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A distributed minimum-distortion routing algorithm with in-network data processing

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The Strong Integral Input-to-State Stability Property in Dynamical Flow Networks

Nils Gustav Nilsson

Dynamical flow networks serve as macroscopic models for, e.g., transportation networks, queuing networks, and distribution networks. While the flow dynamics in such networks follow the conservation of mass on the links, the outflow from each link is often ...

Piscataway2024

In-network devices around the world monitor and tamper with connections for many reasons, including intrusion prevention, combating spam or phishing, and country-level censorship. Connection tampering seeks to block access to specific domain names or keywo ...

New York2023

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The CA1 region of the hippocampus is one of the most studied regions of the rodent brain, thought to play an important role in cognitive functions such as memory and spatial navigation. Despite a wealth of experimental data on its structure and function, i ...

2023

An automatized signal timing detection at signalized intersections with detailed vehicle trajectory data

Nikolaos Geroliminis, Emmanouil Barmpounakis, Jasso Espadaler Clapés

Signalized intersections are a fundamental part of urban networks. Their understanding is crucial to identify congestion patterns, queues, delays, and safety issues in local and network level. In this work, we analyze multimodal vehicle trajectories and pr ...

2022

Updates for automatic analysis and post-processing of JET neutral particle analysers for TT and DT campaigns

Henri Weisen

The data processing from both JET Neutral Particle Analysers (NPAs), high energy and low energy detector systems, has been updated for needs of operating in different scenarios with several isotopes in tritium and deuterium plasmas in the 2021 campaigns. T ...

IOP Publishing Ltd2022

There is an increasing interest in a fast-growing machine learning technique called Federated Learning (FL), in which the model training is distributed over mobile user equipment (UEs), exploiting UEs' local computation and training data. Despite its advan ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Data & Figures on the Multiscale Spatiotemporal Characterization of Embodied Environmental Efficiency of Building Structures in Geneva from 1850 to 2018

Corentin Jean Dominique Fivet, Catherine Elvire L. De Wolf, Serena Vanbutsele

Process data, figures, and figure data resulting from the study on Multiscale Spatiotemporal Characterization of Embodied Environmental Efficiency of Building Structures in Geneva from 1850 to 2018. ...

2021

The paper “Dynamic efficiency in multilayer transportation networks” (Bellocchi, Geroliminis, 2018) [1] introduced new performance measures to quantify dynamically the effect of traffic congestion in a multilayer network. Based on these measures, we explor ...

2020

Network coded multipath and related techniques

Emre Telatar, Arno Schneuwly, Derya Malak

Techniques are disclosed for adaptive coding and scheduling of packets in wireless networks. The adaptive coding and scheduling can be achieved by utilizing a discrete water filling (DWF) scheme. In an example, a computer-implemented method to adaptively c ...

2020

Exponential Collapse Of Social Beliefs Over Weakly-Connected Heterogeneous Networks

Ali H. Sayed, Augusto José Rabelo Almeida Santos

We consider a distributed social learning problem where a network of agents is interested in selecting one among a finite number of hypotheses. The data collected by the agents might be heterogeneous, meaning that different sub-networks might observe data ...

IEEE2019