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arXiv 2024年

作者： Chen, Chuan Liao, Tianchi Deng, Xiaojun Wu, Zihou Huang, Sheng Zheng, Zibin School of Computer Science and Engineering Sun Yat-sen University Guangzhou510006 China Guangdong Key Laboratory of Big Data Analysis and Processing China School of Software Engineering Sun Yat-sen University Zhuhai519000 China Zhuhai Key Laboratory of Trusted Large Language Models China School of Systems Science and Engineering Sun Yat-sen University Guangzhou510006 China

In the field of heterogeneous federated learning (FL), the key challenge is to efficiently and collaboratively train models across multiple clients with different data distributions, model structures, task objectives, computational capabilities, and communication resources. This diversity leads to significant heterogeneity, which increases the complexity of model training. In this paper, we first outline the basic concepts of heterogeneous FL and summarize the research challenges in FL in terms of five aspects: data, model, task, device and communication. In addition, we explore how existing state-of-the-art approaches cope with the heterogeneity of FL, and categorize and review these approaches at three different levels: data-level, model-level, and architecture-level. Subsequently, the paper extensively discusses privacy-preserving strategies in heterogeneous FL environments. Finally, the paper discusses current open issues and directions for future research, aiming to promote the further development of heterogeneous FL. Copyright © 2024, The Authors. All rights reserved.

关键词： Federated learning

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Human lunar base:“Lunar Palace 1”team of Beihang University unveils China’s“Lunar Palace”plan

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The Innovation 2024年第2期5卷 3-4页

作者： Hui Liu Zhikai Yao Hong Liu Institute of Environmental Biology and Life Support Technology School of Biological Science and Medical EngineeringBeihang UniversityBeijing 100083China Internet Joint Research Center of Aerospace Biotechnology&Medical Engineering Beihang UniversityBeijing 100083China State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijing 100083China

Recently,the“Lunar Palace 1”team of Beihang University,China,in response to the long-term habitation and healthcare of humans on the Moon,released the“Lunar Palace”plan through the official account“Beihang University”on WeChat’s video *** the development of crewed deep-space exploration,human permanent residence on the Moon is no longer an unattainable dream but an anticipated *** on the Moon will live in a Lunar Palace equipped with a bioregenerative life support system(BLSS),creating an Earth-like environment,much like the Lunar Palace 1 facility on Earth.

关键词： Earth Human equipped

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Preserving Location Privacy of IoT Devices in Heterogeneous Edge Computing Architecture Through Deniability-Based Authentication

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IEEE Transactions on Consumer Electronics 2025年

作者： Ali, Ikram Li, Jianqiang Chen, Jie Chen, Yong Ullah, Shamsher Wakeel, Abdul Shenzhen University National Engineering Laboratory of Big Data System Computing Technology Shenzhen518060 China Shenzhen University College of Computer Science and Software Engineering Shenzhen518060 China University of Electronic Science and Technology of China School of Automation Engineering Chengdu611731 China National University of Sciences and Technology Military College of Signals Department of Electrical Engineering Islamabad Pakistan

Edge computing moves cloud services closer to consumer Internet of Things (IoT) devices, reducing latency and bandwidth usage. This setup enables faster responses but also introduces new security challenges, particularly concerning location privacy when sender and receiver use different security techniques. The authentication process in such architectures can expose the location of IoT devices. To address this issue, researchers have proposed various privacy-preserving schemes. However, these are computationally heavy for IoT devices. To tackle this issue, we propose two novel heterogeneous deniable authentication schemes: HDA-IoT-I and HDA-IoT-II. These schemes use public-key infrastructure and identity-based cryptography to protect the location privacy of IoT devices in heterogeneous edge computing environments. Our schemes enable the designated edge device to verify the source of a message without being able to prove its origin to a third party, thus preserving privacy. Additionally, they incorporate a batch verification method, which speeds up the verification of multiple deniable authenticators. The proposed schemes are formally proven secure in the random oracle model based on the hardness assumption of elliptic curve inverse computational Diffie-Hellman problem. The performance evaluation demonstrate that our schemes significantly enhance computational and communication efficiency, making them suitable for IoT devices. © 2025 IEEE.

