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research on Low Overhead Fast Repair Array Code Algorithm

International Journal of Network Security 2025年第3期27卷 594-604页

作者： Xiong, Pan Hong, Tieyuan Wang, Yuheng Tang, Dan Cai, Hongliang Zhang, Junyan School of Software Engineering Chengdu University of Information Technology Sichuan Province Engineering Technology Research Center of Support Software of Informatization Application Chengdu610225 China

With the growth of exponential data, disk data storage is becoming increasingly important. In the storage system, single-disk and dual-disk loss are more and more serious. To ensure the efficiency and speed of data restoration is crucial to the reliability of the storage system. The Row Diagonal Parity Code (RDP) indicates that the combined recovery algorithm can reduce the total number of disks that are read when a single-disk fault is rectified by 25%. However, when a two-disk fault is rectified, all disk elements must work together. In order to improve the efficiency and speed of single and double disk fault repair, the RDP Code is extended, and a Rapid Rows Diagonal Parity Code (RRDP code) with local repair property is proposed. On the premise of global horizontal coding of RDP code, RRDP code is computed by XOR to generate a local horizontal check column, and it participates in global horizontal redundancy calculation. The local horizontal redundancy check column shortens the repair chain by constructing the"missing diagonal" and then it has the function of local repair. Through theoretical analysis, RRDP code has decent and fast decoding complexity and I/O reading cost of single and dual disk fault repair under the premise of constant coding cost, which greatly saves the fault repair cost. © (2025), (International Journal of Network Security). All rights reserved.

关键词： Restoration

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A Hierarchical Approach based Energy Consumption Optimization of Industrial Robots

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IEEE Transactions on Automation Science and engineering 2025年 22卷 15177-15187页

作者： Xiao, Wei Chen, Xubing Fu, Zhongtao Han, Guirong Wuhan Institute of Technology School of Mechanical & Electrical Engineering Wuhan430205 China Hubei Research Center of Intelligent Welding Equipment and Software Engineering Technology Wuhan430205 China

Due to the wide application and low energy efficiency of industrial robots (IRs), energy consumption (EC) optimization techniques for them have attracted increasing attention. At present, the methods for optimizing the EC of IRs are generally simple. Energy saving for IRs through conventional methods is always achieved through optimizing the joint trajectory, which generally requires pre-planning of the joint trajectory and has limited energy efficiency improvement. Besides, it is time and labor consuming. In this paper, a hierarchical EC optimization method for IRs based on inverse kinematics solution and dynamic time-scaling method based on modified particle swarm optimization (DTS-MPSO) is proposed, with the previously established EC prediction model. For the primary EC optimization, inverse kinematics for the joint angles is performed firstly under a given initial operating posture of the IRs, then the set of joint angles with the lowest EC is selected. In the secondary EC optimization process, DTS-MPSO optimization is applied to further minimize the EC of IRs. Verification experiments with an ABB robot were conducted according to the joint angles obtained through inverse kinematics and those after secondary optimization. It is proved that EC is saved by 10.68% and 39.27% by the inverse kinematics and DTS-MPSO method respectively. The single EC for the robot to move from the initial posture to the initial operating posture was reduced by 45.76% in total when it operated under the trajectory after hierarchical optimization. The EC is effectively saved, and the trajectory for minimum EC can be automatically planned with this method. © 2004-2012 IEEE.

关键词： Industrial robots

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A Helmet Detection Algorithm Based on Transformers with Deformable Attention Module

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Chinese Journal of Electronics 2025年第1期34卷 229-241页

作者： Songle Chen Hongbo Sun Yuxin Wu Lei Shang Xiukai Ruan Engineering Research Center of Post Big Data Technology and Application of Jiangsu Province Nanjing University of Posts and Telecommunications State Key Lab for Novel Software Technology Nanjing University Institute of Intelligent Locks Wenzhou University

