In her 35 years as a psychologist, NTNU researcher Audrey van der Meer has studied everything from baby swimming to what ...

Abstract: Power transformers are critical assets in power networks, whose reliability directly impacts grid resilience and stability. Traditional condition monitoring approaches, often rule-based or ...

Neural Oscillatory Interference Networks for Inherently Interpretable Deep Learning Computation Note: This README is an ultra-condensed summary of the research reports published by Unpatentable.org.

This repository contains a Monte-Carlo solver to train neural-network variational wavefunction to solve continuous-space Fermi systems [M Geier, K Nazaryan, T Zaklama, L Fu, Phys. Rev. B 112, 045119 ...

Deep learning has added a new dimension to engineering applications, from 5G signal processing to predictive maintenance in power grids. It automatically detects equipment failures and optimizes ...

Molecular circuits capable of autonomous learning could unlock novel applications in fields such as bioengineering and synthetic biology. To this end, existing chemical implementations of neural ...

Background In an ophthalmology emergency department, determining treatment urgency is crucial for patient safety and the efficient use of resources. The aim of this study was to use artificial ...

One of the nation’s largest refrigerated trucking carriers and intermodal logistics providers on Monday threw its support behind a proposed merger of Union Pacific Railroad and Norfolk Southern ...

This article is part of an ongoing column on AI and planning by urban planner and AI expert, Tom Sanchez. Read more installments here. Urban planners aren’t expected to become AI engineers. But with ...

ABSTRACT: Similarity-based prediction modeling is a common method for estimating the remaining useful life (RUL) of a machine. The present study proposes a novel similarity-based multidimensional ...