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Wireless electronic tattoos 12

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Wireless electronic tattoos

12th International Workshop on Structural Health Monitoring: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT), IWSHM 2019

作者： Lu, Nanshu Jeong, Hyoyoung Department of Aerospace Engineering and Engineering Mechanic Department of Biomedical Engineering Department of Electrical and Computer Engineering Texas Materials Institute University of Texas at Austin 2501 Speedway Austin78712 United States Department of Electrical and Computer Engineering University of Texas at Austin 2501 Speedway Austin78712 United States

ISBN: (纸本)9781605956015

Wearable electronics are finding emerging applications in mobile health, rehabilitation, prosthetics/exoskeletons, athletic training, human-machine interaction, etc. However, our skin is soft, curvilinear and dynamic whereas wafer-based electronics are hard, planar, and rigid. As a result, state-of-the-art wearables can only be strapped or clipped on human body. The development of flexible and stretchable electronics offers a remedy for such challenge. E-tattoos represent a class of stretchable circuits, sensors, and actuators that are ultrathin, ultrasoft, skin-conformable and deformable just like a temporary tattoo. Our group has invented a low-cost, dry and freeform "cut-solder-paste" method for the rapid prototyping of multilayer and reconfigurable wireless e-tattoos. This method has been proved to work for thin film metals, polymers, ceramics, 2D materials and their integration with rigid integrated circuits (ICs). Through a modular and multilayer design, we created e-tattoos that can wirelessly receive power and transmit data through near field communication (NFC) and Bluetooth. Such e-tattoos can conform to any part of human skin for electrophysiological, mechanical, thermal and optical sensing. © 2019 by DEStech Publications, Inc. All rights reserved.

关键词： Internet of things

Computing Multiple Image Reconstructions with a Single Hypernetwork

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arXiv 2022年

作者： Wang, Alan Q. Dalca, Adrian V. Sabuncu, Mert R. School of Electrical and Computer Engineering Cornell Tech New YorkNY United States Department of Radiology Weill Cornell Medical School New YorkNY United States Computer Science and Artificial Intelligence Lab Massachusetts Institute of Technology CambridgeMA United States A.A. Martinos Center for Biomedical Imaging Massachusetts General Hospital CambridgeMA United States

Deep learning based techniques achieve state-of-the-art results in a wide range of image reconstruction tasks like compressed sensing. These methods almost always have hyperparameters, such as the weight coefficients that balance the different terms in the optimized loss function. The typical approach is to train the model for a hyperparameter setting determined with some empirical or theoretical justification. Thus, at inference time, the model can only compute reconstructions corresponding to the pre-determined hyperparameter values. In this work, we present a hypernetwork-based approach, called HyperRecon, to train reconstruction models that are agnostic to hyperparameter settings. At inference time, HyperRecon can efficiently produce diverse reconstructions, which would each correspond to different hyperparameter values. In this framework, the user is empowered to select the most useful output(s) based on their own judgement. We demonstrate our method in compressed sensing, super-resolution and denoising tasks, using two large-scale and publicly-available MRI datasets. Our code is available at https://***/alanqrwang/hyperrecon. © 2022, CC BY.

关键词： Image reconstruction

Reinforcement Learning-Based Edge Caching for IoT in Compute-First Networks

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IEEE Transactions on Consumer Electronics 2025年

作者： Asmat, Hamid Din, Ikram Ud Almogren, Ahmad Rodrigues, Joel J. P. C. Department of Information Technology University of Haripur Haripur22620 Pakistan King Saud University College of Computer and Information Sciences Chair of Cyber Security Department of Computer Science Riyadh11633 Saudi Arabia Post-graduation Program in Electrical Engineering Teresina Brazil

6G networks require ultra-low latency and intelligent resource management in IoT environments. Compute-First Networking (CFN), integrating distributed computing and edge caching, addresses backhaul congestion. This paper proposes CaRL, a DRL-based caching framework using TD3 algorithm. CaRL optimizes cache placement at edge nodes by incorporating real-time network state, content popularity, and resource utilization. Simulations show CaRL improves cache hit ratio, reduces latency, and enhances bandwidth efficiency, and ensures secure caching decisions under dynamic network conditions. Unlike existing methods, CaRL adapts to dynamic network conditions by integrating latency, CPU, and memory metrics, demonstrating scalability and adaptability in CFN-driven 6G environments. © 1975-2011 IEEE.

