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17th IEEE International Conference on Mechatronics and Automation, ICMA 2020

作者： Zhang, Yu Liu, Jun Han, Zhu Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechanical System Design and Intelligent Control Tianjin300384 China

ISBN: (纸本)9781728164151

In rotating machinery, because of high-speed working characteristics and terrible working conditions with variable cycles and variable loads, it is easy for rotors to cause a crack initiation and propagation, which may cause serious harm or even the life-threatening. The super harmonic component is an important role of the crack detection. But it is difficult to reflect the super harmonic component in the high-speed region after super harmonic resonances. In this paper, the dynamic equation of a nonlinear rotor system with a crack is considered, the potential energy expression of the cracked rotor is derived, and the concept of energy tracks is proposed. In the distortion of energy tracks, the effects of different crack parameters and nonlinear parameters on the vibration characteristics of the rotor system are compared. The results show that the energy trajectory distortion can diagnose the crack fault. It provides a new research method for vibration response analyses and fault diagnoses of cracked rotor system. © 2020 IEEE.

关键词： Crack detection

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Research on Asymmetrical Dual-rotor System Based on the Energy Orbit 17

Research on Asymmetrical Dual-rotor System Based on the Ener...

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17th IEEE International Conference on Mechatronics and Automation, ICMA 2020

作者： Han, Zhu Liu, Jun Zhang, Yu Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechanical System Design and Intelligent Control Tianjin300384 China

ISBN: (纸本)9781728164151

Studying the vibration of asymmetrical dual-rotor is very important for aero engines. In this paper, based on the vibration characteristics of an aero-engine, a different novel coupled dynamic model is proposed based on the spring recovery characteristics of rotor. The model dynamic equations of asymmetrical dual-rotor are obtained by the Lagrange equation, and vibration resonance curves of high pressure and low pressure rotors are numerically simulated and theoretically analyzed by using the Runge-Kutta algorithm. The research show that the system occurs combined vibration, harmonic vibration and superharmonic vibration. In addition, the vibration occurring mechanism was investigated and verified in detail through numerical simulation. For the first time, the concept of energy orbit was introduced into the dual-rotor model system. The energy orbit represents the vibration characteristics and energy exchange process of the model system. Energy orbit is a new energy orbit method for analyzing vibration characteristics of rotor system. The new researches of this paper will show a different research direction for complex dual-rotor systems. © 2020 IEEE.

关键词： Equations of motion

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RobustPFL: Robust Personalized Federated Learning

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IEEE Transactions on Dependable and Secure computing 2025年

作者： Chen, Guorong Wang, Wei Wu, Yufang Li, Chao Xu, Guangquan Ji, Shouling Li, Tao Shen, Meng Han, Yufei Xi'an Jiaotong University Ministry of Education Key Lab for Intelligent Networks and Network Security Xi'an China Beijing Jiaotong University 3 Shangyuancun Beijing Key Laboratory of Security and Privacy in Intelligent Transportation Beijing100044 China Tianjin University Tianjin Key Laboratory of Advanced Networking College of Intelligence and Computing Tianjin300350 China Zhejiang University College of Computer Science and Technology Hangzhou310027 China ITAI Haihe Lab Tianjin China Nankai University College of Computer Science Tianjin300350 China Beijing Institute of Technology School of Cyberspace Security Beijing100081 China Peng Cheng Laboratory Cyberspace Security Research Center Shenzhen518066 China INRIA Bretagne Rennes35042 France

Conventional federated learning (FL) coordinated by a central server focuses on training a global model and protecting the privacy of clients' training data by storing it locally. However, the statistical heterogeneity hinders the global model from adapting to the non-IID distributions among clients. Moreover, untrusted and unreliable central servers and malicious clients may compromise model integrity and availability, thus degrading the robustness of FL. To address these challenges, we present RobustPFL, a decentralized personalized federated learning (PFL) approach that combines α-based Layer-position Normalized Similarity (α-LNS) and local collaborative training to improve personalized performance while utilizing a blockchain-based committee mechanism to coordinate the aggregation process, thereby achieving high personalized accuracy and robustness. Extensive experiments show that our RobustPFL approach outperforms multiple algorithms, including Local training, FedAvg, FedReptile, Per-FedAvg, FedBN, and SPFL, on MNIST, CIFAR10, EMNIST, and N-BaIoT datasets in four non-IID settings. We also evaluate RobustPFL's effectiveness against attacks - poisoning attacks and free-riding attacks. Particularly, for three prevalent poisoning attacks (backdoor, label flipping, and model poisoning attacks), we compare non-defensive (FedAvg) and defensive (Krum, trimmed mean, Bulyan, FedBN, FLAME, and FangTrmean) methods with our proposed RobustPFL. The results show that our approach achieves significant defensive effects. © 2004-2012 IEEE.

