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Improving Entity Linking in Chinese Domain by Sense Embedding Based on Graph Clustering

Journal of Computer science & technology 2023年第1期38卷 196-210页

作者：张照博钟芷漫袁平鹏金海 National Engineering Research Center for Big Data Technology and System Huazhong University of Science and Technology Wuhan 430074China Service Computing Technology and System Laboratory Huazhong University of Science and Technology Wuhan 430074China Cluster and Grid Computing Laboratory Huazhong University of Science and TechnologyWuhan 430074China School of Computer Science and Technology Huazhong University of Science and TechnologyWuhan 430074China

Entity linking refers to linking a string in a text to corresponding entities in a knowledge base through candidate entity generation and candidate entity *** is of great significance to some NLP(natural language processing)tasks,such as question *** English entity linking,Chinese entity linking requires more consideration due to the lack of spacing and capitalization in text sequences and the ambiguity of characters and words,which is more evident in certain *** Chinese domains,such as industry,the generated candidate entities are usually composed of long strings and are heavily *** addition,the meanings of the words that make up industrial entities are sometimes *** semantic space is a subspace of the general word embedding space,and thus each entity word needs to get its exact ***,we propose two schemes to achieve better Chinese entity ***,we implement an ngram based candidate entity generation method to increase the recall rate and reduce the nesting ***,we enhance the corresponding candidate entity ranking mechanism by introducing sense *** the contradiction between the ambiguity of word vectors and the single sense of the industrial domain,we design a sense embedding model based on graph clustering,which adopts an unsupervised approach for word sense induction and learns sense representation in conjunction with *** test the embedding quality of our approach on classical datasets and demonstrate its disambiguation ability in general *** confirm that our method can better learn candidate entities’fundamental laws in the industrial domain and achieve better performance on entity linking through experiments.

关键词： natural language processing(NLP) domain entity linking computational linguistics word sense disambiguation knowledge graph

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Stochastic Gradient Compression for Federated Learning over Wireless Network

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China Communications 2024年第4期21卷 230-247页

作者： Lin Xiaohan Liu Yuan Chen Fangjiong Huang Yang Ge Xiaohu School of Electronic and Information Engineering South China University of TechnologyGuangzhou 510641China Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Ministry of Industry and Information TechnologyNanjing University of Aeronautics and AstronauticsNanjing 210016China School of Electronic Information and Communications Huazhong University of Science and TechnologyWuhan 430074China

As a mature distributed machine learning paradigm,federated learning enables wireless edge devices to collaboratively train a shared AI-model by stochastic gradient descent(SGD).However,devices need to upload high-dimensional stochastic gradients to edge server in training,which cause severe communication *** address this problem,we compress the communication by sparsifying and quantizing the stochastic gradients of edge *** first derive a closed form of the communication compression in terms of sparsification and quantization ***,the convergence rate of this communicationcompressed system is analyzed and several insights are ***,we formulate and deal with the quantization resource allocation problem for the goal of minimizing the convergence upper bound,under the constraint of multiple-access channel *** show that the proposed scheme outperforms the benchmarks.

关键词： federated learning gradient compression quantization resource allocation stochastic gradient descent(SGD)

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Trial application of the envelope method to the potential ambiguity problem

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Nuclear science and Techniques 2024年第1期35卷 73-80页

作者： Li-Yuan Hu Yu-Shou Song Fundamental Science on Nuclear Safety and Simulation Technology Laboratory Harbin Engineering UniversityHarbin 150001China College of Nuclear Science and Technology Harbin Engineering UniversityHarbin 150001China Key Laboratory of Nuclear Safety and Advanced Nuclear Energy Technology Ministry of Industry and Information TechnologyHarbin 150001China

