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Analysis of atmospheric effects on the continuous variable quantum key distribution

Chinese Physics B 2022年第11期31卷 211-218页

作者： Tao Liu Shuo Zhao Ivan B.Djordjevic Shuyu Liu Sijia Wang Tong Wu Bin Li Pingping Wang Rongxiang Zhang Department of Electronic and Communication Engineering North China Electric Power UniversityBaoding 071003China Hebei Key Laboratory of Power Internet of Things Technology North China Electric Power UniversityBaoding 071003China Baoding Key Laboratory of Optical Fiber Sensing and Optical Communication Technology North China Electric Power UniversityBaoding 071003China Department of Electrical and Computer Engineering University of Arizona1230 E Speedway BlvdTucsonArizona 85721USA College of Physics Science and Technology Hebei UniversityBaoding 071002China

Atmospheric effects have significant influence on the performance of a free-space optical continuous variable quantum key distribution(CVQKD)*** this paper,we investigate how the transmittance,excess noise and interruption probability caused by atmospheric effects affect the secret-key rate(SKR)of the *** signal wavelengths,two weather conditions,two detection schemes,and two types of attacks are considered in our *** expression aims at calculating the interruption probability is proposed based on the Kolmogorov spectrum *** results show that a signal using long working wavelength can propagate much further than that of using short ***,as the wavelength increases,the influence of interruption probability on the SKR becomes more significant,especially within a certain transmission ***,interruption probability must be considered for CVQKD by using long-signal ***,different detection schemes used by the receiver will result in different transmission distances when subjected to individual attacks and collective attacks,respectively.

关键词： atmospheric effect continuous variable key distribution free space quantum communication secret-key rate

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ERASE-Net: Efficient Segmentation Networks for Automotive Radar Signals

ERASE-Net: Efficient Segmentation Networks for Automotive Ra...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Shihong Fang Haoran Zhu Devansh Bisla Anna Choromanska Satish Ravindran Dongyin Ren Ryan Wu Department of Electrical and Computer Engineering Learning Systems Laboratory New York University NY USA NXP Semiconductors San Jose CA USA

Among various sensors for assisted and autonomous driving systems, automotive radar has been considered as a robust and low-cost solution even in adverse weather or lighting conditions. With the recent development of radar technologies and open-sourced annotated data sets, semantic segmentation with radar signals has become very promising. However, existing methods are either computationally expensive or discard significant amounts of valuable information from raw 3D radar signals by reducing them to 2D planes via averaging. In this work, we introduce ERASE-Net, an Efficient RAdar SEgmentation Network to segment the raw radar signals semantically. The core of our approach is the novel detect-then-segment method for raw radar signals. It first detects the center point of each object, then extracts a compact radar signal representation, and finally performs semantic segmentation. We show that our method can achieve superior performance on radar semantic segmentation task compared to the state-of-the-art (SOTA) technique. Furthermore, our approach requires up to 20×less computational resources. Finally, we show that the proposed ERASE-Net can be compressed by 40% without significant loss in performance, significantly more than the SOTA network, which makes it a more promising candidate for practical automotive applications.

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Simulation benchmarks of the PIC-MCC codes XPDP1 and VSim for capacitively coupled plasma helium and argon discharges

Simulation benchmarks of the PIC-MCC codes XPDP1 and VSim fo...

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IEEE International Conference on Plasma Science (ICOPS)

作者： G.-N. Wang K. Aranganadin H.-Y. Hsu J.P. Verboncoeur M.-C. Lin Department of Electrical and Biomedical Engineering Multidisciplinary Computational Laboratory Hanyang University Seoul Republic of Korea Department of electrical and computer engineering Michigan Michigan State University Michigan Michigan United States of America Department of Mechanical Engineering National Taipei University of Technology Taipei Taiwan

