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40th IEEE International Conference on Data engineering, ICDE 2024

作者： Wang, Yanling Zhang, Jing Zhang, Lingxi Liu, Lixin Dong, Yuxiao Li, Cuiping Chen, Hong Yin, Hongzhi School of Information Renmin University of China China Zhongguancun Laboratory China Alibaba Group China Tsinghua University Department of Computer Science and Technology China School of Information Technology and Electrical Engineering The University of Queensland Australia

ISBN: (纸本)9798350317152

Open-world semi-supervised learning (Open-world SSL) for node classification, that classifies unlabeled nodes into seen classes or multiple novel classes, is a practical but under-explored problem in the graph community. As only seen classes have human labels, they are usually better learned than novel classes, and thus exhibit smaller intra-class variances within the embedding space (named as imbalance of intra-class variances between seen and novel classes). Based on empirical and theoretical analysis, we find the variance imbalance can negatively impact the model performance. Pre-trained feature encoders can alleviate this issue via producing compact representations for novel classes. However, creating general pre-trained encoders for various types of graph data has been proven to be challenging. As such, there is a demand for an effective method that does not rely on pre-trained graph encoders. In this paper, we propose an IMbalance-A ware method named OpenIMA for Open-world semi-supervised node classification, which trains the node classification model from scratch via contrastive learning with bias-reduced pseudo labels. Extensive experiments on seven popular graph benchmarks demonstrate the effectiveness of OpenIMA, and the source code has been available on GitHub11https://***/RUCKBReasoning/OpenIMA. © 2024 IEEE.

关键词： Signal encoding

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Reducing the data acquisition time in optical scanning holography based on data correlation

Reducing the data acquisition time in optical scanning holog...

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2024 Frontiers in Optics, FiO 2024

作者： Duan, Jilu Luo, Yatao Zhang, Yaping Poon, Ting-Chung Yunnan Provincial Key Laboratory of Modern Information Optics Kunming University of Science and Technology Yunnan Kunming650500 China Bradley Department of Electrical and Computer Engineering Virginia Tech BlacksburgVA24061 United States

We use the mean square error (MSE) to evaluate the correlation of data that skips similar hologram lines in optical scanning holography. This approach has notably decreased the data acquisition duration in experimenta... 详细信息

关键词： Optical correlation

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Imaging atomic-scale chemistry from fused multi-modal electron microscopy

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npj Computational Materials 2022年第1期8卷 164-171页

作者： Jonathan Schwartz Zichao Wendy Di Yi Jiang Alyssa J.Fielitz Don-Hyung Ha Sanjaya D.Perera Ismail El Baggari Richard D.Robinson Jeffrey A.Fessler Colin Ophus Steve Rozeveld Robert Hovden Department of Materials Science and Engineering University of MichiganAnn ArborMIUSA Mathematics and Computer Science Division Argonne National LaboratoryLemontILUSA Advanced Photon Source Facility Argonne National LaboratoryLemontILUSA Dow Chemical Co. MidlandMIUSA Department of Material Science and Engineering Cornell UniversityIthacaNew YorkUSA School of Integrative Engineering Chung-Ang UniversitySeoulRepublic of Korea Department of Physics Cornell UniversityIthacaNYUSA The Rowland Institute at Harvard CambridgeMAUSA Department of Electrical Engineering and Computer Science University of MichiganAnn ArborMIUSA National Center for Electron Microscopy Lawrence Berkeley National LaboratoryMolecular FoundryBerkeleyCAUSA Applied Physics Program University of MIchiganAnn ArborMIUnited States

Efforts to map atomic-scale chemistry at low doses with minimal noise using electron microscopes are fundamentally limited by inelastic ***,fused multi-modal electron microscopy offers high signal-to-noise ratio(SNR)recovery of material chemistry at nano-and atomic-resolution by coupling correlated information encoded within both elastic scattering(high-angle annular dark-field(HAADF))and inelastic spectroscopic signals(electron energy loss(EELS)or energy-dispersive x-ray(EDX)).By linking these simultaneously acquired signals,or modalities,the chemical distribution within nanomaterials can be imaged at significantly lower doses with existing detector *** many cases,the dose requirements can be reduced by over one order of *** high SNR recovery of chemistry is tested against simulated and experimental atomic resolution data of heterogeneous nanomaterials.

