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arXiv 2025年

作者： Golchoubian, Mahsa Ghafurian, Moojan Azad, Nasser Lashgarian Dautenhahn, Kerstin Department of Systems Design Engineering University of Waterloo Waterloo Canada Department of Electrical and Computer Engineering University of Waterloo Waterloo Canada Departments of Electrical and Computer Engineering and Systems Design Engineering University of Waterloo Waterloo Canada

It has been suggested that autonomous vehicles can improve efficiency and safety of the transportation systems. While research in this area often focuses on autonomous vehicles which operate on roads, the deployment of low-speed, autonomous vehicles in unstructured, crowded environments has been studied less well and requires specific considerations regarding their interaction with pedestrians. For making the operation of these vehicles acceptable, their behaviour needs to be perceived as safe by both pedestrians and the passengers riding the vehicle. In this paper we conducted an online survey with 116 participants, to understand people’s preferences with respect to an autonomous golf cart’s behaviour in different interaction scenarios. We measured people’s self-reported perceived safety towards different behaviour of the cart in a variety of scenarios. Results suggested that despite the unstructured nature of the environment, the cart was expected to follow common traffic rules when interacting with a group of pedestrians. Copyright © 2025, The Authors. All rights reserved.

关键词： Vehicle safety

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Design and Development of a Fixed-Wing Tail-Sitter Tethered VTOL Drone with Custom Autopilot and Robust Control Techniques 16th

Design and Development of a Fixed-Wing Tail-Sitter Tether...

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16th APCA International Conference on Automatic Control and Soft Computing, CONTROLO 2024

作者： Safaee, Ahmad Aguiar, A. Pedro Santos, Filipe Neves Moreira, Antonio Paulo SYSTEC-ARISE Research Center for Systems and Technologies Faculty of Engineering University of Porto Porto4200-465 Portugal INESC-TEC-Institute for Systems and Computer Engineering Technology and Science CRIIS-Centre for Robotics in Industry and Intelligent Systems Porto4200-465 Portugal INESC-TEC-Institute for Systems and Computer Engineering and DEEC/FEUP - Department of Electrical and Computer Engineering Faculty of Engineering of the University of Porto Porto4200-465 Portugal

ISBN: (纸本)9783031817236

The need for aerial platforms capable of sustained operation is critical in fields such as surveillance, agricultural monitoring, disaster response, and temporary telecommunication systems. Traditional unmanned aerial vehicles (UAVs) are hampered by limited battery capacity and inefficient energy utilization. This paper introduces an autonomous vertical flight drone tethered to a ground-based platform, which overcomes these limitations. The drone is designed to optimize its position and energy usage by harnessing wind currents, functioning similarly to a kite when conditions permit. This is enabled by a custom-designed autopilot system comprising both hardware and software tailored for this application. We detail the model identification process for three vertical take-off and landing (VTOL) drone systems, employing authentic data that measures lateral positional errors from the tether. Robust mixed sensitivity controllers are developed and implemented. The effectiveness of these controllers is validated through simulations showing their capability to handle uncertainties. Furthermore, the practical application and robust performance of the system are confirmed by a real-world case study, highlighting its potential in real operational environments. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： VTOL/STOL aircraft

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Time-varying Mie resonators for real-time manipulation of quantum emitter radiation

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Physical Review B 2025年第12期111卷 125419-125419页

作者： Mohammad Mojtaba Sadafi Achiles Fontana da Mota Hossein Mosallaei Metamaterials Laboratory Electrical and Computer Engineering Department Northeastern University Boston Massachusetts 02115 USA Department of Electrical Engineering University of Brasilia Brasilia DF 70910-900 Brazil

Quantum emitters are fundamental to advancing technologies such as secure quantum communication, high-resolution imaging, and quantum computing by enabling on-demand single-photon generation. Precise control over the spectral and radiation characteristics of quantum emitters is crucial for optimizing quantum devices and integrated photonic systems. Nevertheless, traditional designs based on passive materials impose fixed functionality postfabrication, limiting the ability to tune spontaneous emission dynamically. This study introduces time-varying Mie resonators as a dynamic means to achieve real-time control over the spontaneous emission of a quantum source. A theoretical framework combining the time-Floquet method with multipole expansion is developed to model light-matter interactions in time-modulated environments. Our findings reveal that time modulation enables precise control over multipolar resonant modes, compensating for frequency detuning in the quantum emitter's radiation through an optimal feedback strategy. Moreover, we demonstrate that time modulation can facilitate directional control of far-field emission by selectively exciting specific multipoles and manipulating their mutual coupling. We further show that transverse Kerker conditions enhance radiation directionality and that time modulation can convert nonradiating anapole states into radiating modes via symmetry breaking. Our findings provide a comprehensive framework for real-time manipulation of quantum emitter radiation and open up possibilities for unique applications in integrated quantum physics.

