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36th International Conference on Software Engineering and Knowledge Engineering, SEKE 2024

作者： Su, Lisha Yan, Rong College of Computer Science Inner Mongolia University Inner Mongolia Key Laboratory of Multilingual Artificial Intelligence Technology National & Local Joint Engineering Research Center of Intelligent Information Processing Technology for Mongolian Hohhot010021 China

ISBN: (纸本)1891706594

Joint extraction of entities and relations is an essential task in information extraction. Recently, tagging-based models have gained attention but with poor performance on overlapping triplets, which confronted the issues like cascading errors, information redundancy, and sensitivity to subject extraction. To solve the issue of overlapping triplets, we propose a model combined Gated Attention Unit (GAU) and Multi-head Attention Mechanism (MHA) in this paper. This model distinguishes features for entities and relations, and performs entity recognition for each head entity, different head entities are matched to the same or different tail entities. Then specific tail entity tagging is applied to determine all possible relations and corresponding tails. At the same time, in order to better solve the long-distance dependence and complex multiple relations between entities, GAU and MHA are used to enhance the semantic representation, effectively identify entities and relations, and enhance the learning ability and generalization ability of the model. Experiment results on the public datasets DuIE2.0 and CMeIE show that our model performs better than baselines. © 2024 Knowledge Systems Institute Graduate School. All rights reserved.

关键词： Semantics

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Verifiable searchable symmetric encryption for conjunctive keyword queries in cloud storage

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Frontiers of Computer Science 2022年第6期16卷 103-121页

作者： Qingqing GAN Joseph K.LIU Xiaoming WANG Xingliang YUAN Shi-Feng SUN Daxin HUANG Cong ZUO Jianfeng WANG Guangzhou Key Laboratory of Multilingual Intelligent Processing School of Information Science and Technology/School of Cyber SecurityGuangdong University of Foreign StudiesGuangzhou510006China Department of Computer Science Jinan UniversityGuangzhou510632China Faculty of Information Technology Monash UniversityClayton3168Australia State Key Laboratory of Integrated Service Networks(ISN) Xidian UniversityXi’an710071China

Searchable symmetric encryption(SSE)has been introduced for secure outsourcing the encrypted database to cloud storage,while maintaining searchable *** various SSE schemes,most of them assume the server is honest but curious,while the server may be trustless in the real *** a malicious server not honestly performing the queries,verifiable SSE(VSSE)schemes are constructed to ensure the verifiability of the search ***,existing VSSE constructions only focus on single-keyword search or incur heavy computational cost during *** address this challenge,we present an efficient VSSE scheme,built on OXT protocol(Cash et al.,CRYPTO 2013),for conjunctive keyword queries with sublinear search *** proposed VSSE scheme is based on a privacy-preserving hash-based accumulator,by leveraging a well-established cryptographic primitive,Symmetric Hidden Vector Encryption(SHVE).Our VSSE scheme enables both correctness and completeness verifiability for the result without pairing operations,thus greatly reducing the computational cost in the verification ***,the proposed VSSE scheme can still provide a proof when the search result is ***,the security analysis and experimental evaluation are given to demonstrate the security and practicality of the proposed scheme.

关键词： searchable symmetric encryption verifiability conjunctive keyword queries hash-based accumulator cloud storage

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Optimal control of Constrained Trajectory Optimization Problem of UAV with Limited Sensing

Optimal Control of Constrained Trajectory Optimization Probl...

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2024 China Automation Congress, CAC 2024

作者： Xiao, Long Liu, Miao Wu, Xialai Guo, Shaopan Shi, Benyun Ci, Wenyan College of Computer and Information Engineering College of Artificial Intelligence Nanjing Tech University Nanjing China Huzhou Key Laboratory of Intelligent Sensing and Optimal Control for Industrial Systems Huzhou University Huzhou China

ISBN: (纸本)9798350368604

Optimal control of constrained unmanned aerial vehicle (UAV) trajectory optimization problem is one of the frontiers and hotspots of UAV research. The various constraints generated by physical limitations and obstacles in the environment increase the difficulties of solving the trajectory optimization problem, especially when the limited sensing ability is taken into consideration. This paper presents the receding horizon optimization method to obtain optimal control for the UAV with limited sensing range in a complex environment with obstacles. To improve efficiency, a path constraint processing method is proposed to reduce the number of constraints in the nonlinear programming problem (NLP). The proposed main structure and detailed algorithm are also given. The numerical results demonstrate the effectiveness of the proposed method compared with the classical Gauss pseudospectral method. © 2024 IEEE.

关键词： Nonlinear programming

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Digital-Twin-Based Clock Synchronization in Industrial IoT Systems 13

Digital-Twin-Based Clock Synchronization in Industrial IoT S...

