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DIG: Improved DINO for Graffiti Detection

IEEE Transactions on Systems, Man, and Cybernetics: Systems 2025年第5期55卷 3557-3569页

作者： Wang, Bingshu Mao, Qianchen Liu, Aifei Chen, Long Chen, C. L. Philip Northwestern Polytechnical University School of Software Xi’an710129 China Shenzhen University Guangdong Key Laboratory of Intelligent Information Processing Shenzhen Key Laboratory of Media Security Shenzhen518060 China University of Macao Department of Computer and Information Science China South China University of Technology School of Computer Science and Engineering Guangzhou510641 China

Graffiti detection is essential in historic building protection and urban neighborhood management. Graffiti detection has made significant progress in recent years based on the development of deep learning. However, small-scale graffiti, interference from the background, and the false detection of word parts in graffiti make it a challenging problem. This article proposes a Transformer-based high-precision graffiti detection method, namely DIG. Precisely, it consists of three modules: 1) Spatial query selection (SQS), scale-aware IoU loss (SIL);2) Denoising Task with binary contrastive denoising (BCDN);and 3) IoU-guided box denoising (IBD) modules. To detect small-scale graffiti, this paper proposes SIL to help the loss function to perceive small-scale graffiti and large-scale graffiti fairly. To reduce the false detection of word parts, this article presents the SQS module, which integrates spatial information into the query selection process of the Encoder to filter out falsely detected bounding boxes within the graffiti. To reduce the interference from the background, this article introduces a denoising task with BCDN and IBD modules, improving the model’s ability to distinguish graffiti from the background and accurately select appropriate bounding boxes. A large number of experimental results on the STORM dataset show that our method achieves state-of-the-art results with an AP50 of 87.9%. Moreover, DIG achieved competitive results on the FineFM dataset for mask detection. This indicates that DIG can also be conveniently transferred to detect other scenarios. © 2013 IEEE.

关键词： Historic preservation

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Edge-Cloud Cooperation-Driven Intelligent Sustainability Evaluation Strategy Based on IoT and CPS for Energy-Intensive Manufacturing Industries

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IEEE Internet of Things Journal 2025年第9期12卷 12287-12297页

作者： Ma, Shuaiyin Huang, Yuming Chen, Yanping Xiao, Qinge Xu, Jun Leng, Jiewu Xi’an University of Posts and Telecommunications Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing Xi’an Key Laboratory of Big Data and Intelligent Computing School of Computer Science and Technology Xi’an710121 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Xidian University Advanced Manufacturing Technology Innovation Center Guangzhou Institute of Technology Guangzhou510555 China Guangdong University of Technology Guangdong Provincial Key Laboratory of Computer Integrated Manufacturing System State Key Laboratory of Precision Electronic Manufacturing Technology and Equipment Guangzhou510006 China

The advancement of the Industry 5.0 in information technology has led to increased interest in integrating edge-cloud cooperation with Internet of Things (IoT) and cyber-physical system (CPS) designs. This integration effectively reduces service delays and provides real-time analysis feedback to physical spaces, attracting attention from both academia and industry. These advanced technologies enhance production system intelligence, their alignment with circular economy principles for promoting sustainability has been overlooked. To address this gap, this article proposes an intelligent sustainability evaluation strategy driven by edge-cloud cooperation, IoT, and CPS. The proposed approach aims to enhance production sustainability and intelligence through circular economy perspectives. It introduces improved gray relation analysis and deep clustering network techniques to extract meaningful insights from diverse indicators within the evaluation system. By analyzing relationships between different equipment and workshops, it provides an analytical method that enhances production efficiency while reducing energy consumption and resource waste. To further validate the proposed method, an illustrative example using a partner company’s production data demonstrates its accuracy. © 2014 IEEE.

关键词： Circular economy

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An Evolutionary Multitasking Algorithm for Efficient Multiobjective Recommendations

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2025年第3期6卷 518-532页

作者： Tian, Ye Ji, Luke Hu, Yiwei Ma, Haiping Wu, Le Zhang, Xingyi Anhui University Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Hefei230601 China Anhui University Institutes of Physical Science and Information Technology Hefei230601 China Hefei University of Technology Key Laboratory of Knowledge Engineering with Big Data Hefei230029 China

