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arXiv 2024年

作者： Ma, Jun Li, Feifei Kim, Sumin Asakereh, Reza Le, Bao-Hiep Nguyen-Vu, Dang-Khoa Pfefferle, Alexander Wei, Muxin Gao, Ruochen Lyu, Donghang Yang, Songxiao Purucker, Lennart Marinov, Zdravko Staring, Marius Lu, Haisheng Dao, Thuy Thanh Ye, Xincheng Li, Zhi Brugnara, Gianluca Vollmuth, Philipp Foltyn-Dumitru, Martha Cho, Jaeyoung Mahmutoglu, Mustafa Ahmed Bendszus, Martin Pflüger, Irada Rastogi, Aditya Ni, Dong Yang, Xin Zhou, Guang-Quan Wang, Kaini Heller, Nicholas Papanikolopoulos, Nikolaos Weight, Christopher Tong, Yubing Udupa, Jayaram K. Patrick, Cahill J. Wang, Yaqi Zhang, Yifan Contijoch, Francisco McVeigh, Elliot Ye, Xin He, Shucheng Haase, Robert Pinetz, Thomas Radbruch, Alexander Krause, Inga Kobler, Erich He, Jian Tang, Yucheng Yang, Haichun Huo, Yuankai Luo, Gongning Kushibar, Kaisar Amankulov, Jandos Toleshbayev, Dias Mukhamejan, Amangeldi Egger, Jan Pepe, Antonio Gsaxner, Christina Luijten, Gijs Fujita, Shohei Kikuchi, Tomohiro Wiestler, Benedikt Kirschke, Jan S. de la Rosa, Ezequiel Bolelli, Federico Lumetti, Luca Grana, Costantino Xie, Kunpeng Wu, Guomin Puladi, Behrus Martín-Isla, Carlos Lekadir, Karim Campello, Victor M. Shao, Wei Brisbane, Wayne Jiang, Hongxu Wei, Hao Yuan, Wu Li, Shuangle Zhou, Yuyin Wang, Bo AI Collaborative Centre University Health Network Department of Laboratory Medicine and Pathobiology University of Toronto Vector Institute Toronto Canada Peter Munk Cardiac Centre University Health Network Toronto Canada Toronto General Hospital Research Institute University Health Network Department of Computer Science University of Toronto University Health Network Vector Institute Toronto Canada University of Science Vietnam National University Ho Chi Minh City Viet Nam Institute of Computer Science University of Freiburg Freiburg Germany School of Medicine and Health Harbin Institute of Technology Harbin China Division of Image Processing Department of Radiology Leiden University Medical Center Leiden Netherlands Department of System and Control Engineering School of Engineering Institute of Science Tokyo Formerly Tokyo Institute of Technology Tokyo Japan Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology Karlsruhe Germany School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China School of Electrical Engineering and Computer Science University of Queensland Brisbane Australia School of Cyberspace Hangzhou Dianzi University Hangzhou China Division for Computational Radiology and Clinical AI The Department of Neuroradiology University Hospital Bonn Germany Division for Computational Radiology and Clinical AI The Department of Neuroradiology University Hospital Bonn Germany Department of Neuroradiology Heidelberg University Hospital Heidelberg Germany Division for Computational Radiology and Clinical AI Department of Neuroradiology University Hospital Bonn Germany School of Biomedical Engineering Shenzhen University Shenzhen China School of Biological Science and Medical Engineering Southeast University Nanjing China Department of Urology Cleveland Clinic Cleveland United States Department of Computer Science University of Minnesota Minneapolis United St

Promptable segmentation foundation models have emerged as a transformative approach to addressing the diverse needs in medical images, but most existing models require expensive computing, posing a big barrier to their adoption in clinical practice. In this work, we organized the first international competition dedicated to promptable medical image segmentation, featuring a large-scale dataset spanning nine common imaging modalities from over 20 different institutions. The top teams developed lightweight segmentation foundation models and implemented an efficient inference pipeline that substantially reduced computational requirements while maintaining state-of-the-art segmentation accuracy. Moreover, the post-challenge phase advanced the algorithms through the design of performance booster and reproducibility tasks, resulting in improved algorithms and validated reproducibility of the winning solution. Furthermore, the best-performing algorithms have been incorporated into the open-source software with a user-friendly interface to facilitate clinical adoption. The data and code are publicly available to foster the further development of medical image segmentation foundation models and pave the way for impactful real-world applications. © 2024, CC BY-NC-SA.