ISBN: (数字)9798350360912

ISBN: (纸本)9798350360929

In the field of plasma physics, the combination of the particle-in-cell (PIC) simulations with Monte Carlo collisions (MCC) has proven to be a significant tool for exploring the complexities of capacitively coupled plasma (CCP) discharges. Our prior work has showcased the effectiveness of the XPDP1 code, a PIC-MCC simulation tool, in aligning with the VSim simulation package for low-temperature helium CCP discharges. Advancing from this baseline, the current study broadens the examination to include argon discharges, presenting a detailed benchmarking of the XPDP1 code for argon gas settings. Argon CCP discharges introduce unique challenges compared to those of helium, including increased sensitivity to simulation variables like the number of particles and mesh sizes, and a more complex route to stabilization. To improve the precision of our simulations, we replaced the functional cross-sectional data in XPDP1 with the more detailed LXCat database, consistent with our method for helium discharges. This modification has led to a good agreement between the XPDP1 and the VSim simulations for both helium and argon CCP discharges. The thorough benchmarks of the XPDP1 code against VSim package not only validate both codes for different CCP discharges but serve as a foundation for extending the study of CCP discharges to higher dimensions. The findings confirm the adaptability and accuracy of XPDP1 in managing different gas environments in CCP simulations. Detailed simulation results and discussions will be presented.

关键词： Adaptation models Codes Sensitivity Simulation Benchmark testing Discharges (electric) Plasmas

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Corona Loss Calculation for Unconventional High Surge Impedance Loading Transmission Lines

Corona Loss Calculation for Unconventional High Surge Impeda...

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Annual North-American Power Symposium

作者： Mushfiqul Abedin Khan Mona Ghassemi Department of Electrical and Computer Engineering Zero Emission Realization of Optimized Energy Systems (ZEROES) Laboratory The University of Texas at Dallas Richardson TX USA

Corona effects are one of the most important factors to take into consideration when designing an overhead transmission line. Corona discharges cause power loss which should be considered during transmission line design. Unconventional high surge impedance loading (HSIL) lines have subconductors placed anywhere in space and have no bundle symmetry. They have the potential to produce greater natural power than conventional lines and conventional HSIL lines. This paper calculates corona loss in both fair and foul weather conditions for an envisaged unconventional HSIL line. It is seen that the unconventional lines under discussion undergo much greater corona loss than the conventional lines and conventional HSIL lines.

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SFDA-rPPG: Source-Free Domain Adaptive Remote Physiological Measurement with Spatio-Temporal Consistency

arXiv

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arXiv 2024年

作者： Xie, Yiping Yu, Zitong Wu, Bingjie Xie, Weicheng Shen, Linlin Computer Vision Institute School of Computer Science & Software Engineering Shenzhen Institute of Artificial Intelligence and Robotics for Society Guangdong Key Laboratory of Intelligent Information Processing Shenzhen University Shenzhen518060 China School of Computing and Information Technology Great Bay University Dongguan523000 China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen518060 China Singapore

Remote Photoplethysmography (rPPG) is a non-contact method that uses facial video to predict changes in blood volume, enabling physiological metrics measurement. Traditional rPPG models often struggle with poor generalization capacity in unseen domains. Current solutions to this problem is to improve its generalization in the target domain through Domain Generalization (DG) or Domain Adaptation (DA). However, both traditional methods require access to both source domain data and target domain data, which cannot be implemented in scenarios with limited access to source data, and another issue is the privacy of accessing source domain data. In this paper, we propose the first Source-free Domain Adaptation benchmark for rPPG measurement (SFDA-rPPG), which overcomes these limitations by enabling effective domain adaptation without access to source domain data. Our framework incorporates a Three-Branch Spatio-Temporal Consistency Network (TSTC-Net) to enhance feature consistency across domains. Furthermore, we propose a new rPPG distribution alignment loss based on the Frequency-domain Wasserstein Distance (FWD), which leverages optimal transport to align power spectrum distributions across domains effectively and further enforces the alignment of the three branches. Extensive cross-domain experiments and ablation studies demonstrate the effectiveness of our proposed method in source-free domain adaptation settings. Our findings highlight the significant contribution of the proposed FWD loss for distributional alignment, providing a valuable reference for future research and applications. The source code is available at https://***/XieYiping66/SFDA-rPPG. Copyright © 2024, The Authors. All rights reserved.