The optical potential ambiguity is a long-standing problem in the analysis of elastic scattering *** a specific collid-ing system,ambiguous potential families can lead to different behaviors in the nearside and farside scattering *** contrast,the envelope method can decompose the experimental data into two components with negative and positive deflection angles,***,a question arises as to whether the comparison between the calculated nearside(or farside)component and the derived positive-deflection-angle(or negative-deflection-angle)component can help analyze the potential ambiguity *** this study,we conducted a trial application of the envelope method to the potential ambiguity *** envelope method was improved by including uncertainties in the experimental *** colliding systems of 16O+28Si at 215.2 MeV and 12C+12C at 1016 MeV were considered in the *** each colliding system,the angular distribution experimental data were described nearly equally well by two potential sets,one of which is“surface transpar-ent”and the other is *** calculated angular distributions were decomposed into nearside and farside scattering *** the improved envelope method,the experimental data were decomposed into the positive-deflection-angle and negative-deflection-angle components,which were then compared with the calculated nearside and farside *** capability of the envelope method to analyze the potential ambiguities was also discussed.

关键词： Elastic scattering Optical potential ambiguities Envelope method Nearside/farside decomposition

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Breaking the efficiency limitations of dissipative Kerr solitons using nonlinear couplers

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science China(Physics,Mechanics & Astronomy) 2024年第3期67卷 88-94页

作者： Ming Li Xiao-Xiao Xue Yan-Lei Zhang Xin-Biao Xu Chun-Hua Dong Guang-Can Guo Chang-Ling Zou CAS Key Laboratory of Quantum Information University of Science and Technology of ChinaHefei 230026China CAS Centerfor Excellence in Quantum Information and Quantum Physics University of Science and Technology of ChinaHefei 230026China Department of Electronic Engineering Beijing National Research Center for Information Science and TechnologyTsinghua University Beijing 100084China

Dissipative Kerr solitons(DKS) have long been suffering from poor power conversion efficiency when driven by continuous-wave lasers. By deriving the critical coupling condition of a multimode nonlinear optics system in a generalized theoretical framework,two efficiency limitations of the conventional pump method of DKS are revealed: the effective coupling rate is too small and is also power-dependent. A general approach is provided to resolve this challenge by introducing two types of nonlinear couplers to couple the soliton cavity and CW input through nonlinear processes. The collective coupler opens multiple coupling channels and the self-adaptive coupler builds a power-independent effective external coupling rate to the DKS for approaching the generalized critical coupling condition, which promises near-unity power conversion efficiencies. For instance, a conversion efficiency exceeding 90% is predicted for aluminum nitride microrings with a nonlinear coupler utilizing second-harmonic generation. The mechanism applies to various nonlinear processes, including Raman and Brillouin scattering, and thus paves the way for micro-solitons toward practical applications.

关键词： Kerr frequency comb conversion efficiency nonlinear coupler

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Multi-IRS-Aided Secure Communication in UAV-MEC Networks

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IEEE Transactions on Vehicular technology 2025年第5期74卷 7327-7338页

作者： Gao, Yuan Wang, Zhenyu Zhang, Yu Lu, Weidang Tang, Jie Zhao, Nan Gao, Feifei Academy of Military Science of the PLA Beijing China Zhejiang University of Technology College of Information Engineering Hangzhou310023 China Dalian University of Technology School of Information and Communication Engineering Dalian116024 China Tsinghua National Laboratory for Information Science and Technology Beijing100084 China

With the merits of high mobility and easy deployment, mounting mobile edge computing (MEC) servers on unmanned aerial vehicles(UAVs) can efficiently fulfill the task offloading of ground users (GUs) over a large area. Nevertheless, data security is a challenging issue for the computation offloading in UAV-MEC networks, especially when there exist flying eavesdroppers. An intelligent reflecting surface (IRS) assisted secure communication scheme for a UAV-MEC network is proposed in this paper, wherein multiple IRSs are utilized to help the secure computation offloading from GUs against a UAV eavesdropper. Our aim is to maximize the secure computation capacity through the joint optimization of the IRS phase-shift, allocation of communication and computing resources and trajectory of UAV. We firstly solve the problem under a fixed UAV trajectory by alternating optimization to obtain the resource allocation and IRS phase-shift, wherein Dinkebach and Taylor expansion methods are used to transform the subproblems into tractable forms. Then, by adopting the proximal policy optimization, a joint optimization approach which further incorporates the UAV trajectory optimization is proposed. Numerical results verify that compared with benchmarks, the proposed scheme efficiently improves the system secure computation capacity. © 1967-2012 IEEE.