关键词： Open source software

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Loss-tolerant quantum key distribution with mixed signal states

引用

Physical Review A 2020年第6期102卷 062607-062607页

作者： J. Eli Bourassa Ignatius William Primaatmaja Charles Ci Wen Lim Hoi-Kwong Lo Department of Physics University of Toronto Toronto Canada Centre for Quantum Technologies National University of Singapore Singapore Department of Electrical and Computer Engineering National University of Singapore Singapore Center for Quantum Information and Quantum Control University of Toronto Toronto Canada Department of Electrical and Computer Engineering University of Toronto Toronto Canada Department of Physics University of Hong Kong Hong Kong

The security of measurement device-independent quantum key distribution (MDI QKD) relies on a thorough characterization of one's optical source output, especially any noise in the state preparation process. Here, we provide an extension of the loss-tolerant protocol [Phys. Rev. A 90, 052314 (2014)], a leading proof technique for analyzing the security of QKD, to MDI QKD protocols that employ mixed signal states. We first reframe the core of the proof technique, noting its generalization to treat d-dimensional signal encodings. Concentrating on the qubit signal state case, we find that the mixed states can be interpreted as providing Alice and Bob with a virtual shield system they can employ to reduce Eve's knowledge of the secret key. We then introduce a simple semidefinite programming method for optimizing the virtual twisting operations they can perform on the shield system to yield a higher key rate, along with an example calculation of fundamentally achievable key rates in the case of random polarization modulation error.

关键词： Optical quantum information processing Quantum cryptography

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Operational parameters affecting harmonic resonance in electrical submersible pump systems

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Canadian Journal of electrical and computer engineering 2019年第3期42卷 183-197页

作者： Liang, Xiaodong El-Kadri, Ahmad Department of Electrical and Computer Engineering University of Saskatchewan SaskatoonSKS7N 5A9 Canada Sustaining Surface Power and Control Singapore Integration Center Schlumberger Singapore

electrical submersible pump (ESP) systems in the oil field have unique features due to the long cabling effect. The electrical system for a typical ESP installation consists of a variable frequency drive (VFD), a multi-tap step-up transformer, a surface cable, a downhole main cable, a motor lead extension (MLE) cable, and an electrical submersible motor. A load filter is usually required in a VFD-ESP system. In this paper, several operational parameters that can significantly affect operating conditions of an ESP system are demonstrated through field measurements and simulation of a practical ESP system currently in operation in Alberta, Canada. The simulation model is also validated by comparing with field measurement data. This analysis is beneficial to field engineers and ESP system operators to understand better the impacts of equipment parameter settings. © 2003-2010 IEEE Canada.

关键词： Frequency response

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A SINS Error Correction Approach Based on Dual-Threshold ZV Detection and Cubature Kalman Filter

A SINS Error Correction Approach Based on Dual-Threshold ZV ...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Ruijie Xu Shichao Chen Wenqiao Sun Yisheng Lv Jialiang Luo Ying Tang The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences College of Information Science & Technology Beijing University of Chemical Technology Beijing China The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems The Center of National Railway Intelligent Transportation System Engineering and Technology Institute of Automation Chinese Academy of Sciences China Academy of Railway Sciences Corporation Limited Beijing China China Academy of Railway Sciences Corporation Limited Transportation and Economics Research Institute and the Center of National Railway Intelligent Transportation System Engineering and Technology Beijing China The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences School of Information Engineering China University of Geosciences Beijing Beijing China Department of Electrical and Computer Engineering Rowan University Glassboro USA

