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A I I E Transactions 2023年第3期55卷 301-313页

作者： Jia Shu Miao Song Beilun Wang Jing Yang Shaowen Zhu a School of Management and Economics University of Electronic Science and Technology of China Chengdu China b Department of Logistics and Maritime Studies Faculty of Business The Hong Kong Polytechnic University Hong Kong China c School of Computer Science and Engineering Southeast University Nanjing China d Department of Management Science and Engineering School of Economics and Management Southeast University Nanjing China d Department of Management Science and Engineering School of Economics and Management Southeast University Nanjing Chinae Modern Logistics Center National University of Singapore (Chongqing) Research Institute Chongqing China

In this article, we study a humanitarian relief network design problem, where the demand for relief supplies in each affected area is uncertain and can be met by more than one relief facility. Given a certain cost budget, we simultaneously optimize the decisions of relief facility location, inventory pre-positioning, and relief facility to affected area assignment so as to maximize the responsiveness. The problem is formulated as a chance-constrained stochastic programming model in which a joint chance constraint is utilized to measure the responsiveness of the humanitarian relief network. We approximate the proposed model by another model with chance constraints, which can be solved based on two settings of the demand information in each affected area: (i) the demand distribution is given; and (ii) the partial demand information, e.g., the mean, the variance, and the support, is given. We use a case study of the 2014 Typhoon Rammasun to illustrate the application of the model. Computational results demonstrate the effectiveness of the solution approaches and show that the chance-constrained stochastic programming models are superior to the deterministic model for humanitarian relief network design.

关键词： Responsiveness maximization humanitarian relief network design chance-constrained stochastic programming

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B-scan-sectioned dynamic micro-optical coherence tomography for bulk-motion suppression

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Chinese Optics Letters 2022年第2期20卷 34-39页

作者： Chaoliang Chen Weisong Shi Zhiyuan Qiu Victor X.D.Yang Wanrong Gao Advanced Photonics Center School of Electronic Science&EngineeringSoutheast UniversityNanjing 210096China Department of Optical Engineering Nanjing University of Science and TechnologyNanjing 210094China Department of Electrical Computerand Biomedical EngineeringRyerson UniversityTorontoOntario M5B 2K3Canada Division of Neurosurgery Sunnybrook Health Sciences CentreTorontoOntario M4N 3M5Canada Division of Neurosurgery Faculty of MedicineUniversity of TorontoTorontoOntario M5T 1P5Canada

In this Letter, we present B-scan-sectioned dynamic micro-optical coherence tomography(BD-MOCT) for high-quality subcellular dynamic contrast imaging. Dynamic micro-optical coherence tomography(D-MOCT) is a functional optical coherence tomography(OCT) technique performed on high-resolution(micron level) OCT systems;hundreds of consecutive B-scans need to be acquired for dynamic signal extraction, which requires relatively long data acquisition time. Bulk motions occurring during data acquisition(even at the micron level) may degrade the quality of the obtained dynamic contrast images. In BD-MOCT, each full B-scan is divided into several sub-B-scans, and each sub-B-scan repeats multiple times before the sample beam moves to the next sub-B-scan. After all of the sub-B-scans for a full B-scan are completely acquired, we stitch all of the sub-B-scans into the same number of full B-scans. In this way, the time interval between two consecutive stitched B-scans could be reduced multiple times for bulk-motion suppression. The performed scanning protocol modulates the scanning sequences of fast scanning and repeat scanning for improving the dynamic contrast image quality, while the total data acquisition time remains almost the same.

关键词： optical coherence tomography high-resolution imaging dynamic imaging bulk-motion suppression

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Co2-Induced Switching between Mof-Based Bio-Mimic Slow Anion Channel and Proton Pump for Medical Exhalation Detection

SSRN

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SSRN 2024年

作者： Chen, Honghao Yue, Xiaorui Fan, Yifei Zheng, Bin Lv, Sitao Wang, Fengnan Gao, Yixun Li, Hao Lee, Yi-Kuen French, Patrick J. Umar Siddiqui, Ahmad M. Wang, Yao Zhou, Guofu Guangdong Provincial Key Laboratory of Optical Information Materials and Technology Institute of Electronic Paper Displays South China Academy of Advanced Optoelectronics South China Normal University Guangzhou510006 China National Center for International Research on Green Optoelectronics South China Normal University Guangzhou510006 China Department of Thoracic Oncology State Key Laboratory of Respiratory Diseases The First Affiliated Hospital of Guangzhou Medical University Guangzhou510006 China Department of Mechanical & Aerospace Engineering Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong Department of Electronic & Computer Engineering Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong BE Lab Faculty EWI Delft University of Technology Delft2628CD Netherlands Najran University Najran11001 Saudi Arabia