关键词： Differential privacy

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Effect of the configuration and concentration of B-doping on the thermal properties and structural stability of graphene: A theoretical study

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Diamond and Related Materials 2025年 156卷

作者： Li, Dongbo Da, Liangguo Huang, Kaifeng Li, Dong Yu, Liang Wang, Haini Yu, Yaqi Wu, Long Tang, Yunqing School of Mechanical and Electrical Engineering Huainan Normal University Huainan232038 China Human-computer collaborative robot Joint Laboratory of Anhui Province Huainan232038 China School of Mechanical Engineering Shandong University Jinan250061 China State Key Laboratory of Advanced Equipment and Technology for Metal Forming Shandong University Jinan250061 China Key Laboratory of High Efficiency and Clean Mechanical Manufacture Ministry of Education Shandong University Jinan250061 China

The thermal properties and structural stability of B-doped graphene were investigated by employing density functional theory (DFT), ab initio molecular dynamics (AIMD), and molecular dynamics (MD) simulations, with a focus on the effects of doping configuration and concentration. DFT calculations indicate that B-doping reduces the cohesive energy of graphene, consequently diminishing its structural stability. Among the three B double-doping configurations, only the para configuration exhibits a phonon dispersion without imaginary frequencies, whereas both meta and ortho configurations show imaginary frequencies, indicating structural instability. The AIMD results further demonstrate that B-doped graphene preferentially undergoes cleavage at B[sbnd]B bonds, leading to decreased structural stability. MD results show that B-doping significantly reduces the thermal conductivity of graphene. At a doping concentration is 0.6 %, the thermal conductivity of meta and para configurations decreases to 48.08 % and 54.6 % of that of the pristine graphene, respectively. The results of phonon properties show that B-doping reduces the phonon participation rate and induces strong phonon localization at the B-doped site. These results and conclusions will provide valuable theoretical insights for the thermal design of graphene-based semiconductor devices. © 2025 Elsevier B.V.

关键词： Temperature distribution

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Special relativity effects on chaos and periodic orbits - a semianalytic approach

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Physical Review Research 2025年第1期7卷 013241-013241页

作者： Jun-Yin Huang Hong-Ya Xu Liang Huang Ying-Cheng Lai School of Electrical Computer and Energy Engineering Arizona State University Tempe Arizona 85287 USA Lanzhou Center for Theoretical Physics Key Laboratory of Theoretical Physics of Gansu Province Key Laboratory for Quantum Theory and Applications of MOE and School of Physical Science and Technology Lanzhou University Lanzhou Gansu 730000 China Department of Physics Arizona State University Tempe Arizona 85287 USA

In the study of nonlinear dynamics and chaos, analytically solvable physical models are rare. We investigate the classical motion of a trapped relativistic particle, subject to an electric and a magnetic field. When the directions of the electric and magnetic fields coincide, the dynamics are integrable. As the magnetic field rotates away from the direction of the electric field, a transition to chaos occurs. Based on the approach in a previous work in the nonrelativistic regime [Narimanov et al., Phys. Rev. B 57, 9807 (1998)], we introduce a particular Lorentz transformation to extend the framework to the relativistic regime, which enables us to derive the Poincaré map and obtain semianalytic formulas for periodic orbits of low periods. The transformation also makes it possible to assess, semianalytically, the role of the degree of the relativistic motion of the particle in its dynamics, revealing that the special relativity effects can enhance chaos. As numerical simulations have played a dominant role in investigating nonlinear physical systems exhibiting chaos and in many cases are the only feasible tool to probe into the system dynamics, our semianalytic approach is unique and leads to additional insights into the interplay between special relativity and chaos.

