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Domain generalization with semi-supervised learning for people-centric activity recognition

Science China(Information Sciences) 2025年第1期68卷 171-188页

作者： Jing LIU Wei ZHU Di LI Xing HU Liang SONG Academy for Engineering & Technology Fudan University Shanghai East-bund Research Institute on Networking Systems of AI School of Optoelectronic Information and Computer Engineering University of Shanghai for Science & Technology

People-centric activity recognition is one of the most critical technologies in a wide range of real-world applications,including intelligent transportation systems, healthcare services, and brain-computer interfaces. Large-scale data collection and annotation make the application of machine learning algorithms prohibitively expensive when adapting to new tasks. One way of circumventing this limitation is to train the model in a semi-supervised learning manner that utilizes a percentage of unlabeled data to reduce the labeling burden in prediction tasks. Despite their appeal, these models often assume that labeled and unlabeled data come from similar distributions, which leads to the domain shift problem caused by the presence of distribution gaps. To address these limitations, we propose herein a novel method for people-centric activity recognition,called domain generalization with semi-supervised learning(DGSSL), that effectively enhances the representation learning and domain alignment capabilities of a model. We first design a new autoregressive discriminator for adversarial training between unlabeled and labeled source domains, extracting domain-specific features to reduce the distribution gaps. Second, we introduce two reconstruction tasks to capture the task-specific features to avoid losing information related to representation learning while maintaining task-specific consistency. Finally, benefiting from the collaborative optimization of these two tasks, the model can accurately predict both the domain and category labels of the source domains for the classification task. We conduct extensive experiments on three real-world sensing datasets. The experimental results show that DGSSL surpasses the three state-of-the-art methods with better performance and generalization.

关键词： activity recognition deep learning domain generalization semi-supervised learning adversarial training

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Data-driven output regulation control for constrained linear systems

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Science China(Information Sciences) 2025年第3期68卷 338-353页

作者： Chaoyu XIA Yi DONG Chaoli WANG Shengyuan XU Shanghai Research Institute for Intelligent Autonomous Systems Tongji University College of Electronic and Information Engineering Shanghai Research Institute for Intelligent Autonomous SystemsTongji University Department of Control Science and Engineering School of Optical-Electrical and Computer EngineeringUniversity of Shanghai for Science and Technology Department of Automation Nanjing University of Science and Technology

This study introduces a data-driven approach for state and output feedback control addressing the constrained output regulation problem in unknown linear discrete-time systems. Our method ensures effective tracking performance while satisfying the state and input constraints, even when system matrices are not available. We first establish a sufficient condition necessary for the existence of a solution pair to the regulator equation and propose a data-based approach to obtain the feedforward and feedback control gains for state feedback control using linear programming. Furthermore, we design a refined Luenberger observer to accurately estimate the system state, while keeping the estimation error within a predefined set. By combining output regulation theory, we develop an output feedback control strategy. The stability of the closed-loop system is rigorously proved to be asymptotically stable by further leveraging the concept of λ-contractive sets.

关键词： output regulation constrained system data-driven.

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Generalized Regenerating Codes and Node Repair on Graphs

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IEEE Transactions on Information Theory 2025年第3期71卷 1613-1630页

作者： Patra, Adway Barg, Alexander University of Maryland Department of Electrical and Computer Engineering The Institute for Systems Research College ParkMD20742 United States

We consider regenerating codes in distributed storage systems where connections between the nodes are constrained by a graph. In this problem, the failed node downloads the information stored at a subset of vertices of the graph for the purpose of recovering the lost data. Compared to the standard setting, regenerating codes on graphs address two additional features. The repair information is moved across the network, and the cost of node repair is determined by the graphical distance from the helper nodes to the failed node. Accordingly, the helpers far away from the failed node may be expected to contribute less data for repair than the nodes in the neighborhood of that node. We analyze regenerating codes with nonuniform download for repair on graphs. Moreover, in the process of repair, the information moved from the helpers to the failed node may be combined through intermediate processing, reducing the repair bandwidth. We derive lower bounds for communication complexity of node repair on graphs, including repair schemes with nonuniform download and intermediate processing, and construct codes that attain these bounds. Additionally, some of the nodes may act as adversaries, introducing errors into the data moved in the network. For repair on graphs in the presence of adversarial nodes, we construct codes that support node repair and error correction in systematic nodes. © 1963-2012 IEEE.

