Results 51 to 60 of about 114,074 (272)

Beyond Presumptions: Toward Mechanistic Clarity in Metal‐Free Carbon Catalysts for Electrochemical H2O2 Production via Data Science

Advanced Materials, EarlyView.
Metal‐free carbon catalysts enable the sustainable synthesis of hydrogen peroxide via two‐electron oxygen reduction; however, active site complexity continues to hinder reliable interpretation. This review critiques correlation‐based approaches and highlights the importance of orthogonal experimental designs, standardized catalyst passports ...
Dayu Zhu, Hsi‐wen Wu, Xiao Wang, Jie Zhang   +3 more
wiley   +1 more source

Detection and Estimation of Gas Sources With Arbitrary Locations Based on Poisson's Equation

IEEE Open Journal of Signal Processing
Accurate estimation of the number and locations of dispersed material sources is critical for optimal disaster response in Chemical, Biological, Radiological, or Nuclear accidents.
Dmitriy Shutin, Thomas Wiedemann, Patrick Hinsen   +2 more
doaj   +1 more source

Seismic Signal Compression Using Nonparametric Bayesian Dictionary Learning via Clustering

Algorithms, 2017
We introduce a seismic signal compression method based on nonparametric Bayesian dictionary learning method via clustering. The seismic data is compressed patch by patch, and the dictionary is learned online.
Xin Tian, Song Li
doaj   +1 more source

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

Advanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj, Roshni Satheesh Babu, Yuxin Xia, Eva Bestelink, Radu Sporea, Nikos Hastas, Ioannis Zeimpekis, Dimitra G. Georgiadou, Sayani Majumdar   +8 more
wiley   +1 more source

Feature Enhancement of Interferometric Synthetic Aperture Radar Image Formation Using Sparse Bayesian Learning in Joint Sparsity Approach

Leida xuebao, 2018
A novel sparse Bayesian learning approach with a joint sparsity model is proposed for Interferometric Synthetic Aperture Radar (InSAR) image formation to realize the feature enhancements of interferometric phase denoising and speckle reduction.
Hou Yuxing, Xu Gang
doaj   +1 more source

Spatiotemporal Sparse Bayesian Learning with Applications to Compressed Sensing of Multichannel Physiological Signals

, 2014
Energy consumption is an important issue in continuous wireless telemonitoring of physiological signals. Compressed sensing (CS) is a promising framework to address it, due to its energy-efficient data compression procedure.
Jung, Tzyy-Ping, Makeig, Scott, Pi, Zhouyue, Rao, Bhaskar D., Zhang, Zhilin   +4 more
core   +1 more source

Bidirectional Process Prediction in the Laser‐Induced‐Graphene Production Using Blackbox Deep Learning

Advanced Materials Technologies, EarlyView.
This study shows that a lightweight blackbox neural network provides a practical, cost‐effective solution for bidirectional process prediction in laser‐induced graphene (LIG) fabrication. Achieving high predictive performance with minimal overhead, the approach democratizes machine learning (ML) for resource‐limited environments.
Maxim Polomoshnov, Nitheesh M. Nair, Gerardo Hernández‐Sosa, Markus Reischl   +3 more
wiley   +1 more source

Dissecting the Ecological Structure of Health and Disease in the Global Gut Microbiome

Advanced Science, EarlyView.
We introduce Wiredancer, a framework that identifies three continuous ecological factors of the gut microbiota. These factors exhibit distinct patterns across health and disease, jointly capturing disrupted ecological stability and offering a new perspective for precision diagnostics and therapeutic strategies.
Baoyuan Zhu, Shuhao Chen, Yunheng Diao, Wei Wang, Yuanyuan Huang, Liqin Liang, Xiaodan Lu, Rui Han, Minxin Guo, Zhaobo Li, Shuhong Wang, Hehua Li, Chenyu Liu, Jing Zhou, Dongsheng Xiong, Xiaobo Li, Yuping Ning, Xuetao Shi, Fengchun Wu, Kai Wu   +19 more
wiley   +1 more source

Non-Line-of-Sight Imaging via Sparse Bayesian Learning Deconvolution

Photonics
By enhancing transient fidelity before geometric inversion, this work revisits the classical LCT-based non line-of-sight (NLOS)imaging paradigm and establishes a unified Bayesian sparse-enhancement framework for reconstructing hidden objects under photon-
Yuyuan Tian, Weihao Xu, Dingjie Wang, Ning Zhang, Songmao Chen, Peng Gao, Xiuqin Su, Wei Hao   +7 more
doaj   +1 more source

Bayesian Reinforcement Learning via Deep, Sparse Sampling

, 2020
We address the problem of Bayesian reinforcement learning using efficient model-based online planning. We propose an optimism-free Bayes-adaptive algorithm to induce deeper and sparser exploration with a theoretical bound on its performance relative to ...
Basu, Debabrota, Dimitrakakis, Christos, Grover, Divya   +2 more
core