关键词： Photoplethysmography

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Integrated Precoder and Trajectory Design for MIMO UAV-Assisted Relay System With Finite-Alphabet Inputs

arXiv

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arXiv 2024年

作者： Di, Haoyang Zhu, Xiaodong Shao, Yulin School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China State Key Laboratory of Internet of Things for Smart City Department of Electrical and Computer Engineering University of Macau China Department of Electrical and Electronic Engineering Imperial College London United Kingdom

Unmanned aerial vehicles (UAVs) are gaining widespread use in wireless relay systems due to their exceptional flexibility and cost-effectiveness. This paper focuses on the integrated design of UAV trajectories and the precoders at both the transmitter and UAV in a UAV-assisted relay communication system, accounting for transmit power constraints and UAV flight limitations. Unlike previous works that primarily address multiple-input single-output (MISO) systems with Gaussian inputs, we investigate a more realistic scenario involving multipleinput multiple-output (MIMO) systems with finite-alphabet inputs. To tackle the challenging and inherently non-convex problem, we propose an efficient solution algorithm that leverages successive convex approximation and alternating optimization techniques. Simulation results validate the effectiveness of the proposed algorithm, demonstrating its capability to optimize system performance. Copyright © 2024, The Authors. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

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A volumetric change detection framework using UAV oblique photogrammetry–a case study of ultra-high-resolution monitoring of progressive building collapse

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International Journal of Digital Earth 2021年第11期14卷 1705-1720页

作者： Ningli Xu Debao Huang Shuang Song Xiao Ling Chris Strasbaugh Alper Yilmaz Halil Sezen Rongjun Qin Geospatial Data Analytics Lab The Ohio State UniversityColumbusOHUSA Photogrammetric Computer Vision Lab The Ohio State UniversityColumbusOHUSA Department of Civil Environmental and Geodetic EngineeringThe Ohio State UniversityColumbusOHUSA Department of Electrical and Computer Engineering The Ohio State UniversityColumbusOHUSA Translational Data Analytics Institute The Ohio State UniversityColumbusOHUSA Engineering Technology Services The Ohio State UniversityColumbusOHUSA

In this paper,we present a case study that performs an unmanned aerial vehicle(UAV)based fine-scale 3D change detection and monitoring of progressive collapse performance of a building during a demolition ***-temporal oblique photogrammetry images are collected with 3D point clouds generated at different stages of the *** geometric accuracy of the generated point clouds has been evaluated against both airborne and terrestrial LiDAR point clouds,achieving an average distance of 12 cm and 16 cm for roof and façade *** propose a hierarchical volumetric change detection framework that unifies multi-temporal UAV images for pose estimation(free of ground control points),reconstruction,and a coarse-to-fine 3D density change *** work has provided a solution capable of addressing change detection on full 3D time-series datasets where dramatic scene content changes are presented *** change detection results on the building demolition event have been evaluated against the manually marked ground-truth changes and have achieved an F-1 score varying from 0.78 to 0.92,with consistently high precision(0.92–0.99).Volumetric changes through the demolition progress are derived from change detection and have been shown to favorably reflect the qualitative and quantitative building demolition progression.

