Results 91 to 100 of about 334,773 (381)

Deep Learning for Launching and Mitigating Wireless Jamming Attacks [PDF]

IEEE Transactions on Cognitive Communications and Networking, 2018
An adversarial machine learning approach is introduced to launch jamming attacks on wireless communications and a defense strategy is presented. A cognitive transmitter uses a pre-trained classifier to predict the current channel status based on recent ...
T. Erpek, Y. Sagduyu, Yi Shi
semanticscholar   +1 more source

Jamming in hierarchical networks [PDF]

Computer Physics Communications, 2015
We study the Biroli-Mezard model for lattice glasses on a number of hierarchical networks. These networks combine certain lattice-like features with a recursive structure that makes them suitable for exact renormalization group studies and provide an alternative to the mean-field approach.
Xiang Cheng, Stefan Boettcher
openaire   +2 more sources

Emergent traffic jams

Physical Review E, 1995
We study a single-lane traffic model that is based on human driving behavior. The outflow from a traffic jam self-organizes to a critical state of maximum throughput. Small perturbations of the outflow far downstream create emergent traffic jams with a power law distribution $P(t) \sim t^{-3/2}$ of lifetimes, $t$.
Kai Nagel, Kai Nagel, Maya Paczuski, Maya Paczuski   +3 more
openaire   +4 more sources

Numerical Studies of Influencing Factors on the Homogeneity of the Powder Mixture during the Powder Spreading Process of Powder Bed Fusion–Laser Beam/Metal

Advanced Engineering Materials, EarlyView.
AISI 304L stainless steel powder is mixed with silicon nitride (Si3N4) powder and processed by PBF‐LB/M, allowing partial retention of Si3N4. The numerical approach effectively predicts the Si3N4 powder homogeneity and N content distribution on the powder bed. Recent studies have focused on the alloying of nitrogen (N) in high‐alloy stainless steels by
Yuanbin Deng, Ziping Sang, Jiali Zhang, Felix Radtke, Louis Becker, Simone Herzog, Sebastian Weber, Christoph Broeckmann   +7 more
wiley   +1 more source

The first jamming crossover: geometric and mechanical features

, 2012
The jamming transition characterizes athermal systems of particles interacting via finite range repulsive potentials, and occurs on increasing the density when particles cannot avoid making contacts with those of their first coordination shell.
Massimo Pica Ciamarra, Okabe A., Peter Sollich   +2 more
core   +1 more source

AFRL: Adaptive federated reinforcement learning for intelligent jamming defense in FANET

Journal of Communications and Networks, 2020
The flying ad-hoc network (FANET) is a decentralized communication network for the unmanned aerial vehicles (UAVs). Because of the wireless nature and the unique network properties, FANET remains vulnerable to jamming attack with additional challenges ...
Nishat I. Mowla, Nguyen H. Tran, Inshil Doh, K. Chae   +3 more
semanticscholar   +1 more source

Engineering the Hierarchical Porosity of Granular Hydrogel Scaffolds Using Porous Microgels to Improve Cell Recruitment and Tissue Integration

Advanced Functional Materials, Volume 35, Issue 12, March 18, 2025.
By fabricating and covalently assembling gelatin methacryloyl (GelMA) porous microgels, a new class of granular hydrogel scaffolds with hierarchical porosity is developed. These scaffolds have a significantly higher void fraction than their counterparts made up of nonporous microgels, enhancing cell recruitment and tissue integration. This research may
Alexander Kedzierski, Sina Kheirabadi, Arian Jaberi, Zaman Ataie, Catherine L. Mojazza, Marisa L. Williamson, Anton M. Hjaltason, Aneesh Risbud, Yuanhui Xiang, Amir Sheikhi   +9 more
wiley   +1 more source

A jamming transition from under- to over-parametrization affects generalization in deep learning [PDF]

Journal of Physics A: Mathematical and Theoretical, 2018
In this paper we first recall the recent result that in deep networks a phase transition, analogous to the jamming transition of granular media, delimits the over- and under-parametrized regimes where fitting can or cannot be achieved.
S. Spigler, M. Geiger, Stéphane d'Ascoli, Levent Sagun, G. Biroli, M. Wyart   +5 more
semanticscholar   +1 more source

Jamming Bandits—A Novel Learning Method for Optimal Jamming [PDF]

IEEE Transactions on Wireless Communications, 2016
Can an intelligent jammer learn and adapt to unknown environments in an electronic warfare-type scenario? In this paper, we answer this question in the positive, by developing a cognitive jammer that adaptively and optimally disrupts the communication between a victim transmitter–receiver pair.
Amuru, S., Tekin, C., Van Der Schaar, M., Buehrer, R.M.   +3 more
openaire   +3 more sources

High‐Performance Low‐Emissivity Paints Enabled by N‐Doped Poly(benzodifurandione) (n‐PBDF) for Energy‐Efficient Buildings

Advanced Functional Materials, EarlyView.
This study introduces a scalable and colored low‐emissivity (low‐e) paint achieved by spraying an ultrathin n‐doped poly(benzodifurandione) (n‐PBDF) coating onto various colored substrates. The low‐e paint enhances thermal regulation by reducing mid‐infrared thermal emissivity to 0.19, thereby stabilizing indoor temperatures across diverse climates ...
Xiaojie Liu, Won‐June Lee, Daniel William Carne, Yanpei Tian, Andrea Felicelli, Yue Lei, Joseph A. Romo, Liyan You, Zixin Xiong, Orlando Gabriel Rivera Gonzalez, Abdulrahman Aljwirah, Qiaoqiang Gan, Jianguo Mei, Xiulin Ruan   +13 more
wiley   +1 more source