关键词： Magnetic fields

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Generalized Correspondence Matching via Flexible Hierarchical Refinement and Patch Descriptor Distillation

Generalized Correspondence Matching via Flexible Hierarchica...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Yu Han Ziwei Long Yanting Zhang Jin Wu Zhijun Fang Rui Fan School of Computer Science and Technology Donghua University Shanghai P. R. China Shanghai Research Institute for Intelligent Autonomous Systems the State Key Laboratory of Intelligent Autonomous Systems and Frontiers Science Center for Intelligent Autonomous Systems Machine Intelligence & Autonomous Systems (MIAS) Group the College of Electronics & Information Engineering Tongji University Shanghai P. R. China Department of Electronics and Computer Engineering The Hong Kong University of Science and Technology P. R. China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Correspondence matching plays a crucial role in numerous robotics applications. In comparison to conventional hand-crafted methods and recent data-driven approaches, there is significant interest in plug-and-play algorithms that make full use of pre-trained backbone networks for multi-scale feature extraction and leverage hierarchical refinement strategies to generate matched correspondences. The primary focus of this paper is to address the limitations of deep feature matching (DFM), a state-of-the-art (SoTA) plug-and-play correspondence matching approach. First, we eliminate the pre-defined threshold employed in the hierarchical refinement process of DFM by leveraging a more flexible nearest neighbor search strategy, thereby preventing the exclusion of repetitive yet valid matches during the early stages. Our second technical contribution is the integration of a patch descriptor, which extends the applicability of DFM to accommodate a wide range of backbone networks pre-trained across diverse computer vision tasks, including image classification, semantic segmentation, and stereo matching. Taking into account the practical applicability of our method in real-world robotics applications, we also propose a novel patch descriptor distillation strategy to further reduce the computational complexity of correspondence matching. Extensive experiments conducted on three public datasets demonstrate the superior performance of our proposed method. Specifically, it achieves an overall performance in terms of mean matching accuracy of 0.68, 0.92, and 0.95 with respect to the tolerances of 1, 3, and 5 pixels, respectively, on the HPatches dataset, outperforming all other SoTA algorithms. Our source code, demo video, and supplement are publicly available at ***/GCM.

关键词： Performance evaluation Accuracy Semantic segmentation Source coding Image matching Supervised learning Pose estimation

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CEC-CNN: A Consecutive Expansion-Contraction Convolutional Network for Very Small Resolution Medical Image Classification

arXiv

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arXiv 2022年

作者： Vezakis, Ioannis Vezakis, Antonios Gourtsoyianni, Sofia Koutoulidis, Vassilis Matsopoulos, George K. Koutsouris, Dimitrios Biomedical Engineering Laboratory School of Electrical and Computer Engineering National Technical University of Athens Greece Aretaieion Hospital Medical School National Kapodistrian University of Athens Greece

Deep Convolutional Neural Networks (CNNs) for image classification successively alternate convolutions and downsampling operations, such as pooling layers or strided convolutions, resulting in lower resolution features the deeper the network gets. These downsampling operations save computational resources and provide some translational invariance as well as a bigger receptive field at the next layers. However, an inherent side-effect of this is that high-level features, produced at the deep end of the network, are always captured in low resolution feature maps. The inverse is also true, as shallow layers always contain small scale features. In biomedical image analysis engineers are often tasked with classifying very small image patches which carry only a limited amount of information. By their nature, these patches may not even contain objects, with the classification depending instead on the detection of subtle underlying patterns with an unknown scale in the image’s texture. In these cases every bit of information is valuable;thus, it is important to extract the maximum number of informative features possible. Driven by these considerations, we introduce a new CNN architecture which preserves multi-scale features from deep, intermediate, and shallow layers by utilizing skip connections along with consecutive contractions and expansions of the feature maps. Using a dataset of very low resolution patches from Pancreatic Ductal Adenocarcinoma (PDAC) CT scans we demonstrate that our network can outperform current state of the art models. Copyright © 2022, The Authors. All rights reserved.

关键词： Image classification

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Energy and Reserve Scheduling Based on Security Constrained Convex Optimal Power Flow Considering Wind Power Generation in Europe

Energy and Reserve Scheduling Based on Security Constrained ...