关键词： materials chemistry fused

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Long-Term Water Quality Prediction with Patch Savitsky-Golay Filtering and Transformer

Long-Term Water Quality Prediction with Patch Savitsky-Golay...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Lin, Yongze Qiao, Junfei Bi, Jing Yuan, Haitao Zhai, Jiahui Zhou, MengChu Beijing University of Technology Beijing Laboratory of Smart Environmental Protection Beijing100124 China School of Information Science and Technology Beijing University of Technology Beijing100124 China College of Computer Beijing University of Technology Beijing100124 China School of Automation Science and Electrical Engineering Beihang University Beijing100191 China New Jersey Institute of Technology Department of Electrical and Computer Engineering Newark07102 United States

ISBN: (纸本)9781665410205

In many fields, time series prediction is gaining more and more attention, e.g., air pollution, geological hazards, and network traffic prediction. Water quality prediction is based on historical data to predict future water quality. However, it is difficult to learn a representation map from a time series that captures the trends and fluctuations to effectively remove noise from time series data and capture complex nonlinear relationships. To solve these problems, this work proposes a time series prediction model, called PSGT for short, which integrates Patch Savitsky-Golay filtering and Transformer. First, this work adopts a Patching method to embed sub-time series data and obtains the trends and semantic information of the time series. Second, it uses the Savitsky-Golay filtering to effectively remove the noise data in the patch and improve the prediction accuracy. Third, it uses a Transformer mechanism to address the nonlinear problem of water quality time series and improve long-term prediction capability. Two real-world datasets are utilized to evaluate the proposed PSGT, and experiments prove that PSGT performs better than other benchmark models by at least 6%. © 2024 IEEE.

关键词： Self-supervised learning

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A Wearable Paper-Based Hybrid Energy Harvester from Human Sweat and Ambient Moisture 38

A Wearable Paper-Based Hybrid Energy Harvester from Human Sw...

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38th IEEE International Conference on Micro Electro Mechanical Systems, MEMS 2025

作者： Gao, Yang Choi, Seokheun State University of New York at Binghamton Bioelectronics & Microsystems Laboratory Department of Electrical & Computer Engineering BinghamtonNY United States State University of New York at Binghamton Center for Research in Advanced Sensing Technologies and Environmental Sustainability BinghamtonNY United States

ISBN: (纸本)9798331508890

We present a wearable, paper-based energy harvester that combines a sweat-driven microbial fuel cell (MFC) with an ambient moisture-enabled electric generator (MEG), capable of simultaneously or independently harnessing energy from both human sweat and the environment. Paper stands out as an ideal substrate for wearable applications, offering flexibility and easy integration through straightforward printing methods. Due to the simple design of the MFC and MEG, both devices can be seamlessly integrated into a single sheet of paper. The biocatalyst-embedded anode of the MFC is positioned directly against the skin for optimal sweat absorption, while the hygroscopic region of the MEG faces outward to efficiently capture ambient moisture. At low humidity levels, the energy harvesting is primarily driven by the MFC, while in the absence of sweat, the MEG takes over as the main power source. This dual functionality ensures continuous and sustainable power generation, making the system highly efficient and reliable for long-term wearable applications. © 2025 IEEE.

关键词： Microbial fuel cells

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Scattering exceptional point in the visible

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Light(science & Applications) 2023年第10期12卷 2228-2235页

作者： Tao He Zhanyi Zhang Jingyuan Zhu Yuzhi Shi Zhipeng Li Heng Wei Zeyong Wei Yong Li Zhanshan Wang Cheng-Wei Qiu Xinbin Cheng MOE Key Laboratory of Advanced Micro-Structured Materials Shanghai 200092China Institute of Precision Optical Engineering School of Physics Science and EngineeringTongji UniversityShanghai 200092China Shanghai Institute of Intelligent Science and Technology Tongji UniversityShanghai 200092China Shanghai Frontiers Science Center of Digital Optics Shanghai 200092China Shanghai Professional Technical Service Platform for Full-Spectrum and High-Performance Optical Thin Film Devices and Applications Shanghai 200092China Department of Electronic Science and Technology Tongji UniversityShanghai 201804China Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore Institute of Acoustics School of Physics Science and EngineeringTongji UniversityShanghai 200092China