关键词： Federated learning

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Redundant Data Detection and Deletion to Meet Privacy Protection Requirements in Blockchain-Based Edge computing Environment

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China Communications 2024年第3期21卷 149-159页

作者： Zhang Lejun Peng Minghui Su Shen Wang Weizheng Jin Zilong Su Yansen Chen Huiling Guo Ran Sergey Gataullin Cyberspace Institute Advanced Technology Guangzhou UniversityGuangzhou 510006China College of Information Engineering Yangzhou UniversityYangzhou 225127China School Math&Computer Science Quanzhou Normal UniversityQuanzhou 362000China Computer Science Department City University of Hong KongHong Kong 999077China School of Computer and Software Nanjing University of Information Science and TechnologyNanjing 21004China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and TechnologyAnhui UniversityHefei 230601China Department of Computer Science and Artificial Intelligence Wenzhou UniversityWenzhou 325035China Guangzhou University Library Guangzhou UniversityGuangzhou 510006China Central Economic and Mathematics Institute Russian Academy of Sciences MIREA-Russian Technological University Moscow RegionRussia

With the rapid development of information technology,IoT devices play a huge role in physiological health data *** exponential growth of medical data requires us to reasonably allocate storage space for cloud servers and edge *** storage capacity of edge nodes close to users is *** should store hotspot data in edge nodes as much as possible,so as to ensure response timeliness and access hit rate;However,the current scheme cannot guarantee that every sub-message in a complete data stored by the edge node meets the requirements of hot data;How to complete the detection and deletion of redundant data in edge nodes under the premise of protecting user privacy and data dynamic integrity has become a challenging *** paper proposes a redundant data detection method that meets the privacy protection *** scanning the cipher text,it is determined whether each sub-message of the data in the edge node meets the requirements of the hot *** has the same effect as zero-knowledge proof,and it will not reveal the privacy of *** addition,for redundant sub-data that does not meet the requirements of hot data,our paper proposes a redundant data deletion scheme that meets the dynamic integrity of the *** use Content Extraction Signature(CES)to generate the remaining hot data signature after the redundant data is *** feasibility of the scheme is proved through safety analysis and efficiency analysis.

关键词： blockchain data integrity edge computing privacy protection redundant data

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A Novel Linear Machine Learning Method Based on DNA Hybridization Reaction Circuit

IEEE Transactions on NanoBioscience

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IEEE Transactions on NanoBioscience 2025年第3期24卷 374-385页

作者： Chengye Zou Qiang Zhang Bin Wang Changjun Zhou Yongwei Yang Xuncai Zhang School of Information Science and Engineering Yanshan University Qinhuangdao China Informedia Electronic Company Ltd. Dalian China School of Computer Science and Technology Dalian University of Technology Dalian China Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education and the School of Software Engineering Dalian University Dalian China School of Computer Science and Technology Zhejiang Normal University Jinhua China School of Mathematics and Computer Science Tongling University Tongling Anhui China College of Electrical and Electronic Engineering Zhengzhou University of Light Industry Zhengzhou China

DNA hybridization reaction is a significant technology in the field of semi-synthetic biology and holds great potential for use in biological computation. In this study, we propose a novel machine learning model based on a DNA hybridization reaction circuit. This circuit comprises a computation training component, a test component, and a learning algorithm. Compared to conventional machine learning models based on semiconductors, the proposed machine learning model harnesses the power of DNA hybridization reaction, with the learning algorithm implemented based on the unique properties of DNA computation, enabling parallel computation for the acquisition of learning results. In contrast to existing machine learning models based on DNA circuits, our proposed model constitutes a complete synthetic biology computation system, and utilizes the “dual-rail” mechanism to achieve the DNA compilation of the learning algorithm, which allows the weights to be updated to negative values. The proposed machine learning model based on DNA hybridization reaction demonstrates the ability to predict and fit linear functions. As such, this study is expected to make significant contributions to the development of machine learning through DNA hybridization reaction circuits.