关键词： Edge computing

Robust Frequency Control of Power Systems under Time-varying Loads 51

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Robust Frequency Control of Power Systems under Time-varying...

51st North American Power Symposium, NAPS 2019

作者： Wang, Zhenhua He, Haibo Sun, Yan Computer and Biomedical Engineering University of Rhode Island Department of Electrical KingstonRI02881 United States

ISBN: (纸本)9781728104072

In this paper, the load frequency control of multi-region power systems is studied. We propose a robust controller based on the frequency deviation between different regions. Using the non-smooth theory, we analyze the conditions for the feedback parameters of the proposed controller. Furthermore, the effectiveness of the proposed controller is evaluated on a four-region power system. © 2019 IEEE.

关键词： Controllers

Topological Metamaterials

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arXiv 2022年

作者： Ni, Xiang Yves, Simon Krasnok, Alex Alu, Andrea Photonics Initiative Advanced Science Research Center City University of New York New YorkNY10031 United States Department of Electrical and Computer Engineering Florida International University MiamiFL33174 United States Department of Electrical Engineering City College The City University of New York 160 Convent Avenue New York10031 United States Physics Program The Graduate Center The City University of New York 365 Fifth Avenue New York10016 United States

Unlike geometrical features, such as shape or volume, the topological properties of an object do not change continuously, but only due to abrupt transitions associated with a change in the integer quantities that describe these properties - known as topological invariants. In turn, this resilience of topological features is associated with intrinsic robustness. For example, the topological invariant known as the Chern number, associated with the quantization of the Hall conductance in a two-dimensional electron gas, supports disorder-immune electron transport at the surface of topological insulators (TIs). One of the most significant breakthroughs in physics of the last decade has been the discovery that materials with non-trivial topological properties for electronic, electromagnetic, acoustic and mechanical responses can be designed and manufactured at our will through engineered metamaterials (MMs). Here, we review the foundation and the state-of-the-art advances of topological photonics, acoustics and mechanical MMs. We discuss how topological MMs enable nontrivial wave phenomena in physics, engineering, of great interest for a broad range of interdisciplinary science disciplines such as classical and quantum chemistry. We first introduce the foundations of topological materials and the main concepts behind their peculiar features, including the concepts of topological charge and geometric phase. We then discuss the topology of electronic band structures in natural topological materials, like topological insulators and gapless Dirac and Weyl semimetals. Based on these concepts, we review the concept, design and response of topologically nontrivial MMs in photonics and phononics, including topological phases in 2D MMs with and without time-reversal symmetry, Floquet TIs based on spatial and temporal modulation, topological phases in 3D MMs, higher-order topological phases in MMs, non-Hermitian and nonlinear topological MMs and the topological features of scatteri

关键词： Metamaterials

Multiregion Multiscale Image Segmentation with Anisotropic Diffusion 25th

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Multiregion Multiscale Image Segmentation with Anisotropic D...

