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2023 China Automation Congress, CAC 2023

作者： Liu, Yiheng Fu, Yao Wang, Tian Cao, Yaofu Yan, Junlu Snoussi, Hichem School of Automation Science and Electrical Engineering Beihang University Beijing China Changchun Institute of Optics Fine Mechanics and Physics China Academy of Sciences Chang Chun China Institute of Artificial Intelligence SKLSDE Beihang University Zhongguancun Laboratory Beijing China State Grid Information & Telecommunication Branch Beijing China University of Technology of Troye Laboratory of Computer Science and Digital Society Troyes France

ISBN: (纸本)9798350303759

The smart grid is perceived as a complex cyber-physical ecosystem consisting of a variety of infrastructures. The increasing intricacy and interconnectivity of smart grid elements have rendered security a vital consideration. A significant number of research papers have being conducted to mitigate the cyber-attacks. Nevertheless, the majority of existing security measures concentrates on addressing specific attacks or safeguarding individual components, lacking a comprehensive approach that integrates these solutions to protect the safety of the overall system. In this article, we outline relevant literatures. Initially, we delve into several significant cyber attacks to identify possible threats in the smart grid. Subsequently, we present suitable cyber security countermeasures. Lastly, we propose the research challenges, along with significant research gaps, in order to provide insights into potential future research directions. © 2023 IEEE.

关键词： Smart power grids

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Enhancing Pulmonary Nodule Classification performance with TriCaps-RL: A Capsule Network Reinforcement Learning Approach

Journal of Network Intelligence

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Journal of Network Intelligence 2024年第3期9卷 1441-1459页

作者： Zheng, Guang-Yuan Zhang, Fu-Quan Cheng, Chen Shan, Hong-Tao Soomro, Nouman Qadeer Liu, Yi College of Information Technology Shanghai Jian Qiao University Shanghai201306 China School of Mathematics and Computer Science Yanan University Shaanxi 716000 China School of Computer and Data Science Minjiang University No.200 Xiyuangong Road Fuzhou University Town Fuzhou350108 China Digital Media Art Key Laboratory of Sichuan Province Sichuan Conservatory of Music Chengdu610021 China Fuzhou Technology Innovation Center of intelligent Manufacturing information System Minjiang University Fuzhou350108 China Fujian Province University Fuzhou350300 China College of Business Shanghai Jian Qiao University Shanghai201306 China College of Electronic and Electrical Engineering Shanghai University of Engineering Science Shanghai201620 China Software Department Mehran University of Engineering & Technology Sindh 76062 Pakistan

Distinguishing the manifestations of pulmonary nodules poses a significant challenge in the medical field, demanding the expertise of experienced radiologists. This complexity results in the high cost and inadequacy of sample labeling. In response, this study introduces a reinforcement learning approach, denoted as TriCaps-RL, for the classification of pulmonary nodules based on CT signs. This approach initially employs the Q-value loss to train a single CapsNet. When the performance of the CapsNet plateaus and further enhancement becomes challenging, the loss function is progressively replaced by a triplet metric to augment performance. Consequently, a more nuanced differentiation among various types of pulmonary nodules is achieved. The proposed method can improve its performance through interactions with radiologists during their CT image reading process, thereby mitigating the shortage of radiologists and addressing the time-consuming issue of training sample labeling in medical image research. This paper delves into the fine-grained classification of pulmonary nodules using deep reinforcement learning based on CT imaging signs. In comparison to previous studies that primarily concentrate on the benign/malignant classification of lung nodules, this fine-grained classification of nodules founded on CT imaging signs proves to be more valuable for medical practitioners in making accurate diagnostic decisions. © 2024, Taiwan Ubiquitous Information CO LTD. All rights reserved.

