No abstract

This paper presents a novel method for visualizing the dynamics of evolutionary algorithms in the form of complex networks. We discuss the analogy between individuals in populations in an arbitrary evolutionary algorithm and vertices of a complex network, as well as between edges in a complex network and communication between individuals in a population. The possibility of visualizing the dynamics of a complex network using the coupled map lattices method and control by means of chaos control techniques are also discussed.

a b s t r a c tThis paper discusses the possibility of using evolutionary algorithms for the reconstruction of chaotic systems. The main aim of this work is to show that evolutionary algorithms are capable of the reconstruction of chaotic systems without any partial knowledge of internal structure, i.e. based only on measured data and a predefined set of basic mathematical ''objects''. Algorithm SOMA and differential evolution were used in reported experiments here. Systems selected for numerical experiments here is the well-known Lorenz system, Simplest Quadratic Flow, Double Sroll, Damped Driven Pendulum and Nosé-Hoover oscillator. For each algorithm repeated simulations were done, totaling 20 simulations. According to obtained results it can be stated that evolutionary reconstruction is an alternative and promising way as to how to identify chaotic systems.

The paper focuses on methods of Advanced Persistent Threat (APT) in connection with current cyber network attacks.It contains examples of major cyber-attacks which were associated with APTs over the past years. Methodology of an ATP attack is discussed and current trends are used to predict future APT targeting. In conclusion the options of base security policies are provided that could help to protect or enhance the defense against these modern worldwide cyber threats.

Brain‐computer interface (BCI) provides direct communication between the brain and an external device. BCI systems have become a trendy field of research in recent years. These systems can be used in a variety of applications to help both disabled and healthy people. Concerning significant BCI progress, we may assume that these systems are not very far from real‐world applications. This review has taken into account current trends in BCI research. In this survey, 100 most cited articles from the WOS database were selected over the last 4 years. This survey is divided into several sectors. These sectors are Medicine, Communication and Control, Entertainment, and Other BCI applications. The application area, recording method, signal acquisition types, and countries of origin have been identified in each article. This survey provides an overview of the BCI articles published from 2016 to 2020 and their current trends and advances in different application areas.