Results 101 to 110 of about 43,821 (259)
Role of Wadsley Defects and Cation Disorder to Enhance MoNb12O33 Diffusion
Advanced Energy Materials, EarlyView.Wadsley‐Roth niobates are high‐rate capable and durable anode materials for lithium‐ion batteries. Defect‐tailoring of MoNb12O33 is shown to substantially enhance lithium diffusion. Computational models were used to separate the effects of cation disorder and Wadsley defects to identify that both led to the occupation of fast diffusion sites at lower ...
CJ Sturgill +10 more
wiley +1 more source
Advanced Energy and Sustainability Research, EarlyView.Triboelectric nanogenerators are vital for sustainable energy in future technologies such as wearables, implants, AI, ML, sensors and medical systems. This review highlights improved TENG neuromorphic devices with higher energy output, better stability, reduced power demands, scalable designs and lower costs.
Ruthran Rameshkumar +2 more
wiley +1 more source
Graph‐based imitation and reinforcement learning for efficient Benders decomposition
AIChE Journal, EarlyView.Abstract This work introduces an end‐to‐end graph‐based agent for accelerating the computational efficiency of Benders Decomposition. The agent's policy is parameterized by a graph neural network, which takes as input a bipartite graph representation of the master problem and proposes a candidate solution.
Bernard T. Agyeman +3 more
wiley +1 more source
Domain‐Aware Implicit Network for Arbitrary‐Scale Remote Sensing Image Super‐Resolution
Advanced Intelligent Discovery, EarlyView.Although existing arbitrary‐scale image super‐resolution methods are flexible to reconstruct images with arbitrary scales, the characteristic of training distribution is neglected that there exists domain shift between samples of various scales. In this work, a Domain‐Aware Implicit Network (DAIN) is proposed to handle it from the perspective of domain
Xiaoxuan Ren +6 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley +1 more source
Threshold decoding of hospitals self-original conventional codes
Доклады Белорусского государственного университета информатики и радиоэлектроники, 2019 The efficiency of threshold decoding of non-binary self-orthogonal convolutional codes in the communication channel with additive white Gaussian noise with the correction of t (t ≥ 1) symbolic errors is considered.
E. G. Makeichik +2 more
doaj
Advanced Intelligent Discovery, EarlyView.Large language models are transforming microbiome research by enabling advanced sequence profiling, functional prediction, and association mining across complex datasets. They automate microbial classification and disease‐state recognition, improving cross‐study integration and clinical diagnostics.
Jieqi Xing +4 more
wiley +1 more source
Reed-Solomon Hybrid Codes for Optical Communications
Journal of Engineering and Sustainable Development, 2013 The astonishing performance of concatenated codes attracted many researchers and this has resulted in an explosive amount of literature since their introduction few years ago.
Awatif Ali Jafaar
doaj
A convolutional code-based sequence analysis model and its application. [PDF]
Int J Mol Sci, 2013 Liu X, Geng X.
europepmc +1 more source
Advanced Intelligent Discovery, EarlyView.Exosomes are emerging as powerful biomarkers for disease diagnosis and monitoring. This review highlights the integration of surface‐enhanced Raman spectroscopy with artificial intelligence to enhance molecular fingerprinting of exosomes. Machine learning and deep learning techniques improve spectral interpretation, enabling accurate classification of ...
Munevver Akdeniz +2 more
wiley +1 more source