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International Conference on Green Energy, Computing and Intelligent Technology 2024 (GEn-CITy 2024)

作者： Linfeng Liu Filbert H. Juwono W. K. Wong Erick Purwanto Tingyan Jin Yuyang Zhen Sustainable Energy Technology Program Xi'an Jiaotong-Liverpool University Suzhou People's Republic of China Department of Electrical and Electronic Engineering Xi'an Jiaotong-Liverpool University Suzhou People's Republic of China Department of Electrical and Computer Engineering Curtin University Malaysia Miri Malaysia Department of Computing Xi'an Jiaotong-Liverpool University Suzhou People's Republic of China School of Mechanical and Electrical Engineering Beijing Information Science and Technology University Beijing People's Republic of China School of Instrument Science and Technology Beijing University of Technology Beijing People's Republic of China

ISBN: (数字)9781837242863

In this study, we explore the classification and prediction capabilities of three models—Genetic programming (GP), Logistic Regression (LR), and the Kolmogorov-Arnold Network (KAN)—on the task of sodium-ion battery life prediction. By leveraging a dataset composed of multiple battery characteristics, we aim to determine the remaining power of sodium-ion batteries using these machine learning models. The KAN model, being a novel approach, demonstrates superior performance across various metrics, including accuracy, precision, recall, and F1 score, when compared to the other two models. This highlights the potential of KAN as a robust model for complex classification tasks in the field of battery life prediction.

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Reducing Effective System Dimensionality with Long-Range Collective Dipole-Dipole Interactions

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Physical Review Letters 2024年第17期132卷 173803-173803页

作者： Ashwin K. Boddeti Yi Wang Xitlali G. Juarez Alexandra Boltasseva Teri W. Odom Vladimir Shalaev Hadiseh Alaeian Zubin Jacob Elmore Family School of Electrical and Computer Engineering Purdue University West Lafayette Indiana 47907 USA Birck Nanotechnology Center Purdue University West Lafayette Indiana 47907 USA Graduate Program in Applied Physics Northwestern University Evanston Illinois 60208 USA Department of Materials Science and Engineering Northwestern University Evanston Illinois 60208 USA Department of Chemistry Northwestern University Evanston Illinois 60208 USA School of Physics and Astronomy Purdue University West Lafayette Indiana 47907 USA

Dimensionality plays a crucial role in long-range dipole-dipole interactions (DDIs). We demonstrate that a resonant nanophotonic structure modifies the apparent dimensionality in an interacting ensemble of emitters, as revealed by population decay dynamics. Our measurements on a dense ensemble of interacting quantum emitters in a resonant nanophotonic structure with long-range DDIs reveal an effective dimensionality reduction to d¯=2.20(12), despite the emitters being distributed in 3D. This contrasts with the homogeneous environment, where the apparent dimension is d¯=3.00. Our work presents a promising avenue to manipulate dimensionality in an ensemble of interacting emitters.

关键词： Light-matter interaction Long-range interactions Metamaterials Optics & lasers Photonics Plasmonics Quantum optics

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Vacuum Ultraviolet Light-Generating Metalens

Vacuum Ultraviolet Light-Generating Metalens

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2022 International Conference on Optics-Photonics Design and Fabrication, ODF 2022

作者： Tseng, Ming Lun Semmlinger, Michael Zhang, Ming Arndt, Catherine Huang, Tzu-Ting Yang, Jian Kuo, Hsin Yu Su, Vin-Cent Chen, Mu Ku Chu, Cheng Hung Cerjan, Benjamin Tsai, Din Ping Nordlander, Peter Halas, Naomi J. Institute of Electronics National Yang Ming Chiao Tung University Hsinchu300 Taiwan Research Center for Applied Sciences Academia Sinica Taipei115 Taiwan Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States Laboratory for Nanophotonics Rice University HoustonTX77005 United States Applied Physics Graduate Program Rice University HoustonTX77005 United States Department of Physics and Astronomy Rice University HoustonTX77005 United States Department of Physics National Taiwan University Taipei10617 Taiwan Department of Electrical Engineering National United University Miaoli36003 Taiwan Department of Electrical Engineering City University of Hong Kong Kowloon Hong Kong Department of Chemistry Rice University HoustonTX77005 United States