Global Navigation Satellite Systems (GNSS) can provide real-time positioning information for outdoor users, but cannot for indoor scenarios or heavily occluded outdoor scenarios. Strap-down Inertial Navigation System (SINS) are widely used to locate people in complex interior or heavily occluded outdoor scenarios due to its light weight and low power consumption. However, IMU of SINS are noisy, and the sampling data error is large, which is a divergence of the error with time. Therefore, it will generate a positioning accumulation error, which affects the final positioning accuracy. The problem of cumulative IMU errors is usually dealt with by Zero-Velocity Update (ZUPT). The zero-velocity detection part of basic ZUPT method usually uses a single threshold to determine the gait of pedestrian, which often has the problem of gait misjudgment and omission. To address these problems, this paper proposes a composite conditional detection method to solve the problem of misjudgment in the zero-velocity interval. In addition, we redesign the zero-velocity update algorithm and uses the Cubature Kalman filter (CKF) for pedestrian positioning error correction. The experimental results demonstrate that the proposed ZUPT method based on dual-threshold detection can better detect the interval between pedestrian motion and stationery than ones with single threshold. The zero-velocity update algorithm based on CKF has higher performance than conventional EKF and UKF methods, which constrains the cumulative error of SINS to about 0.2% of the whole walking distance.

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Structural systems theory: An overview of the last 15 years

arXiv

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arXiv 2020年

作者： Ramos, Guilherme Aguiar, A. Pedro Pequito, Sérgio Department of Electrical and Computer Engineering Faculty of Engineering University of Porto Portugal Delft Center for Systems and Control Delft University of Technology Delft2600 AA Netherlands

In this paper, we provide an overview of the research conducted in the context of structural systems since the latest survey by Dion et al. in 2003. We systematically consider all the papers that cite this survey as well as the seminal work in this field that took place on and after the publication of the later survey, are published in peer-reviewed venues and in English. Structural systems theory deals with parametric systems where parameters might be unknown and, therefore, addresses the study of systems properties that depend only on the systems structure (or topology) described by the inter-dependencies between state variables. Remarkably, structural systems properties hold generically (i.e., almost always) under the assumption that parameters are independent. Therefore, it constitutes an approach to assess necessary conditions that systems should satisfy. In recent years, structural systems theory was applied to design systems that attain such properties, as well as to endure resilient/security and privacy properties. Furthermore, structural systems theory enables the formulation of such topics as combinatorial optimization problems, which allow us to understand their computational complexity and find algorithms that are efficiently deployed in the context of large-scale systems. In particular, we present an overview of how structural systems theory has been used in the context of linear time-invariant systems, as well as other dynamical models, for which a brief description of the different problem statements and solutions approaches are presented. Next, we describe recent variants of structural systems theory, as well as different applications of the classical and new approaches. Finally, we provide an overview of recent and future directions in this field. Copyright © 2020, The Authors. All rights reserved.

关键词： Combinatorial optimization

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Policy evaluation and seeking for multi-agent reinforcement learning via best response

arXiv

引用

arXiv 2020年

作者： Yan, Rui Duan, Xiaoming Shi, Zongying Zhong, Yisheng Marden, Jason R. Bullo, Francesco Department of Automation Tsinghua University Beijing100084 China Mechanical Engineering Department Center of Control Dynamical Systems and Computation UC Santa BarbaraCA93106-5070 United States Department of Electrical and Computer Engineering UC Santa Barbara CA93106-5070 United States