关键词： Quantum computers

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Massive GaN micro-LED array based underwater wireless optical communication

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Optics Express 2025年第9期33卷 19527-19534页

作者： Lv, Zhijian Liu, Xinyi Wu, Shuang Zhang, Wenwei Yue, C. Patrick Liu, Zhaojun Sino-German College of Intelligent Manufacturing Shenzhen Technology University Shenzhen China Department of Electrical and Electronic Engineering Southern University of Science and Technology Shenzhen China State Key Laboratory of Advanced Displays and Optoelectronics Technologies The Integrated Circuit Design Center Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong

High-speed underwater wireless optical communication technology is a much-needed communication technology in current underwater applications, and micro-LED is a promising light source option. Considering the limitation of transmission distance due to the low optical power of a single micro-LED pixel, an underwater wireless optical communication system based on a novel massive GaN micro-LED array includes more than 5000 pixels fabricated via flip-chip technology is proposed, which can achieve 165-Mbps and 90-Mbps at 37.7 m and 73.5 m, respectively. Therefore, the feasibility of realizing a high data rate and long transmission distance in an underwater wireless optical communication system based on a novel massive micro-LED array is confirmed. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Fiber to the x

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Intelligent Reflecting Surface-Assisted Adaptive Beamforming for Blind Interference Suppression

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IEEE Transactions on Signal Processing 2025年 73卷 1744-1758页

作者： Wang, Peilan Fang, Jun Wang, Bin Li, Hongbin University of Electronic Science and Technology of China National Key Laboratory of Wireless Communications Chengdu611731 China Guangdong Dejiu New Energy Company Ltd Foshan528200 China Stevens Institute of Technology Department of Electrical and Computer Engineering HobokenNJ07030 United States

In this paper, we consider the problem of adaptive beamforming (ABF) for intelligent reflecting surface (IRS)-assisted systems, where a single antenna receiver, aided by a close-by IRS, tries to decode signals from a legitimate transmitter in the presence of multiple unknown interference signals. Such a problem is formulated as an ABF problem with the objective of minimizing the average received signal power subject to certain constraints. Unlike canonical ABF in array signal processing, we do not have direct access to the covariance matrix that is needed for solving the ABF problem. Instead, for our problem, we only have some quadratic compressive measurements of the covariance matrix. To address this challenge, we propose a sample-efficient method that directly solves the ABF problem without explicitly inferring the covariance matrix. Compared with the methods which explicitly recover the covariance matrix from its quadratic compressive measurements, our proposed method achieves a substantial improvement in terms of sample efficiency. Simulation results show that our method, using a small number of measurements, can effectively nullify the interference signals and enhance the signal-to-interference-plus-noise ratio (SINR). © 1991-2012 IEEE.

关键词： Signal to noise ratio

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Accurate, Secure, and Efficient Semi-Constrained Navigation Over Encrypted City Maps

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IEEE Transactions on Dependable and Secure Computing 2025年第3期22卷 2642-2658页

作者： Li, Meng Chen, Yifei Gao, Jianbo Wu, Jingyu Zhang, Zijian He, Jialing Zhu, Liehuang Conti, Mauro Lin, Xiaodong Hefei University of Technology Key Laboratory of Knowledge Engineering with Big Data Ministry of Education Hefei230002 China Hefei University of Technology School of Computer Science and Information Engineering Hefei230002 China Hefei University of Technology Anhui Province Key Laboratory of Industry Safety and Emergency Technology Intelligent Interconnected Systems Laboratory of Anhui Province Hefei230002 China Beijing Institute of Technology School of Cyberspace Science and Technology Beijing100811 China University of Science and Technology of China School of Computer Science and Technology Hefei230026 China Beijing Institute of Technology Southeast Institute of Information Technology Fujian Putian351100 China Chongqing University College of Computer Science Chongqing400044 China University of Padua Department of Mathematics HIT Center Padua35131 Italy Delft University of Technology Faculty of Electrical Engineering Mathematics and Computer Science Delft2628 CD Netherlands University of Guelph School of Computer Science GuelphONN1G 2W1 Canada

