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Individualized Data Generation in Personalized Federated Learning

IEEE Transactions on Mobile Computing 2025年

作者： Cai, Yunyun Xi, Wei Shen, Yuhao Sun, Cerui Wang, Shuai Gong, Wei Zhao, Jizhong Xi'an Jiaotong University Faculty of Electronic and Information Engineering Xi'an China Southeast University School of Computer Science and Engineering Nanjing China University of Science and Technology of China School of Computer science and Technology Hefei China

Most Personalized Federated Learning (PFL) algorithms merge the model parameters of each client with other (similar or generic) model parameters to optimize the personalized model (PM). However, the merged model parameters in these algorithms may fit low relevance data, thereby limiting the performance of PM. In this paper, we generate similar data for each client through the collaboration of a generic model (GM) on the server, rather than merging model parameters. To train a generator capable of generating data for all classes on the server without real data, we employ the GM as the discriminator in adversarial training with the generator. Additionally, we introduce a similarity assessment metric, which allows for the assessment of the similarity between local data and data from other classes. Nevertheless, the presence of non-IID data among clients can weaken the performance of the GM, consequently impacting the training of the generator and similarity assessment. To address this issue, we design a directive mechanism so that GM can be optimized during adversarial training without the need for additional training. The experimental results validate the superiority of our algorithm over state-of-the-art algorithms in terms of accuracy, loss, and convergence speed. © 2002-2012 IEEE.

关键词： Federated learning

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Low carbon deposition on LaCrO3-based high-temperature CO2 sensors

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Ceramics International 2025年

作者： Sun, Congcong Zhang, Huanhuan Wang, Xiaoli Jiang, Xiaoqing Zhang, Xin Jian, Jiawen Jin, Han Zou, Jie Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo315211 China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai200240 China

Platinum (Pt)-based amperometric sensors are promising for carbon dioxide (CO2) monitoring in high-temperature industrial flue gases. However, the traditional Pt electrode is limited due to the carbon deposits in CO2-rich environments. In this work, perovskite oxide LaCrO3 is proposed as sensing electrode (SE) to mitigate carbon deposition due to the low catalytic ability of CO2. The carbon deposition tests were conducted at 750 °C for 100 h in a 13 % CO2 environment. The results indicate that the signal attenuation rate of the LaCrO3-based sensor is 8 % lower than that of the Pt-based sensor. The scanning electron microscope reveals that carbon particles on the Pt SE surface are more and larger than those on the LaCrO3 SE surface. These findings suggest that the LaCrO3-based CO2 sensor effectively mitigates carbon deposition and enhances the long-term stability. © 2025 Elsevier Ltd and Techna Group S.r.l.

关键词： Carbon electrodes

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Spatiotemporal-Aware Visual Captioning using Vision-Language Pre-Training Model

Spatiotemporal-Aware Visual Captioning using Vision-Language...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Shuai Wu Weidong Yang Shuyan Wu School of Computer Science Fudan University China Faculty of Electronic and Information Engineering Xi’an Jiaotong University Xi’an China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Current visual captioning technologies typically transform 3D/2D visual information into one-dimensional sequential data and employ language models to generate corresponding descriptions. This approach, however, compromises the spatiotemporal information in visual data, making it difficult for models to capture temporal variations and the relative spatial relationships between objects. To address this issue, we propose STPos-VC, a pre-trained vision-language model that maps visual information from the visual vector space to the textual vector space through a visual-text mapper and generates natural language descriptions using a decoder. The mapper incorporates three-dimensional rotational position encoding, which effectively preserves the relative spatiotemporal positional relationships. Furthermore, we pre-train the model on a mixed dataset comprising images and videos through a visual question-answering framework, enabling the model to perform well even with small sample sizes. Experimental results across multiple datasets demonstrate that, compared to existing methods, STPos-VC achieves superior performance in both general-purpose and domain-specific applications.