25th International Conference on Pattern Recognition Workshops, ICPR 2020

作者： Prasath, V. B. Surya Thanh, Dang Ngoc Hoang Hai, Nguyen Hoang Dvoenko, Sergey Department of Electrical Engineering and Computer Science University of Cincinnati CincinnatiOH45221 United States Division of Biomedical Informatics Cincinnati Children’s Hospital Medical Center CincinnatiOH45229 United States Department of Biomedical Informatics College of Medicine University of Cincinnati CincinnatiOH45267 United States Department of Pediatrics University of Cincinnati College of Medicine CincinnatiOH45257 United States Department of Information Technology School of Business Information Technology University of Economics Ho Chi Minh City Ho Chi Minh City Viet Nam Department of Computer Science Vietnam-Korea University of Information and Communication Technology – The University of Danang Danang Viet Nam Department of Information Security Institute of Applied Mathematics and Computer Science Tula State University Tula city Russia

ISBN: (纸本)9783030688202

We present a multiregion image segmentation approach which utilizes multiscale anisotropic diffusion based scale spaces. By combining powerful edge preserving anisotropic diffusion smoothing with isolevel set linking and merging, we obtain coherent segments which are tracked across multiple scales. A hierarchical tree representation of the given input image with progressively simplified regions is used with intra-scale splitting and inter-scale merging for obtaining multiregion segmentations. Experimental results on natural and medical images indicate that multiregion, multiscale image segmentation (MMIS) approach obtains coherent segmentation results. © 2021, Springer Nature Switzerland AG.

关键词： Diffusion

Landau Polaritons in a Full-Dielectric Three-Dimensional Photonic-Crystal Cavity

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Landau Polaritons in a Full-Dielectric Three-Dimensional Pho...

Conference on Lasers and Electro-Optics (CLEO)

作者： Fuyang Tay Ali Mojibpour Shuang Liang Andrey Baydin Arash Ahmadivand Nicolas Marquez Peraca Hongjing Xu Geoff C. Gardner Michael J. Manfra David Hagenmüller Junichiro Kono Department of Electrical and Computer Engineering Rice University Houston Texas USA Applied Physics Graduate Program Smalley-Curl Institute Rice University Houston Texas USA Department of Physics and Astronomy Purdue University West Lafayette IN USA Birck Nanotechnology Center Purdue University West Lafayette IN USA Smalley-Curl Institute Rice University Houston Texas USA Department of Physics and Astronomy Rice University Houston Texas USA Microsoft Quantum Purdue Purdue University West Lafayette IN USA School of Electrical and Computer Engineering Purdue University West Lafayette IN USA School of Materials Engineering Purdue University West Lafayette IN USA ISIS (UMR 7006) Université de Strasbourg and CNRS Strasbourg France Department of Materials Science and Nano Engineering Rice University Houston Texas USA

We fabricated a full-dielectric three-dimensional photonic-crystal cavity containing an ultrahigh-mobility two-dimensional electron gas. By applying a strong perpendicular magnetic field, we created Landau polaritons ... 详细信息

ISBN: (数字)9781957171050

ISBN: (纸本)9781665466660

关键词： Couplings HEMTs Laser modes Polaritons Magnetic fields Gas lasers MODFETs

Transformation between elastic dipoles, quadrupoles, octupoles and hexadecapoles driven by surfactant self-assembly in nematic emulsion

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arXiv 2022年

作者： Senyuk, Bohdan Mozaffari, Ali Crust, Kevin Zhang, Rui de Pablo, Juan J. Smalyukh, Ivan I. Department of Physics and Soft Materials Research Center University of Colorado Boulder CO United States Pritzker School of Molecular Engineering The University of Chicago ChicagoIL United States Department of Physics The Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong Center for Molecular Engineering Argonne National Laboratory LemontIL United States Department of Electrical Computer and Energy Engineering Materials Science and Engineering Program University of Colorado Boulder CO United States Renewable and Sustainable Energy Institute National Renewable Energy Laboratory University of Colorado Boulder CO United States

Emulsions comprising isotropic fluid drops within a nematic host are of interest for applications ranging from biodetection to smart windows, which rely on changes of molecular alignment structures around the drops in response to chemical, thermal, electric and other stimuli. We show that absorption or desorption of trace amounts of common surfactants can drive continuous transformations of elastic multipoles induced by the droplets within the uniformly aligned nematic host. Out-of-equilibrium dynamics of director structures emerge from a controlled self-assembly or desorption of different surfactants at the drop-nematic interfaces, with ensuing forward and reverse transformations between elastic dipoles, quadrupoles, octupoles and hexadecapoles. We characterize inter-transformations of droplet-induced surface and bulk defects, probe elastic pair interactions and discuss emergent prospects for fundamental science and applications of the reconfigurable nematic emulsions. © 2022, CC BY-NC-ND.

