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1st International Symposium on Intelligent Computing and Networking, ISICN 2024

作者： Sun, Kangkang Xu, Hansong Zhang, Xiaojin Hua, Kun Li, Jianhua Shanghai Key Laboratory of Integrated Administration Technologies for Information Security School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China Department of Electrical Engineering California Polytechnic State University San Luis ObispoCA93407 United States

ISBN: (纸本)9783031674464

The Vehicular Digital Twin Network (VDTN) integrates digital twin (DT) models of connected and autonomous vehicles (CAVs) to facilitate smart sensing, management, and collaboration in the physical realm. VDTN synchronizes extensive data on roads, vehicles, and operators, including sensitive information like user location and driving habits. To address these privacy concerns and enhance model efficiency, we introduce a time-sensitive local differential privacy-based federated learning framework (FedTS) tailored for VDTN. This framework assigns varying privacy levels to DT models during model-sharing intervals, considering the time sensitivity of VDTNs. Comparative analysis with state-of-the-art algorithms, such as differentially-private stochastic gradient descent (DP-SGD), demonstrates significant improvements in both security and model performance. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Federated learning

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Performance Optimization for Vehicular Cooperative Sensing: A Graph Attention Based Reinforcement Learning Approach

Performance Optimization for Vehicular Cooperative Sensing: ...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Li, Xuefei Chen, Mingzhe Liu, Danpu Zhang, Zhilong Quek, Tony Q. S. Beijing Laboratory of Advanced Information Network Beijing University of Posts and Telecommunications Beijing100876 China University of Miami Department of Electrical and Computer Engineering Institute for Data Science and Computing Coral GablesFL33146 United States Information Systems Technology and Design Pillar Singapore University of Technology and Design 487372 Singapore

ISBN: (纸本)9798350351255

In this paper, the problem of collaborative vehicle sensing is investigated. In the considered model, a set of cooperative vehicles provide sensing information to sensing request vehicles with limited sensing and communication resources. A base station (BS) determines the subset of sensing request vehicles that each cooperative vehicle will serve and the sub-regions that each cooperative vehicle will detect. We formulate an optimization problem aiming to maximize the number of successfully detected sub-regions of sensing request vehicles while satisfying the cooperative sensing energy requirement by jointly determining the cooperative vehicle association and the sensing sub-region selection. To solve this problem, we propose a graph attention based reinforcement learning (RL) algorithm that can generate the graph information vectors based on the correlation between each cooperative vehicle and each sensing request vehicle. Using the learned graph information, the joint cooperative vehicle association and sensing sub-region selection strategy will be determined. Simulation results show that the proposed scheme can improve the number of successfully detected sub-regions of sensing request vehicles by up to 12.5% compared to the conventional RL algorithm without using graph attention networks (GANs). © 2024 IEEE.

关键词： Reinforcement learning

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Focused Bidirectional Search Trees: A Bidirectional Optimal Fast Matching Method for Robot Path Planning

Focused Bidirectional Search Trees: A Bidirectional Optimal ...

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2023 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2023

作者： Li, Chenming Wang, Jiankun Meng, Max Q.-H. The Chinese University of Hong Kong Department of Electronic Engineering Hong Kong Hong Kong Southern University of Science and Technology Shenzhen Key Laboratory of Robotics Perception and Intelligence Department of Electronic and Electrical Engineering Shenzhen China Southern University of Science and Technology Jiaxing Research Institute Jiaxing China University of Alberta Department of Electrical and Computer Engineering Canada

ISBN: (纸本)9798350327182

Robot path planning in high-dimensional continuous space is of great significance in robotics. The conventional bidirectional fast marching method utilizes brute-force search to explore the space, which is computationally expensive. Though improving the planning efficiency, heuristic-based bidirectional fast marching search results in a suboptimal path under a predetermined number of random samples. To address these issues, we propose Focused Bidirectional Fast Marching Trees (FBFMT*), developing a novel vertex exploring sequence to constrain the forward and backward searches within the brute-force searched regions. It enables the search trees to meet in the middle of the solution path, which guarantees the optimality under the current set of samples and searches faster than the bidirectional brute-force strategy. Extensive simulations in different scenarios validate the superiority of the proposed method, showing that FBFMT∗ can speed up the planning process and find a better solution. We also extend the proposed method to general conditions so that the forward and backward searches of FBFMT∗ can meet at any portion of the path. FBFMT∗ reveals that the heuristic-based bidirectional fast marching search strategy can be a general and efficient technique for robot path planning in high-dimensional continuous spaces. © 2023 IEEE.