关键词： Visualization Closed captioning Transforms Signal processing Encoding Vectors Data models Spatiotemporal phenomena Speech processing Videos

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Navigating the Road Ahead: A Comprehensive Survey of Radio Resource Allocation for Vehicle Platooning in C-V2X Communications

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IEEE Communications Surveys and Tutorials 2025年第2期27卷 1326-1362页

作者： Yang, Chenyu Kwong, Chiew Foong Chieng, David Kar, Pushpendu Yau, Kok-Lim Alvin Chen, Yusen University of Nottingham Ningbo China Next Generation Internet of Everything Laboratory Department of Electrical and Electronic Engineering Ningbo315100 China University of Nottingham Ningbo China Next Generation Internet of Everything Laboratory School of Computer Science Ningbo315100 China Universiti Tunku Abdul Rahman Lee Kong Chian Faculty of Engineering and Science Kajang47500 Malaysia Zhejiang Communications Investment Group Company Ltd. Hangzhou310020 China

Vehicle-to-everything (V2X) communications have emerged as an indispensable component of the Intelligent Transportation Systems (ITS), fostering innovations that enhance road safety and traffic efficiency. Within this transformative landscape, vehicle platooning has been identified by the Cellular-V2X (C-V2X) standards as an advanced V2X use case with the potential to reshape the future of ITS. However, the stringent requirements of such applications necessitate an optimized spectrum efficiency. Consequently, Radio Resource Allocation (RRA) has emerged as a critical and central component in addressing this challenge. This paper provides a comprehensive examination of RRA tailored specifically to the context of vehicle platooning. It presents an overview of fundamental concepts, including V2X communications, vehicle platooning, and RRA standards, which is followed by an in-depth review of the state-of-the-art, categorized based on the underlying communication technologies, RRA modes, and coverage conditions. By analyzing the existing literature, this paper identifies several key research challenges and potential opportunities, offering insightful guidance for shaping future research in this field. © 1998-2012 IEEE.

关键词： Vehicle to Everything

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Developing a Test Strategy for Mathematics of Arrays Computation Cores

Developing a Test Strategy for Mathematics of Arrays Computa...

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International Electrical engineering Congress (iEECON)

作者： Ian Grout Lenore Mullin Department of Electronic and Computer Engineering Faculty of Science and Engineering University of Limerick Limerick Ireland Department of Computer Science College of Nanotechnology Science and Engineering University at Albany SUNY Albany U.S.A.

ISBN: (数字)9798331543952

ISBN: (纸本)9798331543969

Small size, hardware-only, custom data processing cores connected to a host processor are increasingly considered in digital systems design to provide the ability for accelerating data processing operations through hardware acceleration and parallel processing. These can be realized in different forms such as a custom core connected to a host processor on the same die as the processor, as a separate die (e.g., a chiplet) within the same package as the processor or as a separate Integrated Circuit. These require advanced design flows, low-geometry fabrication processes, and suitable test circuit insertion to implement a suitable test strategy. In this paper, the testability of custom hardware cores is considered through test circuit insertion based on the IJTAG standard. The core is to perform data processing operations based on the Mathematics of Arrays and serial communications is based on the Serial Peripheral Interface. This interface is used for both normal operating mode and the IJTAG based test mode. The system design is considered at the pre-synthesis design development stage and identifies architectural considerations for such system designs.

关键词： Fabrication Electrical engineering Memory management Parallel processing Data processing Mathematics Arrays System analysis and design Standards Hardware acceleration

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Performance Comparison of Interpolation Methods for Enriching WiFi Fingerprint Database 24

Performance Comparison of Interpolation Methods for Enrichin...

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9th International Conference on Cloud Computing and Internet of Things, CCIOT 2024

作者： Vu-Thanh, Trung He, Jing Duong-Bao, Ninh Thi, Luong Nguyen Lee, Seon-Woo Nguyen-Huu, Khanh College of Computer Science and Electronic Engineering Hunan University Changsha China Faculty of Mathematics and Informatics Dalat University Dalat Viet Nam Faculty of Information Technology Dalat University Dalat Viet Nam Division of Software Hallym University Chuncheon Korea Republic of Department of Electronics and Telecommunications Dalat University Dalat Viet Nam

ISBN: (纸本)9798400717161

Recently, WiFi Fingerprinting-based indoor positioning systems have gained significant attention due to the low cost of infrastructure deployment. In the data collection process, a higher density of reference points may lead to better positioning results. However, it makes this process time-consuming and laborious. To solve this problem, this study applies and compares different interpolation methods to enrich the fingerprint database without increasing the cost of the collection process. To evaluate the performance of the chosen methods, five interpolation methods are implemented in a multi-condition WiFi Fingerprinting dataset. Moreover, to check the robustness of the methods, different numbers of reference points are considered when creating the new interpolated fingerprint databases. According to the results, inverse distance weighting (IDW) is the most suitable interpolation method with low complexity and stable performance. The IDW-based database achieves an average interpolation error of less than 6 dBm compared to the original database. When applying this interpolated database to perform positioning tasks, it helps reduce the collection cost by 30% with slightly lower positioning results compared to the original database. This work demonstrates the feasibility of using interpolation to ease the data collection process of WiFi Fingerprinting, especially in complex and big areas such as airports or hospitals. Copyright © 2024 held by the owner/author(s). Publication rights licensed to ACM.

