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Towards practical data alignment in production federated learning

Frontiers of Computer Science 2025年第1期19卷 167-169页

作者： Yexuan SHI Wei YU Yuanyuan ZHANG Chunbo XUE Yuxiang ZENG Zimu ZHOU Manxue GUO Lun XIN Wenjing NIE State Key Laboratory of Complex&Critical Software Environment and Advanced Innovation Center for Future Blockchain and Privacy Computing Beihang UniversityBeijing 100191China Zhongguancun Pan Connected Mobile Communication Technology Innovation and Application Research Institute Beijing 100088China China Mobile Research Institute Beijing 100053China School of Data Science City University of Hong KongHong Kong 999077China

1 Introduction Federated learning has emerged as a promising par-adigm for collaborative model training that facilitates cooperation among multiple parties while ensuring data privacy[1].Successful alignment of data across parties is crucial for effective federated learning[2].This alignment involves harmonizing heterogeneous data from different parties to identify shared data for joint model *** set intersection(PSI)is a technique that allows the alignment of common entities between parties without revealing additional ***,efficiently performing data alignment with PSI in federated learning[3],especially when dealing with highly unbalanced data,remains challenging due to the low efficiency.

关键词： alignment dealing parties

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Interpersonal Relationship Analysis with Dyadic EEG Signals via Learning Spatial-Temporal Patterns

Interpersonal Relationship Analysis with Dyadic EEG Signals...

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4th International Workshop on Human Brain and Artificial Intelligence, HBAI 2024

作者： Ji, Wenqi Liu, Fang Du, Xinxin Liu, Niqi Zhou, Chao Yu, Minjing Guo, Xinyue Zhao, Guozhen Liu, Yong-Jin Department of Computer Science and Technology Tsinghua University Beijing100084 China State Key Laboratory of Media Convergence and Communication Communication University of China Beijing100024 China Institute of Software Chinese Academy of Sciences Beijing100190 China College of Intelligence and Computing Tianjin University Tianjin300072 China CAS Key Laboratory of Behavioral Science Institute of Psychology Beijing100049 China

ISBN: (纸本)9789819640003

Interpersonal relationship quality is pivotal in social and occupational contexts. Existing analysis of interpersonal relationships mostly rely on subjective self-reports, whereas objective quantification remains challenging. In this paper, we propose a novel social relationship analysis framework using spatio-temporal patterns derived from dyadic EEG signals, which can be applied to quantitatively measure team cooperation in corporate team building, and evaluate interpersonal dynamics between therapists and patients in psychiatric therapy. First, we constructed a dyadic-EEG dataset from 72 pairs of participants with two relationships (stranger or friend) when watching emotional videos simultaneously. Then we proposed a deep neural network on dyadic-subject EEG signals, in which we combine the dynamic graph convolutional neural network for characterizing the interpersonal relationships among the EEG channels and 1-dimension convolution for extracting the information from the time sequence. To obtain the feature vectors from two EEG recordings that well represent the relationship of two subjects, we integrate deep canonical correlation analysis and triplet loss for training the network. Experimental results show that the social relationship type (stranger or friend) between two individuals can be effectively identified through their EEG data. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Deep neural networks

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TDiffSal: Text-Guided Diffusion Saliency Prediction Model for Images 27th

TDiffSal: Text-Guided Diffusion Saliency Prediction Model fo...

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27th International Conference on Pattern Recognition, ICPR 2024

作者： Zhang, Nana Xiong, Min Zhu, Dandan Zhu, Kun Zhai, Guangtao School of Computer Science and Technology Donghua University No. 2999 Renmin North Road Songjiang District Shanghai201620 China State Key Laboratory for Novel Software Technology Nanjing University Nanjing210093 China Institute of AI Education Shanghai East China Normal University No. 3663 Zhongshan North Road Putuo District Shanghai200333 China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University No. 4800 Cao’an Highway Jiading District Shanghai201804 China Institute of Image Communication and Network Engineering Shanghai Jiao Tong University No. 800 Dongchuan Road Minhang District Shanghai200240 China