Navigation services enable users to find the shortest path from a starting point S to a destination D, reducing time, gas, and traffic congestion. Still, navigation users risk the exposure of their sensitive location data. Our motivation arises from how users can accurately, securely, and efficiently navigate from S to Dwhile passing through k unordered stops, i.e., midway locations with a non-fixed visiting order. In this work, we formally define Semi-Constrained Navigation (SCN) and present a novel scheme Hermestoachieveaccurate,secure, andefficient SCN. Specifically, weproposeadivide-and-conquerapproachtostrikeagoodbalance betweenaccuracyandefficiency. It recursively depth-first-searches the whole area (a navigation tree) and invokes five carefully-crafted strategies stop-by-stop to compute three subpaths in three se quential subareas. We construct a path-distance oracle to encrypt the road graph and securely implement the strategies by using homomorphic encryption and garble circuits. We formally prove the security in the random oracle model and analyze the search complexity to be less than O(k2). We experiment over a real-world city map and compare with six baselines. Results show that path search with k = 4 among N = 1000 intersections requires 5.58 seconds with a 3.2% distance deviation rate and an 82.5% path similarity. © 2004-2012 IEEE.

关键词： Traffic congestion

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Location Privacy Preservation Crowdsensing With Federated Reinforcement Learning

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IEEE Transactions on Dependable and Secure Computing 2025年第3期22卷 1877-1894页

作者： You, Zhichao Dong, Xuewen Liu, Ximeng Gao, Sheng Wang, Yongzhi Shen, Yulong Xidian University School of Computer Science and Technology The Engineering Research Center of Blockchain Technology Application and Evaluation Ministry of Education Xi'an710071 China Shaanxi Key Laboratory of Blockchain and Secure Computing Xi'an710071 China Fuzhou University College of Computer and Data Science Fuzhou350025 China Central University of Finance and Economics School of Information Beijing102206 China California State Polytechnic University Pomona Department of Computer Information Systems PomonaCA91768 United States Xidian University School of Computer Science and Technology Xi'an710071 China Shaanxi Key Laboratory of Network and System Security Xi'an710071 China

Crowdsensing has become a popular method of sensing data collection while facing the problem of protecting participants' location privacy. Existing location-privacy crowdsensing mechanisms focus on static tasks and participants without considering sensing tasks' time requirements and participants' mobility, which cannot achieve satisfactory collected data quality and task completion in crowdsensing with dynamic tasks and participants. Inspired by this, we proposed a location-preservation crowdsensing mechanism, FedSense, considering dynamic tasks and participants based on federated learning (FL) and reinforcement learning (RL). In FedSense, through RL's outstanding decision-making ability, participants select sensing tasks to perform by well-trained RL models without uploading location information to servers for task allocation. We propose an independent tasks selection environment that defines actions, states, and rewards of RL to enable FedSense to achieve satisfactory task completion and data quality while preserving location privacy. Besides, FedSense applies an asynchronous FL aggregation algorithm that reduces participants' network stabilization and device computing ability requirements. Analysis proves that participants' location information does not leave the local device during the model training and task selection process, effectively avoiding privacy leakage. Simulation shows that compared with existing location-preservation crowdsensing mechanisms, FedSense achieves the highest task completion and sensing accuracy for dynamic tasks and participants. © 2024 IEEE.

关键词： Data privacy

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Private Computation of Boolean Functions Using Single Qubits 15th

Private Computation of Boolean Functions Using Single Qubit...

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15th International Conference on Parallel Processing and Applied Mathematics, PPAM 2024

作者： Rahmani, Zeinab Pinto, Armando N. Barbosa, Luis S. Department of Electronics Telecommunications and Informatics University of Aveiro Aveiro Portugal Instituto de Telecomunicações Aveiro Portugal International Iberian Nanotechnology Laboratory Braga Portugal Department of Computer Science University of Minho Braga Portugal Institute of Systems and Computer Engineering Technology and Science Braga Portugal