Represented by evolutionary algorithms and swarm intelligence algorithms, nature-inspired metaheuristics have been successfully applied to recommender systems and amply demonstrated effectiveness, in particular, for multiobjective recommendation. Owing to the population-based search paradigm, these algorithms can produce a number of recommendation lists, making diverse tradeoffs between multiple metrics and meeting the requirements of accuracy, novelty, diversity, and other user preferences. However, these algorithms are criticized for the low efficiency of the optimization process, especially when the number of users is large. To address this issue, this article proposes an evolutionary multitasking-based recommendation method, where each task corresponds to a user and all the tasks are optimized simultaneously, thus highly improving the efficiency of recommendation. To enhance the convergence speed, all the users are divided into multiple populations according to the similarity between their preferences, where each population evolves with internal knowledge transfer between users, and all the populations evolve with external knowledge transfer between populations. Experimental results on various datasets verify that the proposed method can better balance between multiple metrics than classical and deep neural network-based recommendation methods and exhibits significantly higher efficiency than evolutionary multiobjective optimization-based recommendation methods. © 2024 IEEE. All rights reserved.

关键词： Multiobjective optimization

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A data representation method using distance correlation

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Frontiers of computer Science 2025年第1期19卷 1-14页

作者： Xinyan LIANG Yuhua QIAN Qian GUO keyin ZHENG Institute of Big Data Science and Industry Shanxi UniversityTaiyuan 030006China Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education Shanxi UniversityTaiyuan 030006China School of Computer Science and Technology Taiyuan University of Science and TechnologyTaiyuan 030024China Shanxi Key Laboratory of Big Data Analysis and Parallel Computing Taiyuan University of Science and TechnologyTaiyuan 030024China

Association in-between features has been demonstrated to improve the representation ability of data. However, the original association data reconstruction method may face two issues: the dimension of reconstructed data is undoubtedly higher than that of original data, and adopted association measure method does not well balance effectiveness and efficiency. To address above two issues, this paper proposes a novel association-based representation improvement method, named as AssoRep. AssoRep first obtains the association between features via distance correlation method that has some advantages than Pearson’s correlation coefficient. Then an improved matrix is formed via stacking the association value of any two features. Next, an improved feature representation is obtained by aggregating the original feature with the enhancement matrix. Finally, the improved feature representation is mapped to a low-dimensional space via principal component analysis. The effectiveness of AssoRep is validated on 120 datasets and the fruits further prefect our previous work on the association data reconstruction.

关键词： association representation distance correlation classification

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Enhancing GNSS Signal Authentication through Multi-Antenna Systems

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IEEE Transactions on Wireless Communications 2025年第5期24卷 4361-4376页

作者： Tan, Haijun Xie, Ning Huang, Lei Li, Hongbin Pengcheng National Laboratory of China Control and Network Foundation Laboratory Shenzhen518107 China Shenzhen University State Key Laboratory of Radio Frequency Heterogeneous Integration Guangdong Key Laboratory of Intelligent Information Processing College of Electronics and Information Engineering Shenzhen518060 China Stevens Institute of Technology Department of Electrical and Computer Engineering HobokenNJ07030 United States

The Global Navigation Satellite System (GNSS) receiver has become indispensable in navigation applications due to its affordability and reliable accuracy. Despite its widespread use, GNSS is vulnerable to manipulation by malicious entities within the inherently insecure wireless landscape. This paper proposes innovative GNSS signal authentication strategies that employing multiple antennas to counteract spoofing attacks. Leveraging a multi-antenna framework enhances the distinguishability of spoofing signals over traditional single-antenna configurations. Importantly, the proposed approaches capitalize on spatial characteristics, which are independent of the GNSS signal's intrinsic features, to accurately identify spoofing attacks. Specifically, we propose a Direction-of-Arrival (DOA)-based authentication scheme to address scenarios where authentic signals are blocked during spoofing attacks. Additionally, for situations where both authentic and spoofing signals coexist at the receiver, we propose a Spatial Filter (SF)-based authentication scheme. Through rigorous theoretical analysis and comprehensive simulations, we not only validate the proposed schemes but also demonstrate their robustness and effectiveness in enhancing GNSS signal security. The simulation results, aligning closely with theoretical predictions, underscore the superiority of the proposed schemes in safeguarding against spoofing threats. © 2002-2012 IEEE.