ISBN: (纸本)9783031781858

Existing visual saliency prediction methods mainly focus on single-modal visual saliency prediction, while ignoring the significant impact of text on visual saliency. To more comprehensively explore the influence of text on human attention in images, we propose a text-guided diffusion saliency prediction model, named TDiffSal. In specific, recent studies on stable diffusion models have shown promising performance in unifying tasks due to their inherent generalization ability. Inspired by this, a novel diffusion model for generalized visual-text saliency prediction is proposed, which formulates the prediction issue as a conditional generative task of the saliency map by employing input visual and text as the conditions. Meanwhile, we introduce a multi-head fusion module to effectively integrate text features and image features, which can efficiently guide the image denoising process and progressively refine the generated saliency map to make it semantically relevant to the text. Additionally, we employ an efficient pre-training strategy to enhance the robustness and generalization of the proposed model. We conduct extensive experiments on benchmark datasets to demonstrate its superior performance compared to other state-of-the-art methods. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Prediction models

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Compromising Rechargeable Sensor Networks in Marine Environment

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IEEE Transactions on Mobile computing 2025年

作者： Wang, Qiwei Lin, Chi Dai, Haipeng Obaidat, Mohammad S. Hsiao, Kuei-Fang Fan, Xin Dalian University of Technology School of Software Technology & DUT-RU International School of Information Science and Engineering China Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province Dalian116620 China Nanjing University State Key Laboratory for Novel Software Technology Nanjing210023 China University of Science and Technology Beijing School of Computer and Communication Engineering Beijing100083 China SRM University Department of Computational Intelligence School of Computing SRM Nagar TN Kattankulathur603203 India The Amity University School of Engineering UP Noida201301 India The King Abdullah II School of Information Technology The University of Jordan Amman11942 Jordan

Marine Wireless Rechargeable Sensor Networks (MWRSNs), enhanced by recent Wireless Power Transfer (WPT) technology, present a significant advancement in extending network life. Traditional methods improve network performance through algorithm optimization, but neglect charging security, exposing networks to potential attacks. This paper addresses this problem from an adversarial view and develops a novel attack for MWRSN through Denying of Charge (DoC) to maximize network destructiveness. We start by establishing a generalized on-demand charging model, essential for developing DoC tactics. Subsequently, we unveil the Collaborative DoC (CoDoC) algorithm, capable of manipulating and falsifying charging requests. Central to CoDoC is the Request Prediction Method (RPM), which forecasts the initiation of charging requests and facilitates rapid request surges to enhance the attack's efficacy. CoDoC is able to disguise the presence of the attack, which is able to escape from being detected by the base station. Theoretical analyses are provided to explore the features of the proposed scheme. To demonstrate the outperformed features of the proposed schemes, extensive simulations and test-bed experiments are conducted. Our analysis and extensive simulations demonstrate that CoDoC increases sensor node failures by 20% to 142% compared to traditional methods, highlighting its effectiveness in marine environments. © 2002-2012 IEEE.

关键词： Charging stations

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LarTap: A Luminance-aware Framework with Text-correlation Priors for Multi-Exposure Image Fusion

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IEEE Transactions on Circuits and Systems for Video Technology 2025年

作者： Wang, Enlong Li, Jiawei Yan, Tiantian Lei, Jia Zhou, Shihua Wang, Bin Liu, Jinyuan Kasabov, Nikola K. Dalian University Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian116622 China University of the Science and Technology Beijing School of Computer and Communication Engineering Beijing100083 China Xi’an Jiaotong University School of Software Engineering Shaanxi Xi’an710049 China Dalian Univer sity of Technology School of Mechanical Engineering Dalian116024 China Auckland University of Technology Knowledge Engineering and Discovery Research Institute Auckland1061 New Zealand

Conventional imaging devices often struggle to produce high-dynamic-range (HDR) images that accurately represent natural scenes. To overcome this limitation, multi-exposure image fusion (MEF) techniques have been introduced as a viable solution. Existing MEF approaches aim to enhance performance by optimizing or searching architectures. However, they face challenges in precise feature extraction and scene reconstruction, leading to distortion in the fused images. Additionally, most methods do not adequately address luminance variations across different image regions, which may result in the loss of essential details. To address these challenges, we present a novel luminance-aware MEF framework that integrates text-correlation priors (LarTap). By embedding textual information into fusion process, the proposed framework enhances content extraction and comprehension. Specifically, it consist of two key components: the text-image correlation network (N1) and the multi-exposure fusion network (N2). First, N1 performs correlation training to achieve a holistic alignment between text and image pairs. Its iterative vision encoders (VEs) generate text-correlated prior knowledge to facilitate the fusion process in N2. Second, N2 leverages these priors for scene reconstruction and dynamically adjusts luminance based on comparative perception. Extensive experiments on multiple datasets demonstrate that LarTap outperforms state-of-the-art methods. © 1991-2012 IEEE.

