Results 111 to 120 of about 26,356,550 (281)
Single‐filament material extrusion enables spatial stiffness programming through locally controlled thermal foaming of TPU. A data‐driven G‐code framework tunes porosity from 15.7% to 40.7% and hardness from 90 to 63 Shore A within and across layers. Monolithic hands and soft actuators consequently achieve distinct programmed motions without material ...
Rosanna Rifino +3 more
wiley +1 more source
To detect internal valve leakage in liquid-filled pipelines, a method using kernel principal component analysis (KPCA) is proposed to analyze acoustic emission (AE) signals for leakage detection.
Runlin Zhang +4 more
doaj +1 more source
On‐Chip Photonic Neural Network Architectures
This review presents a comprehensive overview of on‐chip photonic neural network architectures, covering key photonic building blocks, representative network types, and emerging applications. Recent advances, implementation challenges, and future directions are examined, highlighting the potential of integrated photonics to enable ultrafast, energy ...
Seokjin Hong +7 more
wiley +1 more source
TacScope: A Miniaturized Vision‐Based Tactile Sensor for Surgical Applications
TacScope is a compact, vision‐based tactile sensor designed for robot‐assisted surgery. By leveraging a curved elastomer surface with pressure‐sensitive particle redistribution, it captures high‐resolution 3D tactile feedback. TacScope enables accurate tumor detection and shape classification beneath soft tissue phantoms, offering a scalable, low‐cost ...
Md Rakibul Islam Prince +3 more
wiley +1 more source
On Optimizing Hyperspectral Inversion of Soil Copper Content by Kernel Principal Component Analysis
Heavy metal pollution not only causes detrimental effects on the environment but also poses threats to human health; thus, it is crucial to monitor the heavy metal content in the soil.
Fei Guo +4 more
doaj +1 more source
Two-Phase Incremental Kernel PCA for Learning Massive or Online Datasets
As a powerful nonlinear feature extractor, kernel principal component analysis (KPCA) has been widely adopted in many machine learning applications. However, KPCA is usually performed in a batch mode, leading to some potential problems when handling ...
Feng Zhao +5 more
doaj +1 more source
Continual Learning for Multimodal Data Fusion of a Soft Gripper
Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley +1 more source
Pak Biawak, a necrobot, embodies an unusual fusion of biology and robotics. Designed to repurpose natural structures after death, it challenges conventional boundaries between nature and engineering. Its movements are precise yet unsettling, raising questions about sustainability, ethics, and the untapped potential of biointegrated machines.
Leo Foulds +2 more
wiley +1 more source
The importance of selecting the optimal number of principal components for fault detection using principal component analysis [PDF]
Includes summary.Includes bibliographical references.Fault detection and isolation are the two fundamental building blocks of process monitoring. Accurate and efficient process monitoring increases plant availability and utilization.
Khwambala, Patricia Helen
core +1 more source
Multimodal Engagement Assessment in Children During Invented Story Paradigm With a Social Robot
A multimodal framework is proposed to assess children's engagement during storytelling interactions with a social robot. Gaze, physiological, and behavioral data are combined and validated against observer ratings. An automated gaze‐labeling strategy is introduced, and supervised classifiers achieve high accuracy. The study supports scalable engagement
Laura Fiorini +7 more
wiley +1 more source