关键词： DNA Machine learning Computational modeling Catalysis Training Biological system modeling Machine learning algorithms Integrated circuit modeling Semiconductor device modeling Electronic mail

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LinNet: linear network for efficient point cloud representation learning 24

LinNet: linear network for efficient point cloud representat...

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Proceedings of the 38th International Conference on Neural Information Processing Systems

作者： Hao Deng Kunlei Jing Shengmei Cheng Cheng Liu Jiawei Ru Jiang Bo Lin Wang State-Province Joint Engineering and Research Center of Advanced Networking and Intelligent Information Services School of Information Science and Technology Northwest University and Shaanxi Key Laboratory of Higher Education Institution of Generative Artificial Intelligence and Mixed Reality School of Software Engineering Xi'an Jiaotong University and Department of Computing The Hong Kong Polytechnic University

ISBN: (纸本)9798331314385

Point-based methods have made significant progress, but improving their scalability in large-scale 3D scenes is still a challenging problem. In this paper, we delve into the point-based method and develop a simpler, faster, stronger variant model, dubbed as LinNet. In particular, we first propose the disassembled set abstraction (DSA) module, which is more effective than the previous version of set abstraction. It achieves more efficient local aggregation by leveraging spatial anisotropy and channel anisotropy separately. Additionally, by mapping 3D point clouds onto 1D space-filling curves, we enable parallelization of down-sampling and neighborhood queries on GPUs with linear complexity. LinNet, as a purely point-based method, outperforms most previous methods in both indoor and outdoor scenes without any extra attention, and sparse convolution but merely relying on a simple MLP. It achieves the mIoU of 73.7%, 81.4%, and 69.1% on the S3DIS Area5, NuScenes, and SemanticKITTI validation benchmarks, respectively, while speeding up almost 10x times over PointNeXt. Our work further reveals both the efficacy and efficiency potential of the vanilla point-based models in large-scale representation learning. Our code will be available at https://***/DengH293/LinNet.

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A knowledge-user behavior-driven aircraft assembly tooling design knowledge recommendation approach

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Hangkong Xuebao/Acta Aeronautica et Astronautica Sinica 2025年第9期46卷

作者： Wang, Zuoxu Wang, Xin Meng, Shuang Zheng, Lianyu School of Mechanical Engineering and Automation Beihang University Beijing100191 China Beijing Key Laboratory of Digital Design and Manufacturing Technology Beijing100191 China MIIT Key Laboratory of Intelligent Manufacturing Technology for Aeronautics Advanced Equipments Beijing100191 China

Facing the challenge of frequent changes on aircraft models，it is necessary to achieve rapid design for aircraft assembly tooling. Aircraft product assembly tooling design is a long-term and high-cost tasks. designers invest significant time and effort in tooling design，heavily relying on personal experience，with limited support and inheritance of tooling design knowledge. To address this issue，this study proposed an assembly tooling design knowledge recommendation approach based on knowledge graph and user behavior feedback. First，a knowledge document repository and a domain knowledge label network are constructed，forming a knowledge graph. Then，by constructing and activating a knowledge push scenario model，the priority of knowledge documents is computed based on their relevance between the knowledge push scenario and knowledge tags. Additionally，a knowledge push adjustment mechanism is proposed，and the priority of the knowledge documents will be adjusted based on user behaviors. Using aircraft wall panel tooling design as an example，this study validates the effectiveness of the user behavior-based parameter adjustment mechanism in knowledge recommendation. The example demonstrates that the accuracy of the proposed method in pushing the top 5 relevant knowledge documents is 0. 83. Results also show that tags with higher search frequency are ranked higher，and user ratings of"helpful"significantly increase the priority of recommended knowledge under the same recommendation frequency. Additionally，a prototype system for aircraft panel assembly tooling design knowledge push is developed on the CATIA platform，applying the method to facilitate designers’efficient access to relevant tooling knowledge. © 2025 Chinese Society of Astronautics. All rights reserved.

