Results 111 to 120 of about 448,103 (274)

Roundness and positioning deviation prediction in single point incremental forming using deep learning approaches

Advances in Mechanical Engineering, 2019
This article proposes a deep learning technique for the prevision of the geometric accuracy in single point incremental forming. Moreover, predicting geometric accuracy is one of the most crucial measures of part quality.
Sofien Akrichi, Amira Abbassi, Sabeur Abid, Noureddine Ben yahia   +3 more
doaj   +1 more source

Learning strategies and general cognitive ability as predictors of gender- specific academic achievement

Frontiers in Psychology, 2015
Recent research has revealed that learning behavior is associated with academic achievement at the college level, but the impact of specific learning strategies on academic success as well as gender differences therein are still not clear. Therefore, the
Stephanie eRuffing, Stephanie eRuffing, F.- Sophie eWach, Frank M. eSpinath, Roland eBrünken, Julia eKarbach, Julia eKarbach   +6 more
doaj   +1 more source

Transducers Across Scales and Frequencies: A System‐Level Framework for Multiphysics Integration and Co‐Design

Advanced Materials Technologies, EarlyView.
Transducers convert physical signals into electrical and optical representations, yet each mechanism is bounded by intrinsic trade‐offs across bandwidth, sensitivity, speed, and energy. This review maps transduction mechanisms across physical scale and frequency, showing how heterogeneous integration and multiphysics co‐design transform isolated ...
Aolei Xu, Mengyao Xiao, Zhouli Sui, Yinpeng Wang, Daoye Zheng, Yuxin Liu, Luwei Wang, Huajun Liu, Chengkuo Lee   +8 more
wiley   +1 more source

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

Non‐Invasive Multidimensional Capacitive Sensing for In Vivo Traumatic Brain Injury Monitoring

Advanced Materials Technologies, EarlyView.
Single‐electrode, multidimensional capacitive sensors noninvasively assess cerebral autoregulation and compliance for traumatic brain injury monitoring. ABSTRACT Traumatic brain injury (TBI) is a major cause of death and disability, but invasive intracranial pressure (ICP) monitoring is risky, and current non‐invasive methods lack the resolution and ...
Shawn Kim, Yu‐Jen Cheng, Tianyi Li, Nathan White, Xu Wang, Kristyn Ringgold, Lauren Neidig, Younghoon Kwon, Jae‐Hyun Chung   +8 more
wiley   +1 more source

Future-proofing class-incremental learning

Machine Vision and Applications
Exemplar-Free Class Incremental Learning is a highly challenging setting where replay memory is unavailable. Methods relying on frozen feature extractors have drawn attention recently in this setting due to their impressive performances and lower computational costs.
Jodelet, Quentin, Liu, Xin, Phua, Yin Jun, Murata, Tsuyoshi   +3 more
openaire   +2 more sources

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

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

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

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