Results 111 to 120 of about 42,098 (267)

Uncertainty‐Aware Deep Ensembles for Robust and Reliable Chemical Sensor Arrays

Advanced Science, EarlyView.
A reliability‐aware electronic nose is developed using photothermally anchored metal‐catalyst decorated metal oxide nanofiber sensor arrays combined with deep ensemble learning. Diverse catalytic nanofiber channels generate gas‐specific response patterns, enabling selective identification and quantification of sulfur‐containing gases.
Sungwoo Eo, Ji‐Hwan Eum, Suk‐Jeong Kwon, Minji Sagong, Dongchan Kim, Dong‐Ha Kim   +5 more
wiley   +1 more source

CauFinder: Steering Cell‐State and Phenotype Transitions by Causal Disentanglement Learning

Advanced Science, EarlyView.
CauFinder combines causal disentanglement modeling and network control to prioritize causal drivers of cell‐state transitions from observational transcriptomic data. The framework separates transition‐relevant signals from spurious associations, nominates intervention targets across biological and disease contexts, and identifies DAAM1 as an actionable
Chengming Zhang, Zexi Chen, Yuanxiang Miao, Zuolin Shen, Deyu Cai, Shijie Tang, Yun Xue, Weifeng Guo, Hongbin Ji, Jian Liu, Kazuyuki Aihara, Luonan Chen   +11 more
wiley   +1 more source

Liquid Metals in Radio Frequency Applications: A Review of Physics, Manufacturing, and Emerging Technologies

Advanced Electronic Materials, EarlyView.
This paper reviews the physics of liquid metals in RF devices, including the influence of mechanical strain on resonance as well as fabrication methods and strategies for designing tunable and strain‐tolerant inductors, capacitors, and antennas.
Md Saifur Rahman, William J. Scheideler
wiley   +1 more source

A General and Efficient Framework for the Rapid Design of Miniaturized, Wideband, and High‐Bit RIS

Advanced Electronic Materials, EarlyView.
A general and efficient framework is proposed for the rapid design of high‐performance reconfigurable intelligent surfaces (RISs). This framework integrates advanced antenna design techniques and incorporates various load types, quantities, and values to achieve the design of high‐performance RISs.
Jun Wei Zhang, Zheng Xing Wang, Wanwan Cao, Zhen Jie Qi, Li Jie Wu, Han Qing Yang, Qun Yan Zhou, Si Ran Wang, Hui Dong Li, Jun Yan Dai, Jiang Luo, Jun Wei Wu, Jia Nan Zhang, Zhen Zhang, Qiang Cheng   +14 more
wiley   +1 more source

Conformal Reconfigurable Intelligent Surfaces: A Cylindrical Geometry Perspective

Advanced Electronic Materials, EarlyView.
Cylindrical reconfigurable intelligent surfaces are explored for low‐complexity beam steering using one‐bit meta‐atoms. A multi‐level modeling approach, including optimization‐based synthesis, demonstrates that even minimal hardware can support directive scattering.
Filippo Pepe, Ivan Iudice, Giuseppe Castaldi, Marco Di Renzo, Vincenzo Galdi   +4 more
wiley   +1 more source

Terahertz Channel Modeling, Estimation and Localization in RIS‐Assisted Systems

Advanced Electronic Materials, EarlyView.
Reconfigurable intelligent surfaces have become a recent intensive research focus. Based on practical applications, channel strategies for RIS‐assisted terahertz wireless communication systems are categorized into three different types: channel modeling, channel estimation, and channel localization.
Hongjing Wang, Weipeng Wang, Xuan Cong, Shiyu Wang, Gao Li, Sen Gong, Lin Huang, Hongxin Zeng, Yaxin Zhang, Ziqiang Yang   +9 more
wiley   +1 more source

Fundamental Challenges, Physical Implementations, and Integration Strategies for Ising Machines in Large‐Scale Optimization Tasks

Advanced Electronic Materials, EarlyView.
Ising machines are emerging as specialized hardware solvers for computationally hard optimization problems. This review examines five major platforms—digital CMOS, analog CMOS, emerging devices, coherent optics, and quantum systems—highlighting physics‐rooted advantages and shared bottlenecks in scalability and connectivity.
Hyunjun Lee, Joon Pyo Kim, Sanghyeon Kim
wiley   +1 more source

RadarTCN: Lightweight Online Classification Network for Automotive Radar Targets Based on TCN

Automotive radar is one of the key sensors for intelligent driving. Radar image sequences contain abundant spatial and temporal information, enabling target classification.
Zhi Liu, Hongyuan Jing, Mengmeng Zhang, Yuan Li   +3 more
core   +1 more source

Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference

Advanced Electronic Materials, EarlyView.
This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho, Dae‐won Kim, Yujin Kim, Jung‐Heum Na, Yuwon Jeong, Dong‐Yeop Lee, Shinhyun Choi   +6 more
wiley   +1 more source

Risk-Aware Resource Allocation Strategy for Target Tracking in a Cognitive Radar Network. [PDF]

Sensors (Basel)
Lee JY, Park J.
europepmc   +1 more source