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International Joint Conference on Neural Networks (IJCNN)

作者： Heping Liu Songbai Liu Junkai Ji Qiuzhen Lin Jianyong Chen Kay Chen Tan College of Computer Science and Software Engineering Shenzhen University Shenzhen China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China Department of Computing The Hong Kong Polytechnic University

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

Integrating personalization into federated learning is crucial for addressing data heterogeneity and surpassing the limitations of a single aggregated model. Personalized federated learning excels at capturing inter-client similarities and meeting diverse client needs through custom-made models. However, even with personalized approaches, it’s essential to aggregate knowledge among clients to ensure universal benefits. This paper proposes Federated Dual Objectives and Dual Models (FedDodm), a novel approach that employs two independent models to separately address explicit personalization and implicit generalization objectives in personalized federated learning. By treating these objectives as distinct loss functions and training models accordingly, we achieve a balance between the two through a fusion method. Extensive experiments across various models and learning tasks demonstrate that FedDodm outperforms state-of-the-art federated learning approaches, marking a significant advancement in effectively integrating personalized and generalized knowledge.

关键词： Training Federated learning Aggregates Neural networks Data models

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IEEE T-BIOM Editorial Board Changes

IEEE Transactions on Biometrics, Behavior, and Identity Scie...

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IEEE Transactions on Biometrics, Behavior, and Identity Science 2024年第1期7卷 1-2页

作者： Naser Damer Weihong Deng Jianjiang Feng Vishal M. Patel Ajita Rattani Mark Nixon Smart Living & Biometric Technologies Fraunhofer Institute for Computer Graphics Research IGD Darmstadt Germany Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunications Beijing China Department of Automation Tsinghua University Beijing China Department of Electrical and Computer Engineering Johns Hopkins University Baltimore MD USA Department of Computer Science and Engineering College of Engineering University of North Texas Denton TX USA

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DasAtom: A Divide-and-Shuttle Atom Approach to Quantum Circuit Transformation

arXiv

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arXiv 2024年

作者： Huang, Yunqi Gao, Dingchao Ying, Shenggang Li, Sanjiang Faculty of Engineering and Information Technology University of Technology SydneyNSW2007 Australia Key Laboratory of System Software Chinese Academy of Sciences State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences China

Neutral atom (NA) quantum systems are emerging as a leading platform for quantum computation, offering superior or competitive qubit count and gate fidelity compared to superconducting circuits and ion traps. However, the unique features of NA devices, such as long-range interactions, long qubit coherence time, and the ability to physically move qubits, present distinct challenges for quantum circuit compilation. In this paper, we introduce DasAtom, a novel divide-and-shuttle atom approach designed to optimise quantum circuit transformation for NA devices by leveraging these capabilities. DasAtom partitions circuits into subcircuits, each associated with a qubit mapping that allows all gates within the subcircuit to be directly executed. The algorithm then shuttles atoms to transition seamlessly from one mapping to the next, enhancing both execution efficiency and overall fidelity. For a 30-qubit Quantum Fourier Transform (QFT), DasAtom achieves a 415.8x improvement in fidelity over the move-based algorithm Enola and a 10.6x improvement over the SWAP-based algorithm Tetris. Notably, this improvement is expected to increase exponentially with the number of qubits, positioning DasAtom as a highly promising solution for scaling quantum computation on NA platforms. © 2024, CC BY.

关键词： Qubits

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Round-trip information timeliness based energy storage control for cyber-physical integrated multi-energy system

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Journal of Energy Storage 2025年 127卷

作者： Liao, Haijun Zhang, Hongshuo Che, Wenxuan Li, Ziming Zhou, Wen Zhou, Zhenyu Tariq, Muhammad State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing102206 China Electrical Engineering Department National University of Computer and Emerging Sciences Islamabad44000 Pakistan