关键词： Knowledge graph

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MLFuse: Multi-Scenario Feature Joint Learning for Multi-Modality Image Fusion

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IEEE Transactions on Multimedia 2025年

作者： Lei, Jia Li, Jiawei Liu, Jinyuan Wang, Bin Zhou, Shihua Zhang, Qiang Wei, Xiaopeng Kasabov, Nikola K. Dalian University Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian116622 China University of Science and Technology Beijing School of Computer and Communication Engineering Beijing100083 China Dalian University of Technology School of Mechanical Engineering Dalian116024 China Dalian University of Technology School of Computer Science and Technology Dalian116024 China Auckland University of Technology Knowledge Engineering and Discovery Research Institute Auckland1010 New Zealand Ulster University Intelligent Systems Research Center LondonderryBT52 1SA United Kingdom

Multi-modality image fusion (MMIF) entails synthesizing images with detailed textures and prominent objects. Existing methods tend to use general feature extraction to handle different fusion tasks. However, these methods have difficulty breaking fusion barriers across various modalities owing to the lack of targeted learning routes. In this work, we propose a multi-scenario feature joint learning architecture, MLFuse, that employs the commonalities of multi-modality images to deconstruct the fusion progress. Specifically, we construct a cross-modal knowledge reinforcing network that adopts a multipath calibration strategy to promote information communication between different images. In addition, two professional networks are developed to maintain the salient and textural information of fusion results. The spatial-spectral domain optimizing network can learn the vital relationship of the source image context with the help of spatial attention and spectral attention. The edge-guided learning network utilizes the convolution operations of various receptive fields to capture image texture information. The desired fusion results are obtained by aggregating the outputs from the three networks. Extensive experiments demonstrate the superiority of MLFuse for infrared-visible image fusion and medical image fusion. The excellent results of downstream tasks (i.e., object detection and semantic segmentation) further verify the high-quality fusion performance of our method. The code is publicly available at https://***/jialei-sc/MLFuse. © 1999-2012 IEEE.

关键词： Semantic Segmentation

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Speech Emotion Recognition Based on Three-Channel Feature Fusion of CNN and BiLSTM 2020

Speech Emotion Recognition Based on Three-Channel Feature Fu...

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4th International Conference on Innovation in Artificial Intelligence, ICIAI 2020

作者： Huang, Lilong Dong, Jing Zhou, Dongsheng Zhang, Qiang Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian University Dalian China School of Computer Science and Technology Dalian University of Technology Dalian China

ISBN: (纸本)9781450376587

It is important for human-computer natural interaction that the computer can quickly and effectively identify the interactor's emotional state. We proposed a three-channel feature fusion algorithm based on Convolutional Neural Network and Bidirectional Long Short-Term Memory Network for speech emotion recognition. Mel-Frequency Cepstral Coefficients and its first and second-order difference features were input into three channels and trained respectively for exploiting the emotional information contained in the dynamic features. By splicing and fusing the features obtained by three channels, the recognition rates of proposed algorithm reached 96.562% and 92.34% on CASIA corpus with six emotional states and on EMO-DB corpus with seven emotional states respectively. © 2020 ACM.

关键词： Long short-term memory

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Effects of Visual and Auditory Instructions on Space Station Procedural Tasks

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Space(Science & Technology) 2024年第1期4卷 479-489页

作者： Yan Zhao You Li Ao Jiang HongRui Zhang HaoTian She WenHao Zhan Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of TechnologyBeijing 100081China Key Laboratory of Biomimetic Robots and Systems of Chinese Ministry Beijing Institute of TechnologyBeijing 100081China National Key Laboratory of Human Factors Engineering China Astronaut Research and Training CenterBeijing 100094China Dyson School of Design Engineering Imperial College LondonLondonUK School of Medical Technology Beijing Institute of TechnologyBeijing 100081China

In order to compare the effects of visual and auditory instructions on the crew when guiding astronauts to complete the procedural tasks in the space station,in this study,subjects were recruited to complete the programmed task of starting from the node module,locating the scientific cabinet and spectrometer,and finally operating the orbital replaceable unit on the ***,the task performance,eye movement parameters,and cognitive load induced by 2 kinds of instructions in the task were statistically *** results showed that there were highly significant differences in terms of task completion time,the NASA-TLX(Task Load Index)total score,and eye movement index between the 2 instructions(P<0.01).There were also significant differences in error rate and effort(P<0.05).This study proves that visual instruction interaction is better than auditory *** work provides important reference for the selection of human–computer interaction mode for procedural tasks on space *** also provides the experience and theoretical evidence missing so far and proves the benefits of augmented reality assistance in terms of task performance and human factors.

关键词： programmed task visual auditory instructions cognitive load starting node modulelocating visual instructions auditory instructions space stationin procedural tasks

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