关键词： Lung cancer

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A Multi-Layer Collaboration Framework for Industrial Parks with 5G Vehicle-to-Everything Networks

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engineering 2021年第6期7卷 818-831页

作者： Yanjun Shi Qiaomei Han Weiming Shen Xianbin Wang Department of Mechanical Engineering Dalian University of TechnologyDalian 116024China Department of Electrical and Computer Engineering Western UniversityLondonON N6A 3K7Canada State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074China

The fifth-generation(5G)wireless communication networks are expected to play an essential role in the transformation of vertical *** many exciting applications to be enabled by 5G,logistics tasks in industry parks can be performed more efficiently via vehicle-to-everything(V2X)*** this paper,a multi-layer collaboration framework enabled by V2X is proposed for logistics management in industrial *** proposed framework includes three layers:a perception and execution layer,a logistics layer,and a configuration *** addition to the collaboration among these three layers,this study addresses the collaboration among devices,edge servers,and cloud *** effective logistics in industrial parks,task collaboration is achieved through four functions:environmental perception and map construction,task allocation,path planning,and vehicle *** dynamically coordinate these functions,device–edge–cloud collaboration,which is supported by 5G slices and V2X communication technology,is ***,the analytical target cascading method is adopted to configure and evaluate the collaboration schemes of industrial ***,a logistics analytical case study in industrial parks is employed to demonstrate the feasibility of the proposed collaboration framework.

关键词： 5G Vehicle-to-everything Industrial park Logistics Device–edge–cloud collaboration Analytical target cascading

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Design and Experimental Investigation of Trikarenos: A Fault-Tolerant 28nm RISC-V-based SoC

arXiv

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arXiv 2024年

作者： Rogenmoser, Michael Wiese, Philip Forlin, Bruno Endres Gürkaynak, Frank K. Rech, Paolo Menicucci, Alessandra Ottavi, Marco Benini, Luca The Integrated Systems Laboratory ETH Zurich Switzerland The Computer Architecture for Embedded Systems The University of Twente Netherlands The Department of Industrial Engineering The University of Trento Italy The Department of Space Engineering The Delft University of Technology Netherlands The Computer Architecture for Embedded Systems The University of Twente Netherlands The Department of Electronic Engineering The University of Rome Tor Vergata Italy The Integrated Systems Laboratory ETH Zurich Switzerland The Department of Electrical Electronic and Information Engineering The University of Bologna Italy

We present a fault-tolerant by-design RISC-V SoC and experimentally assess it under atmospheric neutrons and 200 MeV protons. The dedicated ECC and Triple-Core Lockstep countermeasures correct most errors, guaranteein... 详细信息

关键词： Fault tolerance

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Trikarenos: Design and Experimental Characterization of a Fault-Tolerant 28nm RISC-V-based SoC

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IEEE Transactions on Nuclear Science 2025年

作者： Rogenmoser, Michael Wiese, Philip Forlin, Bruno Endres Gurkaynak, Frank K. Rech, Paolo Menicucci, Alessandra Ottavi, Marco Benini, Luca Integrated Systems Laboratory ETH Zurich Switzerland Computer Architecture for Embedded Systems University of Twente Netherlands Department of Industrial Engineering University of Trento Italy Delft University of Technology Department of Space Engineering Netherlands University of Rome Department of Electronic Engineering Tor Vergata Italy Information Engineering at the University of Bologna Department of Electrical Electronic Italy

RISC-V-based fault-tolerant system-on-chip (SoC) designs are critical for the new generation of automotive and space SoC architectures. However, reliability assessment requires characterization under controlled radiation doses to accurately quantify the fault tolerance of the fabricated designs. This work analyzes the Trikarenos design, a SoC implemented in TSMC 28nm, for single event upset (SEU) vulnerability under atmospheric neutron and 200MeV proton radiation, comparing these results to simulation-based fault injection. All faults in error correction codes (ECC) protected memory are corrected by a scrubber, showing an estimated cross-section per bit of up to 1.09 × 10−14 cm2 bit−1. Furthermore, the triple-core lockstep (TCLS) mechanism implemented in Trikarenos is validated and is shown to correct errors affecting a cross-section up to 3.23 × 10−11 cm2, with the remaining uncorrectable vulnerability below 5.36 × 10−12 cm2. When augmenting the experimental analysis of fabricated chips with gate-level fault injection in simulation, 99.10% of injections into the SoC produced correct results, while 100% of injections in the TCLS-protected cores were handled *** 12.28%of all injected faults leading to a TCLS recovery, this indicates an approximate effective flip-flop cross-section of up to 1.28 × 10−14 cm2/FF. © 1963-2012 IEEE.