The cyber–physical integrated multi-energy system (MES) with energy storage plays an essential supporting role in achieving low-carbon operation of distribution grid. Distributed consensus optimization is the core principle to facilitate cost-efficient operation of MES under the volatility of renewable energy output and load. However, the economic control of cyber–physical integrated MES neglects the close coupling between the physical-domain control stability and cyber-domain information interaction timeliness. Meanwhile, there lacks a timeliness model reflecting the timeliness loss in the round-trip information interaction among multi-energy subsystems, and a consensus optimization method considering the round-trip information timeliness and multi-energy subsystem influences, thereby weaking control stability and convergence performance. Thus, a round-trip timeliness model for cyber-domain MES is developed, and a cyber–physical integrated MES control problem is constructed to minimize the total control cost by jointly optimizing cyber-domain interaction sequence, physical-domain consensus variable weights, and multi-energy subsystem output power. A round-trip timeliness minimization-driven control algorithm for cyber–physical integrated MES is proposed. In the offline phase, K-means and radial basis function are used to fit the influence of MESs. In the online phase, a low-complexity externality matching algorithm is proposed to optimize the interaction sequence and adjust the consensus variable update process to improve information timeliness and control economy. Simulation results demonstrate that the proposed algorithm has superior performances in economic control of MES and convergence speed. © 2025

关键词： Boolean functions

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Applying system Thinking to Learn from Accident of Modern Automatic Control systems

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Chinese Journal of Electronics 2025年第2期23卷 409-414页

作者： Ru Niu Yuan Cao Xiaocheng Ge Tao Tang State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China School of Electronics and Information Engineering National Engineering Research Center of Rail Transportation Operation and Control System Beijing Jiaotong University Beijing China Department of Computer Science University of York York UK

Modern societies increasingly rely on automatic control systems. These systems are hardly pure technical systems; instead they are complex socio-technical systems, which consist of technical elements and social components. It is necessary to have a systematic approach to analyze these systems because it is growing evidence that accidents from these systems usually have complex causal factors which form an interconnected network of events, rather than a simple cause-effect chain. We take railway Train control systems (TCS) as an example to demonstrate the importance of the socio-technical approach to analyze the system. The paper presents an investigation of recent high-speed railway accident by applying STAMP - one of the most notable socio-technical system analysis techniques, outlines improvements to the system which could avoid similar accidents in the future. We also provide our valuable feedback for the use of STAMP.

关键词： Sociotechnical systems Analytical models systematics Railway accidents Transportation Medical services Rail transportation systems thinking Research and development Accidents

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Tailoring Highly Confined Electric-field Based Optical Skyrmions

Tailoring Highly Confined Electric-field Based Optical Skyrm...

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Progress in Electromagnetic Research Symposium (PIERS)

作者： J. Chen X. Shen Y. Zeng Q. Zhan School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai China Shanghai Key Laboratory of Modern Optical System University of Shanghai for Science and Technology Shanghai China

ISBN: (数字)9798350375909

ISBN: (纸本)9798350375916

Optical skyrmions are quasi-particles with nontrivial topological textures, which hold potential applications in optical information processing, transmission, and storage. There are various three-dimensional physical vectors to construct the optical skyrmions, such as spin skyrmions, Stokes skyrmions, Poynting vector skyrmions, and so on. Here, we present a method to construct tightly focused electric-field skyrmions based on the array antenna radiation theory. A multiple concentric-ring array of dipoles (MCAD) is placed at the focal region of the high numerical aperture (NA) lens to mimic the topological structure of the desired electric field skyrmion, and the radiation pattern of the MCAD is derived to form the incident fields at the pupil planes of the high NA lenses in a 4π focusing setup. The characteristics of the generated focal field are quantitatively evaluated by using the Debye diffraction integral theory. The results demonstrate that two types of electric field vector topologies, i.e., skyrmion and meron, can be created with adjustable polarity, vorticity, and helicity. Additionally, the normal direction of the plane containing the skyrmion or meron can also be customized, increasing the degrees of freedom in tailoring optical skyrmions.

关键词： Electric potential Optical diffraction Information processing Vectors Topology Electric fields Pupils

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Operating-Envelopes-Aware Decentralized Welfare Maximization for Energy Communities

arXiv

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arXiv 2023年

作者： Alahmed, Ahmed S. Cavraro, Guido Bernstein, Andrey Tong, Lang School of Electrical and Computer Engineering Cornell University IthacaNY United States Power System Engineering Center National Renewable Energy Laboratory GoldenCO United States

We propose an operating-envelope-aware, prosumer-centric, and efficient energy community that aggregates individual and shared community distributed energy resources and transacts with a regulated distribution system operator (DSO) under a generalized net energy metering tariff design. To ensure safe network operation, the DSO imposes dynamic export and import limits, known as dynamic operating envelopes, on end-users’ revenue meters. Given the operating envelopes, we propose an incentive-aligned community pricing mechanism under which the decentralized optimization of community members’ benefit implies the optimization of overall community welfare. The proposed pricing mechanism satisfies the cost-causation principle and ensures the stability of the energy community in a coalition game setting. Numerical examples provide insights into the characteristics of the proposed pricing mechanism and quantitative measures of its performance. © 2023, CC BY.