ISBN: (纸本)9783031856990

Secure Multiparty Computation (SMC) facilitates secure collaboration among multiple parties while safeguarding the privacy of their confidential data. This paper introduces a two-party quantum SMC protocol designed for evaluating binary Boolean functions using single qubits. Complexity analyses demonstrate a reduction of 66.7% in required quantum resources, achieved by utilizing single qubits instead of multi-particle entangled states. However, the quantum communication cost has increased by 40% due to the amplified exchange of qubits among participants. Furthermore, we bolster security by performing additional quantum operations along the y-axis of the Bloch sphere, effectively hiding the output from potential adversaries. We design the corresponding quantum circuit and implement the proposed protocol on the IBM Qiskit platform, yielding reliable outcomes. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Qubits

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Exploiting the Potential of Self-Supervised Monocular Depth Estimation via Patch-Based Self-Distillation

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IEEE Internet of Things Journal 2025年第11期12卷 18042-18055页

作者： Yu, Ting Pan, Shan Chen, Wei Tian, Zijian Wang, Zehua Yu, F. Richard Leung, Victor C. M. Postdoctoral Research Station China RongTong Academy of Sciences Group Corporation Limited Beijing100022 China China RongTong Artificial Intelligence Research Center Beijing100022 China China University of Mining and Technology School of Artificial Intelligence Beijing100083 China China University of Mining and Technology School of Computer Science and Technology Xuzhou221116 China School of Artificial Intelligence Beijing100083 China The University of British Columbia Department of Electrical and Computer Engineering VancouverBCV6T 1Z4 Canada Carleton University Department of Systems and Computer Engineering OttawaONK1S 5B6 Canada Shenzhen University College of Computer Science and Software Engineering Shenzhen518060 China

Perceiving scene depth and 3D structure is one of the key tasks for Internet of Video Things (IoVT) devices to understand and interact with the environment. Self-supervised monocular depth estimation has demonstrated significant potential in leveraging large-scale unlabeled datasets to achieve competitive performance, thereby playing an increasingly important role in depth estimation. Despite recent methods providing additional supervisory signals through self-distillation strategies to improve depth estimation, an effective method for generating pseudo-depth labels suitable for addressing occlusion issues among elements far from the camera remains unexplored. To address this limitation, we propose a Patch-based Self-Distillation Learning Framework to exploit the potential of self-supervised monocular depth estimation in recovering fine-grained scene depth. In the proposed framework, elements far from the camera within the input image are enlarged by enlarging and cropping operations in the patch-based self-distillation branch. Guided by photometric consistency, the model learns the detailed occlusion relationships among elements from the enlarged patches, producing patch depth maps with fine structures. In the main branch, which takes full-scale images as input, patch depth maps serve as pseudo-depth labels through self-distillation loss to provide additional supervisory signals for regions where photometric consistency fails to offer effective supervision. This forces the depth estimation network to recover fine structures of elements far from the camera in full-scale input images. Regarding the architecture of the depth estimation network, we introduce a bin-center prediction. In this prediction, a global aggregator based on self-attention provides additional scene structure queries for adaptive scene depth discretization. Finally, to encourage the model to explore more general cues for depth inference beyond road plane cues, we propose a PatchMix data augmentati

关键词： Image enhancement

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Quantum Assisted Combinatorial Benders' Algorithm for the Synergy of Hydrogen and Power Distribution systems with Mobile Storage

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IEEE Transactions on Power systems 2025年

作者： Li, Mingze Wang, Siyuan Fan, Lei Han, Zhu University of Houston Department of Electrical and Computer Engineering The Department of Engineering Technology HoustonTX77204 United States Argonne National Laboratory Energy Systems and Infrastructure Analysis Division LemontIL60439 United States University of Houston Department of Engineering Technology The Department of Electrical and Computer Engineering HoustonTX77204 United States The University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States

The growth of hydrogen infrastructure is expected to aid in the integration of fluctuating renewable energy in distribution systems. To leverage the hydrogen system flexibility, this work presents a mixed-binary quadratic program (MBQP) model for synergistic operations of hydrogen and power distribution systems, wherein truck-mounted mobile hydrogen storage facilities are modeled for the schedule of their routes and loading/unloading quantities. A quantum-assisted combinatorial Benders' decomposition algorithm is designed for our MBQP model to deploy the solving of master and sub-problems on a quantum processing unit (QPU) and a classical CPU, respectively. The master problem is reformulated as a quadratic unconstrained binary optimization (QUBO) problem, which can be efficiently solved by quantum annealers. The proposed approach was tested on a hybrid quantum annealing and classical computing platform. Results show a trend to outperform the CPU-based commercial solvers as the problem scale increases. © 1969-2012 IEEE.

关键词： Quantum computers

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