Inspired by the activation mechanism of slow anion channels (SLAC1) in plants that proton pump reversibly induces plant stomata open for CO2 adsorption, a CO2-switching H+ conduction/HCO3– diffusion dual ion channel ( PCBD ion channel) was constructed by assembling γ-cyclodextrin-MOF (γ-CD-MOF) and 3,4,9,10-perylenetetracarboxylic acid (PTCA) for CO2 chemiresistive sensing. The obtained CO2 sensor exhibited high response (Rg/R0 = 1.33, 50 ppm) and selectivity, low practical limit of detection (1 ppm) and excellent consistency (94.5%) with a commercial infrared CO2 meter at room temperature. It is indicated that hydrogen bond networks in PCBD ion channel will be enlarged with the increasing of carboxylic group’s content on perylene skeleton, thereby modulating proton conductivity at molecular level and furthermore CO2 sensing performance of the composite. The PCBD ion channel-based sensor has been utilized to distinguish the exhaled CO2 concentration between lung cancer patients and healthy individuals, illustrating its promising application prospect in non-invasive diagnose. © 2024, The Authors. All rights reserved.

关键词： Carbon dioxide

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Free-electron-driven X-ray caustics from strained van der Waals materials

Free-electron-driven X-ray caustics from strained van der Wa...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Xihang Shi Yaniv Kurman Michael Shentcis Liang Jie Wong F. Javier García de Abajo Ido Kaminer Solid State Institute and Faculty of Electrical and Computer Engineering Technion – Israel Institute of Technology Haifa Israel School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore ICFO—Institut de Ciencies Fotoniques The Barcelona Institute of Science and Technology Castelldefels Spain ICREA—Institució Catalana de Recerca i Estudis Avançats Barcelona Spain

We show that X-ray caustics and specifically X-ray Airy beams can be created from free-electron interactions with strained van der Waals materials.

ISBN: (数字)9781957171050

ISBN: (纸本)9781665466660

We show that X-ray caustics and specifically X-ray Airy beams can be created from free-electron interactions with strained van der Waals materials.

关键词： Free electron lasers X-ray lasers Lasers and electrooptics Laser beams Electrooptical waveguides

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Intelligent Reflecting Surface Enabled Sensing: Cramér-Rao Lower Bound optimization

Intelligent Reflecting Surface Enabled Sensing: Cramér-Rao ...

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IEEE Globecom Workshops

作者： Xianxin Song Jie Xu Fan Liu Tony Xiao Han Yonina C. Eldar School of Science and Engineering Future Network of Intelligence Institute and Guangdong Provincial Key Laboratory of Future Networks of Intelligence The Chinese University of Hong Kong (Shenzhen) China Department of Electrical and Electronic Engineering Southern University of Science and Technology China wireless Technology Lab 2012 Laboratories Huawei China Faculty of Mathematics and Computer Science Weizmann Institute of Science Israel

ISBN: (纸本)9781665459761

This paper investigates intelligent reflecting surface (IRS) enabled non-line-of-sight (NLoS) wireless sensing, in which an IRS is deployed to assist an access point (AP) to sense a target in its NLoS region. It is assumed that the AP is equipped with multiple antennas and the IRS is equipped with a uniform linear array. The AP aims to estimate the target’s direction-of-arrival (DoA) with respect to the IRS, based on the echo signals from the AP-IRS-target-IRS-AP link. Under this setup, we jointly design the transmit beamforming at the AP and the reflective beamforming at the IRS to minimize the CramérRao lower bound (CRLB) on estimation error. Towards this end, we first obtain the CRLB expression for estimating the DoA in closed form. Next, we optimize the joint beamforming design to minimize the CRLB, via alternating optimization, semi-definite relaxation, and successive convex approximation. Numerical results show that the proposed design based on CRLB minimization achieves improved sensing performance in terms of mean squared error, as compared to the traditional schemes with signal-to-noise ratio maximization and separate beamforming.