Wearing a helmet is one of the effective measures to protect workers' safety. To address the challenges of severe occlusion, multi-scale, and small target issues in helmet detection, this paper proposes a helmet detection algorithm based on deformable attention transformers. The main contributions of this paper are as follows. A compact end-to-end network architecture for safety helmet detection based on transformers is proposed. It cancels the computationally intensive transformer encoder module in the existing detection transformer(DETR) and uses the transformer decoder module directly on the output of feature extraction for query decoding, which effectively improves the efficiency of helmet detection. A novel feature extraction network named Swin transformer with deformable attention module(DSwin transformer) is proposed. By sparse cross-window attention, it enhances the contextual awareness of multi-scale features extracted by Swin transformer, and keeps high computational efficiency simultaneously. The proposed method generates the query reference points and query embeddings based on the joint prediction probabilities, and selects an appropriate number of decoding feature maps and sparse sampling points for query decoding, which further enhance the inference capability and processing speed. On the benchmark safety-helmet-wearing-dataset(SHWD), the proposed method achieves the average detection accuracy mAP@0.5 of 95.4% with 133.35G floating-point operations per second(FLOPs) and 20 frames per second(FPS), the state-of-the-art method for safety helmet detection.

关键词： Head Accuracy Network architecture Benchmark testing Transformers Feature extraction Safety Decoding Computational efficiency Detection algorithms

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A sharding blockchain-based UAV system for search and rescue missions

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Frontiers of Computer Science 2025年第3期19卷 103-118页

作者： Xihan ZHANG Jiashuo ZHANG Jianbo GAO Libin XIA Zhi GUAN Hao HU Zhong CHEN School of Computer Science Peking UniversityBeijing 100871China Peking University Chongqing Research Institute of Big Data Chongqing 401329China National Engineering Research Center for Software Engineering Peking UniversityBeijing 100871China State Key Lab for Novel Software Technology Nanjing UniversityNanjing 210023China

Sharding is a promising technique to tackle the critical weakness of scalability in blockchain-based unmanned aerial vehicle(UAV)search and rescue(SAR)*** breaking up the blockchain network into smaller partitions called shards that run independently and in parallel,shardingbased UAV systems can support a large number of search and rescue UAVs with improved scalability,thereby enhancing the rescue ***,the lack of adaptability and interoperability still hinder the application of sharded blockchain in UAV SAR *** refers to making adjustments to the blockchain towards real-time surrounding situations,while interoperability refers to making cross-shard interactions at the mission *** address the above challenges,we propose a blockchain UAV system for SAR missions based on dynamic sharding *** from the benefits in scalability brought by sharding,our system improves adaptability by dynamically creating configurable and mission-exclusive shards,and improves interoperability by supporting calls between smart contracts that are deployed on different *** implement a prototype of our system based on Quorum,give an analysis of the improved adaptability and interoperability,and conduct experiments to evaluate the *** results show our system can achieve the above goals and overcome the weakness of blockchain-based UAV systems in SAR scenarios.

关键词： blockchain sharding unmanned aerial vehicle search and rescue blockchain interoperability

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3DGCformer: 3-Dimensional Graph Convolutional transformer for multi-step origin–destination matrix forecasting

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Applied Intelligence 2025年第6期55卷 1-18页

作者： Huang, Yiou Deng, Hao Zhao, Shengjie School of Computer Science and Technology Tongji University Shanghai China Key Laboratory of Embedded System and Service Computing Shanghai China Engineering Research Center of Key Software Technologies for Smart City Perception and Planning Ministry of Education Shanghai China

Forecasting Human mobility is of great significance in the simulation and control of infectious diseases like COVID-19. To get a clear picture of potential future outbreaks, it is necessary to forecast multi-step Origin–Destination (OD) matrices for a relatively long period in the future. However, multi-step Origin–Destination Matrix Forecasting (ODMF) is a non-trivial problem. First, previous ODMF models only forecast the OD matrix for the next time-step, and they cannot perform well on long-term multi-step forecasts due to error accumulation. Second, many ODMF methods capture spatial and temporal dependencies with separate modules, which is insufficient to model spatio-temporal correlations in the time-varying OD matrix sequence. To address the challenges in multi-step ODMF, we propose 3-Dimensional Graph Convolutional Transformer (3DGCformer). As an enhancement of the original 3DGCN, we propose a novel Origin–Destination Feature Propagation (ODFP) rule between 3DGCN layers and integrate 2 3DGCNs with different spatio-temporal graphs and corresponding feature propagation rules to model the formation of OD flows in a more comprehensive way. For multi-step forecasts, 3DGCformer uses Transformer to capture long-term global temporal dependency, and adapt its decoder using labeled tokens to avoid error accumulation and improve time efficiency. To avoid information loss as the number of regions increases, we propose a patch embedding approach to convert data from 3DGCNs to the Transformer module. We perform extensive experiments on 4 real-world human mobility datasets, and the results show that our proposed model outperforms the state-of-the-art methods. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Convolution