关键词： Maintenance engineering Codes Costs Network coding IP networks Bandwidth Symbols Encoding Vectors Standards

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Fuzzy clustering for electric field characterization and its application to thunderstorm interpretability

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Digital Communications and Networks 2025年第2期11卷 299-307页

作者： Xu Yang Hongyan Xing Xinyuan Ji Wei Xu Witold Pedrycz School of Electronics and Information Engineering Nanjing University of Information Science and Technology Department of Electrical and Computer Engineering University of Alberta Systems Research Institute Polish Academy of Sciences Department of Computer Engineering Faculty of Engineering and Natural Sciences Istinye University

Changes in the Atmospheric Electric Field Signal(AEFS) are highly correlated with weather changes, especially with thunderstorm activities. However, little attention has been paid to the ambiguous weather information implicit in AEFS changes. In this paper, a Fuzzy C-Means(FCM) clustering method is used for the first time to develop an innovative approach to characterize the weather attributes carried by AEFS. First, a time series dataset is created in the time domain using AEFS attributes. The AEFS-based weather is evaluated according to the time-series Membership Degree(MD) changes obtained by inputting this dataset into the FCM. Second, thunderstorm intensities are reflected by the change in distance from a thunderstorm cloud point charge to an AEF apparatus. Thus, a matching relationship is established between the normalized distance and the thunderstorm dominant MD in the space domain. Finally, the rationality and reliability of the proposed method are verified by combining radar charts and expert experience. The results confirm that this method accurately characterizes the weather attributes and changes in the AEFS, and a negative distance-MD correlation is obtained for the first time. The detection of thunderstorm activity by AEF from the perspective of fuzzy set technology provides a meaningful guidance for interpretable thunderstorms.

关键词： Atmospheric electric field (AEF) Thunderstorm Fuzzy C-means (FCM) Attribute

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Evaluation of micro-dispersion on oil recovery during low-salinity water-alternating-CO2 processes in sandstone cores: An integrated experimental approach

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Petroleum Science 2025年第1期22卷 277-295页

作者： Jia-Xin Wang Leng Tian Can Huang Xiao-Jiao Deng Daoyong Tony Yang Rui-Heng Wang Jia-Hao Lin Jin-Yang Wei CNOOC Research Institute Co. Ltd. College of Petroleum Engineering China University of Petroleum (Beijing) State Key Laboratory of Offshore Oil Exploitation Research Center for Natural Gas Geology and Engineering China University of Petroleum (Beijing) Exploration and Development Research Institute Jianghan Oilfield Branch Company Sinopec PetroChina Oil Gas and New Energy Company Energy Systems Engineering Faculty of Engineering and Applied Science University of Regina Exploration and Development Research Institute of PetroChina Changqing Oilfield Company No.3 Gas Production Plant of PetroChina Changqing Oilfield Company

Low-salinity water（LSW） and CO2could be combined to perform better in a hydrocarbon reservoir due to their synergistic advantages for enhanced oil recovery（EOR）; however, its microscopic recovery mechanisms have not been well understood due to the nature of these two fluids and their physical reactions in the presence of reservoir fluids and porous media. In this work, well-designed and integrated experiments have been performed for the first time to characterize the in-situ formation of microdispersions and identify their EOR roles during a LSW-alternating-CO2（CO2-LSWAG） process under various conditions. Firstly, by measuring water concentration and performing the Fourier transform infrared spectroscopy（FT-IR） analysis, the in-situ formation of micro-dispersions induced by polar and acidic materials was identified. Then, displacement experiments combining with nuclear magnetic resonance（NMR） analysis were performed with two crude oil samples, during which wettability,interfacial tension（IFT）, CO2dissolution, and CO2diffusion were quantified. During a CO2-LSWAG process, the in-situ formed micro-dispersions dictate the oil recovery, while the presence of clay minerals,electrical double-layer（EDL） expansion and multiple ion exchange（MIE） are found to contribute *** formed micro-dispersions are induced by CO2via diffusion to mobilize the CO2-diluted oil, alter the rock wettability towards more water-wet, and minimize the density contrast between crude oil and water.

