Related papers: Temporal Variation Measure Analysis: An Improved S…
Temporal networks, i.e., networks in which the interactions among a set of elementary units change over time, can be modelled in terms of time-varying graphs, which are time-ordered sequences of graphs over a set of nodes. In such graphs,…
Graphs are commonly used to represent objects, such as images and text, for pattern classification. In a dynamic world, an object may continuously evolve over time, and so does the graph extracted from the underlying object. These changes…
In this paper, a new efficient feature extraction method based on the adaptive threshold of wavelet package coefficients is presented. This paper especially deals with the assessment of autonomic nervous system using the background…
In order to reach the sensitivity required to detect gravitational waves, pulsar timing array experiments need to mitigate as much noise as possible in timing data. A dominant amount of noise is likely due to variations in the dispersion…
Patterns in temporal data can often be found across different scales, such as days, weeks, and months, making effective visualization of time-based data challenging. Here we propose a new approach for providing focus and context in…
The characterization of heart dynamics with a view to distinguish abnormal from normal behavior is an interesting topic in clinical sciences. Here we present an analysis of the Electro-cardiogram (ECG) signals obtained under controlled…
Graph models provide efficient tools to capture the underlying structure of data defined over networks. Many real-world network topologies are subject to change over time. Learning to model the dynamic interactions between entities in such…
Every design choice will have different effects on different units. However traditional A/B tests are often underpowered to identify these heterogeneous effects. This is especially true when the set of unit-level attributes is…
Within many real-world networks the links between pairs of nodes change over time. Thus, there has been a recent boom in studying temporal graphs. Recognizing patterns in temporal graphs requires a proximity measure to compare different…
This paper deals with the state estimation of linear time-invariant systems using distributed observers with local sampled-data measurement and aperiodic communication. Each observer agent perceives partial information of the system to be…
We propose an analysis of heart rate marathon runners implemented by computing a multifractal spectrum based on p-exponents. We draw physiological conclusions about their performance. Finally, we link this analysis with the disturbances of…
Early detection of changes in the frequency of events is an important task, in, for example, disease surveillance, monitoring of high-quality processes, reliability monitoring and public health. In this article, we focus on detecting…
Variations of instantaneous heart rate appears regularly oscillatory in deeper levels of anesthesia and less regular in lighter levels of anesthesia. It is impossible to observe this "rhythmic-to-non-rhythmic" phenomenon from raw…
We have carried out a pilot study on a standard collection of electrocardiograms from patients who suffer from congestive heart failure, and subjects without cardiac pathology, using receiver-operating-characteristic (ROC) analysis. The…
We demonstrate experimentally a scheme to measure small temporal delays, much smaller than the pulse width, between optical pulses. Specifically, we observe an interference effect, based on the concepts of quantum weak measurements and weak…
Psychophysiology investigates the causal relationship of physiological changes resulting from psychological states. There are significant challenges with machine learning-based momentary assessments of physiology due to varying data…
Receiver-operating-characteristic (ROC) analysis was used to assess the suitability of various heart rate variability (HRV) measures for correctly classifying electrocardiogram records of varying lengths as normal or revealing the presence…
Cardiac time intervals (CTIs) are important parameters for assessing cardiac function and can be measured using non-invasive methods such as electrocardiography (ECG) and seismocardiography (SCG). It is widely accepted that SCG signals,…
Complex spatiotemporal patterns of action potential duration have been shown to occur in many mammalian hearts due to a period-doubling bifurcation that develops with increasing frequency of stimulation. Here, through high-resolution…
We consider change point detection for the volatility in second order linear parabolic stochastic partial differential equations based on high frequency spatio-temporal data. We give a test statistic to detect changes in the volatility…