Machine Learning

Time- and Frequency-Domain Dynamic Spectrum Access: Learning Cyclic Medium Access Patterns in Partially Observable Environments

Upcoming communication systems increasingly often tackle the spectrum scarcity problem through the coexistence with legacy systems in the same frequency band. Cognitive Radio presents popular methods for Dynamic Spectrum Access (DSA) that enable …

Hybrid Modelling by Machine Learning Corrections of Analytical Model Predictions towards High-Fidelity Simulation Solutions

Within the fields of materials mechanics, the consideration of physical laws in machine learning predictions besides the use of data can enable low prediction errors and robustness as opposed to predictions only based on data. On the one hand, …

Artificial Neural Networks for Sensor Data Classification on Small Embedded Systems

In this paper we investigate the usage of machine learning for interpreting measured sensor values in sensor modules. In particular we analyze the potential of artificial neural networks (ANNs) on low-cost microcontrollers with a few kilobytes of …

Predicting long-term dynamics of soil salinity and sodicity on a global scale

Knowledge of spatiotemporal distribution and likelihood of (re)occurrence of salt-affected soils is crucial to our understanding of land degradation and for planning effective remediation strategies in face of future climatic uncertainties. However, …

A machine learning-based method for simulation of ship speed profile in a complex ice field

Computational methods for predicting ship speed profile in a complex ice field have traditionally relied on mechanistic simulations. However, such methods have difficulties capturing the entire complexity of ship– ice interaction process due to the …

A Review of the Application of Machine Learning and Data Mining Approaches in Continuum Materials Mechanics

Machine learning tools represent key enablers for empowering material scientists andengineers to accelerate the development of novel materials, processes and techniques. One of the aims of using such approaches in the field of materials science is to …

Data Science Based Mg Corrosion Engineering

Magnesium exhibits a high potential for a variety of applications in areas such as transport, energy and medicine. However, untreated magnesium alloys are prone to corrosion, restricting their practical application. Therefore, it is necessary to …