This paper introduces two metrics (cycle-based and memory-based metrics), grounded on a dynamical game-theoretic solution concept called sink equilibrium, for the evaluation, ranking, and computation of policies in multi-agent learning. We adopt strict best response dynamics (SBRD) to model selfish behaviors at a meta-level for multi-agent reinforcement learning. Our approach can deal with dynamical cyclical behaviors (unlike approaches based on Nash equilibria and Elo ratings), and is more compatible with single-agent reinforcement learning than α-rank which relies on weakly better responses. We first consider settings where the difference between largest and second largest underlying metric has a known lower bound. With this knowledge we propose a class of perturbed SBRD with the following property: only policies with maximum metric are observed with nonzero probability for a broad class of stochastic games with finite memory. We then consider settings where the lower bound for the difference is unknown. For this setting, we propose a class of perturbed SBRD such that the metrics of the policies observed with nonzero probability differ from the optimal by any given tolerance. The proposed perturbed SBRD addresses the opponent-induced non-stationarity by fixing the strategies of others for the learning agent, and uses empirical game-theoretic analysis to estimate payoffs for each strategy profile obtained due to the perturbation. Copyright © 2020, The Authors. All rights reserved.

关键词： Game theory

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Content Distribution based on Joint V2I and V2V Scheduling in mmWave Vehicular Networks

arXiv

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arXiv 2022年

作者： Su, Lan Niu, Yong Han, Zhu Ai, Bo He, Ruisi Wang, Yibing Wang, Ning Su, Xiang The State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China The Frontiers Science Center for Smart High-Speed Railway System Beijing Jiaotong University Beijing100044 China The National Mobile Communications Research Laboratory Southeast University Nanjing211189 China The Department of Electrical and Computer Engineering University of Houston HoustonTX77004 United States The Department of Computer Science and Engineering Kyung Hee University Seoul446-701 Korea Republic of The State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China The School of Information Engineering Zhengzhou University Zhengzhou450001 China The Norwegian University of Science and Technology Norway and University of Oulu Finland

With the explosive growth of vehicle applications, vehicular networks based on millimeter wave (mmWave) bands have attracted interests from both academia and industry. mmWave communications are able to utilize the huge available bandwidth to provide multiple Gbps transmission rates among vehicles. In this paper, we address the content distribution scheduling problem in mmWave vehicular networks. It has been challenging for all vehicles in the same network to complete content downloading due to the limited communication resources of roadside units (RSUs) and the high mobility of vehicles. We propose a joint vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) scheduling scheme to minimize the total number of content distribution time slots from a global optimization perspective. In the V2I phase, the RSU serially transmits integrity content to vehicles, which are selected according to the vehicular network topology and transmission scheduling scheme. In the V2V phase, full-duplex communications and concurrent transmissions are exploited to achieve content sharing between vehicles and improve transmission efficiency. Performance evaluations demonstrate that our proposed scheme reduces the number of time slots and significantly improves system throughput when compared with other schemes, especially under large-size file transfers and a large number of vehicles. Copyright © 2022, The Authors. All rights reserved.

关键词： Millimeter waves

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Urban Digital Twins for Intelligent Road Inspection

Urban Digital Twins for Intelligent Road Inspection

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IEEE International Conference on Big Data

作者： Rui Fan Yikang Zhang Sicen Guo Jiahang Li Yi Feng Shuai Su Yanting Zhang Wenshuo Wang Yu Jiang Mohammud Junaid Bocus Xingyi Zhu Qijun Chen the Department of Control Science & Engineering Frontiers Science Center for Intelligent Autonomous Systems and State Key Laboratory of Intelligent Autonomous Systems Robotics & Artificial Intelligence Laboratory (RAIL) Tongji University Shanghai P. R. China Department of Computer Science & Technology Donghua University Shanghai P. R. China Department of Civil Engineering McGill University Montreal Canada CTO office at ClearMotion Billerica MA USA Department of Electrical & Electronic Engineering the University of Bristol BS8 1UB U.K Key Laboratory of Road and Traffic Engineering of Ministry of Education Tongji University Shanghai P. R. China

ISBN: (纸本)9781665480468

Urban digital twin (UDT) technologies offer new opportunities for intelligent road inspection (IRI). This paper first reviews the state-of-the-art algorithms used in the two key components of UDT-based IRI systems: (1) multi-temporal, multi-dimension, multi-score, and heterogeneous road data acquisition, and (2) road distress detection. This paper then summarizes the UDTIRI competition, organized in conjunction with IEEE Bigdata 2022. More details on our competition are available at ***/view/udtiri-workshop/bigdata-2022.

