In fields such as finance, medicine, engineering, and science, making real-time predictions during transient periods characterized by sudden and large changes is a hard challenge for machine learning. Humans keep memory of these transient events, abstractly learn the most relevant rules and reuse them when similar events occur, which stems from episodic memory that allows storage and recall of similar ...

CRDTs (Conflict-free Replicated Data Types) have properties desirable for large-scale distributed systems with variable network latency or transient partitions. With CRDT, data are always available for local updates and data states converge when the replicas have incorporated the same updates. Undo is useful for correcting human mistakes and for restoring system-wide invariant violated due to long ...

OOPP is a component based middleware platform with support for complex distributed applications. The main goal of OOPP is to create an expressive programming model for distributed applications where by default details are hidden for the programmer. When necessary, reflection is used to expose and sometimes modify these details. All interaction with an OOPP component are specified by its component ...

The interest in video anomaly detection systems that can detect different types of anomalies, such as violent behaviours in surveillance videos, has gained traction in recent years. The current approaches employ deep learning to perform anomaly detection in videos, but this approach has multiple problems. For example, deep learning in general has issues with noise, concept drift, explainability, ...

Over the past decades, histopathological cancer diagnostics has become more complex, and the increasing number of biopsies is a challenge for most pathology laboratories. Thus, development of automatic methods for evaluation of histopathological cancer sections would be of value. In this study, we used 624 whole slide images (WSIs) of breast cancer from a Norwegian cohort. We propose a cascaded ...

This chapter introduces and discusses a novel “health-energy nexus under pandemic uncertainty” concept that arises as a consequence of the current pandemic that we are experiencing worldwide. In light of the pandemic implications on the power and energy systems, we discuss how the global health conditions are tightly connected with the energy consumption needs and how the two areas closely interact ...

The multiple signal classification algorithm (MUSICAL) is a statistical super-resolution technique for wide-field fluorescence microscopy. Although MUSICAL has several advantages, such as its high resolution, its low computational performance has limited its exploitation. This paper aims to analyze the performance and scalability of MUSICAL for improving its low computational performance. We first ...

<i>Background</i> - Individuals with diabetes are using mobile health (mHealth) to track their self-management. However, individuals can understand even more about their diabetes by sharing these patient-gathered data (PGD) with health professionals. We conducted experience-based co-design (EBCD) workshops, with the aim of gathering end-users’ needs and expectations for a PGD-sharing system.<p> ...

In Norway, where all associate professors (“førsteamanuensis”) who are qualified as a (full) professor are offered a personal professorship, it is no other than the associate professor him/herself who stands in the way of the Professor title. This article reviews 12 success criteria in order to achieve qualifications as (full) professor: (1) Accept professional challenges, (2) always consider ...

Artificial intelligence is currently a hot topic in medicine. However, medical data is often sparse and hard to obtain due to legal restrictions and lack of medical personnel for the cumbersome and tedious process to manually label training data. These constraints make it difficult to develop systems for automatic analysis, like detecting disease or other lesions. In this respect, this article ...