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Recent Advances in Parity-Time Symmetry-Enabled Electromagnetic Sensors

Progress In Electromagnetics Research B 2024年 105卷 107-121页

作者： Yang, Minye Ye, Zhilu Chen, Pai-Yen Erricolo, Danilo Department of Electrical and Computer Engineering University of Illinois Chicago ChicagoIL60607 United States State Key Laboratory for Manufacturing Systems Engineering Electronic Materials Research Laboratory Key Laboratory of the Ministry of Education School of Electronic Science and Engineering Xi’an Jiaotong University Shaanxi Xi’an710049 China State Key Laboratory for Manufacturing Systems Engineering The Key Laboratory of Biomedical Information Engineering of Ministry of Education Center for Mitochondrial Biology and Medicine School of Life Science and Technology International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technology Xi’an Key Laboratory for Biomedical Testing and High-end Equipment Xi’an Jiaotong University Shaanxi Xi’an710049 China

Parity-time (PT) reversal symmetry, as a representative example in the field of non-Hermitian physics, has attracted widespread research interest in the past few years due to its extraordinary wave dynamics. PT symmetry enables unique spectral singularities including the exceptional point (EP) degeneracy where two or more eigenvalues and eigenvectors coalesce, as well as the coherent perfect absorber-laser (CPAL) point where laser and its time-reversal counterpart (i.e., coherent perfect absorber) can coexist at the same frequency. These singular points not only give rise to new physical phenomena but also provide new plausibility for building the next-generation sensors and detectors with unprecedented sensitivity. To date, investigations into EPs and CPAL points have unveiled their great potential in various sensing scenarios across a broad spectral range, spanning optics, photonics, electronics, and acoustics. In this review article, we will discuss ongoing developments of EP- and CPAL-based sensors composed of PT-synthetic structures and offer a glimpse into the future research directions in this emerging field. © (2024), (Electromagnetics Academy). All rights reserved.

关键词： Eigenvalues and eigenfunctions

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Virtual Sensing of Room Activity Using Passive Environmental Sensors

Virtual Sensing of Room Activity Using Passive Environmental...

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International Conference on Internet of Things 2024, ICIoT 2024

作者： Li, Yeqin Chieng, David Kwong, Chiew Foong Lee, Boon Giin Zhang, Yunfan Wang, Yin Lin, Ting-Jung Next-Generation Internet of Everything Laboratory Department of Electrical and Electronic Engineering University of Nottingham Ningbo China Ningbo China School of Computer Science University of Nottingham Ningbo China Ningbo China Department of Electrical and Computer Engineering Duke University United States HealthyPhoton Technology Co. Ltd. Ningbo315042 China

A data-driven approach has been developed to classify indoor activities using only commonly available passive environmental sensors, such as CO2, temperature, humidity, and passive infrared (PIR). An integrated IoT system comprising of sensor nodes, edge node and an intelligent server is designed and developed to provide real-time activity classification. Spectral Clustering and bidirectional long short-term memory (BiLSTM) are employed to achieve automatic labeling and room state prediction. The results show that the overall classification accuracy ranges from 88% to 96% for five target states across three distinct environments using CO2 and PIR values as input variables. Additionally, incorporating more input variables has been evaluated to access the ability of real-time classification of proposed model. An innovative monitoring mode can provide a different approach for detecting activities and occupancy in the future. © The Institution of engineering & Technology 2024.

