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Self-aligned dual-beam superresolution laser direct writing with a polarization-engineered depletion beam

Photonics Research 2024年第6期12卷 1194-1200页

作者： GUOLIANG CHEN DEWEI MO JIAN CHEN QIWEN ZHAN School of Optical-Electrical and Computer Engineering University of Shanghai for Science and TechnologyShanghai 200093China Shanghai Key Laboratory of Modern Optical System University of Shanghai for Science and TechnologyShanghai 200093China Zhangjiang Laboratory Shanghai 201204China

A fiber-based,self-aligned dual-beam laser direct writing system with a polarization-engineered depletion beam is designed,constructed,and *** system employs a vortex fiber to generate a donut-shaped,cylindrically polarized depletion beam while simultaneously allowing the fundamental mode excitation beam to pass *** results in a co-axially self-aligned dual-beam source,enhancing stability and mitigating assembly *** size of the central dark spot of the focused cylindrical vector depletion beam can be easily adjusted using a simple polarization rotation *** a depletion wavelength of 532 nm and an excitation wavelength of800 nm,the dual-beam laser direct writing system has demonstrated a single linewidth of 63 nm and a minimum line spacing of 173 *** optimization of this system may pave the way for practical superresolution photolithography that surpasses the diffraction limit.

关键词： polarization beam depletion

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An NTT/INTT Accelerator with Ultra-High Throughput and Area Efficiency for FHE 24

An NTT/INTT Accelerator with Ultra-High Throughput and Area ...

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61st ACM/IEEE Design Automation Conference, DAC 2024

作者： Lu, Zhaojun Yu, Weizong Xu, Peng Wang, Wei Zhang, Jiliang Feng, Dengguo Hubei Key Laboratory of Distributed System Security School of Cyber Science and Engineering Hust Wuhan JinYinHu Laboratory Hubei Wuhan China School of Cyber Science and Engineering Hust Hubei Wuhan China School of Computer Science and Technology Hust Hubei Wuhan China Hnu Hunan Changsha China State Key Laboratory of Cryptology Beijing China

ISBN: (纸本)9798400706011

As a core arithmetic operation and security guarantee of Fully Homomorphic Encryption (FHE), Number Theoretic Transform (NTT) of a large degree is the primary source of computational and time overhead. In this paper, we propose a scalable and conflict-free memory mapping algorithm that breaks the memory bound and releases a large amount of on-chip resources. A flexible and no-stall hardware/software pipeline architecture is designed to boost the throughput of NTT/INTT of N = 216 to over 48,543 operations per second with area efficiency, which 4× and 10× speed up the FPGA-based (HPCA'23) and GPU-based (HPCA'23) schemes. © 2024 Copyright is held by the owner/author(s). Publication rights licensed to ACM.

关键词： Memory architecture

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Advances in Noble Metal-Decorated Metal Oxide Nanomaterials for Chemiresistive Gas Sensors:Overview

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Nano-Micro Letters 2023年第6期15卷 353-427页

作者： Li‑Yuan Zhu Lang‑Xi Ou Li‑Wen Mao Xue‑Yan Wu Yi‑Ping Liu Hong‑Liang Lu State Key Laboratory of ASIC and System Shanghai Institute of Intelligent Electronics and SystemsSchool of MicroelectronicsFudan UniversityShanghai 200433People’s Republic of China School of Opto‑Electronic Information and Computer Engineering University of Shanghai for Science and TechnologyShanghai 200093People’s Republic of China State Key Laboratory of Metal Matrix Composites School of Material Science and EngineeringShanghai Jiao Tong UniversityShanghai 200240People’s Republic of China

