检索结果-内蒙古大学图书馆

Traffic Density Estimation by Distributed Proxy Model Learning for Internet-of-Vehicle

IEEE Internet of Things Journal 2025年

作者： Li, Qilei Cheng, Jing-An Gao, Mingliang Chen, Jinyong Jeon, Gwanggil Shandong University of Technology School of Electrical and Electronic Engineering Zibo255000 China Queen Mary University of London School of Electronic Engineering and Computer Science LondonE1 4NS United Kingdom Incheon National University Department of Embedded Systems Engineering Incheon22012 Korea Republic of

Autonomous driving has been significantly advanced in todays society, which revolutionized daily routines and facilitated the development of the Internet of Vehicles (IoV). A crucial aspect of this system is understanding traffic density to enable intelligent traffic management. With the rapid improvement in deep neural networks (DNNs), the accuracy of density estimation has markedly improved. However, there are two main issues that remain unsolved. Firstly, current DNN-based models are excessively heavy, characterized by an overwhelming number of training parameters (millions or even billions) and substantial computational complexity, indicated by a high number of FLOPs. These requirements for storage and computation severely limit the practical application of these models, especially on edge devices with limited capacity and computational power. Secondly, despite the superior performance of DNN models, their effectiveness largely depends on the availability of large-scale data for training. Growing privacy concerns have made individuals increasingly hesitant to allow their data to be publicly used for model training, particularly in vehicle-related applications that might reveal personal movements, which leads to data isolation issues. In this paper, we address these two problems at once with a systematic framework. Specifically, we introduce the Proxy Model Distributed Learning (PMDL) model for traffic density estimation. PMDL model is composed of two main components. First, we introduce a proxy model learning strategy that transfers fine-grained knowledge from a larger master model to a lightweight proxy model, i.e., a proxy model. Second, we design a distributed learning strategy that trains multiple proxy models with privacy-aware local data and seamlessly aggregates these models via a global parameter server. This ensures privacy protection while significantly improving estimation performance compared to training models with limited, isolated data. We tested

关键词： Differential privacy

来源：评论

学校读者我要写书评

暂无评论

Enabling All-to-Circular Polarization Up-Conversion by Nonlinear Chiral Metasurfaces with Rotational Symmetry

引用

Physical Review Letters 2025年第2期134卷 023804-023804页

作者： Dmitrii Gromyko Jun Siang Loh Jiangang Feng Cheng-Wei Qiu Lin Wu Science Mathematics and Technology (SMT) Singapore University of Technology and Design (SUTD) 8 Somapah Road 487372 Singapore Singapore Department of Electrical and Computer Engineering National University of Singapore 4 Engineering Drive 3 117583 Singapore Singapore Institute of High Performance Computing ASTAR (Agency for Science Technology and Research) 1 Fusionopolis Way No. 16-16 Connexis 138632 Singapore Singapore

We introduce a stacking strategy to design nonlinear chiral metasurfaces with high rotational symmetry, enabling degenerate quasi-bound-in-the-continuum resonances of absolute chirality. This symmetry allows for converting a circularly polarized pump into a circularly polarized nonlinear signal. Consequently, our rotation-symmetric bilayered metasurface design, tailored to respond solely to one specific circular polarization, can up-convert a linear or arbitrary polarized pump into circularly polarized nonlinear signals. The intensity ratios of these signals scale as the fourth (second) power of the chiral resonance amplitude for the second (third) harmonic.

关键词： Circular polarization

来源：评论

学校读者我要写书评

暂无评论

Resource and Trajectory Optimization for Secure Enhancement in IRS-Assisted UAV-MEC Systems

引用

IEEE Transactions on Vehicular Technology 2025年

作者： Zhang, Fuyuqi Ding, Yu Cao, Mingfeng Wu, Mengru Lu, Weidang Nallanathan, Arumugam Zhejiang University of Technology College of Information Engineering Hangzhou310023 China Queen Mary University of London School of Electronic Engineering and Computer Science LondonE1 4NS United Kingdom Kyung Hee University Department of Electronic Engineering Gyeonggido Yongin-si17104 Korea Republic of

Intelligent reflecting surface (IRS)-assisted unmanned aerial vehicle-mobile edge computing (UAV-MEC) systems have brought great advancements in future networks. However, due to the line-of-sight transmission, confidential task information is highly susceptible to interception by malicious UAV eavesdroppers, posing a significant security challenge. To overcome this challenge, we aim to design a joint resource and trajectory optimization scheme to enhance the secure performance of the IRS-assisted UAV-MEC system. Specifically, the minimum secrecy capacity of users is maximized by optimizing time allocation, transmit power, local computation CPU frequency, IRS phase shifts, and UAV trajectory while satisfying users' task processing capacity requirements. To address the non-convex optimization problem, we first employ mathematical techniques to simplify it into a more tractable form, and subsequently decompose it into several sub-problems. These sub-problems can be solved iteratively through combining phase alignment with successive convex approximation. Simulation results verify that our proposed scheme can improve the secrecy capacity performance of the considered IRS-assisted UAV-MEC system compared with benchmarks. © 1967-2012 IEEE.