关键词： Sensor nodes

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Free-electron crystals for enhanced X-ray radiation

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Light(science & Applications) 2024年第7期13卷 1299-1309页

作者： Lee Wei Wesley Wong Xihang Shi Aviv Karnieli Jeremy Lim Suraj Kumar Sergio Carbajo Ido Kaminer Liang Jie Wong School of Electrical and Electronic Engineering Nanyang Technological University50 Nanyang AvenueSingapore 639798Singapore. Solid State Institute and Faculty of Electrical and Computer Engineering Technion–Israel Institute of TechnologyHaifa 3200003Israel. School of Electrical Engineering Fleischman Faculty of EngineeringTel Aviv UniversityTel Aviv 69978Israel Department of Applied Physics Stanford UniversityStanfordCA 94305USA. Science Mathematics and TechnologySingapore University of Technology and Design8 Somapah RoadSingapore 487372Singapore. Electrical and Computer Engineering Department UCLA420 WestwoodLos AngelesCA 90095USA. Physics and Astronomy Department UCLA475 Portola PlazaLos AngelesCA 90095USA. SLAC National Accelerator Laboratory Stanford University2575 Sand Hill RoadMenlo ParkCA 94025USA

Bremsstrahlung—the spontaneous emission of broadband radiation from free electrons that are deflected by atomic nuclei—contributes to the majority of X-rays emitted from X-ray tubes and used in applications ranging from medical imaging to semiconductor chip ***,we show that the bremsstrahlung intensity can be enhanced significantly—by more than three orders of magnitude—through shaping the electron wavefunction to periodically overlap with atoms in crystalline ***,we show how to shape the bremsstrahlung X-ray emission pattern into arbitrary angular emission profiles for purposes such as unidirectionality and ***,we find that these enhancements and shaped emission profiles cannot be attributed solely to the spatial overlap between the electron probability distribution and the atomic centers,as predicted by the paraxial and nonrecoil theory for free electron light *** work highlights an unprecedented regime of free electron light emission where electron waveshaping provides multi-dimensional control over practical radiation processes like *** results pave the way towards greater versatility in table-top X-ray sources and improved fundamental understanding of quantum electron-light interactions.

关键词： overlap attributed arbitrary

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Linear Model-Based Optimal VVC Intercoding Rate Control Scheme 1

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Proceedings of the 4th International Conference on Neural Computing for Advanced Applications, NCAA 2023

作者： Wei, Xuekai Zhou, Mingliang Liao, Xingran State Key Laboratory of Internet of Things for Smart City and Department of Electrical and Computer Engineering University of Macau 999078 China School of Computer Science Chongqing University Chongqing400044 China Department of Computer Science City University of Hong Kong Kowloon 999077 Hong Kong

ISBN: (数字)9789819958443

ISBN: (纸本)9789819958436

In this paper, we propose a rate control (RC) scheme with a linear model in versatile video coding (VVC) intercoding, our method introduces a compromise global Lagrange multiplier to minimize the distortion induced under group-of-pictures (GOP)- and frame-level bit budget constraints. To obtain the optimal solution, the corresponding problem is transformed into a convex optimization problem. Then, the Karush-Kuhn-Tucker (KKT) conditions are used to obtain the optimal quantization parameter (QP). The experimental results show that our RC algorithm achieves better coding efficiency, a better RC effect, and higher subjective quality than the default algorithm in VVC Test Model (VTM) 17.0 and other state-of-the-art algorithms. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Convex optimization

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Polarization‑entangled photon‑pair source with van der Waals 3R‑WS_(2) crystal

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eLight 2024年第1期4卷 99-106页

作者： Jiangang Feng Yun‑Kun Wu Ruihuan Duan Jun Wang Weijin Chen Jiazhang Qin Zheng Liu Guang‑Can Guo Xi‑Feng Ren Cheng‑Wei Qiu Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore CAS Key Laboratory of Quantum Information University of Science and Technology of ChinaHefei 230026China CAS Center for Excellence in Quantum Information and Quantum Physics University of Science and Technology of ChinaHefei 230026China Hefei National Laboratory University of Science and Technology of ChinaHefei 230088China School of Materials Science and Engineering Nanyang Technological UniversitySingapore 639798Singapore Department of Optical Science and Engineering and Shanghai Frontiers Science Research Base of Intelligent Optoelectronics and PerceptionFudan UniversityShanghai 200433China