关键词： Roads Data acquisition Inspection Big Data Rough surfaces Digital twins

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Diagonal catalysts in quantum adiabatic optimization

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Physical Review A 2021年第2期103卷 022608-022608页

作者： Tameem Albash Matthew Kowalsky Department of Electrical and Computer Engineering University of New Mexico Albuquerque New Mexico 87131 USA Department of Physics and Astronomy and Center for Quantum Information and Control CQuIC University of New Mexico Albuquerque New Mexico 87131 USA Department of Physics and Astronomy University of Southern California Los Angeles California 90089 USA Center for Quantum Information Science & Technology University of Southern California Los Angeles California 90089 USA

We propose a protocol for quantum adiabatic optimization whereby an intermediary Hamiltonian that is diagonal in the computational basis is turned on and off during the interpolation. This “diagonal catalyst” serves to bias the energy landscape towards a given spin configuration, and we show how this can remove the first-order phase transition present in the standard protocol for the ferromagnetic p spin and the weak-strong cluster problems. The success of the protocol also makes clear how it can fail: biasing the energy landscape towards a state only helps in finding the ground state if the Hamming distance from the ground state and the energy of the biased state are correlated. We present examples where biasing towards low-energy states that are nonetheless very far in Hamming distance from the ground state can severely worsen the efficiency of the algorithm compared to the standard protocol. Our results for the diagonal catalyst protocol are analogous to results exhibited by adiabatic reverse annealing, so our conclusions should apply to that protocol as well.

关键词： Adiabatic quantum optimization

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Underwater acoustic intelligent spectrum sensing with multimodal data fusion: An Mul-YOLO approach

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Future Generation computer Systems 2025年 173卷

作者： Li, Yufang Zhang, Liliang Wang, Kai Xu, Lingwei Gulliver, T. Aaron Department of Information Science and Technology Qingdao University of Science and Technology Qingdao266061 China Xiangyang Sub-center of National Engineering Research Center for Water Transport Safety Hubei University of Arts and Science Xiangyang441053 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun130012 China Nanning530006 China Department of Electrical and Computer Engineering University of Victoria VictoriaBC V8W 2Y2 Canada

Realizing the Ocean Internet of Things (OIoT) requires diverse and comprehensive real-time marine data. This creates significant demands on spectrum resources for effective underwater communication. Coexisting users in the OIoT can generate massive amounts of data, which results in competition for underwater acoustic spectrum. To address the problem of poor utilization of this spectrum in complex and dynamic ocean environments, this paper proposes an intelligent spectrum sensing scheme based on multimodal data fusion. First, the system obtains time series data for the underwater acoustic signals and a wavelet transform is used to obtain the corresponding image data. The time series and image data constitute multimodal data that provide a more comprehensive time and space perspective and improve the diversity of features. Then, unsupervised learning with a Denoising Autoencoder is used to extract high-quality features from the time series data. Finally, a parallel dual Backbone YOLO network is constructed to compensate for the inability of traditional YOLO to extract multimodal features. One branch captures key temporal features through a network built with deep separable convolutions, while the other branch captures key spatial features using an improved CSPDarknet. This Mul-YOLO network can extract hierarchical structure information from underwater acoustic signals and integrate the diverse multilevel features of the data to achieve accurate spectrum sensing. Compared with Convolutional Neural Network (CNN), ResNet, Swin-Transformer, ConvNext and YOLOv5 algorithms, the average detection probability of the Mul-YOLO algorithm is increased by about 5.9% to 18.9%, and the average false alarm probability is optimized by about 7% to 12.7% in the range of signal-to-noise ratio from −12 dB to 0 dB. The results given show that the proposed algorithm can detect spectrum holes with high accuracy and effectively avoid interference between users. © 2025 Elsevier B.V.

关键词： Image fusion

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