Zobrazeno 1 - 10
of 371 087
pro vyhledávání: '"SEN, A."'
Publikováno v:
2024 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference Europe (ISGT)
The shift to smart grids has made electrical power systems more vulnerable to sophisticated cyber threats. To protect these systems, holistic security measures that encompass preventive, detective, and reactive components are required, even with encr
Externí odkaz:
http://arxiv.org/abs/2412.04901
This study delves into the role of process awareness in enhancing intrusion detection within Smart Grids, considering the increasing fusion of ICT in power systems and the associated emerging threats. The research harnesses a co-simulation environmen
Externí odkaz:
http://arxiv.org/abs/2412.04902
Publikováno v:
27th International Conference on Electricity Distribution (CIRED 2023)
The integration of information and communication technology in distribution grids presents opportunities for active grid operation management, but also increases the need for security against power outages and cyberattacks. This paper examines the im
Externí odkaz:
http://arxiv.org/abs/2412.04900
Autor:
Agarwal, Kunika, Naik, Sahil Gopalkrishna, Chakraborty, Ananya, Sen, Samrat, Ghosal, Pratik, Paul, Biswajit, Banik, Manik, Patra, Ram Krishna
The zero-error capacity of a noisy classical channel quantifies its ability to transmit information with absolute certainty, i.e., without any error. Unlike Shannon's standard channel capacity, which remains unaffected by pre-shared correlations, zer
Externí odkaz:
http://arxiv.org/abs/2412.04779
Existing self-supervised monocular depth estimation (MDE) models attempt to improve nighttime performance by using GANs to transfer nighttime images into their daytime versions. However, this can introduce inconsistencies due to the complexities of r
Externí odkaz:
http://arxiv.org/abs/2412.04666
We introduce and study Multi-Quantile estimators for the parameters $( \xi, \sigma, \mu)$ of Generalized Extreme Value (GEV) distributions to provide a robust approach to extreme value modeling. Unlike classical estimators, such as the Maximum Likeli
Externí odkaz:
http://arxiv.org/abs/2412.04640
Autor:
Ti, Changpeng, Hassan, Usman, Vatsavai, Sairam Sri, McCarter, Margaret, Vasdev, Aastha, An, Jincheng, Achinuq, Barat, Welp, Ulrich, Cheung, Sen-Ching, Thakkar, Ishan G, Hastings, J. Todd
Patterned nanomagnet arrays (PNAs) have been shown to exhibit a strong geometrically frustrated dipole interaction. Some PNAs have also shown emergent domain wall dynamics. Previous works have demonstrated methods to physically probe these magnetizat
Externí odkaz:
http://arxiv.org/abs/2412.04622
The high costs and risks involved in extensive environment interactions hinder the practical application of current online safe reinforcement learning (RL) methods. While offline safe RL addresses this by learning policies from static datasets, the p
Externí odkaz:
http://arxiv.org/abs/2412.04426
In this paper, we focus on the gravitational waves emitted by a stellar-mass object in a quasi-circular inspiral orbit around a central supermassive polymerized black hole in loop quantum gravity. Treating the stellar-mass object as a massive test pa
Externí odkaz:
http://arxiv.org/abs/2412.04302
Publikováno v:
2023 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)
As the integration of digital technologies and communication systems continues within distribution grids, new avenues emerge to tackle energy transition challenges. Nevertheless, this deeper technological immersion amplifies the necessity for resilie
Externí odkaz:
http://arxiv.org/abs/2412.03973