关键词： Low-salinity water-alternating-CO2 process Micro-dispersion Wettability alteration Clay minerals Electrical double-layer Multiple ion exchange

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Multi-View Test-Time Adaptation for Semantic Segmentation in Clinical Cataract Surgery

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IEEE Transactions on Medical Imaging 2025年第5期44卷 2307-2318页

作者： Li, Heng Ou, Mingyang Li, Haojin Qiu, Zhongxi Niu, Ke Fu, Huazhu Liu, Jiang Southern University of Science and Technology Research Institute of Trustworthy Autonomous Systems Shenzhen518055 China Southern University of Science and Technology Department of Computer Science and Engineering Shenzhen518055 China Beijing Information Science and Technology University Computer School Beijing100192 China Institute of High Performance Computing Agency for Science Technology and Research Fusionopolis Way 138632 Singapore Southern University of Science and Technology Research Institute of Trustworthy Autonomous Systems Department of Computer Science and Engineering Shenzhen518055 China

Cataract surgery, a widely performed operation worldwide, is incorporating semantic segmentation to advance computer-assisted intervention. However, the tissue appearance and illumination in cataract surgery often differ among clinical centers, intensifying the issue of domain shifts. While domain adaptation offers remedies to the shifts, the necessity for data centralization raises additional privacy concerns. To overcome these challenges, we propose a Multi-view Test-time Adaptation algorithm (MUTA) to segment cataract surgical scenes, which leverages multi-view learning to enhance model training within the source domain and model adaptation within the target domain. In the training phase, the segmentation model is equipped with multi-view decoders to boost its robustness against variations in cataract surgery. During the inference phase, test-time adaptation is implemented using multi-view knowledge distillation, enabling model updates in clinics without data centralization or privacy concerns. We conducted experiments in a simulated cross-center scenario using several cataract surgery datasets to evaluate the effectiveness of MUTA. Through comparisons and investigations, we have validated that MUTA effectively learns a robust source model and adapts the model to target data during the practical inference phase. © 1982-2012 IEEE.

关键词： Semantic Segmentation

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Flexiswap: A Cross-Chain Decentralized Exchange Protocol 17

Flexiswap: A Cross-Chain Decentralized Exchange Protocol

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17th International Conference on COMmunication systems and NETworkS, COMSNETS 2025

作者： Singh, Kirti Ribeiro, Vinay J. Mandal, Susmita Indian Institute of Technology Bombay Department of Computer Science and Engineering Mumbai India Institute for Development and Research in Banking Technology Hyderabad India

ISBN: (纸本)9798331531195

Decentralized exchanges (DEXs) have emerged as a promising solution to enhance trustlessness in blockchain ecosystems and mitigate security threats associated with centralized exchanges. While platforms like Uniswap offer certain advantages, their limitation to exchanging tokens within a single blockchain restricts their utility. Moreover, exchanges relying on atomic swaps, such as AtomicDEX, are susceptible to grief attacks and exhibit low success ratios. In response to these challenges, we introduce FlexiSwap, an auction-based decentralized exchange protocol that leverages atomic swaps for exchanging native tokens between smart contract-compatible blockchains. FlexiSwap stands out by combining multiple bids to facilitate one-to-many exchanges, resulting in improved exchange values, successful execution of large-volume exchanges, and an improved success ratio. The protocol incorporates a penalization mechanism to deter grief attacks, ensuring that participants cannot withdraw from an exchange without incurring a loss once the counterparty has committed its assets. We also prove the protocol's safety, liveness, and grief prevention. Our simulation results demonstrate that combining multiple bids helps achieve better exchange values and order-matching success rates. Additionally, we implemented our protocol on Ethereum-based blockchains. The experimental results show that combining bids increases overall gas usage, but the increase in the average gas user per bid is marginal. © 2025 IEEE.

关键词： Kyoto Protocol

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Blur-Deblur Algorithm for Pressure-Sensitive Paint Image Based on Variable Attention Convolution

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computers, Materials & Continua 2025年第3期82卷 5239-5256页

作者： Ruizhe Yu Tingrui Yue Lei Liang Zhisheng Gao School of Computer and Software Engineering Xihua UniversityChengdu610039China College of Aerospace Engineering Nanjing University of Aeronautics and AstronauticsNanjing210016China Low Speed Aerodynamics Institute China Aerodynamics Research and Development CenterMianyang621000China

