Results 161 to 170 of about 2,969,144 (286)
Transformer Fault Diagnosis Based on Knowledge Distillation and Residual Convolutional Neural Networks. [PDF]
Shang H, Wei Y, Zhang S.
europepmc +1 more source
Machine Health Monitoring and Fault Diagnosis Techniques (Volume II)
This Special Issue highlights a diverse range of pioneering research dedicated to fault diagnosis, condition monitoring, and defect detection in various engineering systems [...
Dong Wang, Changqing Shen, Shilong Sun
core +1 more source
The present study shows that Nrf2 directly binds to the Gm26550 promoter, thereby activating Gm26550 transcription and increasing its expression. Mechanistically, Gm26550 promotes IGF1 expression by functionally antagonizing miR‐26a‐5p‐mediated repression and sequestering the RBP KHSRP, thereby enhancing hippocampal neuronal synaptic plasticity and ...
Hongfang Wang +12 more
wiley +1 more source
Transformer fault diagnosis method based on Gramian Angular Field and optimized parallel ShuffleNetV2. [PDF]
Guo Q +6 more
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Sustainable Materials Design With Multi‐Modal Artificial Intelligence
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu +8 more
wiley +1 more source
Based on PCA and SSA-LightGBM oil-immersed transformer fault diagnosis method. [PDF]
Wang J, Chi J, Ding Y, Yao H, Guo Q.
europepmc +1 more source
Smart Nanotechnologies for Multimodal Neuromodulation and Brain Interfacing
Recent advances in smart nanotechnologies are expanding the toolbox for brain interfacing, from wireless neuromodulation and high‐resolution sensing to targeted delivery within the central nervous system. By combining responsive nanomaterials with bioinspired design, these platforms enable multimodal interactions with neurons and glia, while also ...
Tommaso Curiale +6 more
wiley +1 more source
Low-Power Chemiresistive Gas Sensors for Transformer Fault Diagnosis. [PDF]
Mei H, Peng J, Xu D, Wang T.
europepmc +1 more source
Interpretable machine learning reveals how composition and processing govern the formation and microstructural burden of Fe‐rich intermetallic compounds in recycled Al–Si–Fe–Mn alloys. By separating morphology selection from morphology‐conditioned burden partitioning, this framework shows that identical Fe contents can yield different intermetallic ...
Jaemin Wang +2 more
wiley +1 more source
A lightweight deep learning framework for transformer fault diagnosis in smart grids using multiple scale CNN features. [PDF]
Attallah O, Ibrahim RA, Zakzouk NE.
europepmc +1 more source