关键词： Dynamics

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Few-Shot Gearbox Fault Diagnosis Based on Semi-Supervised Prototypical Network and Contrastive Learning

Few-Shot Gearbox Fault Diagnosis Based on Semi-Supervised Pr...

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2023 China Automation Congress, CAC 2023

作者： Cheng, Shulie Liang, Yingjie Ping, Zuowei Liao, Xuechao Wang, Maolin Zhang, Yong School of Information Science and Engineering Wuhan University of Science and Technology Wuhan China Naval University of Engineering National Key Laboratory of Science and Technology on Vessel Integrated Power System Wuhan China School of Computer Science and Technology Wuhan University of Science and Technology Wuhan China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9798350303759

Due to the scarcity of labeled faulty data in industrial practice, fault diagnosis models often face challenges related to overfitting and limited accuracy. This article introduces a novel solution to tackle the problem - a fault diagnosis method that leverages a combination of a semi-supervised prototype network and contrastive learning. Firstly, a limited number of labeled samples is employed to construct pairs of positive and negative samples. And the training method of contrastive learning is used to provide appropriate initial parameters for the autoencoder. Secondly, the autoencoder is employed as a feature mapping function within the prototype network and obtains the prototype using a limited number of labeled samples. Finally, a prototype refinement method fine-tunes the prototype through unlabeled data, reducing the impact of anomalous data and obtaining a more stable and accurate prototype. The effectiveness of the proposed method is evaluated using gearbox data as a validation dataset. Through comparative analysis with other methods, the results demonstrate that the proposed approach achieves superior diagnostic accuracy. © 2023 IEEE.

关键词： Failure analysis

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A Behavioral Recognition-Based Federated Learning Framework for IoT Environments

A Behavioral Recognition-Based Federated Learning Framework ...

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International Joint Conference on Neural Networks (IJCNN)

作者： Ruizhong Du Shuai Li Pengyuan Zhao School of Cyber Security and Computer Hebei University Hebei Key Laboratory of High Trust Information System Baoding China School of Cyber Science and Engineering Wuhan University Wuhan China

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

Identifying the behavior and intent of various Internet of Things (IoT) devices distributed across different environments is a challenge. The previous centralized modeling approach ran the risk of invading privacy. This study develops a federated learning approach enhanced by Long short-term memory (LSTM) networks to improve the accuracy of modeling the behavior of iot devices in decentralized networks. We extract periodic communication features locally at each node, focusing on relevant behavior sequences while protecting privacy. Applying LSTM to these periodic sequences captures the temporal dynamics necessary for behavioral modeling. The federated LSTM model then aggregates the locally learned behavior patterns to classify device sequences and interactions without sharing the raw data. Experiments show that this method can accurately identify the key behaviors of iot devices. By focusing on periodic communication, our technology enables collaborative device behavior identification across distributed nodes without compromising user privacy. This provides a pathway for privacy-protecting behavioral intelligent federated learning in iot environments.

关键词： Privacy Federated learning Focusing Collaboration Feature extraction Internet of Things Object recognition

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Highly integrated reconfigurable radiofrequency filter based on microcomb and a silicon photonic processor

Highly integrated reconfigurable radiofrequency filter based...

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CLEO: Science and Innovations, S and I 2022

作者： Tao, Yuansheng Chang, Lin Shen, Bitao Shu, Haowen Xie, Weiqiang Jin, Ming Tao, Zihan Bai, Bowen Yu, Shaohua Wang, Xingjun Bowers, John E. State Key Laboratory of Advanced Optical Communications System and Networks Department of Electronics School of Electronics Engineering and Computer Science Peking University Beijing100871 China Department of Electrical and Computer Engineering University of California Santa BarbaraCA93106 United States Peng Cheng Laboratory Shenzhen518055 China Frontiers Science Center for Nano-optoelectronics Peking University Beijing100871 China

We demonstrate a novel chip-scale reconfigurable radiofrequency filter by using AlGaAs-on-insulator microcomb and silicon photonics in combination, simultaneously bypassing the employment of bulky pulse shaper and lon... 详细信息

ISBN: (纸本)9781557528209

关键词： Silicon photonics

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