Driving risk assessment is important to guide the actions, states and behaviours of drivers for
the prevention of road incidents or accidents. With the widespread of sensors constantly …

Most of statistics and AI draw insights through modeling discord or variance between
sources (ie, intersource) of information. Increasingly however, research is focusing on …

Obtaining quantitative survey responses that are both accurate and informative is crucial to a
wide range of fields. Traditional and ubiquitous response formats such as Likert and visual …

The growing use of intervals in fields like survey analysis necessitates effective aggregation
methods that can summarize and represent such uncertain data representations. The …

Capturing interval-valued, as opposed to more conventional point-valued data, offers a
potentially efficient method of obtaining richer information in individual responses. In turn …

The capture and analysis of interval-valued data has seen increased interest over recent
years. This offers a direct means to capture and reason about uncertainty in data, whether …

Commercial driving is a complex multifaceted task influenced by personal traits and external
contextual factors, such as weather, traffic, road conditions, etc. Previous intelligent …

This paper adds to a growing body of research into the practical utility of using interval-
valued (IV) response modes to efficiently capture richer quantitative data from people—eg …

With growing significance of interval-valued data, interest in artificial intelligence methods
tailored to this data type is similarly increasing across a range of application domains. Here …

Commercial driving is a complex multifaceted task influenced by drivers' personal traits and
external contextual factors, such as weather, traffic, and road conditions. Current intelligent …