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13th IEEE International Conference on CYBER Technology in Automation, control, and intelligent Systems, CYBER 2023

作者： Cheng, Ting Liu, Shuai Xu, Qimin Zhu, Shanying Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China School of Control Science and Engineering Shandong University Jinan250061 China

ISBN: (纸本)9798350315196

Close and efficient cooperation between devices in the Industrial Internet of Things (IIoT) requires precise clock synchronization as a prerequisite. The uncertainty of IIoT networks and the complexity of industrial environments have led to less precise clock synchronization achieved by traditional algorithms and higher network resource consumption. This paper proposes a digital-twin-based clock synchronization scheme for IIoT systems. By building the digital model for each local clock to predict their clock skew, the information interaction required to achieve synchronization is reduced. In order to model the clock accurately, this paper proposes to use the extended state Kalman filter to handle uncertain dynamics and unknown measurement bias to improve the estimation accuracy of clock skew further. The simulation results show that the proposed algorithm can achieve high- precision clock synchronization while reducing the consumption of network resources. © 2023 IEEE.

关键词： Internet of things

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BLIND QUALITY ASSESSMENT OF NIGHT-TIME IMAGES VIA WEAK ILLUMINATION ANALYSIS

BLIND QUALITY ASSESSMENT OF NIGHT-TIME IMAGES VIA WEAK ILLUM...

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2021 IEEE International Conference on Multimedia and Expo, ICME 2021

作者： Wang, Miaohui Huang, Yijing Zhang, Jialin Guangdong Key Laboratory of Intelligent Information Processing SZU China

ISBN: (纸本)9781665438643

Night-time images can be generated by various camera sensors in many practical applications, and hence how to effectively evaluate the quality of night-time images is an essential research topic. In this article, we propose a novel blind quality assessment method for night-time images. By analyzing the characteristic of night-time images, we first investigate the statistical properties of local luminance information based on the brightness level division, and then measure the masking effect on color and structure information caused by weak illumination. Finally, all extracted quality-aware features and the associated subjective ratings are trained via support vector regression to build the quality assessment model. Extensive experiments on a real-world night-image database validate the superiority of the proposed method over several state-of-the-art blind image quality metrics. © 2021 IEEE

关键词： Luminance

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Harry: A Scalable SIMD-based Multi-literal Pattern Matching Engine for Deep Packet Inspection 42

Harry: A Scalable SIMD-based Multi-literal Pattern Matching ...

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42nd IEEE International Conference on Computer Communications, INFOCOM 2023

作者： Xu, Hao Chang, Harry Zhu, Wenjun Hong, Yang Langdale, Geoff Qiu, Kun Zhao, Jin Fudan University School of Computer Science China Shanghai Key Laboratory of Intelligent Information Processing Shanghai China Intel Asia-Pacific Research & Development Ltd. Shanghai China

ISBN: (纸本)9798350334142

Deep Packet Inspection (DPI) is a significant network security technique. It examines traffic workloads by searching for specific rules. Since every byte of packets needs to be examined by many literal rules, multi-literal matching becomes the performance bottleneck of DPI. FDR, the fastest multi-literal matching engine on CPUs, takes advantage of Single-Instruction-Multiple-Data (SIMD) to alleviate this bottleneck and achieves a performance boost over the widely-used Aho-Corasick (AC) algorithm. However, FDR does not deeply exploit the data-level parallelism of SIMD and its SIMD vector utilization is only 50%. Besides, limited by certain SIMD shift instructions, it cannot benefit from advanced SIMD instruction sets. To overcome these issues, we propose Harry, a scalable and SIMD-based multi-literal matching engine. Harry adopts a column-vector-based matching algorithm to improve the data-level parallelism and SIMD vector utilization. To support the algorithm, it takes two encoding methods to compress the mask table. Also, it utilizes shuffle instruction to implement shift. We implement Harry on commodity CPU and evaluate it with real network traffic and DPI rules. Our evaluation shows that Harry reaches a throughput of 30∼70Gbit/s, up to 52x that of AC and 2.09x of FDR. It has been successfully deployed in Hyperscan. © 2023 IEEE.

关键词： Network security

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Uncertainty analysis of hypersonic flight dynamics under elastic effects

Uncertainty analysis of hypersonic flight dynamics under ela...

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2024 International Conference on Aerospace and Mechanics, ICAM 2024

作者： Li, Shuqing Zeng, Fanlin Xiang, Qiulin School of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin300222 China Tianjin Key Laboratory of Information Sensing and Intelligent Control Tianjin University of Technology and Education Tianjin300222 China

In addressing the aerodynamic-elastic coupling issues of hypersonic vehicles, this study delves into the analysis of the elastic deformation of the aircraft based on mechanistic understanding. It employs the Interval Analysis Method based on Polynomial Approximations to conduct uncertainty analysis of the aerodynamic model under elasticity, delineating the range of uncertainty in the aerodynamic model influenced by elastic deformation. The aerodynamic force of the aircraft under elasticity is connected with the rigid body, and then the aerodynamic layout of the aircraft fuselage and control surface after elastic deformation is calculated to study the influence of the elastic effect on the aerodynamic force. The results show that the change caused by uncertainty has a relatively small effect on lift but a relatively large effect on drag and pitching moment. © 2024 Institute of Physics Publishing. All rights reserved.