关键词： Satellite antennas

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Weakly Coupled 19-Core 5-Mode-Group Ring Core Fiber for Dense Space-Division Multiplexing

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Journal of Lightwave technology 2025年第10期43卷 4959-4966页

作者： Chen, Kaihui Tu, Jiajing Xie, Zhiyuan Ye, Haiqin Chen, Yingyu Liu, Zhibing Li, Jinpei Xiao, Yongguan Shi, Yuetong Shen, Lei Lou, Jie Gao, Shecheng Li, Zhaohui Sun Yat-sen University School of Electronics and Information Technology Guangdong Provincial Key Laboratory of Optoelectronic Information Processing Chips and Systems Guangzhou510006 China Southern Marine Science and Engineering Guangdong Laboratory Zhuhai519000 China Jinan University Department of Electronic Engineering School of Information Science and Technology Guangzhou510632 China Yangtze Optical Fiber and Cable Joint Stock Limited Company State Key Laboratory of Optical Fiber and Cable Manufacture Technology Wuhan430073 China

We propose a 19-core 5-mode-group ring-core fiber capable of supporting up to 380 spatial channels. Each core can support 5 orbital angular momentum (OAM) mode groups (MGs) with topological charge (l) ranging from 1 to 5, all of which have a radial order of 1. In each MG, the number of degenerate modes is 4, which indicates that the scale of multiple-input multiple-output digital signal processing (MIMO-DSP) can be fixed at 4 × 4 at the receiver side. To maintain weak inter-MG coupling, our fiber design focuses on achieving a large effective index difference (Δ neff) between OAM MGs and minimizing the mode field overlap. The fiber consists of 19 trench-assisted ring cores arranged in a compact cladding region, with a large core pitch to reduce inter-core crosstalk. We conduct thorough optical and communication performance evaluations on the fabricated fiber. Experimental results show that the crosstalk between adjacent lower-order MGs (l=1, 2, 3) is below - 30dB/km, and that between higher-order MGs (l = 3, 4, 5) is below - 27dB/km. We also demonstrate the transmission capability of this fiber by multiplexing five OAM MGs across three cores over a 3.5km span in the C band. Each channel transmits a 24-Gbaud dual-polarization quadrature phase shift keying (QPSK) signal, with signal impairments compensated using a 4 × 4 MIMO-DSP algorithm. All signals achieve a bit error rate (BER) below the 20% soft-decision forward error correction (FEC) threshold. Given its low inter-channel crosstalk and robust communication performance, this fiber holds good promise for supporting ultra-high-capacity optical transmission systems. © 1983-2012 IEEE.

关键词： Forward error correction

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Bilateral Pricing for Dynamic Association in Federated Edge Learning

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IEEE Transactions on Mobile Computing 2025年第06期24卷 4684-4697页

作者： Pan, Bangqi Lu, Jianfeng Cao, Shuqin Liu, Jing Tian, Wenlong Li, Minglu Wuhan University of Science and Technology School of Computer Science and Technology Wuhan430065 China Wuhan University of Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System China Dalian University of Technology Ministry of Education Key Laboratory of Social Computing and Cognitive Intelligence China University of South China School of Computer Science and Technology Hengyang421001 China Zhejiang Normal University School of Computer Science and Technology Jinhua321004 China

Devices and servers in Federated Edge Learning (FEL) are self-interested and resource-constrained, making it critical to design incentives to improve model performance. However, dynamic network conditions raise energy consumption, while data heterogeneity undermines device cooperation. Current research overlooks the interplay between system efficiency and device clustering, resulting in suboptimal updates. To address these challenges, we develop BENCH, a bilateral pricing mechanism consisting of three core rules aimed at incentivizing participation from both devices and servers. Specifically, we first design a reward allocation rule, based on the Rubinstein bargaining model, which dynamically allocates rewards. Theoretically, we derive a closed-form solution for this rule, demonstrating BENCH achieves Nash equilibrium. Secondly, we design a device partitioning rule that leverages modularity to group similar devices, facilitating personalized edge aggregation to accelerate local data adaptation. Thirdly, we design an edge matching rule that employs the Kuhn-Munkres algorithm to balance the load at edge servers, thus minimizing the congestion. Together, these three rules enable hierarchical optimization of pricing and associations, effectively mitigating the impact of dynamic costs and device heterogeneity. Extensive experiments demonstrate BENCH's effectiveness in increasing device participation by 28.81% and improving model performance by 2.66% compared to state-of-the-art baselines. © 2002-2012 IEEE.