关键词： Wi-Fi

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A Comparative Study of Optimized-LSTM Models Using Tree-Structured Parzen Estimator for Traffic Flow Forecasting in Intelligent Transportation

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computers, Materials & Continua 2025年第5期83卷 3369-3388页

作者： Hamza Murad Khan Anwar Khan Santos Gracia Villar Luis Alonso DzulLopez Abdulaziz Almaleh Abdullah M.Al-Qahtani Department of Electronics University of PeshawarPeshawar25120KPKPakistan Department of Project Management(L.A.D.L) Higher Polytechnic School(S.G.V)Universidad Europea del AtlanticoSantander39011Spain Faculty of Engineering Universidad Internacional IberoamericanaCampeche24560Mexico Faculty of Engineering Universidade Internacional do CuanzaCuitoEN250BieAngola Department of Project Management Universidad Internacional IberoamericanaCampeche24560Mexico Department of Project Management Department of Management SciencesUniversid de La RomanaLa Romana22000Dominican Reublic Information Systems Department College of Computer ScienceKing Khalid UniversityAbha61421Saudi Arabia Department of Electrical and Electronic Engineering College of Engineering&Computer ScienceJazan UniversityJazan45142Saudi Arabia

Traffic forecasting with high precision aids Intelligent Transport Systems(ITS)in formulating and optimizing traffic management *** algorithms used for tuning the hyperparameters of the deep learning models often have accurate results at the expense of high computational *** address this problem,this paper uses the Tree-structured Parzen Estimator(TPE)to tune the hyperparameters of the Long Short-term Memory(LSTM)deep learning *** Tree-structured Parzen Estimator(TPE)uses a probabilistic approach with an adaptive searching mechanism by classifying the objective function values into good and bad *** ensures fast convergence in tuning the hyperparameter values in the deep learning model for performing prediction while still maintaining a certain degree of *** also overcomes the problem of converging to local optima and avoids timeconsuming random search and,therefore,avoids high computational complexity in prediction *** proposed scheme first performs data smoothing and normalization on the input data,which is then fed to the input of the TPE for tuning the *** traffic data is then input to the LSTM model with tuned parameters to perform the traffic *** three optimizers:Adaptive Moment Estimation(Adam),Root Mean Square Propagation(RMSProp),and Stochastic Gradient Descend with Momentum(SGDM)are also evaluated for accuracy prediction and the best optimizer is then chosen for final traffic prediction in TPE-LSTM *** results verify the effectiveness of the proposed model in terms of accuracy of prediction over the benchmark schemes.

关键词： Short-term traffic prediction sequential time series prediction TPE tree-structured parzen estimator LSTM hyperparameter tuning hybrid prediction model

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Hybrid Convtranslstm for Spatio-Temporal Classification: Identifying Early Parkinson's Disease from Gait Patterns

SSRN

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SSRN 2025年

作者： Mahali, Muhammad Izzuddin Avian, Cries Putro, Nur Achmad Sulistyo Prakosa, Setya Widyawan Leu, Jenq-Shiou Department of Electronic and Computer Engineering National Taiwan University of Science and Technology Taiwan Department of Electronics and Informatics Engineering Faculty of Engineering Universitas Negeri Yogyakarta Indonesia Department Electrical Engineering Faculty of Engineering Universitas Brawijaya Indonesia Department of Computer Science and Electronics Faculty of Mathematics and Natural Sciences Universitas Gadjah Mada Indonesia