Highly sensitive gas sensors with remarkably low detection limits are attractive for diverse practical application fields including real-time environmental monitoring,exhaled breath diagnosis,and food freshness *** various chemiresistive sensing materials,noble metal-decorated semiconducting metal oxides(SMOs)have currently aroused extensive attention by virtue of the unique electronic and catalytic properties of noble *** review highlights the research progress on the designs and applications of different noble metal-decorated SMOs with diverse nanostructures(e.g.,nanoparticles,nanowires,nanorods,nanosheets,nanoflowers,and microspheres)for high-performance gas sensors with higher response,faster response/recovery speed,lower operating temperature,and ultra-low detection *** key topics include Pt,Pd,Au,other noble metals(e.g.,Ag,Ru,and Rh.),and bimetals-decorated SMOs containing ZnO,SnO_(2),WO_(3),other SMOs(e.g.,In_(2)O_(3),Fe_(2)O_(3),and CuO),and heterostructured *** addition to conventional devices,the innovative applications like photo-assisted room temperature gas sensors and mechanically flexible smart wearable devices are also ***,the relevant mechanisms for the sensing performance improvement caused by noble metal decoration,including the electronic sensitization effect and the chemical sensitization effect,have also been summarized in ***,major challenges and future perspectives towards noble metal-decorated SMOs-based chemiresistive gas sensors are proposed.

关键词： Noble metal Bimetal Semiconducting metal oxide Chemiresistive gas sensor Electronic sensitization Chemical sensitization

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Video2Reward: Generating Reward Function from Videos for Legged Robot Behavior Learning 27

Video2Reward: Generating Reward Function from Videos for Leg...

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27th European Conference on Artificial Intelligence, ECAI 2024

作者： Zeng, Runhao Zhou, Dingjie Liang, Qiwei Liu, Junlin Li, Hui Huang, Changxin Li, Jianqiang Hu, Xiping Sun, Fuchun Artificial Intelligence Research Institute Shenzhen MSU-BIT University China College of Mechatronics and Control Engineering Shenzhen University China College of Computer Science and Software Engineering Shenzhen University China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University China Department of Computer Science and Technology Tsinghua University China

ISBN: (纸本)9781643685489

Learning behavior in legged robots presents a significant challenge due to its inherent instability and complex constraints. Recent research has proposed the use of a large language model (LLM) to generate reward functions in reinforcement learning, thereby replacing the need for manually designed rewards by experts. However, this approach, which relies on textual descriptions to define learning objectives, fails to achieve controllable and precise behavior learning with clear directionality. In this paper, we introduce a new video2reward method, which directly generates reward functions from videos depicting the behaviors to be mimicked and learned. Specifically, we first process videos containing the target behaviors, converting the motion information of individuals in the videos into keypoint trajectories represented as coordinates through a video2text transforming module. These trajectories are then fed into an LLM to generate the reward function, which in turn is used to train the policy. To enhance the quality of the reward function, we develop a video-assisted iterative reward refinement scheme that visually assesses the learned behaviors and provides textual feedback to the LLM. This feedback guides the LLM to continually refine the reward function, ultimately facilitating more efficient behavior learning. Experimental results on tasks involving bipedal and quadrupedal robot motion control demonstrate that our method surpasses the performance of state-of-the-art LLM-based reward generation methods by over 37.6% in terms of human normalized score. More importantly, by switching video inputs, we find our method can rapidly learn diverse motion behaviors such as walking and running. © 2024 The Authors.

关键词： Robots

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Advswap: Covert Adversarial Perturbation with High Frequency Info-Swapping for Autonomous Driving Perception 27

Advswap: Covert Adversarial Perturbation with High Frequency...

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27th IEEE International Conference on Intelligent Transportation systems, ITSC 2024

作者： Huang, Yuanhao Zhang, Qinfan Xing, Jiandong Cheng, Mengyue Yu, Haiyang Ren, Yilong Xiong, Xiao School of Transportation Science and Engineering Beihang University Beijing100191 China State Key Lab of Intelligent Transportation System Beijing100191 China Zhongguancun Laboratory Beijing100094 China University of Alberta Department of Electrical and Computer Engineering Edmonton Canada

ISBN: (纸本)9798331505929

Perception module of Autonomous vehicles (AVs) are increasingly susceptible to be attacked, which exploit vulnerabilities in neural networks through adversarial inputs, thereby compromising the AI safety. Some researches focus on creating covert adversarial samples, but existing global noise techniques are detectable and difficult to deceive the human visual system. This paper introduces a novel adversarial attack method, AdvSwap, which creatively utilizes wavelet-based highfrequency information swapping to generate covert adversarial samples and fool the camera. AdvSwap employs invertible neural network for selective high-frequency information swapping, preserving both forward propagation and data integrity. The scheme effectively removes the original label data and incorporates the guidance image data, producing concealed and robust adversarial samples. Experimental evaluations and comparisons on the GTSRB and nuScenes datasets demonstrate that AdvSwap can make concealed attacks on common traffic targets. The generates adversarial samples are also difficult to perceive by humans and algorithms. Meanwhile, the method has strong attacking robustness and attacking transferability. © 2024 IEEE.