In the PSP(Pressure-Sensitive Paint),image deblurring is essential due to factors such as prolonged camera exposure times and highmodel velocities,which can lead to significant image *** deblurring methods applied to PSP images often suffer from limited accuracy and require extensive computational *** address these issues,this study proposes a deep learning-based approach tailored for PSP image *** that PSP applications primarily involve the accurate pressure measurements of complex geometries,the images captured under such conditions exhibit distinctive non-uniform motion blur,presenting challenges for standard deep learning models utilizing convolutional or attention-based *** this paper,we introduce a novel deblurring architecture featuring multiple DAAM(Deformable Ack Attention Module).These modules provide enhanced flexibility for end-to-end deblurring,leveraging irregular convolution operations for efficient feature extraction while employing attention mechanisms interpreted as multiple 1×1 convolutions,subsequently reassembled to enhance ***,we incorporate a RSC(Residual Shortcut Convolution)module for initial feature processing,aimed at reducing redundant computations and improving the learning capacity for representative shallow *** preserve critical spatial information during upsampling and downsampling,we replace conventional convolutions with wt(Haar wavelet downsampling)and dysample(Upsampling by Dynamic Sampling).This modification significantly enhances high-precision image *** integrating these advanced modules within an encoder-decoder framework,we present the DFDNet(Deformable Fusion Deblurring Network)for image blur removal,providing robust technical support for subsequent PSP data *** evaluations on the FY dataset demonstrate the superior performance of our model,achieving competitive results on the GOPRO and HIDE datasets.

关键词： Pressure-sensitive paint deep learning image deblurring typeset variable attention convolution

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Voltage and power control for distributed generation units in islanded microgrids 6th

Voltage and power control for distributed generation units i...

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6th International Conference on Renewable Energies Offshore, RENEW 2024

作者： Rouch, T. Bagheri M’zoughi, F. Aboutalebi, P. Ahmad, I. Garrido, A.J. Garrido, I. Institute of Research and Development of Processes—IIDP Department of Automatic Control and Systems Engineering Faculty of Engineering of Bilbao University of the Basque Country Bilbao Spain

ISBN: (纸本)9781032905570

This article presents an optimized control strategy tailored for DC islanded microgrids, featuring a voltage controller based on mixed H2/H∞ state feedback using linear matrix inequalities (LMIs) and a power controller guided by droop characteristics. A polytopic modeling approach addresses system uncertainties and nonlinearities. The controller aims to stabilize the system, reject disturbances, equitably distribute power among distributed generation units (DGUs), and minimize energy consumption. Regional pole placement ensures welldamped transient responses. Simulation results demonstrate effective management of load perturbations and DGU disconnections, with a comparative analysis against an H∞ controller offering additional insights into performance. © 2025 The Author(s).

关键词： Microgrids

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A Substation Automation System Architecture for Migrating From Decentralized to Centralized Protection and Control in Smart Substations

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IEEE Transactions on Industry Applications 2025年第3期61卷 5173-5186页

作者： Mandal, Anand Muttaqi, Kashem M. Islam, Md. Rabiul Sutanto, Danny Rahman, Anisur Yilmaz, Orhan Vaze, Omkar University of Wollongong Australian Power and Energy Research Institute School of Electrical Computer and Telecommunications Engineering WollongongNSW2522 Australia ABB Australia Digital Systems Electrification Team Australia

The protection of the power system component is crucial for the healthy and reliable operation of the entire grid. Depending upon the equipment being protected and the type of fault it may encounter, various protection functions need to be employed. The paper presents a detailed overview of the evolution of the SAS structure in smart substations facilitating the centralization of multiple protection and control functions. The description detailing the evolution of the substation automation system (SAS), driven by the IEC61850 standard, enabling the transition from conventional substations to digital substations has been highlighted in this paper. The centralized protection and control (CPC) technique, representing an innovative strategy that consolidates all protection and control functions within a single device at the substation level, has been presented in detail. Moreover, the guidelines on the implementation of the CPC architecture in substations along with the approach involved in migration from a decentralized protection scheme to CPC architecture have been proposed considering the existing substation in a power grid. The protection functions employed in the line and transformer bays of the substation have been mathematically described using the actual parameters of the substation equipment. Their effectiveness has been confirmed by analyzing disturbance reports of faults that occurred in both the line and transformer feeders. © 1972-2012 IEEE.

关键词： Transformer substations

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