Results 101 to 110 of about 3,246,502 (304)

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

Advanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj, Roshni Satheesh Babu, Yuxin Xia, Eva Bestelink, Radu Sporea, Nikos Hastas, Ioannis Zeimpekis, Dimitra G. Georgiadou, Sayani Majumdar   +8 more
wiley   +1 more source

STGATN: A novel spatiotemporal graph attention network for predicting pollutant concentrations at multiple stations.

PLoS ONE
Accurately predicting air pollutant concentrations can reduce health risks and provide crucial references for environmental governance. In pollution prediction tasks, three key factors are essential: (1) dynamic dependencies among global monitoring ...
Huazhen Xu, Wei Song, Lanmei Qian, Xiangxiang Mei, Guojian Zou   +4 more
doaj   +1 more source

Monolithic 3D‐Integrated All‐Solid Ion‐Gated Carbon Nanotube Transistors With Tunable Ionic Conductance for Multi‐Timescale Reservoir Computing

Advanced Materials, EarlyView.
A dual‐timescale reservoir based on monolithically 3D (M3D)‐integrated CNT solid ion‐gated transistors is demonstrated. Tunable ionic dynamics and pulse‐engineered operation enable linear and symmetric synaptic updates. The M3D‐integrated array achieves robust temporal encoding and accurate classification of moving MNIST sequences, highlighting its ...
Haksoon Jung, Hanbin Cho, Yongwoo Lee, Seunghun Baek, Hyeongjun Kim, Yun Goo Ro, Hyunhyub Ko, Joonki Suh, Yong‐Young Noh, Jimin Kwon   +9 more
wiley   +1 more source

A multi-channel spatiotemporal SegNet model for short term wind power prediction with sequence decomposition and reconstruction

Results in Engineering
High precision wind power prediction can serve as an important reference for wind power grid integration. However, the complex spatiotemporal correlations between wind turbine operations and the high randomness of wind energy pose serious challenges to ...
Xingdou Liu, Liang Zou, Li Zhang, Jiangong Wang, Zhiyun Han, Yong Li   +5 more
doaj   +1 more source

Phase Engineering of Nanomaterials (PEN): Evolution, Current Challenges, and Future Opportunities

Advanced Materials, EarlyView.
This review summarizes the synthesis, phase transition, advanced characterization spanning ex situ to in situ and operando techniques, and diverse applications of phase engineering of nanomaterials (PEN). It further outlines key challenges and future opportunities, such as phase stability, architecture control, and artificial intelligence (AI)‐driven ...
Ye Chen, Zhanxi Fan, Jingjie Ge, Qiyuan He, Zhuangchai Lai, Jiawei Liu, Chaoliang Tan, Hua Zhang   +7 more
wiley   +1 more source

Field‐Programmed Anisotropy in Magneto‐Piezoelectric Composites for Material‐Encoded Mechanoperception

Advanced Materials, EarlyView.
Field‐programmed anisotropy imparts material‐level intelligence to soft composites. Magnetic torque dynamics drive magneto‐piezoelectric nanowires from random dispersion into deterministic axial alignment. The resulting hierarchical percolation networks confine electromechanical coupling to specific axes and intrinsically decouple superposed force ...
Yubin Kim, Yumin Kwon, Dabin Kim, Minsun Oh, Jin Young Jung, Dongyeong Gim, Kootak Hong, Jun Yeon Hwang, Sang‐Woo Kim, Minjeong Ha   +9 more
wiley   +1 more source

Spatiotemporal Prediction for Log-Gaussian Cox Processes

Journal of the Royal Statistical Society Series B: Statistical Methodology, 2001
Summary Space–time point pattern data have become more widely available as a result of technological developments in areas such as geographic information systems. We describe a flexible class of space–time point processes. Our models are Cox processes whose stochastic intensity is a space–time Ornstein–Uhlenbeck process.
Brix, Anders, Diggle, Peter J.
openaire   +1 more source

Optoelectronic Nanofluidic Neural Networks for Ionic Computing

Advanced Materials, EarlyView.
An ion‐based optoelectronic nanofluidic memristor enables neuromorphic computing in aqueous environments. With tunable ionic memory and multimodal synaptic plasticity, it realizes densely connected ionic neural networks capable of image classification, motion prediction, logic computation, and real‐time in‐sensor computing, advancing fully connected ...
Yaxin Huang, Zhiyuan Du, Changjin Wu, Binglin Zeng, Yingnan Cao, Mingliang Li, Liren Zhang, Qingxin Guo, Chao Huang, Can Li, Jinyao Tang   +10 more
wiley   +1 more source

Construction of a traffic flow prediction model based on neural ordinary differential equations and Spatiotemporal adaptive networks

Scientific Reports
To address the issue of spatiotemporal illusion in short-term traffic flow prediction and deeply explore the underlying short-term traffic flow network characteristics, a traffic flow prediction model that combines long-term spatiotemporal heterogeneity ...
Li Ma, Yunshun Wang, Xiaoshi Lv, Lijun Guo   +3 more
doaj   +1 more source

Spatio-Temporal Multi-Graph Convolution Traffic Flow Prediction Model Based on Multi-Source Information Fusion and Attention Enhancement

Applied Sciences
Traffic flow prediction plays a vital role in intelligent transportation systems, directly affecting travel scheduling, road planning, and traffic management efficiency.
Wenjing Li, Zhongning Sun, Yao Wan
doaj   +1 more source