关键词： Computation offloading

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Combining Local Electromagnetic Scattering and Global Structure Features for SAR Open Set Recognition

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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2025年 18卷 12572-12587页

作者： Lin, Qinjie Sun, Hao Xu, Yanjie Wang, Junyu Ji, Kefeng Kuang, Gangyao National University of Defense Technology State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System College of Electronic Science and Technology Changsha410073 China

Automatic target recognition (ATR) is crucial for synthetic aperture radar (SAR) image interpretation. However, existing SAR ATR primarily rely on algorithms from the field of computer vision, many methods have not adequately considered the imaging sensitivity of SAR images. Moreover, SAR ATR typically follows the closed set assumption, but in dynamic and open real-world environments, SAR systems may encounter target classes that have not been seen during training. To address these issues, this paper proposes a SAR open set recognition (OSR) method that combines local electromagnetic scattering and global structure features. The global structural features focus on the overall relationship between target and background, while the local electromagnetic scattering features can effectively capture the scattering characteristics of target. Hence, we construct a global and local feature guidance (GLGE) network, fuses these complementary features as prior knowledge to guide deep features. Then, a class-anchor-based loss function is constructed by Anchor loss and Tuple loss, which cluster the features of known classes targets around predefined class anchors. Finally, the distance ratio is calculated to identify known classes targets and reject unknown classes targets. The experimental results on the MSTAR and SAR-ACD datasets show that our method outperforms other OSR methods in recall, precision, F1, and accuracy, demonstrating a superior performance in OSR. © 2008-2012 IEEE.

关键词： Automatic target recognition

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Dynamic Charging and Path Planning for UAV-Powered Rechargeable WSNs Using Multi-Agent Deep Reinforcement Learning

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IEEE Transactions on Automation science and engineering 2025年 22卷 15610-15626页

作者： Betalo, Mesfin Leranso Leng, Supeng Seid, Abegaz Mohammed Abishu, Hayla Nahom Erbad, Aiman Bai, Xiaoshan Shenzhen University College of Mechatronics and Control Engineering Shenzhen518060 China University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China Hamad Bin Khalifa University Division of Information and Computing Technology College of Science and Engineering Doha Qatar Shenzhen University College of Mechatronics and Control Engineering National Engineering Laboratory for Big Data System Computing Technology Shenzhen518060 China

Unmanned Aerial Vehicle (UAV)-powered 5G/6G networks integrated with rechargeable wireless sensor networks (RWSNs) offer promising solutions for extending system lifetime, collecting data, and providing computing services and power to sensor nodes (SNs). UAVs offer significant advantages, including exceptional mobility, cost-effective deployment, and the ability to be easily reprogrammed for a wide range of missions. However, the limited onboard power capacity of UAVs, coupled with the lack of dynamic and intelligent charging station (CS) management and inefficient path planning, can lead to SN failure in dynamic mobile environments. To address these challenges, we propose an energy-efficient laser-charged UAV (LCU)-enabled RWSN environment, wherein UAVs, powered by laser beams from ground-based stations, provide services, collect data, and transfer energy to SNs. We formulate a joint optimization problem involving power allocation, dynamic charging strategy (DCS), and path planning to minimize task completion time and sensor node death time. Given the NP-hard nature of the problem, we employ a stochastic game model based on a Markov decision process (MDP) for its solution. To solve this problem, we propose a deep reinforcement learning (DRL) based algorithm that enables real-time charging scheduling decisions while optimizing network performance. We introduce a multi-agent double deep Q-network (MA-DDQN) model to determine the optimal trajectories for all UAVs in large and complex environments. Simulation results demonstrate that the MA-DDQN approach outperforms state-of-the-art techniques, showing significant improvements in terms of average delay, energy consumption, and task completion time. © 2004-2012 IEEE.