Vacuum ultraviolet (VUV) light is of great importance to many applications such as photochemistry and nanolithography. In this talk, a nonlinear metalens composed of ZnO nanoantennas for VUV generation and focusing wi... 详细信息

关键词： Nanoclay

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Imaging of Nanoscale Light Confinement in Plasmonic Nanoantennas by Brownian Optical Microscopy (vol 14, pg 7666, 2020)

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ACS NANO 2020年第9期14卷 12261-12261页

作者： Lee, Yeon Ui Wisna, G. Bimananda M. Hsu, Su-Wen Zhao, Junxiang Lei, Ming Li, Shilong Tao, Andrea R. Liu, Zhaowei Department of Electrical and Computer Engineering University of California San Diego 9500 Gilman Drive La Jolla California 92093 United States Material Science and Engineering Program University of California San Diego 9500 Gilman Drive La Jolla California 92093 United States Department of NanoEngineering University of California San Diego 9500 Gilman Drive La Jolla California 92093 United States Department of Electrical and Computer Engineering University of California San Diego 9500 Gilman Drive La Jolla California 92093 United States Department of Electrical and Computer Engineering University of California San Diego 9500 Gilman Drive La Jolla California 92093 United States Department of Electrical and Computer Engineering University of California San Diego 9500 Gilman Drive La Jolla California 92093 United States Material Science and Engineering Program University of California San Diego 9500 Gilman Drive La Jolla California 92093 United States Department of NanoEngineering University of California San Diego 9500 Gilman Drive La Jolla California 92093 United States Department of Electrical and Computer Engineering University of California San Diego 9500 Gilman Drive La Jolla California 92093 United States Material Science and Engineering Program University of California San Diego 9500 Gilman Drive La Jolla California 92093 United States

The strongly enhanced and confined subwavelength optical fields near plasmonic nanoantennas have been extensively studied not only for the fundamental understanding of light-matter interactions at the nanoscale but also for their emerging practical application in enhanced second harmonic generation, improved inelastic electron tunneling, harvesting solar energy, and photocatalysis. However, owing to the deep subwavelength nature of plasmonic field confinement, conventional optical imaging techniques are incapable of characterizing the optical performance of these plasmonic nanoantennas. Here, we demonstrate super-resolution imaging of ∼20 nm optical field confinement by monitoring randomly moving dye molecules near plasmonic nanoantennas. This Brownian optical microscopy is especially suitable for plasmonic field characterization because of its capabilities for polarization sensitive wide-field super-resolution imaging.

关键词： super-resolution imaging plasmonic nanoantennas hot spot imaging Brownian optical microscopy fluorescence enhancement nanophotonics plasmonics

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Hierarchical B-Frame Video Coding Using Two-Layer CANF Without Motion Coding

Hierarchical B-Frame Video Coding Using Two-Layer CANF Witho...

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Conference on computer Vision and Pattern Recognition (CVPR)

作者： David Alexandre Hsueh-Ming Hang Wen-Hsiao Peng Electrical Engineering and Computer Science International Graduate Program National Yang Ming Chiao Tung University Hsinchu Taiwan Institute of Electronics National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Computer Science National Yang Ming Chiao Tung University Hsinchu Taiwan

Typical video compression systems consist of two main modules: motion coding and residual coding. This general architecture is adopted by classical coding schemes (such as international standards H.265 and H.266) and deep learning-based coding schemes. We propose a novel B-frame coding architecture based on two-layer Conditional Augmented Normalization Flows (CANF). It has the striking feature of not transmitting any motion information. Our proposed idea of video compression without motion coding offers a new direction for learned video coding. Our base layer is a low-resolution image compressor that replaces the full-resolution motion compressor. The low-resolution coded image is merged with the warped high-resolution images to generate a high-quality image as a conditioning signal for the enhancement-layer image coding in full resolution. One advantage of this architecture is significantly reduced computational complexity due to eliminating the motion information compressor. In addition, we adopt a skip-mode coding technique to reduce the transmitted latent samples. The rate-distortion performance of our scheme is slightly lower than that of the state-of-the-art learned B-frame coding scheme, B-CANF, but outperforms other learned B-frame coding schemes. However, compared to B-CANF, our scheme saves 45% of multiply-accumulate operations (MACs) for encoding and 27% of MACs for decoding. The code is available at https://***.

