Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Naeini, Mia"'
Autor:
Haghshenas, Seyed Hamed, Naeini, Mia
State Estimation is a crucial task in power systems. Graph Neural Networks have demonstrated significant potential in state estimation for power systems by effectively analyzing measurement data and capturing the complex interactions and interrelatio
Externí odkaz:
http://arxiv.org/abs/2410.16008
Autor:
Waqas, Asim, Tripathi, Aakash, Stewart, Paul, Naeini, Mia, Schabath, Matthew B., Rasool, Ghulam
Cancer clinics capture disease data at various scales, from genetic to organ level. Current bioinformatic methods struggle to handle the heterogeneous nature of this data, especially with missing modalities. We propose PARADIGM, a Graph Neural Networ
Externí odkaz:
http://arxiv.org/abs/2406.08521
Autor:
Waqas, Asim, Tripathi, Aakash, Ahmed, Sabeen, Mukund, Ashwin, Farooq, Hamza, Schabath, Matthew B., Stewart, Paul, Naeini, Mia, Rasool, Ghulam
Multi-omics research has enhanced our understanding of cancer heterogeneity and progression. Investigating molecular data through multi-omics approaches is crucial for unraveling the complex biological mechanisms underlying cancer, thereby enabling m
Externí odkaz:
http://arxiv.org/abs/2405.08226
Autor:
Hasnat, Md Abul, Naeini, Mia
This article explores the effects of a single bus perturbation in the electrical grid using a Graph Signal Processing (GSP) perspective. The perturbation is characterized by a sudden change in real-power load demand or generation. The study focuses o
Externí odkaz:
http://arxiv.org/abs/2306.03254
Autor:
Sami, Naeem Md, Naeini, Mia
Cascading failures pose a significant threat to power grids and have garnered considerable research interest in the power system domain. The inherent uncertainty and severe impact associated with cascading failures have raised concerns, prompting the
Externí odkaz:
http://arxiv.org/abs/2305.19390
This paper presents a Temporal Graph Neural Network (TGNN) framework for detection and localization of false data injection and ramp attacks on the system state in smart grids. Capturing the topological information of the system through the GNN frame
Externí odkaz:
http://arxiv.org/abs/2212.03390
Autor:
Hossain, Md Jakir1 (AUTHOR) mdjakir@usf.edu, Naeini, Mia1 (AUTHOR)
Publikováno v:
Energies (19961073). Oct2022, Vol. 15 Issue 19, p7105. 17p.
Akademický článek
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