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		题名	作者	年代	出处	被引量
	1	Detection and Localization of Load Redistribution Attacks on Large-scale Systems显示文摘A nearest-neighbor-based detector against load redistribution attacks is presented.The detector is designed to scale from small-scale to very large-scale systems while guaranteeing consistent detection performance.Extensive testing is performed on a realistic large-scale system to evaluate the perfor-mance of the proposed detector against a wide range of attacks,from simple random noise attacks to sophisticated load redistribution attacks.The detection capability is analyzed against different attack parameters to evaluate its sensitivity.A statistical test that leverages the proposed detector is introduced to identify which loads are likely to have been maliciously modified,thus,localizing the attack subgraph.This test is based on ascribing to each load a risk measure(probability of being attacked)and then computing the best posterior likelihood that minimizes log-loss.	Andrea Pinceti Lalitha Sankar Oliver Kosut	2022	Journal of Modern Power Systems and Clean Energy2022，10，2：	2
	2	Effect of packaging atmosphere on the microbial attributes of pearlspot( Etroplus suratensis Bloch)stored at 0 ℃ - 2℃ 显示文摘	Ravi Sankar C N Lalitha K V Jose L	2008	Food Microbiology2008，25，3：	1
	3	Effect of packaging atmosphere on the microbial attributes of pearlspot (Elroplus sttratensis Bloch) stored at 0-2℃ 显示文摘	Ravi Sankar C N Lalitha K V Jose L	2009	Food Microbiology2009，25，3：	1
	4	Effect ofpackaging atmosphere on the microbial attributes of pearlspot {Etroplussuratensis Bloch)stored at 0-2 °C显示文摘	RAVI SANKAR C N LALITHA K V JOSE L	2009	Food Microbiology2009，25，3：	1
	5	Synthetic PMU Data Creation Based on Generative Adversarial Network Under Time-varying Load Conditions显示文摘In this study,a machine learning based method is proposed for creating synthetic eventful phasor measurement unit(PMU)data under time-varying load conditions.The proposed method leverages generative adversarial networks to create quasi-steady states for the power system under slowly-varying load conditions and incorporates a framework of neural ordinary differential equations(ODEs)to capture the transient behaviors of the system during voltage oscillation events.A numerical example of a large power grid suggests that this method can create realistic synthetic eventful PMU voltage measurements based on the associated real PMU data without any knowledge of the underlying nonlinear dynamic equations.The results demonstrate that the synthetic voltage measurements have the key characteristics of real system behavior on distinct time scales.	Xiangtian Zheng Andrea Pinceti Lalitha Sankar Le Xie	2023	Journal of Modern Power Systems and Clean Energy2023，11，1：	0

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