Creating Refined Datasets for Better Chaos Detection.

In recent years, the analysis of signal properties (especially biomedical signals) has become an important research direction. One interesting feature of signals is their potential to be chaotic. This article concerns the issues of classification of real signals or synthetic ones in the context of detecting chaotic properties.

Datasets for learning of unknown characteristics of dynamical systems.

The ability to uncover characteristics based on empirical measurement is an important step in understanding the underlying system that gives rise to an observed time series. This is especially important for biological signals whose characteristic contributes to the underlying dynamics of the physiological processes. Therefore, by studying such signals, the physiological systems that generate them can be better understood.

Serverless computing in omics data analysis and integration.

A comprehensive analysis of omics data can require vast computational resources and access to varied data sources that must be integrated into complex, multi-step analysis pipelines. Execution of many such analyses can be accelerated by applying the cloud computing paradigm, which provides scalable resources for storing data of different types and parallelizing data analysis computations. Moreover, these resources can be reused for different multi-omics analysis scenarios.

Perspectives of using Cloud computing in integrative analysis of multi-omics data.

Integrative analysis of multi-omics data is usually computationally demanding. It frequently requires building complex, multi-step analysis pipelines, applying dedicated techniques for data processing and combining several data sources. These efforts lead to a better understanding of life processes, current health state or the effects of therapeutic activities.

An Analysis of Entropy-Based Eye Movement Events Detection.

Analysis of eye movement has attracted a lot of attention recently in terms of exploring areas of people's interest, cognitive ability, and skills. The basis for eye movement usage in these applications is the detection of its main components-namely, fixations and saccades, which facilitate understanding of the spatiotemporal processing of a visual scene. In the presented research, a novel approach for the detection of eye movement events is proposed, based on the concept of approximate entropy.