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Impact of Image Enhancement for Osteoporosis Detection Based on Deep Learning Algorithm

Impact of Image Enhancement for Osteoporosis Detection Based...

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computer System, Information Technology, and electrical engineering (COSITE), International Conference on

作者： Riza Dianil Iman Roslidar Roslidar Kahlil Muchtar Amalia Amalia Mohammad Syaryadhi Alfatirta Mufti Novi Maulina Department of Electrical and Computer Engineering Universitas Syiah Kuala Banda Aceh Indonesia Department of Computer Science Universitas Sumatera Utara Medan Indonesia Graduate School of System Designs Tokyo Metropolitan University Tokyo Japan Doctorate Student of Doctoral Program in Medical Sciences Faculty of Medicine Universitas Syiah Kuala Banda Aceh Indonesia

Osteoporosis can be defined as a degenerative disease with reduced bone mass and changes in bone architecture that can lead to bone fragility and the risk of fractures. This abnormality can be indicated by the bone density which in visual can be determined using X-Ray images. However, X-Ray images are susceptible to noise, while in image analysis image contrast affects deep learning abilities. Hence, the CLAHE (Contrast Limited Adaptive Histogram Equalization) algorithm is used as a contrast enhancement technique in X-Ray images. This study aims to build a deep learning model using the CLAHE-enhanced image dataset with the ResNet-50 and ResNet-101 architectures. The model was built using two different datasets, namely the original image dataset and the CLAHE-enhanced image dataset. The result shows that the highest performance is given by the ResNet-101 model using the CLAHE-enhanced image dataset with an accuracy rate of 96%, precision of 95%, specificity of 95%, recall of 97% and an Fl-score of 96%, respectively. By using the CLAHE algorithm, the resulting image has high contrast and looks better at displaying features in the image so as to produce better model performance.

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Generative adversarial networks applied to gene expression analysis: An interdisciplinary perspective

Computational and Systems Oncology

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Computational and Systems Oncology 2023年第3期3卷

作者： Ai, Xusheng Smith, Melissa C Feltus, Frank Alex Electrical and Computer Engineering Department Clemson University Clemson SC United States Department of Genetics and Biochemistry Biomedical Data Science & Informatics Program Clemson Center for Human Genetics Clemson University Clemson SC United States

The remarkable flexibility and adaptability of generative adversarial networks (GANs) have led to the proliferation of its models in bioinformatics research. Proteomic and transcriptomic profiles have been shown to be promising methods for discovering and identifying disease biomarkers. However, those analyses were performed by trained human examiners making the process tedious, time consuming, and hard to standardize. With the development of GANs, it is now possible to reduce computational costs and human time for bioinformatics analysis to produce effective biomarkers. Moreover, GANs help address the lack of phenotypic state transitional gene expression data as well as avoid protected human data constraints by generating RNA sequencing (RNA-seq) data from random vectors. The purpose of this review is to summarize the use of GAN approaches and techniques to augment RNA-seq expression data and identify clinically useful biomarkers. We compare different studies that use different types of GAN models to examine the biomarkers. Also, we identify research gaps and challenges that apply GANs to bio-informatics. Finally, we propose potential directions for future research. © 2023 The Authors. Computational and Systems Oncology published by Wiley Periodicals LLC.

关键词： biomarkers data augmentation generative adversarial network RNA sequencing

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Performance limits due to thermal transport in graphene single-photon bolometers

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Physical Review Applied 2024年第1期21卷 014006-014006页

作者： Caleb Fried B. Jordan Russell Ethan G. Arnault Bevin Huang Gil-Ho Lee Dirk Englund Erik A. Henriksen Kin Chung Fong Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge Massachusetts 02139 Department of Earth and Planetary Sciences Harvard University Cambridge Massachusetts 02138 USA Department of Physics Harvard University Cambridge Massachusetts 02138 USA Raytheon BBN Quantum Engineering and Computing Group Cambridge Massachusetts 02138 USA Department of Physics Washington University in St. Louis St. Louis Missouri USA Intelligence Community Postdoctoral Research Fellowship Program Massachusetts Institute of Technology Cambridge Massachusetts 02139 Department of Physics Pohang University of Science and Technology Pohang 790-784 Republic of Korea