关键词： Convex optimization

来源：评论

学校读者我要写书评

暂无评论

TrustChain: A Blockchain Framework for Auditing and Verifying Aggregators in Decentralized Federated Learning

arXiv

引用

arXiv 2025年

作者： Hallaji, Ehsan Razavi-Far, Roozbeh Saif, Mehrdad Department of Electrical and Computer Engineering University of Windsor WindsorONN9B 3P4 Canada Faculty of Computer Science University of New Brunswick FrederictonNBE3B 5A3 Canada

The server-less nature of Decentralized Federated Learning (DFL) requires allocating the aggregation role to specific participants in each federated round. Current DFL architectures ensure the trustworthiness of the aggregator node upon selection. However, most of these studies overlook the possibility that the aggregating node may turn rogue and act maliciously after being nominated. To address this problem, this paper proposes a DFL structure, called TrustChain, that scores the aggregators before selection based on their past behavior and additionally audits them after the aggregation. To do this, the statistical independence between the client updates and the aggregated model is continuously monitored using the Hilbert-Schmidt Independence Criterion (HSIC). The proposed method relies on several principles, including blockchain, anomaly detection, and concept drift analysis. The designed structure is evaluated on several federated datasets and attack scenarios with different numbers of Byzantine nodes. © 2025, CC BY-NC-ND.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Secure and Private Over-The-Air Federated Learning: Biased and Unbiased Aggregation Design

引用

IEEE Transactions on Wireless Communications 2025年

作者： Yan, Na Wang, Kezhi Zhi, Kangda Pan, Cunhua Chai, Kok Keong Vincent Poor, H. King's College London Department of Engineering LondonE1 4NS United Kingdom Department of Computer Science Brunel University London Uxbridge MiddlesexUB8 3PH United Kingdom National Mobile Communications Research Laboratory Southeast University Nanjing210096 China Department of Electrical and Computer Engineering Princeton University PrincetonNJ08544 United States

Over-The-Air federated learning (OTA-FL) presents a promising paradigm that improves the efficiency of local update aggregation by leveraging the superposition property of wireless multiple access channels (MACs). However, it faces significant security and privacy concerns that demand careful consideration. To address these threats associated with OTA-FL, we develop a secure and private over-The-Air federated learning (SP-OTA-FL) framework, which can realize the secure and private aggregation for both OTA-FL with unbiased aggregation (UB-OTA-FL) and OTA-FL with biased aggregation (B-OTA-FL). In this framework, a subset of devices participate in training, while another subset functions as jammers, emitting jamming signals to enhance the security and privacy of the OTA-FL process. In particular, we measure the privacy leakage of users' data using differential privacy (DP) and introduce an innovative application of mean squared error security (MSE-security) to evaluate the security of the OTA-FL system. We conduct convergence analyses for both convex and non-convex loss functions. Building on these analytical results, we separately formulate optimization problems for UB-OTA-FL and B-OTA-FL to enhance the learning performance of SP-OTA-FL by strategically optimizing the scheduling of training participants and jammers. The effectiveness of the proposed schemes is verified through simulations. © 2002-2012 IEEE.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Adaptive Printing of Conductive Microfibers for Seamless Functional Enhancement Across Diverse Surfaces and Shapes

引用

Advanced Fiber Materials 2025年 1-16页

作者： Ka, Stanley Gong Sheng Wang, Wenyu Giddens, Henry Chen, Zhuo Khan, Ahsan Noor Shui, Yuan Andy, Andre Sarker Lyu, Shuyu Hasan, Tawfique Hao, Yang Huang, Yan Yan Shery Department of Engineering University of Cambridge Trumpington Street CambridgeCB2 1PZ United Kingdom The Nanoscience Centre University of Cambridge 11 JJ Thomson Avenue CambridgeCB3 0FF United Kingdom Cambridge Graphene Centre University of Cambridge 9 JJ Thomson Ave. CambridgeCB3 0FA United Kingdom Guangzhou China School of Electronic Engineering and Computer Science Queen Mary University of London 10 Godward Square LondonE1 4FZ United Kingdom