关键词： 3D change detection multitemporal data registration oblique photogrammetry

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rPPG-MAE: Self-supervised Pre-training with Masked Autoencoders for Remote Physiological Measurement

arXiv

引用

arXiv 2023年

作者： Liu, Xin Zhang, Yuting Yu, Zitong Lu, Hao Yue, Huanjing Yang, Jingyu School of Electrical and Information Engineering Tianjin University Tianjin300072 China Computer Vision and Pattern Recognition Laboratory School of Engineering Science Lappeenranta-Lahti University of Technology LUT Lappeenranta53850 Finland Great Bay University Dongguan523000 China Guangzhou511453 China

Remote photoplethysmography (rPPG) is an important technique for perceiving human vital signs, which has received extensive attention. For a long time, researchers have focused on supervised methods that rely on large amounts of labeled data. These methods are limited by the requirement for large amounts of data and the difficulty of acquiring ground truth physiological signals. To address these issues, several self-supervised methods based on contrastive learning have been proposed. However, they focus on the contrastive learning between samples, which neglect the inherent self-similar prior in physiological signals and seem to have a limited ability to cope with noisy. In this paper, a linear self-supervised reconstruction task was designed for extracting the inherent self-similar prior in physiological signals. Besides, a specific noise-insensitive strategy was explored for reducing the interference of motion and illumination. The proposed framework in this paper, namely rPPG-MAE, demonstrates excellent performance even on the challenging VIPL-HR dataset. We also evaluate the proposed method on two public datasets, namely PURE and UBFC-rPPG. The results show that our method not only outperforms existing self-supervised methods but also exceeds the state-of-the-art (SOTA) supervised methods. One important observation is that the quality of the dataset seems more important than the size in self-supervised pre-training of rPPG. The source code is released at https://***/linuxsino/rPPG-MAE. Copyright © 2023, The Authors. All rights reserved.

关键词： Supervised learning

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Sequential fusion estimation for multisensor systems with non-Gaussian noises

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Science China(Information Sciences) 2020年第12期63卷 153-165页

作者： Liping YAN Chenying DI Q.M.Jonathan WU Yuanqing XIA Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology Department of Electrical and Computer Engineering University of Windsor

The sequential fusion estimation for multisensor systems disturbed by non-Gaussian but heavytailed noises is studied in this paper. Based on multivariate t-distribution and the approximate t-filter,the sequential fusion algorithm is presented. The performance of the proposed algorithm is analyzed and compared with the t-filter-based centralized batch fusion and the Gaussian Kalman filter-based optimal centralized fusion. Theoretical analysis and exhaustive experimental analysis show that the proposed algorithm is effective. As the generalization of the classical Gaussian Kalman filter-based optimal sequential fusion algorithm, the presented algorithm is shown to be superior to the Gaussian Kalman filter-based optimal centralized batch fusion and the optimal sequential fusion in estimation of dynamic systems with non-Gaussian noises.

关键词： state estimation sequential fusion non-Gaussian disturbance heavy-tailed noise multivariate t-distribution

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Optical spatiotemporal vortices

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eLight 2023年第1期3卷 156-168页

作者： Chenhao Wan Andy Chong Qiwen Zhan School of Optical-Electrical and Computer Engineering University of Shanghai for Science and TechnologyShanghai 200093China School of Optical and Electronic Information and Wuhan National Laboratory for Optoelectronics Huazhong University of Science and TechnologyWuhan 430074HubeiChina Department of Physics Pusan National UniversityGeumjeong-GuBusan 46241South Korea Zhangjiang Laboratory 100 Haike RoadShanghai 201204China Shanghai Key Lab of Modern Optical System University of Shanghai for Science and TechnologyShanghai 200093China

Spatiotemporal vortices of light,featuring transverse orbital angular momentum(OAM)and energy circulation in the spatiotemporal domain,have received increasing attention *** experimental realization of the controllable generation of spatiotemporal vortices triggers a series of research in this *** review article covers the latest developments of spatiotemporal vortices of light ranging from theoretical physics,experimental generation schemes,and characterization methods,to applications and future *** new degree of freedom in photonic OAM endowed by spatiotemporal vortices paves the way to the discovery of novel physical mechanisms and photonic applications in light science.

关键词： Spatiotemporal optical vortex Orbital angular momentum Spin-orbit interaction Linear momentum density Toroidal vortex Topological charge

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