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A comprehensive survey of visible infrared person re-identification from an application perspective

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Multimedia Tools and Applications 2024年第42期83卷 90243-90270页

作者： Chang, Hua Xu, Xin Liu, Wei Lu, Lingyi Li, Weigang School of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Wuhan430065 China School of Information Science and Engineering Wuhan University of Science and Technology Wuhan China

Person re-identification (ReID) is a significant issue in computer vision, aiming to match the same pedestrian across various cameras. Recent research on this issue has successfully reached a satisfactory performance level in the daytime scenario. However, the performance of ReID in low illumination scenarios suffers a dramatic degradation due to the insufficient personal information captured by visible cameras in low or no light scenarios. To address this challenge, the adoption of novel camera technologies for more effective pedestrian data is imperative. Owing to the constraints of distance and usage scenarios in deploying depth cameras, practical infrared cameras are frequently utilized, spurring research in visible infrared person re-identification (VI-ReID). Significant progress has been made in the field of VI-ReID in recent years, but only a few reviews have categorized this problem based on methodology. This article offers a novel perspective by classifying VI-ReID according to application scenarios. Following our categorization scheme, the main advancements in deep learning for VI-ReID over the past five years have been grouped into three categories as follows: retrieval of infrared images using visible images (V→IR), retrieval of visible images using infrared images (IR→V), and joint retrieval of infrared and visible images (V→IR and IR→V). Next, this survey outlines the available datasets and evaluation metrics. After that, we categorize diverse methodologies under the proposed classification and assess their performance metrics across common datasets. Finally, we present two prospective avenues for future research in this domain, informed by the current state of advancement. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Infrared imaging

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On the Outage of Far-Reach Communications via RIS-Empowered Satellites

On the Outage of Far-Reach Communications via RIS-Empowered ...

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2024 IEEE Pacific Rim Conference on Communications, computers and Signal Processing, PACRIM 2024

作者： Wang, Fan Jiang, Ruihong Liu, Yuan Bao, Tingnan Peng, Mugen Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology Beijing100876 China Research Center for Space Computing System Zhejiang Laboratory Hangzhou311100 China School of Electrical Engineering and Computer Science University of Ottawa OttawaON Canada

ISBN: (纸本)9798350362312

The rising demand for reliable, high-bandwidth satellite communications in far-reach areas drives the integration of low earth orbit (LEO) satellites into future 6G networks. In this paper, we investigate the deployment of reconfigurable intelligent surface (RIS) technology and rate splitting multiple access (RSMA) within LEO satellite systems to improve communication quality and system capacity. We derive closed-form expressions for outage probability (OP) and reliable throughput that validate the theoretical advantages of these technologies under various signal-to-noise ratio conditions. Numerical results demonstrate that, compared with traditional space division multiple access (SDMA) and non-orthogonal multiple access (NOMA) approaches, our RSMA and RIS-integrated framework significantly can reduce OP and enhance reliable throughput with an appropriate power-splitting factor, showcasing its superiority in RIS-enabled satellite communication scenarios. © 2024 IEEE.

关键词： Satellite communication systems

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Two-Stage Robust Optimization Under Decision Dependent Uncertainty

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IEEE/CAA Journal of Automatica Sinica 2022年第7期9卷 1295-1306页

作者： Yunfan Zhang Feng Liu Yifan Su Yue Chen Zhaojian Wang João P.S.Catalão State Key Laboratory of Power System and Generation Equipment the Department of Electrical EngineeringTsinghua UniversityBeijing 100084China Department of Mechanical and Automation Engineering the Chinese University of Hong KongHong Kong SARChina Ministry of Education Key Laboratory of System Control and Information Processing the Department of AutomationShanghai Jiao Tong Universityand also with Shanghai Engineering Research Center of Intelligent Control and ManagementShanghai 200240China Faculty of Engineering of the University of Porto and Institute for Systems and Computer Engineering Technology and Science(INESC TEC)Porto 4200-465Portugal IEEE

