Results 111 to 120 of about 75,080 (277)
Bio‐to‐Robot Transfer of Fish Sensorimotor Dynamics via Interpretable Model
Advanced Intelligent Systems, EarlyView.This study demonstrates how a biologically interpretable model trained on real‐fish muscle activity can accurately predict the motion of a robotic fish. By linking real‐fish sensorimotor dynamics with robotic fish, the work offers a transparent, data‐efficient framework for transferring biological intelligence to bioinspired robotic systems.
Waqar Hussain Afridi +6 more
wiley +1 more source
AI &Innovation, EarlyView.ABSTRACT The rapid evolution of the Internet of Things (IoT) has significantly advanced the field of electrocardiogram (ECG) monitoring, enabling real‐time, remote, and patient‐centric cardiac care. This paper presents a comprehensive survey of AI assisted IoT‐based ECG monitoring systems, focusing on the integration of emerging technologies such as ...
Amrita Choudhury +2 more
wiley +1 more source
IEEE AccessThe dependability and security of transformer differential protection can be compromised by current transformer (CT) saturation, which distorts current measurements and may lead to the maloperation of protective relays.
Sopheap Key +4 more
doaj +1 more source
Biotechnology Progress, EarlyView.Abstract Artificial intelligence and automation are no longer just buzzwords in the biopharmaceutical industry. The manufacturing of a class of biologics, comprising monoclonal antibodies, cell therapies, and gene therapies, is far more complex than that of traditional small molecule drugs.
Shyam Panjwani, Hao Wei, John Mason
wiley +1 more source
Rockburst prediction based on data preprocessing and hyperband‐RNN‐DNN
Deep Underground Science and Engineering, EarlyView.A data preprocessing workflow is proposed to address challenges in rockburst data analysis. Coupled algorithms preprocess the data set, and hyperband optimization is used to enhance RNN performance. Results show that preprocessing improves accuracy, while dense layers enhance model stability and prediction performance.
Yong Fan +4 more
wiley +1 more source
Entropy‐Driven Design of Stable High‐Performance Sodium‐Ion Battery Cathodes
EcoEnergy, EarlyView.This review explores high‐entropy strategies for advanced sodium‐ion battery cathodes, focusing on LTMOs and PBAs. It details how entropy engineering mitigates challenges: phase transitions, interface degradation, and air instability in LTMOs; vacancy defects and crystalline water in PBAs.
Feng Zhan +8 more
wiley +1 more source
Target tracking using deep neural network (DNN)
, 2019 Deep learning is widely used in recent years, and the application of machine learning techniques in computer vision like object detection and tracking has been a prime part in this field. This project mainly introduces a method of a recurrent convolution neural network for object detection and tracking in dim light underwater condition. The convolution
openaire +1 more source
Machine Learning Approaches for GC–MS Data Interpretation in Flavour and Fragrance Analysis
Flavour and Fragrance Journal, EarlyView.The review explores machine learning integration in GC‐MS data analysis for the fragrance and flavour industry, highlighting recent advances and techniques in a context constrained by data scarcity and intellectual property concerns. ABSTRACT This review explores the integration of machine learning (ML) in the analysis of mass spectrometry data ...
Jean‐Baptiste Coffin +3 more
wiley +1 more source
Deep Learning Integration in Optical Microscopy: Advancements and Applications
Microscopy Research and Technique, EarlyView.It explores the integration of DL into optical microscopy, focusing on key applications including image classification, segmentation, and computational reconstruction. ABSTRACT Optical microscopy is a cornerstone imaging technique in biomedical research, enabling visualization of subcellular structures beyond the resolution limit of the human eye ...
Pottumarthy Venkata Lahari +5 more
wiley +1 more source