关键词： Image correlation

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AAV Virtual Antenna Array Deployment for Uplink Interference Mitigation in Data Collection Networks

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IEEE Internet of Things Journal 2025年第8期12卷 10834-10850页

作者： Li, Hongjuan Kang, Hui Sun, Geng Li, Jiahui Wang, Jiacheng Wang, Xue Niyato, Dusit Leung, Victor C. M. Jilin University College of Computer Science and Technology Changchun 130012 China Jilin University College of Computer Science and Technology Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Changchun 130012 China Nanyang Technological University College of Computing and Data Science Jurong West Singapore Jilin University Department of Communication Engineering Changchun 130012 China Artificial Intelligence Research Institute Shenzhen MSU-BIT University Shenzhen 518115 China Shenzhen University College of Computer Science and Software Engineering Shenzhen 518060 China The University of British Columbia Department of Electrical and Computer Engineering Vancouver V6T 1Z4 BC Canada

Autonomous aerial vehicles (AAVs) have gained considerable attention as a platform for establishing aerial wireless networks and communications. However, the Line of Sight (LoS) dominance in air-to-ground (A2G) communications often leads to significant interference with terrestrial networks, reducing communication efficiency among terrestrial terminals. This article explores a novel uplink interference mitigation approach based on the collaborative beamforming (CB) method in multi-AAV network systems. Specifically, the AAV swarm forms an AAV-enabled virtual antenna array (VAA) to achieve the transmissions of gathered data to multiple base stations (BSs) for data backup and distributed processing. However, there is a tradeoff tradeoff between the effectiveness of CB-based interference mitigation and the energy conservation of AAVs. Thus, by optimizing the excitation current weights and hover position of AAVs as well as the sequence of data transmission to various BSs, we formulate an uplink interference mitigation multiobjective optimization problem (MOOP) to decrease interference affection, enhance transmission efficiency, and improve energy efficiency, simultaneously. In response to the computational demands of the formulated problem, we introduce an evolutionary computation method, namely chaotic nondominated sorting genetic algorithm II (CNSGA-II) with multiple improved operators. The proposed CNSGA-II efficiently addresses the formulated MOOP, outperforming several other comparative algorithms, as evidenced by the outcomes of the simulations. Moreover, the proposed CB-based uplink interference mitigation approach can significantly reduce the interference caused by AAVs to nonreceiving BSs. © 2014 IEEE.

关键词： autonomous aerial vehicle (AAV) network Collaborative beamforming (CB) evolutionary computation interference mitigation multiobjective optimization

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NewBalance: Efficient Data Space Management and Algorithmic Optimization for Large-Scale Storage Systems

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Chinese Journal of Electronics 2017年第3期26卷 493-501页

作者： XU Guangping LIN Sheng SHI Kai ZHANG Hua Tianjin Key Laboratory of Intelligence Computing and New Software Technology Computer and Communication Engineering School Tianjin University of Technology

Fragmentation usually occurs when data space of original storage nodes has to be reallocated to new added storage nodes during the scale-out evolution of the large-scale storage *** greatly influences its performance and becomes a challenge to manage the whole *** present an efficient space management framework,called New Balance,to reduce fragmentation with the minimum data movement while keeping the storage system load *** space management framework has two phases including the collection phase and the allocation *** the collection phase,we propose a novel algorithm,called the greedy bi-direction collector,which collects enough space for the new storage *** the allocation phase,we formally represent it as a variant of the bin packing problem and then utilize some bin packing heuristics including the first fitting and the best fitting to allocate collected intervals to new added storage *** experimental results show that the amount of intervals can be reduced by 20%;5%and our algorithmic optimization improves the data lookup performance by at least 10%and the scale-out performance by 2X;X.