In the conventional robust optimization(RO)context,the uncertainty is regarded as residing in a predetermined and fixed uncertainty *** many applications,however,uncertainties are affected by decisions,making the current RO framework *** paper investigates a class of two-stage RO problems that involve decision-dependent *** introduce a class of polyhedral uncertainty sets whose right-hand-side vector has a dependency on the here-and-now decisions and seek to derive the exact optimal wait-and-see decisions for the second-stage problem.A novel iterative algorithm based on the Benders dual decomposition is proposed where advanced optimality cuts and feasibility cuts are designed to incorporate the uncertainty-decision *** computational tractability,robust feasibility and optimality,and convergence performance of the proposed algorithm are guaranteed with theoretical *** motivating application examples that feature the decision-dependent uncertainties are ***,the proposed solution methodology is verified by conducting case studies on the pre-disaster highway investment problem.

关键词： Benders decomposition decision-dependent uncertainty endogenous uncertainty robust optimization(RO)

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Event-Triggered Control for Multi-Agent systems:Event Mechanisms for Information Transmission and Controller Update

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Journal of systems Science & Complexity 2022年第3期35卷 953-972页

作者： LIU Pin XIAO Feng WEI Bo State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power UniversityBeijing 102206China School of Control and Computer Engineering North China Electric Power UniversityBeijing 102206China

This paper investigates the state consensus of linear multi-agent systems in a graph where each agent is equipped with two novel event-triggering *** agent utilizes them to avoid continuous information transmissions with its neighbors and to reduce the frequencies of controller updates,*** of the event-triggering mechanisms defines a threshold of state errors by a constant plus a state-dependent *** other event-triggering mechanism introduces a period of rest time after each *** each agent,both event-triggering mechanisms are fully distributed and are independent of any global *** authors utilize a co-design approach to deal with the interplay between control gains and parameters in event-triggering *** appropriate control gains in control laws and parameters in event-triggering conditions,subsystems employing discrete-time signals from neighbors and discrete-time signals from their controllers achieve the state *** are performed to illustrate the effectiveness of the proposed event-triggering mechanisms.

关键词： Consensus control event-triggering mechanism multi-agent systems output feedback

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Adaptive and augmented active anomaly detection on dynamic network traffic streams

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Frontiers of Information Technology & Electronic engineering 2024年第3期25卷 446-460页

作者： Bin LI Yijie WANG Li CHENG National Key Laboratory of Parallel and Distributed Computing College of ComputerNational University of Defense TechnologyChangsha 410073China College of System Engineering National University of Defense TechnologyChangsha 410073China

Active anomaly detection queries labels of sampled instances and uses them to incrementally update the detection model,and has been widely adopted in detecting network ***,existing methods cannot achieve desirable performance on dynamic network traffic streams because(1)their query strategies cannot sample informative instances to make the detection model adapt to the evolving stream and(2)their model updating relies on limited query instances only and fails to leverage the enormous unlabeled instances on *** address these issues,we propose an active tree based model,adaptive and augmented active prior-knowledge forest(A3PF),for anomaly detection on network trafic streams.A prior-knowledge forest is constructed using prior knowledge of network attacks to find feature subspaces that better distinguish network anomalies from normal *** one hand,to make the model adapt to the evolving stream,a novel adaptive query strategy is designed to sample informative instances from two aspects:the changes in dynamic data distribution and the uncertainty of *** the other hand,based on the similarity of instances in the neighborhood,we devise an augmented update method to generate pseudo labels for the unlabeled neighbors of query instances,which enables usage of the enormous unlabeled instances during model *** experiments on two benchmarks,CIC-IDS2017 and UNSW-NB15,demonstrate that A3PF achieves significant improvements over previous active methods in terms of the area under the receiver operating characteristic curve(AUC-ROC)(20.9%and 21.5%)and the area under the precision-recall curve(AUC-PR)(44.6%and 64.1%).

关键词： Active anomaly detection Network traffic streams Pseudo labels Prior knowledge of network attacks

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