Results 231 to 240 of about 3,865,632 (281)

Self‐Healing and Stretchable Synaptic Transistor

Advanced Functional Materials, EarlyView.
A self‐healing stretchable synaptic transistor (3S‐T) is realized using a p‐PVDF‐HFP‐DBP/PDMS‐MPU‐IU bilayer as gate insulator, where dipole‐dipole interaction enhances polarization to achieve a large memory window. Leveraging its neuronal biomimicry, the synaptic transistor demonstrates electrically compatibility with the biological brain. Furthermore,
Hyongsuk Choo, Sangyong Park, Yoonyi Jeong, Jaepyo Jang, Duhwan Seong, In Soo Kim, Myung‐Gil Kim, Mikyung Shin, Minah Suh, Donghee Son, Jin‐Hong Park   +10 more
wiley   +1 more source

Solution‐Processed Two‐Dimensional Indium Oxide on Sodium‐Embedded Alumina for Reconfigurable Optoelectronic Synaptic Transistors

Advanced Functional Materials, EarlyView.
Wafer‐scale two‐dimensioanl In2Se3 oxidized into InOx on sodium‐embedded beta‐alumina enables multifunctional reconfigurable electronics. Sodium ions accumulate within distinct spatial distribution under drain‐controlle and gate‐controlled operation. Drain‐control operation gives controllability of ultraviolet‐driven optoelectronic synaptic conductance
Jinhong Min, Yonghyun Albert Kwon, Hyunbin Kim, Jihyun Kim, Myeongjin Jung, Jaewon Heo, Gwang Ya Kim, Vlastimil Mazanek, Zdeněk Sofer, In Soo Kim, Jeong Ho Cho, Hyesung Park, Sang Min Won, Joohoon Kang   +13 more
wiley   +1 more source

Texoskeletons: Developing the Fundamental Technologies for Creating Intelligent Soft Robotic Clothing With Integrated 1D Sensors and Actuators

Advanced Functional Materials, EarlyView.
ABSTRACT Traditional wearable exoskeletons rely on rigid structures, which limit comfort, flexibility, and everyday usability. This work introduces the fundamental technologies to create the first soft, lightweight, intelligent textile‐based exoskeletons (Texoskeletons) built using 1D sensors and actuators.
Amy Lukomiak, Rameesh Bulathsinghala, Jack Varga, Shuxin Meng, Kalana Marasinghe, Imaad Refai, Biyon Fernando, Amitkumar Patel, Chamika M. Halloluwa‐Arachchige, Carlos Oliveira, Arash M. Shahidi, Zahra Rahemtulla, Alexander Turner, Ziyun Ding, Bernard X. W. Liew, Andy Kerr, Ezio Preatoni, Theo Hughes‐Riley, Ishara Dharmasena, Pasindu Lugoda   +19 more
wiley   +1 more source

Learning Domain Structures

, 2004
Kemp, Charles, Perfors, Amy, Tenenbaum, Joshua B.   +2 more
openaire   +1 more source

Learning syntactic structure

, 2007
openaire   +1 more source

Structure learning in action

Behavioural Brain Research, 2010
'Learning to learn' phenomena have been widely investigated in cognition, perception and more recently also in action. During concept learning tasks, for example, it has been suggested that characteristic features are abstracted from a set of examples with the consequence that learning of similar tasks is facilitated-a process termed 'learning to learn'
Daniel A Braun, Carsten Mehring, Daniel M Wolpert   +2 more
exaly   +5 more sources

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Mesochronal Structure Learning

Uncertainty in artificial intelligence : proceedings of the ... conference. Conference on Uncertainty in Artificial Intelligence, 2015
Standard time series structure learning algorithms assume that the measurement timescale is approximately the same as the timescale of the underlying (causal) system. In many scientific contexts, however, this assumption is violated: the measurement timescale can be substantially slower than the system timescale (so intermediate time series datapoints ...
Sergey, Plis, David, Danks, Jianyu, Yang
openaire   +2 more sources

Social-Structure Learning

Current Directions in Psychological Science, 2020
Social-structure learning is the process by which social groups are identified on the basis of experience. Building on models of structure learning in other domains, we formalize this problem within a Bayesian framework. According to this framework, the probabilistic assignment of individuals to groups is computed by combining information about ...
Samuel Gershman, Mina Cikara
exaly   +2 more sources