Parkinson's disease (PD) is a prevalent neurodegenerative disorder that affects motor function and impacts millions worldwide. Early diagnosis and precise staging of PD are critical for effective management and timely intervention. Traditional gait analysis focuses on lower limb movement to differentiate between moderate and advanced PD stages;however, integrating upper and lower limb dynamics offers a more comprehensive approach to distinguishing early-stage PD from *** study introduces a novel spatio-temporal model that integrates CNN, Transformer, and BiLSTM layers to classify PD based on the Hoehn and Yahr (H&Y) score. The architecture captures both spatial and temporal dependencies in gait patterns, with a CNN serving as the primary spatial feature extractor, utilizing a temporal-focused kernel, and augmented by a Transformer to enhance temporal feature learning. Additionally, a BiLSTM module is incorporated to effectively capture complex spatio-temporal gait dynamics across all modules. For data augmentation, sliding windows of 500, 800, and 1200 samples were employed, and the model's performance was rigorously assessed through 3-fold and 5-fold cross-subject *** included accuracy, F1-score, recall, precision, and a voting-based confidence score, while t-SNE visualization provided insights into spatio-temporal feature differentiation. The model demonstrated high performance, achieving optimal accuracy of 0.90 and an average confidence score of 0.97 with a 1200-sample window in 5-fold validation. These findings highlight the potential of a spatio-temporal approach incorporating upper and lower limb characteristics in gait analysis as a robust method for PD multi-class classification, supporting early and effective PD diagnosis from raw IMU signals. © 2025, The Authors. All rights reserved.

关键词： Neurodegenerative diseases

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Artificial sensory neurons and their applications

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Journal of Semiconductors 2025年第1期46卷 108-128页

作者： Jiale Shao Hongwei Ying Peihong Cheng Lingxiang Hu Xianhua Wei Zongxiao Li Huanming Lu Zhizhen Ye Fei Zhuge Faculty of Electrical Engineering and Computer Science Ningbo UniversityNingbo 315211China Ningbo Institute of Materials Technology and Engineering Chinese Academy of SciencesNingbo 315201China School of Electronic and Information Engineering Ningbo University of TechnologyNingbo 315211China State Key Laboratory of Environment-friendly Energy Materials Southwest University of Science and TechnologyMianyang 621010China Institute of Wenzhou Zhejiang UniversityWenzhou 325006China State Key Laboratory of Silicon Materials School of Materials Science and EngineeringZhejiang UniversityHangzhou 310027China Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of SciencesShanghai 200072China

With the rapid development of artificial intelligence(AI)technology,the demand for high-performance and energyefficient computing is increasingly *** limitations of the traditional von Neumann computing architecture have prompted researchers to explore neuromorphic computing as a *** computing mimics the working principles of the human brain,characterized by high efficiency,low energy consumption,and strong fault tolerance,providing a hardware foundation for the development of new generation AI *** neurons and synapses are the two core components of neuromorphic computing *** perception is a crucial aspect of neuromorphic computing,where artificial sensory neurons play an irreplaceable role thus becoming a frontier and hot topic of *** work reviews recent advances in artificial sensory neurons and their ***,biological sensory neurons are briefly ***,different types of artificial neurons,such as transistor neurons and memristive neurons,are discussed in detail,focusing on their device structures and working ***,the research progress of artificial sensory neurons and their applications in artificial perception systems is systematically elaborated,covering various sensory types,including vision,touch,hearing,taste,and ***,challenges faced by artificial sensory neurons at both device and system levels are summarized.

关键词： artificial sensory neurons artificial perception systems neuromorphic computing artificial intelligence

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AoI-Aware Sampling, Transmission, and Computation for Edge-Enabled Control System

AoI-Aware Sampling, Transmission, and Computation for Edge-E...

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IEEE Conference on Wireless Communications and Networking

作者： Mingan Luan Zheng Chang Jin Chi School of Computer Science and Engineering University of Electronic Science and Technology of China China Faculty of Information Technology University of Jyvaskyla Finland

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

In this paper, an age of information (AoI)-aware joint design framework of sampling, transmission, computation, and control is considered for industrial cyber-physical systems. To enhance the control performance, we investigate an edge-enabled control scheme, which allows a physical entity to select its sampling adaptively and processing strategies based on de-mand. By analyzing the impact of sampling and short-packet decoding errors, and the coupling relationship between control accuracy and AoI, the AoI -aware control metric is established. Subsequently, we formulate a joint sampling time, computation offloading, and bandwidth allocation optimization problem to minimize the system's control and energy costs. To tackle the formulated NP-hard problem, we develop a BCD-based algorithm leveraging convex and game theories to obtain a joint optimization strategy in an iterative manner. Finally, the performance of the proposed edge-enabled control scheme is verified in the simulation results.

关键词： Measurement Costs NP-hard problem Simulation Scalability Process control Cyber-physical systems Channel allocation Control systems Optimization

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