关键词： Wireless communication Wireless sensor networks Estimation error Direction-of-arrival estimation Array signal processing Minimization Sensors

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Intelligent Reflecting Surface Enabled Sensing: Cramér-Rao Lower Bound Optimization

arXiv

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arXiv 2022年

作者： Song, Xianxin Xu, Jie Liu, Fan Han, Tony Xiao Eldar, Yonina C. School of Science and Engineering Future Network of Intelligence Institute Guangdong Provincial Key Laboratory of Future Networks of Intelligence The Chinese University of Hong Kong Shenzhen China Department of Electrical and Electronic Engineering Southern University of Science and Technology China Wireless Technology Lab Laboratories 2012 Huawei China Faculty of Mathematics and Computer Science Weizmann Institute of Science Israel

This paper investigates intelligent reflecting surface (IRS) enabled non-line-of-sight (NLoS) wireless sensing, in which an IRS is deployed to assist an access point (AP) to sense a target in its NLoS region. It is assumed that the AP is equipped with multiple antennas and the IRS is equipped with a uniform linear array. The AP aims to estimate the target's direction-of-arrival (DoA) with respect to the IRS, based on the echo signals from the AP-IRS-target-IRS-AP link. Under this setup, we jointly design the transmit beamforming at the AP and the reflective beamforming at the IRS to minimize the Cramér-Rao lower bound (CRLB) on estimation error. Towards this end, we first obtain the CRLB expression for estimating the DoA in closed form. Next, we optimize the joint beamforming design to minimize the CRLB, via alternating optimization, semi-definite relaxation, and successive convex approximation. Numerical results show that the proposed design based on CRLB minimization achieves improved sensing performance in terms of mean squared error, as compared to the traditional schemes with signal-to-noise ratio maximization and separate beamforming. Copyright © 2022, The Authors. All rights reserved.

关键词： Beamforming

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Nanowires for UV–vis–IR Optoelectronic Synaptic Devices

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Advanced Functional Materials 2023年第1期33卷 2208807-2208807页

作者： Chen, Xue Chen, Bingkun Jiang, Bei Gao, Tengfei Shang, Gang Han, Su-Ting Kuo, Chi-Ching Roy, Vellaisamy A. L. Zhou, Ye Institute of Microscale Optoelectronics Shenzhen University Shenzhen518060 China College of Physics and Optoelectronic Engineering Harbin Engineering University Harbin150001 China Faculty of Physics and Electronic Science Hubei University Wuhan430062 China Department of Electrical and Computer Engineering University of California DavisCA95616 United States College of Electronics and Information Engineering Shenzhen University Shenzhen518060 China Institute of Organic and Polymeric Materials Research and Development Center of Smart Textile Technology National Taipei University of Technology Taipei10608 Taiwan James Watt School of Engineering University of Glasgow GlasgowG12 8QQ United Kingdom Institute for Advanced Study Shenzhen University Shenzhen518060 China

Simulating biological synaptic functionalities through artificial synaptic devices opens up an innovative way to overcome the von Neumann bottleneck at the device level. Artificial optoelectronic synapses provide a non-contact method to operate the devices and overcome the shortcomings of electrical synaptic devices. With the advantages of high photoelectric conversion efficiency, adjustable light absorption coefficient, and broad spectral range, nanowires (NWs)-based optoelectronic synapses have attracted wide attention. Herein, to better promote the applications of nanowires-based optoelectronic synapses for future neuromorphic systems, the functionalities of optoelectronic synaptic devices and the current progress of NWs optoelectronic synaptic devices in UV–vis–IR spectral range are introduced. Furthermore, a bridge between NWs-based optoelectronic synaptic device and the neuromorphic system is established. Challenges for the forthcoming development of NWs optoelectronic synapses are also discussed. This review may offer a vision into the design and neuromorphic applications of NWs-based optoelectronic synaptic devices. © 2022 Wiley-VCH GmbH.