关键词： Stochastic models

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An anonymous authentication and secure data transmission scheme for the Internet of Things based on blockchain

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Frontiers of Computer science 2024年第3期18卷 183-197页

作者： Xingxing CHEN Qingfeng CHENG Weidong YANG Xiangyang LUO State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou Institute of Information Science and TechnologyZhengzhou 450001China Henan Key Laboratory of Grain Photoelectric Detection and Control Henan University of TechnologyZhengzhou 450001China Henan Province Key Laboratory of Cyberspace Situation Awareness Zhengzhou Institute of Information Science and TechnologyZhengzhou 450001China

With the widespread use of network infrastructures such as 5G and low-power wide-area networks,a large number of the Internet of Things(IoT)device nodes are connected to the network,generating massive amounts of ***,it is a great challenge to achieve anonymous authentication of IoT nodes and secure data *** present,blockchain technology is widely used in authentication and s data storage due to its decentralization and ***,Fan et *** a secure and efficient blockchain-based IoT authentication and data sharing *** studied it as one of the state-of-the-art protocols and found that this scheme does not consider the resistance to ephemeral secret compromise attacks and the anonymity of IoT *** overcome these security flaws,this paper proposes an enhanced authentication and data transmission scheme,which is verified by formal security proofs and informal security ***,Scyther is applied to prove the security of the proposed ***,it is demonstrated that the proposed scheme achieves better performance in terms of communication and computational cost compared to other related schemes.

关键词： Internet of Things blockchain authentication data transmission

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Discriminative feature encoding for intrinsic image decomposition

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Computational Visual Media 2023年第3期9卷 597-618页

作者： Zongji Wang Yunfei Liu Feng Lu Key Laboratory of Network Information System Technology(NIST) Aerospace Information Research InstituteChinese Academy of SciencesBeijing 100190China State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijing 100191China Peng Cheng Laboratory Shenzhen 518000China

Intrinsic image decomposition is an important and long-standing computer vision *** an input image,recovering the physical scene properties is *** physically motivated priors have been used to restrict the solution space of the optimization problem for intrinsic image *** work takes advantage of deep learning,and shows that it can solve this challenging computer vision problem with high *** focus lies in the feature encoding phase to extract discriminative features for different intrinsic layers from an input *** achieve this goal,we explore the distinctive characteristics of different intrinsic components in the high-dimensional feature embedding *** define feature distribution divergence to efficiently separate the feature vectors of different intrinsic *** feature distributions are also constrained to fit the real ones through a feature distribution *** addition,a data refinement approach is provided to remove data inconsistency from the Sintel dataset,making it more suitable for intrinsic image *** method is also extended to intrinsic video decomposition based on pixel-wise correspondences between adjacent *** results indicate that our proposed network structure can outperform the existing state-of-the-art.

关键词： intrinsic image decomposition deep learning feature distribution data refinement

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VSSB-Raft: A Secure and Efficient Zero Trust Consensus Algorithm for Blockchain

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ACM Transactions on Sensor Networks 2024年第2期20卷 1-22页

作者： Tian, Siben Bai, Fenhua Shen, Tao Zhang, Chi Gong, Bei Faculty of Information Engineering and Automation Kunming University of Science and Technology Yunnan Key Laboratory of Computer Technology Applications China Faculty of Information Technology Beijing University of Technology China

To solve the problems of vote forgery and malicious election of candidate nodes in the Raft consensus algorithm, we combine zero trust with the Raft consensus algorithm and propose a secure and efficient consensus algorithm -Verifiable Secret Sharing Byzantine Fault Tolerance Raft Consensus Algorithm (VSSB-Raft). The VSSB-Raft consensus algorithm realizes zero trust through the supervisor node and secret sharing algorithm without the invisible trust between nodes required by the algorithm. Meanwhile, the VSSB-Raft consensus algorithm uses the SM2 signature algorithm to realize the characteristics of zero trust requiring authentication before data use. In addition, by introducing the NDN network, we redesign the communication between nodes and guarantee the communication quality among nodes. The VSSB-Raft consensus algorithm proposed in this paper can make the algorithm Byzantine fault tolerant by setting a threshold for secret sharing while maintaining the algorithm's complexity to be O(n). Experiments show that the VSSB-Raft consensus algorithm is secure and efficient with high throughput and low consensus latency. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Blockchain

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