关键词： Robot programming

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Persona Inconstancy in Multi-Agent LLM Collaboration: Conformity, Confabulation, and Impersonation

arXiv

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arXiv 2024年

作者： Baltaji, Razan Hemmatian, Babak Varshney, Lav R. Department of Electrical and Computer Engineering Beckman Institute for Advanced Science And Technology University of Illinois Urbana-Champaign United States

Multi-agent AI systems can be used for simulating collective decision-making in scientific and practical applications. They can also be used to introduce a diverse group discussion step in chatbot pipelines, enhancing the cultural sensitivity of the chatbot’s responses. These applications, however, are predicated on the ability of AI agents to reliably adopt assigned personas and mimic human interactions. To see whether LLM agents satisfy these requirements, we examine AI agent ensembles engaged in cross-national collaboration and debate by analyzing their private responses and chat transcripts. Our findings suggest that multi-agent discussions can support collective AI decisions that more often reflect diverse perspectives, yet this effect is tempered by the agents’ susceptibility to conformity due to perceived peer pressure and occasional challenges in maintaining consistent personas and opinions. Instructions that encourage debate in support of one’s opinions rather than collaboration increase the rate of inconstancy. Without addressing the factors we identify, the full potential of multi-agent frameworks for producing more culturally diverse AI outputs or more realistic simulations of group decision-making may remain untapped. © 2024, CC BY.

关键词： Chatbots

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Volumetric B1+ field homogenization in 7 Tesla brain MRI using metasurface scattering

arXiv

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arXiv 2024年

作者： Yoon, Gyoungsub Yu, Sunkyu Lee, Jongho Park, Namkyoo Photonic Systems Laboratory Department of Electrical and Computer Engineering Seoul National University Seoul08826 Korea Republic of Intelligent Wave Systems Laboratory Department of Electrical and Computer Engineering Seoul National University Seoul08826 Korea Republic of Laboratory for Imaging Science and Technology Department of Electrical and Computer Engineering Seoul National University Seoul Korea Republic of

Ultrahigh field magnetic resonance imaging (UHF MRI) has become an indispensable tool for human brain imaging, offering excellent diagnostic accuracy while avoiding the risks associated with invasive modalities. When the radiofrequency magnetic field of the UHF MRI encounters the multifaceted complexity of the brain—characterized by wavelength-scale, dissipative, and random heterogeneous materials—detrimental mesoscopic challenges such as B1+ field inhomogeneity and local heating arise. Here we develop the metasurface design inspired by scattering theory to achieve the volumetric field homogeneity in the UHF MRI. The method focuses on finding the scattering ansatz systematically and incorporates a pruning technique to achieve the minimum number of participating modes, which guarantees stable practical implementation. Using full-wave analysis of realistic human brain models under a 7 Tesla MRI, we demonstrate more than a twofold improvement in field homogeneity and suppressed local heating, achieving better performance than even the commercial 3 Tesla MRI. The result shows a noninvasive generalization of constant intensity waves in optics, offering a universal methodology applicable to higher Tesla MRI. © 2024, CC BY.