关键词： Mobile edge computing

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Flexible Pressure Sensor Realized by a Chirped Fiber Bragg Grating Pair for Vital Signs Monitoring

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Journal of Lightwave technology 2025年第10期43卷 4778-4786页

作者： Liu, Chang Liu, Ziqi Wang, Pingping Peng, Dongxian Liu, Zhengyong Sun Yat-sen University School of Electronics and Information Technology Guangdong Provincial Key Laboratory of Optoelectronic Information Processing Chips and Systems Guangzhou510006 China Zhujiang Hospital Southern Medical University Obstetrics and Gynecology Center Department of Gynecology Guangzhou510280 China Zhuhai519082 China

A chirped Fabry-Perot interferometric (CFPI) pressure sensor based on two cascaded chirped 50-micron fiber Bragg gratings is proposed in this paper. Two packaging architectures of linear and circular structures using polydimethylsiloxane (PDMS) are demonstrated, while the latter one significantly improves pressure sensitivity owing to the annular light path in the FP cavity. Compared to the linear packaging configuration, the circular structure exhibits 3.438 times higher sensitivity in terms of wavelength drift with pressure, and a 21.307-fold increase in electrical signal sensitivity to pressure changes. Furthermore, the sensor was employed to measure pulse waveform on the wrist, and blood predictions were made using a convolutional neural network and long short-term memory (CNN-LSTM) model. As a result, the measurement errors for systolic blood pressure (SBP) and diastolic blood pressure (DBP) were -0.122±2.781 mmHg and 0.051±1.711 mmHg, respectively, which meet the standards set by the American Association for the Advancement of Medical Devices (AAMI). The proposed sensor employs a narrowband laser as light source and a photodiode for demodulation, showing the potential of miniaturization and cost reduction in sensing devices while maintaining high sensitivity. Additionally, the flexible sensor structure showcases the feasibility of a simple and highly accurate real-time medical wearable device, offering a promising solution for daily health monitoring. © 1983-2012 IEEE.

关键词： Fabry-Perot interferometers

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Optimization of OFDM LiDAR-Communication Integration System using MIMO and PSO

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IEEE Photonics technology Letters 2025年第12期37卷 655-658页

作者： Cao, Minghua Zhang, Lingyun Zhang, Yue Han, Shengchun Zhang, Xia Shi, Xinhui Lanzhou University of Technology School of Computer and Communication Lanzhou Gansu730050 China Liaocheng University School of Physics Science and Information Engineering Shandong Provincial Key Laboratory of Optical Communications Science and Technology Liaocheng Shandong252000 China

To enhance the anti-interference capability of the orthogonal frequency division multiplexing (OFDM) light detection and ranging (LiDAR)-communication integration system, a multiple input multiple output (MIMO)-OFDM LiDAR-communication integration system is proposed. The system employs MIMO spatial diversity techniques to ensure signal quality and utilizes the particle swarm optimization (PSO) algorithm to optimize the power distribution of LiDAR resource units (RUs). Simulation results demonstrate that, in the 4×4 MIMO configuration, the proposed system achieves a minimum of 7 dB improvement in bit error rate (BER) performance compared to conventional OFDM systems. Additionally, it reduces the peak sidelobe ratio (PSLR) and integrated sidelobe ratio (ISLR) in the range direction by 12.91 dB and 11.92 dB, respectively. Following PSO optimization, the system further decreases the ISLR in the velocity direction by 15.49 dB. © 2025 IEEE.

关键词： Orthogonal frequency division multiplexing

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LOG: A Local-to-Global Optimization Approach for Retrieval-based Explainable Multi-Hop Question Answering 31

LOG: A Local-to-Global Optimization Approach for Retrieval-b...

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31st International Conference on Computational Linguistics, COLING 2025

作者： Xu, Hao Zhao, Yunxiao Zhang, Jiayang Wang, Zhiqiang Li, Ru School of Computer and Information Technology Shanxi University Taiyuan China Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education Shanxi University Taiyuan China

ISBN: (纸本)9798891761964

Multi-hop question answering (MHQA) aims to utilize multi-source intensive documents retrieved to derive the answer. However, it is very challenging to model the importance of knowledge retrieved. Previous approaches primarily emphasize single-step and multi-step iterative decomposition or retrieval, which are susceptible to failure in long-chain reasoning due to the progressive accumulation of erroneous information. To address this problem, we propose a novel Local-tO-Global optimized retrieval method (LOG) to discover more beneficial information, facilitating the MHQA. In particular, we design a pointwise conditional V-information based local information modeling to cover usable documents with reasoning knowledge. We also improve tuplet objective loss, advancing multi-examples-aware global optimization to model the relationship between scattered documents. Extensive experimental results demonstrate our proposed method outperforms prior state-of-the-art models, and it can significantly improve multi-hop reasoning, notably for long-chain reasoning. Our code is available at https://***/yunxiaomr/LOG. © 2025 Association for Computational Linguistics.

关键词： Question answering

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