Results 171 to 180 of about 842,651 (374)

Characterization of Droplet Formation in Ultrasonic Spray Coating: Influence of Ink Formulation Using Phase Doppler Anemometry and Machine Learning

Advanced Materials Technologies, EarlyView.
This study explores how machine learning models, trained on small experimental datasets obtained via Phase Doppler Anemometry (PDA), can accurately predict droplet size (D32) in ultrasonic spray coating (USSC). By capturing the influence of ink complexity (solvent, polymer, nanoparticles), power, and flow rate, the model enables precise droplet control
Pieter Verding, Danny E. P. Vanpoucke, Yunus T. Aksoy, Tobias Corthouts, Maria R. Vetrano, Wim Deferme   +5 more
wiley   +1 more source

In Situ Copper Electroplating Turns Material Extrusion 3D Printers Into Metal–Polymer Hybrid Fabricators

Advanced Materials Technologies, EarlyView.
An in situ electroplating approach for MEX 3D printing is proposed, enabling copper deposition during the fabrication of conductive polymers. The method combines a printer‐integrated plating head, ML‐based g‐code control, and stop‐and‐go printing, achieving near‐bulk copper conductivity and enabling fully embedded, assembly‐free electronic components ...
Gianluca Percoco, Nicola Larovere, Antonio Zagaria, Antonio Pavone, Rosanna Rifino, Gianni Stano   +5 more
wiley   +1 more source

Brain-Inspired Continual Learning: Robust Feature Distillation and Re-Consolidation for Class Incremental Learning

IEEE Access
Artificial intelligence and neuroscience have a long and intertwined history. Advancements in neuroscience research have significantly influenced the development of artificial intelligence systems that have the potential to retain knowledge akin to ...
Hikmat Khan, Nidhal Carla Bouaynaya, Ghulam Rasool   +2 more
doaj   +1 more source

3D Printing of Stretchable, Compressible and Conductive Porous Polyurethane for Soft Robotics

Advanced Materials Technologies, EarlyView.
A 3D‐printable porous dopamine‐polyurethane acrylate elastomer results in conductive, stretchable, and compressible structures that can be metallized in situ through catechol‐mediated silver reduction. The resulting material function as both compliant soft robot with a and strain sensors without complex assemblies, enabling fully 3D‐printed soft ...
Ouriel Bliah, Konstantin Sakharov, Pooi See Lee, Shlomo Magdassi   +3 more
wiley   +1 more source

Incremental Learning From Unbalanced Data with Concept Class, Concept Drift and Missing Features : A Review

, 2014
Pallavi Kulkarni, Roshani Ade
openalex   +1 more source

Balancing the Causal Effects in Class-Incremental Learning

CoRR
Class-Incremental Learning (CIL) is a practical and challenging problem for achieving general artificial intelligence. Recently, Pre-Trained Models (PTMs) have led to breakthroughs in both visual and natural language processing tasks. Despite recent studies showing PTMs' potential ability to learn sequentially, a plethora of work indicates the ...
Junhao Zheng, Ruiyan Wang, Chongzhi Zhang, Huawen Feng, Qianli Ma 0001   +4 more
openaire   +2 more sources

Hierarchical Multi‐Material Architectures With Gradient Design for Dynamic‐Range Flexible Tactile Sensing

Advanced Materials Technologies, EarlyView.
Hierarchical multi‐material TPMS lattices are engineered as flexible tactile sensors by combining soft and stiff elastomeric layers with a conformal conductive coating. The bilayer architecture delivers sensitivity at low pressures while maintaining a broad detectable range under large loads, enabling reliable pressure and vibration monitoring for ...
Reza Noroozi, Domenic Quiquero, Yan Yan Shery Huang, HaoTian Harvey Shi   +3 more
wiley   +1 more source

Overcoming Class Imbalance in Incremental Learning Using an Elastic Weight Consolidation-Assisted Common Encoder Approach

Mathematics
Incremental learning empowers models to continuously acquire knowledge of new classes while retaining previously learned information. However, catastrophic forgetting and class imbalance often impede this process, especially when new classes are ...
Engin Baysal, Cüneyt Bayılmış
doaj   +1 more source

ICICLE: Interpretable Class Incremental Continual Learning [PDF]

, 2023
Dawid Rymarczyk, Joost van de Weijer, Bartosz Zieliński, Bartłomiej Twardowski   +3 more
openalex   +1 more source

Scalable Task Planning via Large Language Models and Structured World Representations

Advanced Robotics Research, EarlyView.
This work efficiently combines graph‐based world representations with the commonsense knowledge in Large Language Models to enhance planning techniques for the large‐scale environments that modern robots will need to face. Planning methods often struggle with computational intractability when solving task‐level problems in large‐scale environments ...
Rodrigo Pérez‐Dattari, Zhaoting Li, Robert Babuška, Jens Kober, Cosimo Della Santina   +4 more
wiley   +1 more source