Ultracompact entangled photon sources are pivotal to miniaturized quantum photonic *** der Waals(vdW)nonlinear crystals promise efficient photon-pair generation and on-chip monolithic integration with nanophotonic ***,it remains challenging to generate maximally entangled Bell states of photon pairs with high purity,generation rate,and fidelity required for practical ***,we realize a polarization-entangled photon-pair source based on spontaneous parametric down conversion in an ultrathin rhombohedral tungsten disulfide(3R-WS2)*** vdW entangled photonic source exhibits a high photon-pair purity with a coincidenceto-accidental ratio of above 800,a generation rate of 31 Hz,and two maximally polarization-entangled Bell states with fidelities exceeding 0.93 and entanglement degree over *** results stem from scalable optical nonlinearity,enhanced second-order susceptibility by electronic transitions,and a well-defined symmetry-enabled selection rule inherent in *** polarization entangled photon source can be integrated with photonic structures for generating more complex entangled states,thus paving an avenue for advanced quantum photonic systems toward computation and metrology.

关键词： purity maximal Polarization

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ANIMC: A Soft Approach for Autoweighted Noisy and Incomplete Multiview Clustering

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2022年第2期3卷 192-206页

作者： Fang, Xiang Hu, Yuchong Zhou, Pan Wu, Dapeng Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering The School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of Information Storage System Ministry of Education of China School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan430074 China Department of Electrical and Computer Engineering University of Florida GainesvilleFL32611 United States

Multiview clustering has wide real-world applications because it can process data from multiple sources. However, these data often contain missing instances and noises, which are ignored by most multiview clustering methods. Missing instances may make these methods difficult to use directly, and noises will lead to unreliable clustering results. In this article, we propose a novel autoweighted noisy and incomplete multiview clustering (ANIMC) approach via a soft autoweighted strategy and a doubly soft regular regression model. First, by designing adaptive semiregularized nonnegative matrix factorization, the soft autoweighted strategy assigns a proper weight to each view and adds a soft boundary to balance the influence of noises and incompleteness. Second, by proposing θ-norm, the doubly soft regularized regression model adjusts the sparsity of our model by choosing different θ. Compared with previous methods, ANIMC has three unique advantages: 1) it is a soft algorithm to adjust our approach in different scenarios, thereby improving its generalization ability;2) it automatically learns a proper weight for each view, thereby reducing the influence of noises;3) it performs doubly soft regularized regression that aligns the same instances in different views, thereby decreasing the impact of missing instances. Extensive experimental results show its superior advantages over other state-of-the-art works. © 2020 IEEE.

关键词： Clustering algorithms

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Distributed Computation Offloading Based on Deep Reinforcement Learning and Blockchain in Internet of Vehicles

Distributed Computation Offloading Based on Deep Reinforceme...

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2023 IEEE/CIC International Conference on Communications in China, ICCC 2023

作者： Zhang, Guobin Luo, Zehao Yang, Tingting Dongguan University of Technology School of Electrical Engineering and Intelligentization Dongguan China Dongguan University of Technology School of Computer Science and Technology Dongguan China Pengcheng Laboratory Shenzhen China

ISBN: (纸本)9798350345384

With the rapid development of Internet of Vehicles (IoV), the traditional centralized cloud computing cannot efficiently satisfy the computation requirements of vehicles. The deployment of mobile edge server (MEC) on road side unit (RSU) can shorten the distance between vehicles and computing servers so as to reduce the service delay. In order to provide wide coverage and more computation resources, we introduce high altitude platform system (HAPS) as a central node for computation controlling in the IoV system. To improve data security and user privacy, blockchain technology is applied to verify and determine the offloading strategy between RSUs. Aiming at minimizing the sum of the transmission and computation time, an optimization problem is formulated under the power and offloading constraints. The deep reinforcement learning (DRL) with the soft actor-critic (SAC) algorithm is utilized to solve the problem. Simulation results demonstrate the time reduction by the application of HAPS and significant superiority of the proposed scheme compared to the existing approaches. © 2023 IEEE.

