Results 61 to 70 of about 30,371 (174)

Empirical Physics‐Based Normal Behavior Modeling of Drive Train Temperatures With High‐Resolution Wind Turbine Operating Data

Wind Energy, EarlyView.
ABSTRACT The installed wind energy capacity increases every year. However, operation and maintenance costs still make up a considerable portion of the levelized costs of electricity. This costs can be greatly reduced by the application of suitable early fault detection methods. The supervisory control and data acquisition system of wind turbines is one
Timo Lichtenstein, Victor von Maltzahn, Karoline Pelka   +2 more
wiley   +1 more source

AI‐Powered Anomaly Detection for Secure Internet of Things (IoT): Optimising XGBoost and Deep Learning With Bayesian Optimisation

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Intelligent and adaptive defence systems that can quickly thwart changing cyberthreats are becoming more and more necessary in the dynamic and data‐intensive Internet of things (IoT) environment. Using the NSL‐KDD benchmark dataset, this paper presents an improved anomaly detection system that combines an optimised sequential neural network ...
Seong‐O Shim, Lal Hussain, Mohammed A. Alqarni, Faisal S. Alsubaei, Rasha Jamal Atwah   +4 more
wiley   +1 more source

Downside risk similarity and M&As

Contemporary Accounting Research, EarlyView.
Abstract Downside risks are ubiquitous and can profoundly impact firm operations and valuation. Failure to adequately assess and manage target firms' downside risks hinders acquirers' ability to integrate and manage these businesses. This article introduces a novel measure of firms' downside risk similarity (DRS) based on risk factor descriptions and ...
Lei Chen, Allen H. Huang, Xinlu Wang, Liang Xu   +3 more
wiley   +1 more source

Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics

, 2019
A recent strategy to circumvent the exploding and vanishing gradient problem in RNNs, and to allow the stable propagation of signals over long time scales, is to constrain recurrent connectivity matrices to be orthogonal or unitary.
Bengio, Yoshua, Gidel, Gauthier, Goyette, Kyle, Kerg, Giancarlo, Lajoie, Guillaume, Touzel, Maximilian Puelma, Vorontsov, Eugene   +6 more
core  

Network medicine and systems pharmacology approaches to predicting adverse drug effects

British Journal of Pharmacology, EarlyView.
Identifying and understanding the relationships between drug intake and adverse effects that can occur due to inadvertent molecular interactions between drugs and targets is a difficult task, especially considering the numerous variables that can influence the onset of such events.
Alessio Funari, Giulia Fiscon, Paola Paci   +2 more
wiley   +1 more source

Financial Time Series Uncertainty: A Review of Probabilistic AI Applications

Journal of Economic Surveys, EarlyView.
ABSTRACT Probabilistic machine learning models offer a distinct advantage over traditional deterministic approaches by quantifying both epistemic uncertainty (stemming from limited data or model knowledge) and aleatoric uncertainty (due to inherent randomness in the data), along with full distributional forecasts.
Sivert Eggen, Tord Johan Espe, Kristoffer Grude, Morten Risstad, Rickard Sandberg   +4 more
wiley   +1 more source

Harnessing Human Mobility Data for Applied Economic Research: Current Knowledge, Challenges, and Emerging Opportunities

Journal of Economic Surveys, EarlyView.
ABSTRACT This paper reviews how large‐scale mobility data can enhance economic analyses, highlighting its contributions to understanding travel behavior, labor markets, social interactions, and health outcomes. We discuss its advantages over traditional mobility data sources, which include real‐time location information and fine spatial resolution ...
Cristina Connolly, Sandro Steinbach, Mike Vo, Xibo Wan   +3 more
wiley   +1 more source

Hollow institutions: Merleau‐Ponty and the possibility of coordinated action

The Southern Journal of Philosophy, EarlyView.
Abstract This article addresses the phenomenon of political powerlessness, understood—following Hannah Arendt—as the separation of “words and deeds,” a condition in which words become “empty” and actions lose their overall intelligibility, increasingly relying on coercion. I take up Merleau‐Ponty's phenomenology of institution to explore this condition.
Daniil Koloskov
wiley   +1 more source

Consistent Dynamic Mode Decomposition

, 2019
We propose a new method for computing Dynamic Mode Decomposition (DMD) evolution matrices, which we use to analyze dynamical systems. Unlike the majority of existing methods, our approach is based on a variational formulation consisting of data alignment
Azencot, Omri, Bertozzi, Andrea, Yin, Wotao   +2 more
core  

Advances and challenges in multiscale biomolecular simulations: artificial intelligence‐driven paradigm shift

Quantitative Biology, Volume 14, Issue 2, June 2026.
Abstract Molecular simulation techniques have become an invaluable tool for elucidating the fundamental principles of life at the molecular level. After nearly five decades of development, biomolecular simulations have evolved to enable the quantitative characterization of complex biomolecular events, such as protein folding, conformational dynamics ...
Wenfei Li, Wei Wang
wiley   +1 more source