Abstract Machine learning has been the corner stone in analysing and extracting information
from data and often a problem of missing values is encountered. Missing values occur …

Across the spectrum of industrial sectors, including pharmaceuticals, chemicals, personal
care products, food additives and their associated regulatory agencies, there is a need to …

While scientific uncertainty always invites the risk of politicization and raises questions of
how to communicate about science, this risk is magnified for COVID-19. The limited data and …

Uncertainty quantification (UQ) is an important benchmark to assess the performance of
artificial intelligence (AI) and particularly deep learning ensembled-based models. However …

This paper updates and builds on 'Modelling with Stakeholders' Voinov and Bousquet, 2010
which demonstrated the importance of, and demand for, stakeholder participation in …

Purpose Life cycle assessment (LCA) is intended as a quantitative decision support tool.
However, the large amount of uncertainty characteristic of LCA studies reduces confidence …

Decision support systems (DSS) have long been used in research, service provision and
extension. Despite the diversity of technological applications in which past agricultural DSS …

Video captioning, in essential, is a complex natural process, which is affected by various
uncertainties stemming from video content, subjective judgment, and so on. In this paper, we …

Parasitic infections are ubiquitous in wildlife, livestock and human populations, and healthy
ecosystems are often parasite rich. Yet, their negative impacts can be extreme …

A building system is highly nonlinear and commonly includes a variety of parameters
ranging from the architectural design to the building mechanical and energy system. Serving …