关键词： Magnetic resonance imaging

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Approximately Counting and Sampling Hamiltonian Motifs in Sublinear Time

arXiv

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arXiv 2025年

作者： Eden, Talya Levi, Reut Ron, Dana Rubinfeld, Ronitt Department of Computer Science Bar Ilan University Israel Efi Arazi School of Computer Science Reichman University Israel School of Electrical and Computer Engineering Tel Aviv University Israel Computer Science and Artificial Intelligence Laboratory MIT United States

Counting small subgraphs, referred to as motifs, in large graphs is a fundamental task in graph analysis, extensively studied across various contexts and computational models. In the sublinear-time regime, the relaxed problem of approximate counting has been explored within two prominent query frameworks: the standard model, which permits degree, neighbor, and pair queries, and the strictly more powerful augmented model, which additionally allows for uniform edge sampling. Currently, in the standard model, (optimal) results have been established only for approximately counting edges, stars, and cliques, all of which have a radius of one. This contrasts sharply with the state of affairs in the augmented model, where algorithmic results (some of which are optimal) are known for any input motif, leading to a disparity which we term the "scope gap" between the two models. In this work, we make significant progress in bridging this gap. Our approach draws inspiration from recent advancements in the augmented model and utilizes a framework centered on counting by uniform sampling, thus allowing us to establish new results in the standard model and simplify on previous results. In particular, our first, and main, contribution is a new algorithm in the standard model for approximately counting any Hamiltonian motif in sublinear time, where the complexity of the algorithm is the sum of two terms. One term equals the complexity of the known algorithms by Assadi, Kapralov, and Khanna (ITCS 2019) and Fichtenberger and Peng (ICALP 2020) in the (strictly stronger) augmented model and the other is an additional, necessary, additive overhead. Our second contribution is a variant of our algorithm that enables nearly uniform sampling of these motifs, a capability previously limited in the standard model to edges and cliques. Our third contribution is to introduce even simpler algorithms for stars and cliques by exploiting their radius-one property. As a result, we simplify all previo

关键词： Stars

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Noise Robustness of Data Re-Uploading Quantum Classifiers 4

Noise Robustness of Data Re-Uploading Quantum Classifiers

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4th IEEE International Conference on Quantum Computing and engineering, QCE 2023

作者： Molina, Daniel E. Hamilton, Kathleen University of Southern California Ming Hsieh Electrical and Computer Engineering Department Los AngelesCA United States Computational Science and Engineering Division Oak Ridge National Laboratory Oak RidgeTN United States

ISBN: (纸本)9798350343236

We investigate the robustness of quantum neural networks (QNNs) trained as binary classifiers against bit flip and depolarizing noise, two channels that emulate a subset of noise present in noisy intermediate-scale quantum (NISQ) devices. The presence of decoherence and other forms of noise poses significant challenges to classification accuracy. To assess the impact of noise on label extraction, and to evaluate the performance and robustness of our models, we trained three different label assignment methods in the presence of various levels of noise. Each QNN model uses 2 qubits to implement a parameterized model and either the qubits of the QNN, or a set of ancilla qubits are used for label extraction. These three different methods project the state of either a single qubit or multiple qubits onto the computational basis. This generates a probability distribution that is post-processed to assign a class label and a class probability. Each QNN is trained using noisy numerical simulation on a dataset with 2 features. Depolarizing noise channels are interleaved with the parameterized gates of the QNN and we include bit flip error prior to extracting the labels. The noise levels for the depolarizing noise and bit flip error are swept over large ranges of values. We deploy QNNs trained at various noise levels on IBM quantum computers- this introduces an additional source of noise due to SWAP gate noise. We observe that the QNNs trained with simulated noise can have good performance on NISQ hardware. © 2023 IEEE.

关键词： Depolarization

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An Exploration of a Heterogeneous Neural Configuration of SNNs 25

An Exploration of a Heterogeneous Neural Configuration of SN...

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Proceedings of the Great Lakes Symposium on VLSI 2025

作者： George Evans Karan P. Patel Catherine D. Schuman Garrett S. Rose Srutarshi Banerjee Hritom Das Department of Electrical Engineering and Computer Science The University of Tennessee Knoxville Knoxville TN USA Argonne National Laboratory Lemont IL USA Department of Electrical & Computer Engineering Oklahoma State University Stillwater OK USA

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Dynamics of self-hybridized exciton–polaritons in 2D halide perovskites

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Light(science & Applications) 2024年第1期13卷 13-22页

