Results 151 to 160 of about 5,451,620 (296)
Quarterly Journal of the Royal Meteorological Society, EarlyView.Precipitation growth and decay due to orography was analyzed using the radar network in Great Britain. Storm direction and speed modulate the intensity of precipitation growth or decay. Windward slopes predominantly exhibit precipitation growth, while leeward areas show precipitation decay.
Chen Li, Miguel Angel Rico‐Ramirez
wiley +1 more source
Weibull Variational Autoencoder for Remaining Useful Life Prediction
Quality and Reliability Engineering International, EarlyView.ABSTRACT Remaining useful life (RUL) prediction is a critical technology for preventing unexpected failures and reducing maintenance costs in modern industrial systems. However, traditional model‐based approaches are limited by the need for explicit mathematical modeling of degradation mechanisms, while data‐driven methods often require large‐scale ...
JunWoo Yu +4 more
wiley +1 more source
Integrating Image Segmentation and Deep Learning to Improve Radio Frequency Propagation Models
International Journal of Satellite Communications and Networking, EarlyView.ABSTRACT This paper proposes a multi‐sensor approach to improve radio frequency (RF) propagation models, which play a key role in the rapidly expanding field of connected vehicle technology. Focusing on the 1‐ to 20‐GHz frequency range, which is critical for both satellite‐to‐vehicle and base station‐to‐vehicle communications, our study introduces a ...
Jonathan Israel +2 more
wiley +1 more source
Indonesia merupakan wilayah yang rentan terhadap gempa bumi karena lokasinya berada di pertemuan tiga lempeng benua dan dikelilingi oleh Cincin Api (Ring of Fire).
Anggraini, Ika Novia +2 more
core +2 more sources
Beginner's Guide to Recurrent Neural Networks (RNNs) with Keras
Understanding Sequential Data Modelling with Keras for Time Series Prediction <strong> Author </strong> Wenyi Pi ( <strong> ORCID </strong> : 0009–0002–2884–2771) Introduction Recurrent Neural Networks (RNNs) are a special type of neural networks that are suitable for learning representations of sequential data like text in ...
openaire +1 more source
ML‐Assisted Adaptive Fade Mitigation for Satellite Connectivity
International Journal of Satellite Communications and Networking, EarlyView.ABSTRACT The demand for reliable and high‐quality wireless networks driven by resource‐intensive applications and services is growing rapidly and invoked the emergence of beyond 5G (B5G) and 6G paradigm and technologies which include satellite systems as part of the nonterrestrial networks (NTN).
Jinwara Surattanagul +4 more
wiley +1 more source
Uncertainty Characterization Framework for Machine Learning Based ACM in Q‐Band Satellite Links
International Journal of Satellite Communications and Networking, EarlyView.ABSTRACT Adaptive coding and modulation (ACM) is a widely utilized technique in satellite communication networks to mitigate the adverse effects of rain fades, particularly in extremely high frequency (EHF) bands. As a core component of fade mitigation techniques (FMTs), ACM improves signal resilience.
Kamolideen Abolarinwa +3 more
wiley +1 more source
Sustainable Development, EarlyView.ABSTRACT The FAO's “blue transformation” roadmap necessitates a fundamental shift towards precision aquaculture to meet global food security targets while minimizing environmental footprints. This review provides a comprehensive overview of how artificial intelligence (AI) and decision support systems (DSS) serve as pivotal enablers for the “better ...
Mustafa Öz, Enes Üstüner
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
Network Latency Estimation for Telesurgery Using Deep Reinforcement Learning
SmartBot, EarlyView.Overview of the proposed two‐stage deep reinforcement learning framework for network latency prediction in telesurgery. The pipeline includes data collection from simulated catheter navigation sessions (Philippines–Botswana), feature engineering, DQN‐based direction prediction (85.8% accuracy), direction‐to‐value transformation, and value forecasting ...
Bakang Kgopolo +2 more
wiley +1 more source