Developing methods to non-destructively deposit conductive materials onto existing objects can enhance their functionalities on-demand. However, designing and creating such structures to accommodate diverse shapes and surface textures of pre-fabricated objects remains challenging. We report an on-demand printing strategy for creating substrate-less, conducting microfiber patterns that can be adaptively deposited onto a wide range of objects, including daily-use stationery, tools, smartwatches, and unconventional materials like porous graphene aerogels. Solution-drawn microfibers are directly deposited onto the object in a semi-wet state upon synthesis, enabling seamless fiber-object integration in a single step. The design and format of the microfiber patterns can be tuned on-demand to adapt to the shapes and surface textures of target objects, ensuring compatibility with user-specific applications. These air-permissive, highly transparent layers minimally obstruct the original appearance and functions of the objects while equipping them with additional sensing, energy conversion, and electronic connectivity capabilities. © The Author(s) 2025.

关键词： Microfibers

来源：评论

学校读者我要写书评

暂无评论

Advantages of two quantum programming platforms in quantum computing and quantum chemistry

引用

Journal of cheminformatics 2025年第1期17卷 77页

作者： Pei-Hua Wang Wei-Yeh Wu Che-Yu Lee Jia-Cheng Hong Yufeng Jane Tseng Undergraduate Program in Intelligent Computing and Big Data Chung Yuan Christian University No. 200 Zhongbei Road Taoyuan 320314 Taiwan. Quantum Information Center Chung Yuan Christian University No. 200 Zhongbei Road Taoyuan 320314 Taiwan. Department of Computer Science and Information Engineering National Taiwan University No. 1 Sec. 4 Roosevelt Road Taipei 10617 Taiwan. Graduate Institute of Biomedical Electronics and Bioinformatics College of Electrical Engineering and Computer Science National Taiwan University No. 1 Sec. 4 Roosevelt Road Taipei 10617 Taiwan. Department of Computer Science and Information Engineering National Taiwan University No. 1 Sec. 4 Roosevelt Road Taipei 10617 Taiwan. yjtseng@csie.ntu.edu.tw. Graduate Institute of Biomedical Electronics and Bioinformatics College of Electrical Engineering and Computer Science National Taiwan University No. 1 Sec. 4 Roosevelt Road Taipei 10617 Taiwan. yjtseng@csie.ntu.edu.tw. Physics Division National Center for Theoretical Sciences No. 1 Sec. 4 Roosevelt Road Taipei 10617 Taiwan. yjtseng@csie.ntu.edu.tw. Center for Quantum Science and Engineering National Taiwan University No. 1 Sec. 4 Roosevelt Road Taipei 10617 Taiwan. yjtseng@csie.ntu.edu.tw.

Quantum computing is at the forefront of technological advancement and has the potential to revolutionize various fields, including quantum chemistry. Choosing an appropriate quantum programming language becomes critical as quantum education and research increase. In this paper, we comprehensively compare two leading quantum programming languages, Qiskit and PennyLane, focusing on their suitability for teaching and research. We delve into their basic and advanced usage, examine their learning curves, and evaluate their capabilities in quantum computing experiments. We also demonstrate using a quantum programming language to build a half adder and a machine learning model. Our study reveals that each language has distinct advantages. While PennyLane excels in research applications due to its flexibility to adjust parameters in detail and access multiple sources of real quantum devices, Qiskit stands out in education because of its web-based graphical user interface and smaller code size. The codes and the dataset used in the studies are available at https://***/wangpeihua1231/quantum-programming-platform .

关键词： PennyLane Qiskit Quantum chemistry Quantum computing Quantum programming language

来源：评论

学校读者我要写书评

暂无评论

Precoding Optimization for Rate Splitting Enabled Internet of Underwater Things over Optical Wireless Underwater Turbulent Channels

引用

IEEE Internet of Things Journal 2025年

作者： Xing, Fangyuan Tong, Fei Liu, Xiaonan Wang, Zhenduo Leung, Victor C. M. Southeast University School of Cyber Science and Engineering Nanjing211189 China School of Natural and Computing Science University of Aberdeen AberdeenAB24 3FX United Kingdom Harbin Engineering University College of Information and Communication Engineering Harbin150001 China Shenzhen MSU-BIT University Artificial Intelligence Research Institute Shenzhen518172 China Shenzhen University College of Computer Science and Software Engineering Shenzhen518060 China The University of British Columbia Department of Electrical and Computer Engineering VancouverBCV6T1Z4 Canada