关键词： Large-scale storage systems Space management Algorithmic optimization Performance evaluation

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Performance of CO-OFDM system with RS-Turbo concatenated code

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Optoelectronics Letters 2015年第6期11卷 457-460页

作者：童峥嵘胡桂彬曹晔张卫华 Key Laboratory of Film Electronics and Communication Devices and Key Laboratory of Intelligent Computing and Novel Software Technology Tianjin University of Technology

In this paper,the RS-Turbo concatenated code is applied to coherent optical orthogonal frequency division multiplexing(CO-OFDM) ***(186,166,8) and Turbo code with code rate of 1/2 are employed for RS-Turbo concatenated *** decoding algorithms,which are Max-Log-MAP algorithm and Log-MAP algorithm,are adopted for Turbo decoding,and the iteration Berlekamp-Massey(BM) algorithm is adopted for RS *** simulation results show that the bit error rate(BER) performance of CO-OFDM system with RS-Turbo concatenated code is significantly improved at high optical signal to noise ratio(OSNR),and the iteration number is reduced compared with that of the Turbo coded ***,when the Max-Log-MAP algorithm is adopted for Turbo decoding,the transmission distance of CO-OFDM system with RS-Turbo concatenated code can reach about 400 km without error,while that of the Turbo coded system can only reach about 240 km when BER is lower than 10^(-4) order of magnitude.

关键词： OFDM系统 RS解码 Max-Log-MAP算法性能 Turbo码正交频分复用解码算法光信噪比

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Research on the transmission performance of turbo codes in DDO-OFDM system

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Optoelectronics Letters 2015年第2期11卷 134-136页

A direct detection optical orthogonal frequency division multiplexing(DDO-OFDM)system using turbo codes is built,and the transmission performance comparison between coded system and uncoded system is *** decoding algorithms,which are Log-maximum a posteriori(MAP),Max-Log-MAP and threshold Max-Log-MAP,are used in the turbo coded *** comparing three decoding algorithms,the system using Max-Log-MAP algorithm has the best bit error rate(BER)*** the transmission distance of 240 km,the uncoded system with transmission rate of 30 Gbit/s can get the BER performance at the degree of 8.93×10-3 with optical signal to noise ratio(OSNR)of24 d B,while the turbo coded system with transmission rate of 50 Gbit/s can achieve it within OSNR of 20 d B.

关键词： Bit error rate Decoding Error statistics Frequency division multiplexing Optical communication Optical signal processing Signal to noise ratio Turbo codes

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Simultaneous measurement of refractive index, temperature and strain based on core diameter mismatch and polarization-maintaining FBG

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Optoelectronics Letters 2013年第3期9卷 238-240页

作者：童峥嵘王洁玉张卫华曹晔 Key Laboratory of Film Electronics and Communication Devices and Key Laboratory of Intelligent Computing and Novel Software Technology School of Computer and Communication Engineering Tianjin University of Technology

A kind of fiber-optic sensor for simultaneous measurement of refractive index of surrounding medium, temperature and strain is described. Based on core diameter mismatch, a multimode-single mode-multimode (MSM) structure is presented. It is demonstrated that the three parameters can be measured respectively by the interference of the core mode and cladding modes excited in the single mode fiber (SMF). Then combined with a polarization-maintaining fiber Bragg grating (PMFBG) which has different sensing properties from MSM structure, three parameters are measured simultaneously. The experimental results show that PMFBG is insensitive to the refractive index and the refractive index sensitivity of the MSM structure is 96.04 nm·RIU^(-1); the temperature sensitivities of the characteristic wavelength for MSM structure and the center wavelengths of fast and slow axes for PMFBG are 0.0911 nm °C^(-1), 0.00976 nm °C^(-1) and 0.0105 nm °C^(-1), respectively; the strain sensitivities of those are -0.013 nm με^(-1), 0.012 nm με^(-1) and 0.012 nm με^(-1), respectively.

关键词：温度敏感性应变灵敏度同时测量折射率不匹配光纤光栅直径 MSM结构

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