关键词： Radiation damage

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A Continual Learning Method for Reducing Class Interference Based on Replay 42

A Continual Learning Method for Reducing Class Interference ...

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42nd Chinese Control Conference, CCC 2023

作者： Xu, Zhibo Wang, Tian Wang, Jian Li, Ce Fu, Yao Snoussi, Hichem School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Institute of Artificial Intelligence Sklsde Beihang University Beijing100191 China Zhongguancun Laboratory Beijing100191 China School of Computer Science Wuhan University Wuhan430072 China China University of Mining and Technology Department of Computer Science and Technology Beijing100083 China Changchun Institute of Optics Fine Mechanics and Physics Chinese Academy of Sciences Changchun130033 China Laboratory of Computer Science and Digital Society University of Technology of Troyes Troyes France

ISBN: (纸本)9789887581543

Although deep neural networks perform well on many individual tasks, they suffer from catastrophic forgetting when learning new tasks continually. Recently, various continual learning methods have been proposed, and some approaches based on replaying memory data achieve promising performance. Maximally Interfered Retrieval is a strong replay-based baseline, however, exists class interference due to class imbalance and lacks the ability to generalize to the real class-incremental scenario. In this paper, aiming at these problems, we design Class cumulative Classifier to replace the shared output layer of the original network, which makes it closer to practical applications, and Class balanced Buffer to address the class imbalance of stored samples. In addition, we propose Retrospect strategy to further improve the accuracy. Experimental results on benchmark datasets show that our method outperforms several strong baselines and is more suitable for complex datasets with more classes. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Image classification

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Knowledge Graph-Based Semantic System for Visual Analytics in Automatic Manufacturing

Knowledge Graph-Based Semantic System for Visual Analytics i...

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2022 International Semantic Web Conference Posters, Demos and Industry Tracks: From Novel Ideas to Industrial Practice, ISWC-Posters-Demos-Industry 2022

作者： Zhou, Baifan Zheng, Zhuoxun Zhou, Dongzhuoran Tan, Zhipeng Savković, Ognjen Yang, Hui Zhang, Yujia Kharlamov, Evgeny SIRIUS Centre Department of Informatics University of Oslo Norway Bosch Center for Artificial Intelligence Germany Department of Computer Science Oslo Metropolitan University Norway Department of Computer Science Free University of Bozen Bolzano Italy RWTH Aachen University Germany Interdisciplinary Laboratory of Digital Sciences France Department of Electrical and Computer Engineering University of Alberta Canada

Visual analytics has been important for many data-driven applications in modern ***, there has been limited research of semantic technologies for visual analytics, which hamstrings its transparency and reusability. To this end, we propose a semantic system that encodes visual analytical solutions in reusable knowledge graphs, which can be translated to executable scripts. Further more, our approach incorporates domain knowledge such as feature type information by linking domain ontologies and visual ontology. This poster paper presents preliminary evaluation of our approach with a Bosch use case with promising results. © 2022 Copyright for this paper by its authors.