关键词： Surface active agents

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arXiv 2023年

作者： Bilgic, Berkin Costagli, Mauro Chan, Kwok-Shing Duyn, Jeff Langkammer, Christian Lee, Jongho Li, Xu Liu, Chunlei Marques, José P. Milovic, Carlos Robinson, Simon Schweser, Ferdinand Shmueli, Karin Spincemaille, Pascal Straub, Sina van Zijl, Peter Wang, Yi Martinos Center for Biomedical Imaging Massachusetts General Hospital Harvard Medical School CharlestownMA United States University of Genoa Genoa Italy Laboratory of Medical Physics and Magnetic Resonance IRCCS Stella Maris Pisa Italy Donders Institute for Brain Cognition and Behaviour Radboud University Nijmegen Netherlands Advanced MRI Section NINDS National Institutes of Health BethesdaMD United States Department of Neurology Medical University of Graz Graz Austria Department of Electrical and Computer Engineering Seoul National University Seoul Korea Republic of Russell H. Morgan Department of Radiology and Radiological Science Johns Hopkins University School of Medicine BaltimoreMD United States F.M. Kirby Research Center for Functional Brain Imaging Kennedy Krieger Institute BaltimoreMD United States Department of Electrical Engineering and Computer Sciences University of California BerkeleyCA United States Helen Wills Neuroscience Institute University of California BerkeleyCA United States Pontificia Universidad Catolica de Valparaiso Valparaiso Chile High Field MR Centre Department of Biomedical Imaging and Image-Guided Therapy Medical University of Vienna Austria Buffalo Neuroimaging Analysis Center Department of Neurology Jacobs School of Medicine and Biomedical Sciences the University at Buffalo BuffaloNY United States Center for Biomedical Imaging Clinical and Translational Science Institute the University at Buffalo BuffaloNY United States Department of Medical Physics and Biomedical Engineering University College London London United Kingdom MRI Research Institute Department of Radiology Weill Cornell Medicine New YorkNY United States Department of Radiology Mayo Clinic JacksonvilleFL United States MRI Research Institute Departments of Radiology and Biomedical Engineering Cornell University New YorkNY United States

This article provides recommendations for implementing quantitative susceptibility mapping (QSM) for clinical brain research. It is a consensus of the ISMRM Electro-Magnetic Tissue Properties Study Group. While QSM technical development continues to advance rapidly, the current QSM methods have been demonstrated to be repeatable and reproducible for generating quantitative tissue magnetic susceptibility maps in the brain. However, the many QSM approaches available give rise to the need in the neuroimaging community for guidelines on implementation. This article describes relevant considerations and provides specific implementation recommendations for all steps in QSM data acquisition, processing, analysis, and presentation in scientific publications. We recommend that data be acquired using a monopolar 3D multi-echo GRE sequence, that phase images be saved and exported in DICOM format and unwrapped using an exact unwrapping approach. Multi-echo images should be combined before background removal, and a brain mask created using a brain extraction tool with the incorporation of phase-quality-based masking. Background fields should be removed within the brain mask using a technique based on SHARP or PDF, and the optimization approach to dipole inversion should be employed with a sparsity-based regularization. Susceptibility values should be measured relative to a specified reference, including the common reference region of whole brain as a region of interest in the analysis, and QSM results should be reported with – as a minimum – the acquisition and processing specifications listed in the last section of the article. These recommendations should facilitate clinical QSM research and lead to increased harmonization in data acquisition, analysis, and reporting. © 2023, CC BY.

关键词： Magnetic resonance imaging