In high-sensitivity bolometers and calorimeters, the photon absorption often occurs at a finite distance from the temperature sensor to accommodate antennas or avoid the degradation of superconducting circuitry exposed to radiation. As a result, thermal propagation from the input to the temperature readout can critically affect detector performance. In this paper we model the performance of a graphene bolometer, accounting for electronic thermal diffusion and dissipation via electron-phonon coupling at low temperatures in three regimes: clean, supercollision, and resonant scattering. Our results affirm the feasibility of a superconducting readout without Cooper-pair breaking by mid- and near-infrared photons, and provide a recipe for designing graphene absorbers for calorimetric single-photon detectors. We investigate the trade-off between the input-readout distance and detector efficiency, and predict an intrinsic timing jitter of approximately 2.7 ps. Based on our result, we propose a spatial-mode-resolving photon detector to increase the communication bandwidth.

关键词： Heat transfer Metrology Optical quantum information processing Graphene Josephson junctions Bolometers Calorimetry Single-photon detectors

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Eigenvalue-Based Micromagnetic Analysis of Switching in Spin-Torque-Driven Structures

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Physical Review Applied 2022年第3期17卷 034016-034016页

作者： Z. Lin I. Volvach X. Wang V. Lomakin Department of Electrical and Computer Engineering University of California San Diego La Jolla California 92093 USA Center for Memory and Recording Research La Jolla California 92093 USA Materials Science and Engineering Program University of California San Diego La Jolla California 92093 USA

We present an eigenvalue-based approach for studying the magnetization dynamics in magnetic nanostructures driven by spintronic excitations, such as spin-transfer torque and spin-orbit torque. The approach represents the system dynamics in terms of normal oscillation modes (eigenstates) with corresponding complex eigenfrequencies. The dynamics is driven by a small number of active eigenstates and often considering just a single eigenstate is sufficient. We develop a perturbation theory that provides semianalytical dynamic solutions by using eigenstates for the case in the absence of damping and spintronic excitations as a basis. The approach provides useful insights into dynamics in such systems and allows solving several difficulties in their modeling, such as extracting the switching current in magnetic random-access memories and understanding switching mechanisms. We show that the presented approach directly predicts the critical switching current, i.e., switching current for an infinite time. The approach also provides solutions for the switching dynamics allowing the switching current to be obtained for a finite switching time, provided that the system symmetry is broken, e.g., by tilting the polarizer, so that switching by a finite pulse is possible.

关键词： Magnetization dynamics Spin transfer torque Spin-orbit torque Spintronics Devices for digital logic, storage & processing Landau-Lifschitz-Gilbert equation Micromagnetic modeling Perturbation theory

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Photovoltaic Microinverter with Hybrid Energy Storage System (HESS) and Virtual Impedance Control for Injection into a Microgrid

Photovoltaic Microinverter with Hybrid Energy Storage System...

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IEEE Annual Southern Power Electronics Conference (SPEC)

作者： Patricio Gaisse Javier Muñoz Marco Rivera Carlos Restrepo Galina Mirzaeva Engineering Systems Doctoral Program Faculty of Engineering University of Talca Curicó Chile Department of Electrical Engineering Faculty of Engineering Universidad de Talca Curicó Chile Doctorate in Engineering Systems Faculty of Engineering Universidad de Talca Curicó Chile School of Electrical Engineering and Computer Science The University of Newcastle Callaghan NSW Australia

In this work, a photovoltaic (PV) microinverter is developed, which includes an hybrid energy storage system based on a battery and an ultracapacitor that are connected in parallel to the dc-link through two buck-boost bidirectional converters. The PV panel is connected in parallel to dc-link through an unidirectional boost converter. For the dc-ac stage, a two-stage Flyback / H-bridge inverter will be considered, which will be used to inject the available power into a microgrid. The study proposes the necessary control strategies to manage the power flow according to generation and injection conditions, where a virtual impedance loop is incorporated in the control of the energy storage elements. The presented results confirm the suitability of the proposed strategy.

关键词： Photovoltaic systems Microgrids Hybrid power systems Batteries Circuit stability Topology Impedance

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