关键词： Reinforcement learning

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Open-World Semi-Supervised Learning for Node Classification 40

Open-World Semi-Supervised Learning for Node Classification

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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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Real-time programmable metasurface for terahertz multifunctional wave front engineering

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Light(science & Applications) 2023年第9期12卷 1795-1806页

作者： Feng Lan Luyang Wang Hongxin Zeng Shixiong Liang Tianyang Song Wenxin Liu Pinaki Mazumder Ziqiang Yang Yaxin Zhang Daniel M.Mittleman Sichuan THz Communication Technology Engineering Research Center School of Electronic Science and EngineeringUniversity of Electronic Science and Technology of ChinaChengdu 611731China Yangtze Delta Region Institute(Huzhou) University of Electronic Science and Technology of ChinaHuzhou 313000China Zhangjiang Laboratory Shanghai 201204China National Key Laboratory of Solid-State Microwave Devices and Circuits Hebei Semiconductor Research InstituteShijiazhuang 050051China Aerospace Information Research Institute Chinese Academy of SciencesBeijing 100094China University of Chinese Academy of Sciences School of ElectronicElectrical and Communication EngineeringBeijing 101408China Department of Electrical Engineering and Computer Science University of MichiganAnn ArborMI 48109USA School of Engineering Brown UniversityProvidenceRI 02912USA

Terahertz(THz)technologies have become a focus of research in recent years due to their prominent role in envisioned future communication and sensing *** of the key challenges facing the field is the need for tools to enable agile engineering of THz wave ***,we describe a reconfigurable metasurface based on GaN technology with an array-of-subarrays *** subwavelength-spaced array,under the control of a 1-bit digital coding sequence,can switch between an enormous range of possible configurations,providing facile access to nearly arbitrary wave front control for signals near 0.34 *** demonstrate wide-angle beam scanning with 1°of angular precision over 70 GHz of bandwidth,as well as the generation of multi-beam and diffuse wave fronts,with a switching speed up to 100 *** device,offering the ability to rapidly reconfigure a propagating wave front for beam-forming or diffusively scattered wide-angle coverage of a scene,will open new realms of possibilities in sensing,imaging,and networking.

关键词： wave scattered arbitrary

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Deep-Learning-Assisted Complete Targets Coverage in Energy-Harvesting IoT Networks

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IEEE Internet of Things Journal 2025年第11期12卷 17780-17790页

作者： Wang, Kunsheng Yang, Changlin Chin, Kwan-Wu Xian, Jun Sun Yat-sen University School of Mathematics Guangdong Guangzhou510275 China Sun Yat-sen University School of Software Engineering Zhuhai519082 China University of Wollongong School of Electrical Computer and Telecommunications Engineering WollongongNSW2522 Australia Minnan Normal University School of Mathematics and Statistics Zhangzhou363000 China Sun Yat-sen University Guangdong Provincial Key Laboratory of Computational Science Guangzhou510275 China

Complete targets coverage is required by many Internet of Things (IoT) applications. In this respect, an important goal is to maximize the number of time slots with complete targets coverage. Achieving such coverage is challenging when devices experience spatio-temporal energy arrivals. To this end, this article outlines a deep learning assisted approach that has an offline stage whereby it determines and stores an exhaustive collection of optimal activation schedules based the energy levels and arrivals of devices. In addition, it presents a network partitioning and training strategy, and outlines an algorithm to mend coverage holes in its online stage. We have compared the proposed approach with the optimal solution, and also a state-of-the-art heuristic algorithm. The results show that our solution achieves 94% of the optimal coverage lifetime. Moreover, the proposed approach has a 35% smaller optimality gap as compared with the said heuristic algorithm. © 2014 IEEE.

关键词： Self-supervised learning

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