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Two Compact Hybrid Band-Pass Filters Using Eighth-Mode Substrate-Integrated Waveguide and Microstrip Resonators

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Progress in Electromagnetics research C 2025年 151卷 167-175页

作者： Tang, Luyao Han, Wei Wei, Hao Li, Yanbin The 54th Research Institute of China Electronics Technology Group Corporation China National Engineering Reasearch Center of Communication Software and Asic Design China

Two compact substrate-integrated waveguide (SIW) filters with hybrid coupling of eighth-mode substrate integrated waveg-uide (EMSIW) resonators and microstrip are proposed in this paper. Hybrid coupled filters were achieved by etching two half-wavelength microstrip resonators (BPF I) or two quarter-wavelength microstrip resonators (BPF II) on the top of traditional second-order EMSIW filters. The topology of the two filters was analyzed. Due to the cross coupling between resonator 1 and resonator 4, two transmission zeros were achieved outside the band of BPF I, which increased the selectivity of the filter. Due to the mixed electromagnetic coupling between resonator 2 and resonator 3, a transmission zero is realized in the stopband of BPF II. To confirm the validity of the two filter models, two filters were designed, produced, and measured. Based on the findings of the measurements, the central frequency of BPF I is recorded at 7.7 GHz, with a fractional bandwidth (FBW) of 18.2%. The insertion loss (IL) within the passband is minimal at 0.8 dB, and the size of the filter is only 8 mm * 4 mm (0.53λg *0.26λg). The filter exhibits enhanced out-of-band suppression due to the presence of two transmission zeros located at frequencies of 6.4 GHz and 10 GHz. The center frequency of BPF II is 19.5 GHz,; the FBW is 20.5%; the IL within the passband is only 0.49 dB; and the size of the filter is only 2 mm ∗ 2 mm (0.34λg *0.34λg). As a result of the mixed electromagnetic coupling effects, a transmission zero occurs at a frequency of 26.7 GHz. The simulation outcomes are consistent with the experimental findings. Compared with other reported SIW filters, the two filters introduced in this study exhibit favorable characteristics such as reduced insertion loss and compact dimensions. © 2025, Electromagnetics Academy. All rights reserved.

关键词： Bandpass filters

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Credible Negotiation for Multi-agent Reinforcement Learning in Long-term Coordination

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ACM Transactions on Autonomous and Adaptive Systems 2025年第1期20卷 1-27页

作者： Gu, Tianlong Zhi, Taihang Bao, Xuguang Chang, Liang Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guilin China Engineering Research Center of Trustworthy Ai Jinan University Guangzhou China

The coordination of multi-agent is one of the critical problems in Multi-agent Reinforcement Learning (MARL). The traditional methods of MARL focus on finding a stochastically acceptable solution called Nash Equilibrium (NE) for all agents from the Markov Game in which multiple equilibria exist. However, learning a fair equilibrium is crucial for the sustainability and stability of collaboration in the long-term coordination game, especially when the leadership competition exists. In this article, we propose the bi-level reinforcement learning method N-Bi-AC, whose solution is a Pareto improvement for traditional NE, to choose a fair Equilibrium. There are two parts in our method, the first is that we propose the Negotiator to determine the leader in stage game, and the other is to update the Q-value of agents in the game by using a bi-level actor-critic learning method based on the Joint Mixed Strategy Equilibrium Q-learning algorithm (JMSE Q-learning). The convergence proof is given, and the learning algorithm is compared with the state-of-the-art algorithms. We found that the proposed N-Bi-AC method successfully converged to a fair NE, which guarantees the fairness of agents in different matrix game environments. © 2025 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Stochastic systems

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Scalable Motion Estimation and Temporal Context Reinforcement for Video Compression Using RGB Sensors

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IEEE Sensors Journal 2025年第10期25卷 18323-18333页