With the booming development of the underwater Internet of Things, underwater devices and data volume are explosively increasing. Thanks to the advantages of high efficiency and low complexity, the emerging rate splitting multiple access (RSMA) can be integrated with underwater optical wireless communication (UOWC), which can help improve resource utilization and system performance. However, the oceanic characteristics are distinctive and pose great challenges for RSMA-enabled UOWC networks. Precoding design is crucial for benefitting from RSMA-enabled systems, and thus, we explore the precoding optimization for RSMA-enabled UOWC networks over underwater turbulent channels. Specifically, the RSMA-enabled UOWC network is modeled, where a combined turbulent channel involving the effects of absorption, scattering, and underwater turbulence is considered, and a message transmission scheme with rate splitting design is analyzed. A precoding problem is formulated to maximize the ergodic sum rate (ESR) under the constraint of total transmitted power. Since the accurate expression of ESR is a non-closed form and intractable, we first propose a consecutive Fenton-Wilkinson (CFW)-based ergodic rate approximation approach to solve this formulation problem. Fenton-Wilkinson moment matching is consecutively employed to achieve a closed-form and low-complexity expression of the ergodic rate, as only Fenton-Wilkinson moment matching method can offer closed-form solutions for underlying parameters of the approximating log-normal distributions. For further solving the non-convex precoding problem, the successive convex approximation (SCA) approach is adopted, which is particularly applicable for resource-limited underwater environments. The effectiveness of the proposed CFW approach and precoding strategy is evaluated by extensive simulation results for various user deployments and different network loads. © 2025 IEEE.

关键词： Normal distribution

来源：评论

学校读者我要写书评

暂无评论

Generative Artificial Intelligence-Supported Pentesting: A Comparison between Claude Opus, GPT-4, and Copilot

arXiv

引用

arXiv 2025年

作者： Martínez, Antonio López Cano, Alejandro Ruiz-Martínez, Antonio Department of Information and Communication Engineering University of Murcia Faculty of Computer Science Murcia Espinardo30100 Spain Legitec Avda. de los Rectores nº2-4 bajo Murcia Espinardo30100 Spain

The advent of Generative Artificial Intelligence (GenAI) has brought a significant change to our society. GenAI can be applied across numerous fields, with particular relevance in cybersecurity. Among the various areas of application, its use in penetration testing (pentesting) or ethical hacking processes is of special interest. In this paper, we have analyzed the potential of leading generic-purpose GenAI tools—Claude Opus, GPT-4 from ChatGPT, and Copilot—in augmenting the penetration testing process as defined by the Penetration Testing Execution Standard (PTES). Our analysis involved evaluating each tool across all PTES phases within a controlled virtualized environment. The findings reveal that, while these tools cannot fully automate the pentesting process, they provide substantial support by enhancing efficiency and effectiveness in specific tasks. Notably, all tools demonstrated utility;however, Claude Opus consistently outperformed the others in our experimental scenarios. © 2025, CC BY.

关键词： Economic and social effects

来源：评论

学校读者我要写书评

暂无评论

From Partial Calibration to Full Potential: A Two-Stage Sparse DOA Estimation for Incoherently-Distributed Sources with Gain-Phase Uncertainty

arXiv

引用

arXiv 2025年

作者： Xu, He Wu, Tuo Liu, Wei Elkashlan, Maged Al-Dhahir, Naofal Debbah, Mérouane Yuen, Chau So, Hing Cheung School of Cyber Science and Engineering Ningbo University of Technology Ningbo315211 China School of Electrical and Electronic Engineering Nanyang Technological University 639798 Singapore Department of Electrical and Electronic Engineering Hong Kong Polytechnic University Kowloon Hong Kong School of Electronic Engineering and Computer Science Queen Mary University of London LondonE1 4NS United Kingdom Department of Electrical and Computer Engineering The University of Texas at Dallas RichardsonTX75080 United States KU 6G Research Center Department of Computer and Information Engineering Khalifa University Abu Dhabi127788 United Arab Emirates Department of Electrical Engineering City University of Hong Kong China

Direction-of-arrival (DOA) estimation for incoherently distributed (ID) sources is essential in multipath wireless communication scenarios, yet it remains challenging due to the combined effects of angular spread and gain-phase uncertainties in antenna arrays. This paper presents a two-stage sparse DOA estimation framework, transitioning from partial calibration to full potential, under the generalized array manifold (GAM) framework. In the first stage, coarse DOA estimates are obtained by exploiting the output from a subset of partly-calibrated arrays (PCAs). In the second stage, these estimates are utilized to determine and compensate for gain-phase uncertainties across all array elements. Then a sparse total least-squares optimization problem is formulated and solved via alternating descent to refine the DOA estimates. Simulation results demonstrate that the proposed method attained improved estimation accuracy compared to existing approaches, while maintaining robustness against both noise and angular spread effects in practical multipath environments. © 2025, CC BY.

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：