Enabling Blockchain Services for IoE with Zk-Rollups.

The Internet of Things includes all connected objects from small embedded systems with low computational power and storage capacities to efficient ones, as well as moving objects like drones and autonomous vehicles. The concept of Internet of Everything expands upon this idea by adding people, data and processing. The adoption of such systems is exploding and becoming ever more significant, bringing with it questions related to the security and the privacy of these objects.

Towards a Blockchain-Based Multi-UAV Surveillance System.

This study describes a blockchain-based multi-unmanned aerial vehicle (multi-UAV) surveillance framework that enables UAV coordination and financial exchange between system users. The objective of the system is to allow a set of Points-Of-Interest (POI) to be surveyed by a set of autonomous UAVs that cooperate to minimize the time between successive visits while exhibiting unpredictable behavior to prevent external agents from learning their movements. The system can be seen as a marketplace where the UAVs are the service providers and the POIs are the service seekers.

Statistical properties of single-mode fiber coupling of satellite-to-ground laser links partially corrected by adaptive optics.

In the framework of satellite-to-ground laser downlinks, an analytical model describing the variations of the instantaneous coupled flux into a single-mode fiber after correction of the incoming wavefront by partial adaptive optics (AO) is presented. Expressions for the probability density function and the cumulative distribution function as well as for the average fading duration and fading duration distribution of the corrected coupled flux are given. These results are of prime interest for the computation of metrics related to coded transmissions over correlated channels, and they are confronted by end-to-end wave-optics simulations in the case of a geosynchronous satellite (GEO)-to-ground and a low earth orbit satellite (LEO)-to-ground scenario.

Identification of protein coding genes in genomes with statistical functions based on the circular code.

A new statistical approach using functions based on the circular code classifies correctly more than 93% of bases in protein (coding) genes and non-coding genes of human sequences. Based on this statistical study, a research software called 'Analysis of Coding Genes' (ACG) has been developed for identifying protein genes in the genomes and for determining their frame. Furthermore, the software ACG also allows an evaluation of the length of protein genes, their position in the genome, their relative position between themselves, and the prediction of internal frames in protein genes.