Exceptional point (EP) is a special degeneracy of non-Hermitian systems. One-dimensional transmission systems operating at EPs are widely studied and applied to chiral conversion and sensing. Lately, two-dimensional systems at EPs have been exploited for their exotic scattering features, yet so far been limited to only the non-visible waveband. Here, we report a universal paradigm for achieving a high-efficiency EP in the visible by leveraging interlayer loss to accurately control the interplay between the lossy structure and scattering lightwaves. A bilayer framework is demonstrated to reflect back the incident light from the left side ( | r_(−1) | >0.999) and absorb the incident light from the right side ( | r_(+1) | < 10^(–4)). As a proof of concept, a bilayer metasurface is demonstrated to reflect and absorb the incident light with experimental efficiencies of 88% and 85%, respectively, at 532 nm. Our results open the way for a new class of nanoscale devices and power up new opportunities for EP physics.

关键词： visible exceptional incident

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Adaptive Frequency Hopping for 5G New Radio mMTC Security

Adaptive Frequency Hopping for 5G New Radio mMTC Security

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2023 IEEE International Conference on Industrial Technology, ICIT 2023

作者： Chan, Wai Ming Kwon, Hyuck M. Chou, Remi A. Love, David J. Fahmy, Sonia Hussain, Syed Rafiul Kim, Sang Wu Valk, Chris Vander Brinton, Christopher G. Marojevic, Vuk Pham, Khanh D. Kim, Taejoon The University of Kansas Department of Electrical Engineering and Computer Science LawrenceKS66045 United States Wichita State University Department of Electrical and Computer Engineering WichitaKS67260 United States School of Computing Wichita State University WichitaKS67260 United States Elmore Family School of Electrical and Computer Engineering Purdue University West LafayetteIN47907 United States Purdue University Department of Computer Science West LafayetteIN47907 United States The Pennsylvania State University Department of Computer Science and Engineering State CollegePA16802 United States Iowa State University Department of Electrical and Computer Engineering AmesIA50011 United States Raytheon Bbn CambridgeMA02138 United States Mississippi State University Department of Ece StarkvilleMS39762 United States Air Force Research Laboratory AlbuquerqueNM87123 United States

ISBN: (纸本)9798350336504

3GPP standards (e.g., LTE and 5G New Radio (NR)) have revolutionized commercial broadband access. Unfortunately, the openness of 3GPP specifications and high-level of adaptability make fifth-generation (5G) networks increasingly sensitive to unsophisticated attacks in the network. While 5G NR has introduced frequency hopping (FH) for massive machine-type communications (mMTC), there has not been a unified approach to designing the FH patterns in practical 5G systems. In this paper, we investigate the multi-user FH design problem at the physical resource grid of the 5G communication networks. We present various criteria for FH pattern design and propose two algorithms that are implementable with low complexity. The first scheme utilizes known interference patterns to design a set of user equipment (UE) FH patterns that are immune to interfering attacks. The second scheme leverages interference statistics and minimizes the expected number of hits by the interferer. Through numerical simulations and analytical modeling, we demonstrate the efficacy of the proposed schemes, which outperform the uniform FH pattern and achieve near-optimal performance. © 2023 IEEE.

关键词： Frequency hopping

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Real-time self-healing dynamics of a Brillouin-Kerr comb in a FP microresonator-filtered laser 16

Real-time self-healing dynamics of a Brillouin-Kerr comb in ...

