Related papers: Seismogenic Mobile Network
Device-Free Localization (DFL) employs passive radio techniques capable to detect and locate people without imposing them to wear any electronic device. By exploiting the Integrated Sensing and Communication paradigm, DFL networks employ…
Earthquake monitoring is necessary to promptly identify the affected areas, the severity of the events, and, finally, to estimate damages and plan the actions needed for the restoration process. The use of seismic stations to monitor the…
Dealing with broadcast scenarios has become a relevant topic in the scientific community. Because of interference, resource management presents a challenge, specially when spatial diversity is introduced. Many researches presented…
A key technical requirement of any future quantum network is the ability to distribute quantum-entangled resources between two spatially separated points at a high rate and high fidelity. Entanglement distribution protocols based on…
In this paper we introduce new models of complex weighted networks sharing several properties with fractal sets: the deterministic non-homogeneous weighted fractal networks and the stochastic weighted fractal networks. Networks of both…
A temporal complex network-based approach is proposed as a novel formulation to investigate turbulent mixing from a Lagrangian viewpoint. By exploiting a spatial proximity criterion, the dynamics of a set of fluid particles is geometrized…
This paper investigates a hybrid radio frequency (RF)/visible light communication (VLC) ultra-small cell network consisting of multiple optical angle-diversity transmitters, one multi-antenna RF access point (AP), and multiple terminal…
We propose an expectation maximization (EM)-based algorithm for semi-blind channel estimation of reciprocal channels in amplify-and-forward (AF) two-way relay networks (TWRNs). By incorporating both data samples and pilots into the…
Motivated by the need for ubiquitous and reliable communications in post-disaster emergency management systems (EMSs), we hereby present a novel and efficient stochastic geometry (SG) framework. This mathematical model is specifically…
The power network reconfiguration algorithm with an "R" modeling approach evaluates its behavior in computing new reconfiguration topologies for the power grid in the context of the Smart Grid. The power distribution network modelling with…
Electromagnetic (EM) communication is nearing its physical and thermodynamic limits, where further performance gains through spectrum optimization alone have become increasingly unsustainable. Finite bandwidth, propagation loss at higher…
A promising short term precursor of major earthquakes (EQ) is very crucial in saving people and preventing huge losses. Ez, atmospheric electrostatic field vertical component, under fair air conditions, is generally oriented downwards…
This article surveys the growing interest in utilizing Deep Learning (DL) as a powerful tool to address challenging problems in earthquake engineering. Despite decades of advancement in domain knowledge, issues such as uncertainty in…
A recently proposed method of constructing seismic networks from 'record breaking events' from the earthquake catalog of California (Phy. Rev. E, 77 6,066104, 2008) was successfull in establishing causal features to seismicity and arrive at…
We introduce the Seismic Language Model (SeisLM), a foundational model designed to analyze seismic waveforms -- signals generated by Earth's vibrations such as the ones originating from earthquakes. SeisLM is pretrained on a large…
The detection of earthquakes is a fundamental prerequisite for seismology and contributes to various research areas, such as forecasting earthquakes and understanding the crust/mantle structure. Recent advances in machine learning…
Combining physics with machine learning models has advanced the performance of machine learning models in many different applications. In this paper, we evaluate adding a weak physics constraint, i.e., a physics-based empirical…
The topology of classical networks is determined by physical links between nodes, and after a network request the links are used to establish the desired connections. Quantum networks offer the possibility to generate different kinds of…
The prediction of the electric field (E-field) plays a crucial role in monitoring radiofrequency electromagnetic field (RF-EMF) exposure induced by cellular networks. In this paper, a deep learning framework is proposed to predict E-field…
Recently advanced low-Earth-orbit (LEO) satellite networks represented by large constellations and advanced payloads provide great promises for enabling high-quality Internet connectivity to any place on Earth. However, the traditional…