Results 141 to 150 of about 67,029 (331)

Anomaly detection using isomorphic analysis for false data injection attacks in industrial control systems [PDF]

Xinchen Zhang, Zhihan Jiang, Yulong Ding, Edith C.‐H. Ngai, Shuang‐Hua Yang, Shuang-Hua Yang, Shuang-Hua Yang   +6 more
openalex   +1 more source

Inroads into epilepsy through high‐frequency oscillations: Achievements and benchmark areas for improvement

Epilepsia, EarlyView.
Abstract High‐frequency oscillations (HFOs) were discovered more than 20 years ago, and since then they have been studied intensively in the context of epilepsy. HFOs encompass a broad spectrum of oscillations, typically ranging from 80 Hz to several kHz, that include both normal and pathological oscillations, documented in people with epilepsy and ...
Christos Panagiotis Lisgaras, Birgit Frauscher, Jean Gotman, Julia Jacobs, Philippe Kahane, Richard J. Staba, Maeike Zijlmans   +6 more
wiley   +1 more source

Adaptive Sliding-Mode Path-Following Control of Cart-Pendulum Robots with False Data Injection Attacks [PDF]

, 2023
Jiadong Liu, Xiaozheng Jin, Chao Deng, Wei‐Wei Che   +3 more
openalex   +1 more source

A two‐sample Mendelian randomization study and mediation analysis exploring the link between cathepsins and epilepsy

Epilepsia Open, EarlyView.
Abstract Objective This study aims to investigate the causal relationship between cathepsins and epilepsy, using Mendelian randomization (MR) and mediation analysis. Methods Publicly accessible summary statistics on epilepsy were obtained from FinnGen and the International League Against Epilepsy Consortium.
Huaiyu Sun, Di Ma, Wuqiong Zhang, Shuai Hou, Zhiqing Chen, Xuewei Li, Hongmei Meng, Daguang Zhang   +7 more
wiley   +1 more source

Detection and mitigation of false data injection attack in DC–DC synchronous boost converter: A real‐time implementation using shallow neural network model

IET Power Electronics, EarlyView., 2023
This article proposes a neural network‐based cyber attack detection and mitigation scheme to detect and mitigate false data injection attacks on the sensors. Neural networks are used for the prediction of duty; a combination of a data sampler and a binary attack detector detects the presence of an attack.
Venkata Siva Prasad Machina, Sreedhar Madichetty, Sriranga Suprabhath Koduru, Mohan Krishna Banda, Sukumar Mishra   +4 more
wiley   +1 more source

Tomtit‐Raven Evolutionary Selector‐Reinforced Attention‐Driven: A High‐Performance and Computationally Efficient Cyber Threat Detection Framework for Smart Grids

Energy Science &Engineering, EarlyView.
Overview of the proposed work. ABSTRACT Identifying cyber threats maintains the security and operational stability of smart grid systems because they experience escalating attacks that endanger both operating data reliability and system stability and electricity grid performance.
Priya R. Karpaga, Praveen Kumar Balachandran, Umawathy Techanamurthy, Muhammad Ammirrul Atiqi Mohd Zainuri   +3 more
wiley   +1 more source

Detection and Localization of False Data Injection Attacks in Smart Grids Applying an Interpretable Fuzzy Genetic Machine Learning/Data Mining Approach [PDF]

Marian B. Gorzałczany, Filip Rudziński
openalex   +1 more source

Inconsistent Transcriptomic Responses to Hexabromocyclododecane in Japanese Quail: A Comparative Analysis of Results From Four Different Study Designs

Environmental Toxicology and Chemistry, EarlyView.
Abstract Efforts to use transcriptomics for toxicity testing have classically relied on the assumption that chemicals consistently produce characteristic transcriptomic signatures that are reflective of their mechanism of action. However, the degree to which transcriptomic responses are conserved across different test methodologies has seldom been ...
Paul Béziers, Elena Legrand, Emily Boulanger, Niladri Basu, Jessica D. Ewald, Paula Henry, Markus Hecker, Jianguo Xia, Natalie Karouna‐Renier, Doug Crump, Jessica Head   +10 more
wiley   +1 more source

Multi‐data classification detection in smart grid under false data injection attack based on Inception network [PDF]

Huan Pan, Hui Yang, Chunning Na, Jian Jin   +3 more
openalex   +1 more source

Exercise‐specific plasma proteomic signatures in racehorses: Candidates for training adaptation and peak load monitoring

Equine Veterinary Journal, EarlyView.
Abstract Background Racehorses undergo profound physiological changes with training and competition, but current biomarkers inadequately capture the complex molecular dynamics of exercise. This study aimed to identify novel plasma biomarkers of training adaptation and peak load using high‐throughput proteomics.
Jowita Grzędzicka, Bianka Świderska, Ewa Sitkiewicz, Izabela Dąbrowska, Olga Witkowska‐Piłaszewicz   +4 more
wiley   +1 more source