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 ...

Radar Beam-park experiments have been very successful in characterizing the distribution of space debris objects, both in terms of orbital parameters but also in terms of limiting the estimates of their radar cross section, or RCS. A recent paper \[0\] used observed range and range rates to refine orbit estimates by matching up the observed SNR curve to that predicted by simulations. This gives good ...

For the largest exceptional simple Lie superalgebra F(4), having dimension (24|16), we provide two explicit geometric realizations as supersymmetries, namely as the symmetry superalgebra of super-PDE systems of second and third order respectively.

The need for interpretable models has fostered the development of self-explainable classifiers. Prior approaches are either based on multi-stage optimization schemes, impacting the predictive performance of the model, or produce explanations that are not transparent, trustworthy or do not capture the diversity of the data. To address these shortcomings, we propose ProtoVAE, a variational autoencoder-based ...

<p>The field of artificial intelligence recently witnessed remarkable growth, leading to the development of complex deep learning models that perform exceptionally across various domains. However, these developments bring forth critical issues. Deep learning models are vulnerable to inheriting and potentially exacerbating biases present in their training data. Moreover, the complexity of these models ...

This thesis investigates the impact four different experimental marine conditions have on the extractability of tire additives meant to protect tires from UV radiation as well as some other common substances found in tires. The impact is evaluated between tire particle size and age to determine if the exposure affects them differently. This thesis finds that the effect of marine conditions on ...

Developing objective assessment approach in maritime simulator training can be a highly challenging task due to the complexity of simulating realistic scenarios, capturing relevant performance indicators and establishing good assessment protocols. This study provides a synthesis of simulation scenario contexts, data collection tools, and data analysis approaches in published simulator training ...

This thesis introduces the first study of instance segmentation applied to gas flares in single beam echo sounder data. We develop a comprehensive dataset consisting of 1,414 images, featuring 5,142 segmented objects identified as gas flare. A key contribution is the adaptation of the Brier score specifically for instance segmentation. Further, we show how to adapt the Weighted Box Fusion (WBF) ...

The hydrocarbon seepage chronology during deglaciation across the formerly glaciated Barents Sea was established using uranium-thorium (U–Th) dating of seep carbonates. Seep carbonates were sampled with remotely operated vehicles (ROV) from the seafloor at three active hydrocarbon seeps (water depth 156–383 m), located in the north-west (Storfjordrenna), north-central (Storbanken High), and south-west ...

Cyber-physical IoT nodes located in environments which are resource-constrained and physically hard to access, like the Arctic tundra, must achieve long operational lifetimes from a single battery and report data over data networks. The nodes sleep most of the time, and only wake up to perform mission tasks, including reporting data. However, networks can become unavailable, or have low bandwidth ...