Zobrazeno 1 - 10
of 165
pro vyhledávání: '"A P Meliopoulos"'
The deep reinforcement learning (DRL) based Volt-VAR optimization (VVO) methods have been widely studied for active distribution networks (ADNs). However, most of them lack safety guarantees in terms of power injection uncertainties due to the increa
Externí odkaz:
http://arxiv.org/abs/2409.18937
The inability to linearly classify XOR has motivated much of deep learning. We revisit this age-old problem and show that linear classification of XOR is indeed possible. Instead of separating data between halfspaces, we propose a slightly different
Externí odkaz:
http://arxiv.org/abs/2312.01541
Autor:
Hua Shi, Xiaojian Zhang, Pan Ge, Victoria Meliopoulos, Pam Freiden, Brandi Livingston, Stacey Schultz-Cherry, Ted M. Ross
Publikováno v:
Human Vaccines & Immunotherapeutics, Vol 20, Iss 1 (2024)
The influenza viruses cause seasonal respiratory illness that affect millions of people globally every year. Prophylactic vaccines are the recommended method to prevent the breakout of influenza epidemics. One of the current commercial influenza vacc
Externí odkaz:
https://doaj.org/article/cef4514323684081929e419941f4c556
The increasing deployment of end use power resources in distribution systems created active distribution systems. Uncontrolled active distribution systems exhibit wide variations of voltage and loading throughout the day as some of these resources op
Externí odkaz:
http://arxiv.org/abs/2207.14642
Complex interconnections between information technology and digital control systems have significantly increased cybersecurity vulnerabilities in smart grids. Cyberattacks involving data integrity can be very disruptive because of their potential to
Externí odkaz:
http://arxiv.org/abs/2102.11401
Autor:
Zemin Yang, Bryan A. Johnson, Victoria A. Meliopoulos, Xiaohui Ju, Peipei Zhang, Michael P. Hughes, Jinjun Wu, Kaitlin P. Koreski, Jemma E. Clary, Ti-Cheng Chang, Gang Wu, Jeff Hixon, Jay Duffner, Kathy Wong, Rene Lemieux, Kumari G. Lokugamage, R. Elias Alvarado, Patricia A. Crocquet-Valdes, David H. Walker, Kenneth S. Plante, Jessica A. Plante, Scott C. Weaver, Hong Joo Kim, Rachel Meyers, Stacey Schultz-Cherry, Qiang Ding, Vineet D. Menachery, J. Paul Taylor
Publikováno v:
Cell Reports, Vol 43, Iss 3, Pp 113965- (2024)
Summary: G3BP1/2 are paralogous proteins that promote stress granule formation in response to cellular stresses, including viral infection. The nucleocapsid (N) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) inhibits stress g
Externí odkaz:
https://doaj.org/article/34285ee87dee48f994909c7562854676
Autor:
Liu, Yu, Singh, Abhinav Kumar, Zhao, Junbo, Meliopoulos, A. P., Pal, Bikash, Ariff, M. A. M., Van Cutsem, Thierry, Glavic, Mevludin, Huang, Zhenyu, Kamwa, Innocent, Mili, Lamine, Mir, Saleem, Taha, Ahmad, Terzija, Vladimir, Yu, Shenglong
Dynamic state estimation (DSE) accurately tracks the dynamics of a power system and provides the evolution of the system state in real-time. This paper focuses on the control and protection applications of DSE, comprehensively presenting different fa
Externí odkaz:
http://arxiv.org/abs/2012.14927
Autor:
Zhao, Junbo, Netto, Marcos, Huang, Zhenyu, Yu, Samson Shenglong, Gomez-Exposito, Antonio, Wang, Shaobu, Kamwa, Innocent, Akhlaghi, Shahrokh, Mili, Lamine, Terzija, Vladimir, Meliopoulos, A. P. Sakis, Pal, Bikash, Singh, Abhinav Kumar, Abur, Ali, Bi, Tianshu, Rouhani, Alireza
Power system dynamic state estimation (DSE) remains an active research area. This is driven by the absence of accurate models, the increasing availability of fast-sampled, time-synchronized measurements, and the advances in the capability, scalabilit
Externí odkaz:
http://arxiv.org/abs/2005.05380
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