Results 51 to 60 of about 4,155 (271)

Resource Allocation in Cognitive Radio Wireless Sensor Networks with Energy Harvesting [PDF]

, 2019
The progress of science and technology and the expansion of the Internet of Things make the information transmission between communication infrastructure and wireless sensors become more and more convenient.
Haitao Xu, Hongjie Gao, Xianwei Zhou, Ruifeng Duan, Chengcheng Zhou   +4 more
core   +1 more source

A Long‐Lived Human Neurovascular PENTA Culture Model Captures Incomplete Vascular Repair and Glia‐Associated Signaling After Traumatic Brain Injury

Advanced Healthcare Materials, EarlyView.
A long‐lived, five‐cell‐type human neurovascular (PENTA) model recreates vascular disorganization and incomplete repair after traumatic brain injury (TBI). By integrating endothelial, glial, neuronal, and immune components within a 3D scaffold, the platform enables time‐resolved analysis of neurovascular remodeling and provides a human‐relevant system ...
Daniel S. Hinrichsen, Sunghyun Jun, Colleen M. Arrasmith, Charitha C. Anamala, Mitchell D. Thielen, Anapaula Garcia, Volha Liaudanskaya   +6 more
wiley   +1 more source

Markov Model-Based Energy Efficiency Spectrum Sensing in Cognitive Radio Sensor Networks

Journal of Computer Networks and Communications, 2016
Cognitive Radio Sensor Network (CRSN), incorporating cognitive radio capability in wireless sensor networks, is a new paradigm of the next-generation sensor network. Sensor nodes are usually battery powered and hence have strict energy constraints.
Yan Jiao, Inwhee Joe
doaj   +1 more source

Cognitive Adaptive Medium Access Control in Cognitive Radio Sensor Networks

IEEE Transactions on Vehicular Technology, 2015
Spectrum sensing is an integral part of medium access control (MAC) in cognitive radio (CR) networks as its reliability determines the success of transmission. However, it is an energy-consuming operation that needs to be minimized for CR sensor networks (CRSNs) due to resource scarcity.
Shah, Ghalib A., Akan, Ozgur B.
openaire   +2 more sources

Spectrum sharing models in cognitive radio networks [PDF]

, 2011
Spectrum scarcity demands thinking new ways to manage the distribution of radio frequency bands so that its use is more effective. The emerging technology that can enable this paradigm shift is the cognitive radio.
Rifà Pous, Helena, Rifà Coma, Josep
core  

Bioinspired Adaptive Sensors: A Review on Current Developments in Theory and Application

Advanced Materials, EarlyView.
This review comprehensively summarizes the recent progress in the design and fabrication of sensory‐adaptation‐inspired devices and highlights their valuable applications in electronic skin, wearable electronics, and machine vision. The existing challenges and future directions are addressed in aspects such as device performance optimization ...
Guodong Gong, You Zhou, Qingxiu Li, Wenyu Zhao, Sunyingyue Geng, Hangfei Li, Yan‐Bing Leng, Shirui Zhu, Guanglong Ding, Yongbiao Zhai, Ziyu Lv, Ye Zhou, Su‐Ting Han   +12 more
wiley   +1 more source

Thermodynamic Limits to Molecular Doping in Conjugated Polymers: A Perspective on Phase Behavior and Miscibility

Advanced Materials, EarlyView.
Molecular doping of conjugated polymers is fundamentally constrained by thermodynamic phase behavior. This Perspective reframes doping efficiency and stability in terms of miscibility limits, binodals, and solvus boundaries, highlighting the role of effective interaction parameters and charge transfer.
Somayeh Kashani, Justin Neu, Sung‐Joo Kwon, Runqio Song, Zixuan Chen, Tajah Trapier, Paschalis Gkoupidenis, David Ginger, Wei You, Jasper J. Michels, Harald Ade   +10 more
wiley   +1 more source

Reinforcement Learning-based Spectrum Sharing for Cognitive Radio [PDF]

, 2011
This thesis investigates how distributed reinforcement learning-based resource assignment algorithms can be used to improve the performance of a cognitive radio system.
Jiang, Tao
core  

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source

Weaving Intelligence: Thermally Drawn Multimaterial Fibers Toward AI‐Enabled Smart Textiles

Advanced Materials, EarlyView.
Thermally drawn multimaterial fibers are rapidly advancing as intelligent structural units for next‐generation smart textiles. Integrating multimaterial architectures with neuromorphic and spiking‐neural‐network principles enables fabrics that can sense, compute, and adapt autonomously.
Vuong Dinh Trung, Jiaxiang Yi, Hieu Nguyen‐Duc, Tien Nu Hoang Lo, Weili Zhao, Chaoqun Dong, Fabien Sorin, Baris Caglar, Lei Wei, Tung Nguyen‐Dang   +9 more
wiley   +1 more source