作者： Surendra B.Anantharaman Jason Lynch Christopher E.Stevens Christopher Munley Chentao Li Jin Hou Hao Zhang Andrew Torma Thomas Darlington Francis Coen Kevin Li Arka Majumdar PJames Schuck Aditya Mohite Hayk Harutyunyan Joshua R.Hendrickson Deep Jariwala Department of Electrical and Systems Engineering University of PennsylvaniaPhiladelphiaPA19104USA KBR Inc. BeavercreekOH45431USA Air Force Research Laboratory Sensors DirectorateWright-Patterson Air Force BaseOH45433USA Department of Physics University of WashingtonSeattleWA98195USA Department of Physics Emory UniversityAtlantaGA30322USA Department of Chemical and Biomolecular Engineering Rice UniversityHoustonTX77005USA Department of Materials Science and Nanoengineering Rice UniversityHoustonTX77005USA Applied Physics Program Smalley‐Curl InstituteRice UniversityHoustonTX77005USA Department of Mechanical Engineering Columbia UniversityNew YorkNY10027USA Department of Electrical and Computer Engineering University of WashingtonSeattleWA98195USA

Excitons,bound electron–hole pairs,in two-dimensional hybrid organic inorganic perovskites(2D HOIPs)are capable of forming hybrid light-matter states known as exciton-polaritons(E–Ps)when the excitonic medium is confined in an optical *** the case of 2D HOIPs,they can self-hybridize into E–Ps at specific thicknesses of the HOIP crystals that form a resonant optical cavity with the ***,the fundamental properties of these self-hybridized E–Ps in 2D HOIPs,including their role in ultrafast energy and/or charge transfer at interfaces,remain ***,we demonstrate that>0.5µm thick 2D HOIP crystals on Au substrates are capable of supporting multiple-orders of self-hybridized E–P *** E–Ps have high Q factors(>100)and modulate the optical dispersion for the crystal to enhance sub-gap absorption and *** varying excitation energy and ultrafast measurements,we also confirm energy transfer from higher energy E–Ps to lower energy E–***,we also demonstrate that E–Ps are capable of charge transport and transfer at *** findings provide new insights into charge and energy transfer in E–Ps opening new opportunities towards their manipulation for polaritonic devices.

关键词： charge polar excitation

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GCM-PDA: A Generative Compensation Model for Progressive Difference Attenuation in Spatiotemporal Fusion of Remote Sensing Images

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IEEE transactions on image processing : a publication of the IEEE Signal Processing Society 2025年 34卷 3817-3832页

作者： Kai Ren Weiwei Sun Xiangchao Meng Gang Yang Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo China Department of Geography and Spatial Information Techniques Ningbo University Ningbo China Ningbo Key Laboratory of Remote Sensing and Ecological Security of Coastal Zone Ningbo China Electrical Engineering and Computer Science Ningbo University Ningbo China

High-resolution satellite imagery with dense temporal series is crucial for long-term surface change monitoring. Spatiotemporal fusion seeks to reconstruct remote sensing image sequences with both high spatial and temporal resolutions by leveraging prior information from multiple satellite platforms. However, significant radiometric discrepancies and large spatial resolution variations between images acquired from different satellite sensors, coupled with the limited availability of prior data, present major challenges to accurately reconstructing missing data using existing methods. To address these challenges, this paper introduces GCM-PDA, a novel generative compensation model with progressive difference attenuation for spatiotemporal fusion of remote sensing images. The proposed model integrates multi-scale image decomposition within a progressive fusion framework, enabling the efficient extraction and integration of information across scales. Additionally, GCM-PDA employs domain adaptation techniques to mitigate radiometric inconsistencies between heterogeneous images. Notably, this study pioneers the use of style transformation in spatiotemporal fusion to achieve spatial-spectral compensation, effectively overcoming the constraints of limited prior image information. Experimental results demonstrate that GCM-PDA not only achieves competitive fusion performance but also exhibits strong robustness across diverse conditions.

关键词： Spatiotemporal phenomena MODIS Spatial resolution Remote sensing Landsat Sensors Reflectivity Image reconstruction Data mining Bayes methods

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