CINE 2020 Keynotes, Invited Lectures and Tutorials

2020 2020 4th International Conference on Computational Intelligence and Networks (CINE)  
The recent ability of obtaining datasets of all events occurring during a football match, including the position of the players and the interactions between them, has opened the door to new kind of studies where it is possible to analyse and quantify the behaviour of a team as a whole, together with the role of single players. Under this framework, the organization of a team can be considered as the result of the interaction between its players, leading to networks based on passes. In this way,
more » ... asses. In this way, it is possible to create passing networks, which are directed (i.e., links between players go in one direction), weighted (i.e., the strength of the links is based on the number of passes between players), spatially embedded (i.e., the Euclidean position of the ball and players is highly relevant) and time evolving (i.e., the network continuously changes its structure). In this lecture, we will see how it is possible to have a new point of view of what is happening in a pitch during a football match using techniques coming from Network Science. Abstract: The talk will describe spontaneous emergence of collective dynamics in networked phase oscillators. As a first step, I will discuss how synchronization may emerge in a graph. Synchronization is a process in which dynamical systems adjust some properties of their trajectories (due to their interactions, or to a driving force) so that they eventually operate in a macroscopically coherent way. A common result is that the vast majority of transitions to synchronization are of the second-order type, continuous and reversible. However, as soon as networked units with complex architectures of interaction are taken into consideration, abrupt and irreversible phenomena may take place, namely Abstract: The data-driven and time-resolved inference of couplings and directionality between two or more sub-systems is an important first step in representing a complex system as a network. Although a large number of time-series-analysis-techniques is now available to assess strength, direction, and functional form of couplings, there still exist a number of unsolved issues for which there are currently no satisfactory solutions. I will showcase some of these issues at the example of evolving epileptic brain networks. Abstract: The multilayer nature of networks has broadened the landscape of network science. In this multilayer description, different kinds of relationships or interactions between the nodes are modeled by allowing the units to be arranged in several layers, either simultaneously or in an alternating fashion. An example of multilayer system can be the transport system of a country or state in which cities or towns would be the nodes, and a distinct network of each bus, train and flight connectivity among the nodes (cities) denotes different layers. Furthermore, a close relationship between structure and dynamics in the process of synchronization in complex networks has been the object of study for a long time; however, it has proved to be particularly important in the case of the "explosive synchronization," where the ensemble reaches suddenly to a fully coherent state through a discontinuous, irreversible First-order like transition, often in the presence of a hysteresis loop. This first order discontinuous transition to synchronization, popularly known as explosive synchronization (ES), in a network has been shown to be originated from considering either degree-frequency correlation, frequency-coupling strength correlation, inertia or adaptively controlled phase oscillators. Here we show that ES is a generic phenomenon, and show that through an appropriate multiplexing, one can achieve explosive synchronization in those networks that are incapable of exhibiting explosive synchronization in isolation. Abstract: The stability of synchronised networked systems is a multi-faceted challenge for many natural and technological fields, from cardiac and neuronal tissue pacemakers to power grids. In the latter case, the ongoing transition to distributed renewable energy sources is leading to a proliferation of dynamical actors. The desynchronisation of a few or even one of those would likely result in a substantial blackout. Thus the dynamical stability of the synchronous state has become a leading topic
doi:10.1109/cine48825.2020.9080699 fatcat:ofxsdyhf5vfrnexkngt45lpeuq