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Sustainable Power and Energy Conference (iSPEC)

作者： Zhao Yuan Electrical Power Systems Laboratory Faculty of Electrical and Computer Engineering University of Iceland Reykjavik Iceland

ISBN: (纸本)9781665414401

Based on security constrained convex optimal power flow (SC-COPF), this paper proposes an energy and operational reserve scheduling approach for the power system. The proposed approach is capable of scheduling energy and operational reserve dynamically according to the power load forecast and the power generation from renewable energy. Reserve requirements to keep the power system in the acceptable security level is equivalently formulated as the linear constraints in the SC-COPF model. The reserve requirements are considered in a statistical way which is a common practice in the power system operations in Europe. For example, the practice in Switzerland of reserve scheduling is to ensure that the maximum probability of power insufficiency should be less than 0.2%. The objective is to minimize the economic cost of the energy production and the reserve provision. The convex optimal power flow (COPF) is used to model the AC power flows of the power network. The capacity constraints of transmission lines are considered in our SC-COPF model by equivalently constraining the power loss variables. The proposed approach is validated by using the modified European transmission network 1354pegase test case. The power load forecast and power generation from renewable energy data from Réseau de Transport d’EÉlectricite (RTE) in France are used for the validation. Numerical results show efficiency of our approach to dynamically schedule the energy and reserve.

关键词： Renewable energy sources Europe Production Wind power generation Dynamic scheduling Mathematical models Numerical models

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High-resolution mid-infrared single-photon upconversion ranging

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Photonics Research 2024年第6期12卷 1294-1302页

作者： SHUHONG JIANG KUN HUANG TINGTING YU JIANAN FANG BEN SUN YAN LIANG QIANG HAO E.WU MING YAN HEPING ZENG State Key Laboratory of Precision Spectroscopy East China Normal UniversityShanghai 200062China Chongqing Key Laboratory of Precision Optics Chongqing Institute of East China Normal UniversityChongqing 401121China Collaborative Innovation Center of Extreme Optics Shanxi UniversityTaiyuan 030006China School of Optical Electrical and Computer Engineering University of Shanghai for Science and TechnologyShanghai 200093China Shanghai Research Center for Quantum Sciences Shanghai 201315China Guangyang Bay Laboratory Chongqing Institute for Brain and IntelligenceChongqing 400064China

Single-photon laser ranging has widespread applications in remote sensing and target ***,highly sensitive light detection and ranging(lidar)has long been restricted in the visible or near-infrared *** appealing quest is to extend the operation wavelength into the mid-infrared(MIR)region,which calls for an infrared photon-counting system at high detection sensitivity and precise temporal ***,we devise and demonstrate an MIR upconversion lidar based on nonlinear asynchronous optical ***,the infrared probe is interrogated in a nonlinear crystal by a train of pump pulses at a slightly different repetition rate,which favors temporal optical scanning at a picosecond timing resolution and a kilohertz refreshing rate ***,the cross-correlation upconversion trace is temporally stretched by a factor of 2×10^(4),which can thus be recorded by a low-bandwidth silicon *** combination with the time-correlated photon-counting technique,the achieved effective resolution is about two orders of magnitude better than the timing jitter of the detector itself,which facilitates a ranging precision of 4μm under a low detected flux of 8×10^(−5) photons per *** presented MIR time-of-flight range finder is featured with single-photon sensitivity and high positioning resolution,which would be particularly useful in infrared sensing and imaging in photon-starved scenarios.

关键词： resolution lidar repetition

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Incentive Design for Eco-driving in Urban Transportation Networks

arXiv

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arXiv 2023年

作者： Niazi, M.B. Umar Cho, Jung-Hoon Dahleh, Munther A. Dong, Roy Wu, Cathy The Laboratory for Information and Decision Systems Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States The Laboratory for Information and Decision Systems Department of Civil and Environmental Engineering Massachusetts Institute of Technology CambridgeMA02139 United States The Department of Industrial and Enterprise Systems Engineering University of Illinois at Urbana-Champaign UrbanaIL61801 United States

Eco-driving emerges as a cost-effective and efficient strategy to mitigate greenhouse gas emissions in urban transportation networks. Acknowledging the persuasive influence of incentives in shaping driver behavior, this paper presents the ‘eco-planner,’ a digital platform devised to promote ecodriving practices in urban transportation. At the outset of their trips, users provide the platform with their trip details and travel time preferences, enabling the eco-planner to formulate personalized eco-driving recommendations and corresponding incentives, while adhering to its budgetary constraints. Upon trip completion, incentives are transferred to users who comply with the recommendations and effectively reduce their emissions. By comparing our proposed incentive mechanism with a baseline scheme that offers uniform incentives to all users, we demonstrate that our approach achieves superior emission reductions and increased user compliance with a smaller budget. © 2023, CC BY.

关键词： Urban transportation

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