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16th Pacific Rim Conference on Lasers and Electro-Optics, CLEO-PR 2024

作者： Du, Junting Lian, Wenxuan Shi, Zhangru Jia, Kunpeng Xie, Zhenda Nie, Mingming Li, Bowen University of Electronic Science and Technology of China Chengdu611731 China National Laboratory of Solid State Microstructures School of Electronic Science and Engineering College of Engineering and Applied Sciences School of Physics Collaborative Innovation Center of Advanced Microstructures Nanjing University Nanjing210093 China Department of Electrical Computer and Energy Engineering University of Colorado Boulder BoulderCO80309 United States

Real-time self-healing dynamics of a tens-of-GHz Brillouin-Kerr frequency comb in a FP-microresonator-filtered laser is observed for the first time using a low-bandwidth oscilloscope and a time magnifier, providing fu... 详细信息

ISBN: (纸本)9798350372076

关键词： Microresonators

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Scale‐wise interaction fusion and knowledge distillation network for aerial scene recognition

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CAAI Transactions on Intelligence Technology 2023年第4期8卷 1178-1190页

作者： Hailong Ning Tao Lei Mengyuan An Hao Sun Zhanxuan Hu Asoke K.Nandi School of Computer Science and Technology Xi'an University of Posts and TelecommunicationsShaanxi Key Laboratory of Network Data Analysis and Intelligent ProcessingXi'anChina Xi'an Key Laboratory of Big Data and Intelligent Computing Xi'anChina School of Electronic Information and Artificial Intelligence Shaanxi University of Science and TechnologyXi'anChina School of Computer Central China Normal UniversityWuhanChina Department of Electronic and Electrical Engineering Brunel University LondonLondonUK Xi'an Jiaotong University Xi'anChina

Aerial scene recognition(ASR)has attracted great attention due to its increasingly essential *** of the ASR methods adopt the multi‐scale architecture because both global and local features play great roles in ***,the existing multi‐scale methods neglect the effective interactions among different scales and various spatial locations when fusing global and local features,leading to a limited ability to deal with challenges of large‐scale variation and complex background in aerial scene *** addition,existing methods may suffer from poor generalisations due to millions of to‐belearnt parameters and inconsistent predictions between global and local *** tackle these problems,this study proposes a scale‐wise interaction fusion and knowledge distillation(SIF‐KD)network for learning robust and discriminative features with scaleinvariance and background‐independent *** main highlights of this study include two *** the one hand,a global‐local features collaborative learning scheme is devised for extracting scale‐invariance features so as to tackle the large‐scale variation problem in aerial scene ***,a plug‐and‐play multi‐scale context attention fusion module is proposed for collaboratively fusing the context information between global and local *** the other hand,a scale‐wise knowledge distillation scheme is proposed to produce more consistent predictions by distilling the predictive distribution between different scales during *** experimental results show the proposed SIF‐KD network achieves the best overall accuracy with 99.68%,98.74%and 95.47%on the UCM,AID and NWPU‐RESISC45 datasets,respectively,compared with state of the arts.

关键词： deep learning image analysis image classification information fusion

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Low-temperature spin Seebeck effect in nonmagnetic vanadium dioxide

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Physical Review B 2024年第2期110卷 024415-024415页

作者： Renjie Luo Tanner J. Legvold Liyang Chen Henry Navarro Ali C. Basaran Deshun Hong Changjiang Liu Anand Bhattacharya Ivan K. Schuller Douglas Natelson Department of Physics and Astronomy Applied Physics Graduate Program Rice Quantum Institute Department of Physics and Center for Advanced Nanoscience Materials Science Division Department of Electrical and Computer Engineering Department of Materials Science and NanoEngineering

The spin Seebeck effect (SSE) is sensitive to thermally driven magnetic excitations in magnetic insulators. Vanadium dioxide in its insulating low-temperature phase is expected to lack magnetic degrees of freedom, as vanadium atoms are thought to form singlets upon dimerization of the vanadium chains. Instead, we find a paramagnetic SSE response in VO2 films that grows as the temperature decreases below 50 K. The field and temperature-dependent SSE voltage is qualitatively consistent with a general model of paramagnetic SSE response and inconsistent with triplet spin transport. Quantitative estimates find a spin Seebeck coefficient comparable in magnitude to that observed in strongly magnetic materials. The microscopic nature of the magnetic excitations in VO2 requires further examination.

关键词： Spin Seebeck effect Paramagnets Strongly correlated systems

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