Results 141 to 150 of about 176,660 (282)

Polar‐low track prediction using machine‐learning methods

Quarterly Journal of the Royal Meteorological Society, EarlyView.
Machine‐learning models are developed to produce reliable and efficient forecasts of polar‐low (PL) trajectories 12 hours ahead. A temporal model (RLSTM) benefiting from the rolling‐forecast strategy, improves overall prediction accuracy and is suitable for quick experimentation, while a spatiotemporal model (PL‐UNet), incorporating both historical and
Ziying Yang, Rune Grand Graversen, Filippo Maria Bianchi, Jiping Liu, Ruibo Lei   +4 more
wiley   +1 more source

How AI and Digital Technologies Can Enhance Sustainable Livestock Manure Management: An Overview From Treatment to Distribution

Sustainable Development, EarlyView.
ABSTRACT Sustainable livestock manure management sits at the nexus of climate, nutrient circularity and water quality. This review explores how artificial intelligence (AI) and digital platforms are used across four management stages, that is, treatment, storage, valorisation and distribution, and figures out where integration fails to deliver ...
Zhan Shi, Feihong Liang, Francesco Marinello, Andrea Pezzuolo   +3 more
wiley   +1 more source

Integrating multimodal data and machine learning for entrepreneurship research

Strategic Entrepreneurship Journal, EarlyView.
Abstract Research Summary Extant research in neuroscience suggests that human perception is multimodal in nature—we model the world integrating diverse data sources such as sound, images, taste, and smell. Working in a dynamic environment, entrepreneurs are expected to draw on multimodal inputs in their decision making.
Yash Raj Shrestha, Vivianna Fang He
wiley   +1 more source

Enhanced glucose forecasting using recurrent neural network and advanced feature engineering. [PDF]

Sci Rep
Osman MH, Mahmoud M, Zakzouk S, Mohamed S, Gomaa I, Darweesh MS, Taha S, Soltan A.   +7 more
europepmc   +1 more source

An electroencephalography sleep staging model based on bidirectional Mamba combining synergistic attention with interactive convolution

Sleep Research, EarlyView.
Abstract Background This study presents SIMSleepSM, a novel single‐channel electroencephalography (EEG) sleep staging model. It addresses two primary challenges: insufficient modeling of long‐range temporal dependencies combined with limited multi‐scale feature extraction, and poor accuracy in identifying the N1 stage.
Ya‐mei Xu, Ding‐Yuan An
wiley   +1 more source

Mamba-based deep learning approach for sleep staging on a wireless multimodal wearable system without electroencephalography. [PDF]

Sleep
Zhang AH, He-Mo A, Yin RF, Li C, Tang Y, Gurve D, van der Horst V, Buchman AS, Ghahjaverestan NM, Goubran M, Wang B, Lim ASP.   +11 more
europepmc   +1 more source

Position Transmission Control in Tendon–Sheath Mechanisms: A Critical Review and a Promising Solution

SmartBot, EarlyView.
Tendon‐sheath mechanisms are widely used in various robotic systems for remote position transmission, including aerospace vehicles, flexible rescue robots, dexterous robotic hands, exoskeleton robots, soft wearable devices, industrial robots, and flexible surgical robots.
Jiaqi Li, Qian Gao
wiley   +1 more source

Anomaly-based intrusion detection on benchmark datasets for network security: a comprehensive evaluation. [PDF]

Sci Rep
Kumar LKS, Nethi SR, Uyyala R, Vurubindi P, Narahari SC, Das AK, K VB, Alenazi MJF.   +7 more
europepmc   +1 more source

Advanced Hybrid Techniques for Cyberattack Detection and Defense in IoT Networks

SECURITY AND PRIVACY, Volume 8, Issue 2, March/April 2025.
ABSTRACT The Internet of Things (IoT) represents a vast network of devices connected to the Internet, making it easier for users to connect to modern technology. However, the complexity of these networks and the large volume of data pose significant challenges in protecting them from persistent cyberattacks, such as distributed denial‐of‐service (DDoS)
Zaed S. Mahdi, Rana M. Zaki, Laith Alzubaidi   +2 more
wiley   +1 more source

A Novel Approach to Energy Management in Electric Steelworks

steel research international, EarlyView.
Feed‐forward neural networks are exploited to estimate electric energy consumptions of the electric arc furnace and ladle furnace processes. The models are used to optimize production schedule so that more energy intensive grades are produced when the cost of energy is lower.
Valentina Colla, Stefano Dettori, Silvia Cateni, Marco Vannucci, Antonella Vignali, Claudio Mocci, Irene Dovichi, Davide Chionna, Lorenzo Vannini, Enrico Paluzzano, Costanzo Pietrosanti, Davide Onesti, Daniele Venier   +12 more
wiley   +1 more source