关键词： Nanowires

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Prox-DBRO-VR: A Unified Analysis on Byzantine-Resilient Decentralized Stochastic Composite Optimization with Variance Reduction

arXiv

引用

arXiv 2023年

作者： Hu, Jinhui Chen, Guo Li, Huaqing Guo, Xiaoyu Ran, Liang Huang, Tingwen School of Automation Central South University Hunan Changsha410083 China School of Electrical Engineering and Telecommunications University of New South Wales SydneyNSW2052 Australia Department of Mechanical Engineering City University of Hong Kong Kowloon Tong Hong Kong Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Southwest University Chongqing400715 China Faculty of Computer Science and Control Engineering Shenzhen University of Advanced Technology Shenzhen518055 China

Decentralized stochastic gradient algorithms efficiently solve large-scale finite-sum optimization problems when all agents in the network are reliable. However, most of these algorithms are not resilient to adverse conditions, such as malfunctioning agents, software bugs, and cyber attacks. This paper aims to handle a class of general composite optimization problems over multi-agent systems (MASs) in the presence of an unknown number of Byzantine agents. Building on a resilient model-aggregation mechanism and the proximal-gradient mapping method, a Byzantine-resilient decentralized stochastic proximal-gradient algorithmic framework is proposed, dubbed ProxDBRO-VR, which achieves an optimization and control goal using only local computations and communications. To asymptotically reduce the noise variance arising from local gradient estimation and accelerate the convergence, we incorporate two localized variance-reduced (VR) techniques (SAGA and LSVRG) into ProxDBRO-VR to design Prox-DBRO-SAGA and Prox-DBRO-LSVRG. By analyzing the contraction relationships among the gradient-learning error, resilient consensus condition, and convergence error in a unified theoretical framework, it is proved that both Prox-DBRO-SAGA and Prox-DBRO-LSVRG, with a well-designed constant (resp., decaying) step-size, converge linearly (resp., sub-linearly) inside an error ball around the optimal solution to the original problem under standard assumptions. A trade-off between convergence accuracy and Byzantine resilience in both linear and sub-linear cases is also characterized. In numerical experiments, the effectiveness and practicability of the proposed algorithms are manifested via resolving a decentralized sparse machine-learning problem under various Byzantine attacks. Copyright © 2023, The Authors. All rights reserved.

关键词： Autonomous agents

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Focused X-ray Beams from Van der Waals Heterostructures

Focused X-ray Beams from Van der Waals Heterostructures

引用

Conference on Lasers and Electro-Optics (CLEO)

作者： Xihang Shi Yaniv Kurman Michael Shentcis Liang Jie Wong F. Javier García de Abajo Ido Kaminer Solid State Institute and Faculty of Electrical and Computer Engineering Technion – Israel Institute of Technology Haifa Israel School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore ICFO—Institut de Ciencies Fotoniques The Barcelona Institute of Science and Technology Castelldefels Spain ICFO—Institució Catalana de Recerca i Estudis Avançats Barcelona Spain

We present the concept of customized van der Waals heterostructures with periodicity tailored to generate pre-designed X-ray patterns from free electrons. As an example, we demonstrate focused X-ray beams.

ISBN: (数字)9781957171050

ISBN: (纸本)9781665466660

关键词： Free electron lasers X-ray lasers Lasers and electrooptics Laser beams Electrooptical waveguides

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Density-aware and Depth-aware Visual Representation for Zero-Shot Object Counting

Density-aware and Depth-aware Visual Representation for Zero...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Fang Nan Feng Tian Ni Zhang Nian Liu Haonan Miao Guang Dai Mengmeng Wang Faculty of Electronic and Information Engineering Xi’an Jiaotong University Xi’an China Ministry of Education Key Laboratory of Intelligent Networks and Network Security Xi’an Jiaotong University Xi’an China School of Automation Northwestern Polytechnical University Xi’an China Computer Vision Department Mohamed bin Zayed University of Artificial Intelligence Abu Dhabi UAE SGIT AI Lab State Grid Corporation of China Zhejiang University of Technology Hang Zhou China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Previous methods often utilize CLIP semantic classifiers with class names for zero-shot object counting. However, they ignore crucial density and depth knowledge for counting tasks. Thus, we propose a density-aware and depth-aware prompt counting model, which captures density information via learning density-aware prompts based on density-aware contrastive loss and incorporates depth guidance with predefined depth-aware prompts. To facilitate the training process, we design two strategies for standard counting loss and the contrastive loss, where the former prioritizes larger and sparser objects initially, gradually focusing on smaller and denser objects, and the latter adopts coarse-to-fine density learning. Besides, we construct a dataset named LVIS-372 with more real-world scenarios and balanced instance distribution compared to existing ones. Finally, the experimental results demonstrate the effectiveness of our proposed method.

关键词： Training Visualization Semantics Focusing Signal processing Acoustics Power capacitors Speech processing Standards

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