Results 61 to 70 of about 75,210 (257)

Soft Hardware, Flowing Software: Reconfigurable Microfluidics for Adaptable Chemical Computation

Advanced Materials, EarlyView.
A reconfigurable microfluidic platform based on soft, photo‐printable, and chemically erasable hydrogel structures printed and erased in situ is used to control flow routing, mixing, chemical patterning, and even chemical computing. Using hardware to control chemical computations decouples logic function from molecular composition, demonstrated via ...
Piet J. M. Swinkels, Brigitta Dúzs, Oliver Skarsetz, Kohei Nishiyama, Andreas Walther   +4 more
wiley   +1 more source

Implicit versus explicit associative learning and experimentally induced placebo hypoalgesia

Journal of Pain Research, 2011
Andrea L Martin-Pichora1,2, Tsipora D. Mankovsky-Arnold3, Joel Katz11Department of Psychology, York University, Toronto, ON, Canada; 2Centre for Student Development and Counseling, Ryerson University, Toronto, ON, Canada; 3Department of Psychology ...
Andrea L Martin-Pichora, Tsipora D. Mankovsky-Arnold, Joel Katz   +2 more
doaj  

Unified framework for quantum classification

Physical Review Research, 2021
Quantum machine learning is an emerging field that combines machine learning with advances in quantum technologies. Many works have suggested great possibilities of using near-term quantum hardware in supervised learning. Motivated by these developments,
Nhat A. Nghiem, Samuel Yen-Chi Chen, Tzu-Chieh Wei   +2 more
doaj   +1 more source

Meta-Learning with Implicit Gradients

CoRR, 2019
A core capability of intelligent systems is the ability to quickly learn new tasks by drawing on prior experience. Gradient (or optimization) based meta-learning has recently emerged as an effective approach for few-shot learning. In this formulation, meta-parameters are learned in the outer loop, while task-specific models are learned in the inner ...
Aravind Rajeswaran, Chelsea Finn, Sham M. Kakade, Sergey Levine   +3 more
openaire   +3 more sources

Advanced Design for Weakly Coupled Resonators by Automatic Active Optimization

Advanced Materials Technologies, EarlyView.
An Automatic Active Optimization (AAO) strategy integrates machine learning predictors and genetic algorithms in a closed‐loop workflow. By iteratively expanding its dataset with new discoveries, AAO overcomes the limits of conventional methods. This approach finds superior microstructural designs beyond the initial sample space. We demonstrate this on
Wei Yue, Yuan Gao, Fanping Sui, Jason Wang, Megan Teng, Peggy Tsao, Huicong Deng, Yande Peng, Liwei Lin   +8 more
wiley   +1 more source

Recent Advances of Slip Sensors for Smart Robotics

Advanced Materials Technologies, EarlyView.
This review summarizes recent progress in robotic slip sensors across mechanical, electrical, thermal, optical, magnetic, and acoustic mechanisms, offering a comprehensive reference for the selection of slip sensors in robotic applications. In addition, current challenges and emerging trends are identified to advance the development of robust, adaptive,
Xingyu Zhang, Liao Wu, Shuai He, Zhao Sha, Yuwan Huang, Shuying Wu, Dewei Chu, Chun H. Wang, Shuhua Peng   +8 more
wiley   +1 more source

Tiny visual latencies can profoundly impair implicit sensorimotor learning

Scientific Reports
Short sub-100 ms visual feedback latencies are common in many types of human-computer interactions yet are known to markedly reduce performance in a wide variety of motor tasks from simple pointing to operating surgical robotics.
Alkis M. Hadjiosif, Y. Dajaj, Tanvi Ranjan, Maurice A. Smith   +3 more
doaj   +1 more source

Vision‐Augmented Wearable Interfaces: Bioinspired Approaches for Realistic AI‐Human‐Machine Interaction

Advanced Materials Technologies, EarlyView.
This review presents recent progress in vision‐augmented wearable interfaces that combine artificial vision, soft wearable sensors, and exoskeletal robots. Inspired by biological visual systems, these technologies enable multimodal perception and intelligent human–machine interaction.
Jihun Lee, Gwuidong Ryu, Kisoo Kim, Feng Xu, Won Gu Lee   +4 more
wiley   +1 more source

Implicit Policy for Reinforcement Learning

CoRR, 2018
We introduce Implicit Policy, a general class of expressive policies that can flexibly represent complex action distributions in reinforcement learning, with efficient algorithms to compute entropy regularized policy gradients. We empirically show that, despite its simplicity in implementation, entropy regularization combined with a rich policy class ...
Yunhao Tang, Shipra Agrawal 0001
openaire   +2 more sources

Soft Robotic Excretory Care Simulator for Nursing Education: Functional and Perceptual Biomimetics Approach

Advanced Robotics Research, EarlyView.
A soft robotic simulator is developed to replicate the digital removal of feces (DRF), a sensitive yet essential nursing procedure. Integrating soft actuators, sensors, and a realistic rectal model, the simulator balances functional fidelity with perceptual realism. Engineering evaluations and nurse feedback confirm its potential to enhance training in
Shoko Miyagawa, Sota Suzuki, Shizuka Watanabe, Zebing Mao, Young Ah Seong, Toshinori Fujie, Tatsuhiro Horii, Kenjiro Tadakuma, Koichi Suzumori, Hiroyuki Nabae, Shingo Maeda   +10 more
wiley   +1 more source