The application of electroencephalogram (EEG) in exploring human psychophysiological
states within the context of buildings has gained prominence. However, existing research …

With the development of network science and graph theory, brain network research has
unique advantages in explaining those mental diseases, the neural mechanism of which is …

This paper is the first to attempt differentially private (DP) topological data analysis (TDA),
producing near-optimal private persistence diagrams. We analyze the sensitivity of …

Introduction The study of attention has been pivotal in advancing our comprehension of
cognition. The goal of this study is to investigate which EEG data representations or features …

Traditional threshold-based methods in brain functional network analysis have some
drawbacks. First, the process of determining thresholds is often based on trial and error …

We present a novel topological characterization of EEG time series signals associated with
two meditative states: autobiographical self-reflection and mantra-based meditation. The …

Topological data analysis (TDA) provide tools that are becoming increasingly popular for
analyzing multivariate time series data. One key aspect in analyzing multivariate time series …

Topological data analysis (TDA) combined with machine learning (ML) algorithms is a
powerful approach for investigating complex brain interaction patterns in neurological …

Topological data analysis (TDA) has proven to be a potent approach for extracting intricate
topological structures from complex and high-dimensional data. In this paper, we propose a …

Modern lean premixed combustors are operated in ultra-lean mode to conform to strict
emission norms. However, this causes the combustors to become prone to lean blowout …