Recent years have seen a dramatic rise in the popularity of autonomous mobile robots
(AMRs) due to their practicality and potential uses in the modern world. Path planning is …

The last decade saw an enormous boost in the field of computational topology: methods and
concepts from algebraic and differential topology, formerly confined to the realm of pure …

In the last decade, there has been a growing body of literature addressing the utilization of
complex network methods for the characterization of dynamical systems based on time …

Change points are abrupt variations in time series data. Such abrupt changes may represent
transitions that occur between states. Detection of change points is useful in modelling and …

Complex network has been a powerful tool for time series analysis by encoding dynamical
temporal information in network topology. In this article, we introduce a framework to build a …

Accurate and real-time forecasting of the price of oil plays an important role in the world
economy. Research interest in forecasting this type of time series has increased …

Multifractality is ubiquitously observed in complex natural and socioeconomic systems.
Multifractal analysis provides powerful tools to understand the complex nonlinear nature of …

As many readers may know, graph theory is a fundamental branch of mathematics that
explores networks made up of nodes and edges, focusing on their paths, structures, and …

Electroencephalogram (EEG) signals acquired from brain can provide an effective
representation of the human's physiological and pathological states. Up to now, much work …

Graph networks can model data observed across different levels of biological systems that
span from population graphs (with patients as network nodes) to molecular graphs that …