Results 201 to 210 of about 6,827,955 (283)

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia, Christian Mark Pelicano   +1 more
wiley   +1 more source

AS‐pHopt: An Optimal pH Prediction Model Enhanced by Active Site of Enzymes

Advanced Intelligent Discovery, EarlyView.
To address the low accuracy of enzyme optimal pH (pHopt) prediction, this study develops active site‐based pHopt (AS‐pHopt), a prediction model enhanced by active site information and pseudo‐label prediction. Integrating key structural and physicochemical features affecting enzyme pHopt, AS‐pHopt uses Evolutionary Scale Modeling (ESM)‐2 with active ...
Wenxiang Song, Xinmin Li, Hongbo Yu, Le Xiong, Guixia Liu, Weihua Li, Yun Tang   +6 more
wiley   +1 more source

Data‐Efficient Cycle‐Level Capacity Prediction Using 1D Deep Convolutional Network

Advanced Intelligent Discovery, EarlyView.
We introduce DeepBat, a deep learning framework featuring a 1D convolutional backbone designed to extract latent degradation patterns from a microstructurally diverse electrode dataset. By learning complex formulation–performance relationships, the model accurately predicts long‐term specific discharge capacity using limited early‐cycle data, providing
Tao Huang, Bing Sun, Zhigang Chen, Chenyu Zhao, Eugene Bakker, Yaojie Lei, Lingfei Zhao, Shijian Wang, Chao Liu, Virginia Xiaojun He, Bahram Shirzadi, Hao Liu, Xin Xi, Ruiliu Liu, Dongqing Wu, Guodong Long, Guoxiu Wang   +16 more
wiley   +1 more source

Catalyst‐Specialized Chemical Language Model Based on Transformer Variational Autoencoder for Catalyst Design and Discovery

Advanced Intelligent Discovery, EarlyView.
We present CatTransVAE, a catalyst‐specialized chemical language model (CLM) built on a transformer variational autoencoder (VAE), developed through pretraining on general compounds followed by fine‐tuning on diverse catalyst databases. A template‐guided generation framework is introduced to enable controlled catalyst design under structural ...
Apakorn Kengkanna, Masahito Ohue
wiley   +1 more source

Behaviorally Adaptive and Inclusive Advanced Driver‐Assistance Systems

Advanced Intelligent Systems, EarlyView.
Advanced driver‐assistance systems (ADASs) are mapped as evolving human‐centered, adaptive technologies linking sensing, driver monitoring, AR/HUD interfaces, patents, regulation, and inclusive design. The review identifies gaps in real‐world evidence, diverse‐driver validation, gaze metrics, and governance, outlining a roadmap for safer, behaviorally ...
Jana Skirnewskaja, Mardavij Roozbehani, Munther A. Dahleh   +2 more
wiley   +1 more source

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Automotive Radar Signal Processing: Research Directions and Practical Challenges

IEEE Journal on Selected Topics in Signal Processing, 2021
Automotive radar is used in many applications of advanced driver assistance systems and is considered as one of the key technologies for highly automated driving.
Florian Engels, Abdelhak M Zoubir, Muhammed Al Kadi   +2 more
exaly   +2 more sources

The Rise of Radar for Autonomous Vehicles: Signal Processing Solutions and Future Research Directions

IEEE Signal Processing Magazine, 2019
Automotive radar is the most promising and fastest-growing civilian application of radar technology. Vehicular radars provide the key enabling technology for the autonomous driving revolution that will have a dramatic impact on everyone's day-to-day ...
Igal Bilik, Oren Longman, Joseph Tabrikian   +2 more
exaly   +2 more sources

Signal Processing: Radar

, 2014
Space-time adaptive processing (STAP) is a processing technique operating in the space-time domain that allows the simultaneous cancellation of clutter and jamming via the computation of a 2D cancellation filter.
M. Barreteau, C. Cantini
semanticscholar   +2 more sources

Radar Signal Processing

IEEE ASSP Magazine (Acoustics, Speech, and Signal Processing), 1985
A review of recent developments in radar signal processing in the presence of clutter is presented, with particular reference to an air-traffic environment. Two different signal processing issues are considered. The first issue relates to the adaptive suppression of clutter (of unknown statistics) and consequent enhancement of the echo produced by a ...
S Haykin
exaly   +2 more sources

A Novel Intercarrier-Interference Free Signal Processing Scheme for OFDM Radar

IEEE Transactions on Vehicular Technology, 2018
Gor Hakobyan, Bin Yang
exaly   +2 more sources