关键词： Hypersonic vehicles

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Improvement of VMD and Compensation Distance for Rolling Bearing Fault Detection Methods 43

Improvement of VMD and Compensation Distance for Rolling Bea...

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43rd Chinese control Conference, CCC 2024

作者： Guo, Kai Xiong, Xin Ma, Jun Kunming University of Science and Technology Faculty of Information Engineering and Automation Kunming650500 China Kunming University of Science and Technology Key Laboratory of Intelligent Control and Application of Yunnan Province Kunming650500 China

ISBN: (纸本)9789887581581

To address the problem of varying detection performance and the lack of universal standards for early fault detection in rolling bearings, a method for early fault detection in rolling bearings based on an improved variational modal decomposition (IVMD) and compensation distance (CD) is proposed from the perspective of constructing performance degradation curves. Firstly, the number of modes K for variational mode decomposition (VMD) is adaptively determined using the estimated signal-to-noise ratio (eSNR) method. Secondly, the probability density function (PDF) distribution of the intrinsic mode function (IMF) obtained from the decomposition is calculated, and the compensation distance (CD) degradation evaluation index is constructed by integrating the inter-class and intra-class distances. Then, a sliding window is used to repair the false fluctuations in the CD degradation index based on linear regression equations and the 3 σ principle, resulting in a sensitive degradation index that accurately characterizes the rolling bearing degradation process Improved Compensation Distance (ICD). Finally, the Chebyshev inequality is used to establish the relationship between the healthy threshold and the ICD index, enabling early fault detection in rolling bearings. Comparative analysis of one set of experiments shows that the proposed method can accurately characterize the degradation process of rolling bearings and effectively detect early faults, providing a new solution for early fault diagnosis of bearings. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Probability density function

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Visual analysis of image features in CT reconstruction based on convolutional neural network

Visual analysis of image features in CT reconstruction based...

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2021 International Conference on Computer Vision and Pattern Analysis, ICCPA 2021

作者： Zhu, Linlin Han, Yu Li, Lei Xi, Xiaoqi Yan, Bin Henan Key Laboratory of Imaging and Intelligent Processing PLA Strategic Support Force Information Engineering University Zhengzhou450001 China

ISBN: (数字)9781510651937

ISBN: (纸本)9781510651920

Computed Tomography (CT) is one of the essential techniques for non-destructive testing. The acquisition of accurate reconstructed images is the basis for the subsequent analytical processing tasks. This paper proposes a convolutional neural network-based CT reconstruction algorithm to generate reconstructed CT images directly from sinogram by the feature coding and decoding capability. The reconstruction of abdominal scanning data is carried out by this method, and the results show that we can quickly obtain corresponding reconstruction results. During the network training, we designed different data pre-processing methods. We analysed the role of each module in the network by visualizing the output features of each module. Finally, the role of different modules in feature extraction and image generation is further analysed. We found that the conversion from projection to image can be effectively achieved using only convolution operations. It is essential for reconstructing CT images using deep learning techniques. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Image reconstruction

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A study on low-dose CT image denoising method based on similar block learning 5

A study on low-dose CT image denoising method based on simil...

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2023 5th International Conference on information Science, Electrical, and Automation Engineering, ISEAE 2023

作者： Fu, Huijuan Xi, Xiaoqi Han, Yu Zhu, Linlin Liu, Mengnan Tan, Siyu Liu, Chang Li, Lei Yan, Bin Henan Key Laboratory of Imaging and Intelligent Processing Pla Strategic Support Force Information Engineering University Zhengzhou45000 China Zhengzhou University School of Software Zhengzhou45000 China

ISBN: (纸本)9781510667440

X-ray tomographic imaging has become an important analytical tool with a wide range of applications. It is inevitable that noise is introduced in CT images, and noise reduction is necessary. To solve this problem, we considered to use the nonlocal property of similar block search and proposed a deep learning network based on similar block learning for noise reduction of micro CT short exposure time scanned images to improve the scanning efficiency while ensuring high quality imaging. The method uses the output of the nonlocal method as a data preprocessing algorithm by combining a nonlocal block matching algorithm with a convolutional neural network, and uses a residual channel attention mechanism to learn the features after feature extraction, which reduces noise while preserving image details. Experimental results show that the method can remove noise from CT images quickly and effectively, and compared with the classical CPCE noise reduction method, the method improves the PSNR index by 1.52 dB, which is consistent with the theoretical assumption. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Noise abatement

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