作者： Huang, Qian Lu, Hao Liu, Wenting Wang, Yiming Hohai University College of Computer Science and Software Engineering Nanjing211100 China Jiangsu Engineering Research Center of Digital Twinning Technology for Key Equipment in Petrochemical Process Changzhou213164 China

We propose a novel deep learned video compression technique, named scalable motion estimation (SME), which is designed for video data generated by sensor systems in smart devices. These devices face unique challenges due to limited bandwidth, constrained computational resources, and the complexity of real-world scenarios. Existing learned video compression methods primarily rely on optical flow for motion estimation;however, optical flow often suffers from inaccuracies and displacement errors, resulting in imprecise motion vectors, and the increasing complexity of models further limits their deployment in resource-constrained environments. To address these issues, the SME framework introduces a hierarchical motion vector enhancement strategy that progressively optimizes motion information in video captured by sensors. In addition, we propose the temporal context reinforcement (TCR) module, which partitions high-dimensional contextual information into three components. Compared to direct context encoding methods, the TCR module optimizes bit allocation, achieving a more balanced distribution of high- and low-frequency information. Extensive experiments on benchmark datasets demonstrate that the SME framework substantially enhances the efficiency and performance of video compression systems on RGB sensor-captured videos, making it particularly suitable for video applications. © 2001-2012 IEEE.

关键词： Optical flows

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Understanding interfacial engineering of surface functionalized boron nitride nanosheets within thermal interface materials

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Science China Materials 2025年第4期68卷 1300-1302页

作者： Gaojie Han Yuezhan Fengg Changyu Shen State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial EquipmentNational Engineering Research Center for Advanced Polymer Processing TechnologyZhengzhou UniversityZhengzhou 450002China

The continuous miniaturization and high-power development of electronic devices have given rise to severe interface thermal issues,which urgently demand highly thermally conductive thermal interface materials(TIMs)to ... 详细信息

关键词： interfacial engineering heat accumulation interface thermal issueswhich thermal interface materials surface functionalized boron nitride nanosheets electronic devices thermal conductivity

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DSCR: A Dynamic Secure Clustering Routing Scheme for UANETs Based on Reputation Mechanism

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IEEE Internet of Things Journal 2025年第10期12卷 14109-14123页

作者： Gong, Yinyan Chen, Yuxiang Li, Kuanching Liang, Wei Li, Xiong Wang, Jin Xiang, Yang Hunan University of Science and Technology School of Computer Science and Engineering Xiangtan411201 China Sanya Research Institute Hunan University of Science and Technology Sanya572024 China School of Computer Science and Engineering Hunan Key Laboratory for Service Computing and Novel Software Technology Xiangtan411201 China Institute for Cyber Security School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China Swinburne University of Technology School of Software and Electrical Engineering HawthornVIC3122 Australia

In UAV ad hoc networks (UANETs), rapid movement of nodes leads to frequent changes in network topology, increasing the risk of packet loss and affecting data transmission. Furthermore, current research on drone clustering lacks security considerations, which reduces the reliability of data transmission. Due to this, improving the stability and reliability of network data transmission in dynamically changing UANETs remains a challenge. In this work, we propose the reputation mechanism dynamically secure cluster routing scheme (DSCR) for UANETs, a design for cluster head election in UANETs using the evaluated value and reputation value of drones and forms clusters through this reputation mechanism to avoid malicious nodes from interfering with the clusters to improve the security of UANETs. We apply a residual link survival time-based intra- and inter-cluster algorithm based on residual link survival time for data forwarding of nodes, optimizing the dynamic routing strategy and reducing the packet loss rate of nodes. In addition, reinforcement learning is used in UANETs to achieve cluster decisions based on the current network state and cluster dynamics, effectively improving the stability of clusters. Experiments were conducted on the proposed method to verify its efficiency and stability. Compared to the ICRA, RICR, and DCA algorithms, the stability of the cluster is improved by 11.92%, 28.12%, and 75.2%, respectively, and the packet loss rate reduced by 41.48%, 44.17%, and 55.74%, demonstrating that DSCR is a compelling dynamic routing solution applicable to UANETs. © 2014 IEEE.

关键词： Drones

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