment of objects’ sizes, shapes, and scanning modalities, it has become more challenging. Many convolutional neural networks (CNN) have recently been designed for segmentation tasks and achieved great success. This paper presents an optimized deep learning solution using DeepLabv3+ ...

Patients with diabetes and health personnel do not have an optimal way of interacting. Health personnel must use multiple ICT systems, such as third-party companies’ services, to access health-related data from diverse vendors’ CGM platforms and Electronic Health Record (EHR). Furthermore, other health-related data like physical activities, quality of life or well-being is often discussed but ...

Thumbnail selection is a very important aspect of online sport video presentation, as thumbnails capture the essence of important events, engage viewers, and make video clips attractive to watch. Traditional solutions in the soccer domain for presenting highlight clips of important events such as goals, substitutions, and cards rely on the manual or static selection of thumbnails. However, such ...

Semantic image segmentation is the process of labeling each pixel of an image with its corresponding class. An encoder-decoder based approach, like U-Net and its variants, is a popular strategy for solving medical image segmentation tasks. To improve the performance of U-Net on various segmentation tasks, we propose a novel architecture called DoubleU-Net, which is a combination of two U-Net ...

The newly founded company Oceanbox is creating a novel oceanographic forecasting system to provide oceanography as a service. These services use mathematical models that generate large hydrodynamic data sets as unstructured triangular grids with high-resolution model areas. Oceanbox makes the model results accessible in a web application. New visualizations are needed to accommodate land-masking and ...

Background: Serious public-health concerns such as overweight and obesity are in many cases caused by excess intake of food combined with decreases in physical activity. Smart scales with wireless data transfer can, together with smart watches and trackers, observe changes in the population’s health. They can present us with a picture of our metabolism, body health, and disease risks. Combining ...

The pyndl package implements Naïve Discriminative Learning (NDL) in Python. NDL is an incremental learning algorithm grounded in the principles of discrimination learning (Rescorla & Wagner, 1972; Widrow & Hoff, 1960) and motivated by animal and human learning research (e.g. Baayen et al., 2011; Rescorla, 1988). Lately, NDL has become a popular tool in language research to examine large corpora and ...

The environment is progressively affected by global warming and pollution, whereas fossil fuel transportation is one of the major causes. This thesis describes a system that aims to support users in choosing environmentally friendly transportation alternatives. The system uses digital nudging to motivate behavioral change in a non-intrusive manner. This project focuses on the presentation of ...