关键词： Knowledge graph

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Mechanical Design with Experimental Verification of a Lightweight Exoskeleton Chair

引用

Journal of Bionic engineering 2021年第2期18卷 319-332页

作者： Zihao Du Zefeng Yan Tiantian Huang Ou Bai Qin Huang Bin Han State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074China Human Cyber-Physical Systems Laboratory Department of Electrical and Computer EngineeringFlorida International UniversityMiami 33174USA Department of Rehabilitation Medicine Union HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430022China

In this study,a human-chair model was developed as the basis for a wearable-chair design.A prototype chair,HUST-EC,based on the model was fabricated and *** the optimization under the golden divisional method,an optimized simulation of the operating mode with the lowest chair height was implemented.A novel multi-link support structure has been established with parameters optimized using Matlab *** stress analysis of the solid models was conducted to ensure the adequate support from the designed chair for the *** subjects participated in the evaluation experiment,who performed both static tasks and dynamic *** experimental results consisted of subjective evaluation and objective *** experimental data demonstrate that(1)the HUST-EC can effectively reduce the activation level of related muscles at a variety of tasks;(2)the plantar pressure was reduced by 54%–67%;(3)the angle between the upper body and the vertical axis was reduced by 59%–77%;(4)the subjective scores for chair comfortability,portability,and stability were all higher than *** results further revealed that the designed chair can reduce the musculoskeletal burden and may improve work efficiency.

关键词： exoskeleton wearable chair bionic robot mechanism design ergonomics

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Sensor Fault Detection and Isolation in Autonomous Nonlinear Systems Using Neural Network-Based Observers

Sensor Fault Detection and Isolation in Autonomous Nonlinear...

引用

European Control Conference (ECC)

作者： John Cao M. Umar B. Niazi Matthieu Barreau Karl Henrik Johansson Division of Decision and Control Systems Digital Futures KTH Royal Institute of Technology Stockholm Sweden Department of Electrical Engineering and Computer Science Laboratory for Information & Decision Systems Massachusetts Institute of Technology Cambridge MA USA

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

This paper presents a novel observer-based approach to detect and isolate faulty sensors in nonlinear systems. The proposed sensor fault detection and isolation (s-FDI) method applies to a general class of nonlinear systems. Our focus is on s-FDI for two types of faults: complete failure and sensor degradation. The key aspect of this approach lies in the utilization of a neural network-based Kazantzis-Kravaris/Luenberger (KKL) observer. The neural network is trained to learn the dynamics of the observer, enabling accurate output predictions of the system. Sensor faults are detected by comparing the actual output measurements with the predicted values. If the difference surpasses a theoretical threshold, a sensor fault is detected. To identify and isolate which sensor is faulty, we compare the numerical difference of each sensor measurement with an empirically derived threshold. We derive both theoretical and empirical thresholds for detection and isolation, respectively. Notably, the proposed approach is robust to measurement noise and system uncertainties. Its effectiveness is demonstrated through numerical simulations of sensor faults in a network of Kuramoto oscillators.

关键词： Uncertainty Fault detection Noise Observers Numerical simulation Sensor systems Sensors

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Condition Assessment and Maintenance Strategy of Flexible DC Distribution Equipment Based on Improved FMEA

Condition Assessment and Maintenance Strategy of Flexible DC...

引用

DC Technologies and Systems (DCTS), IEEE International Conference on

作者： Ruixiong Yang Zhihua Gao Yong Chen Zhiling Luo Chengyu Liu Hengqin Digital Zero Carbon Island Communal Laboratory Zhuhai Power Supply Bureau Guangdong Power Grid Co. Ltd Zhuhai China Electrical and Computer Engineering (ECE) University of Macau Macao China

ISBN: (数字)9798350379464

ISBN: (纸本)9798350379471

Flexible DC distribution technology is a key supporting technology for the flexible transformation of distribution networks. Several demonstration projects of flexible DC distribution networks have been put into operation domestically. However, the condition assessment methods and maintenance strategies for flexible DC distribution equipment are not yet established, leading to challenges such as complex maintenance operations, high workload, and low levels of precision. To address these issues, this paper proposes a condition assessment method for flexible DC distribution equipment based on improved Failure Mode and Effect Analysis (FMEA). First, the potential failure mechanisms and condition indicators of key components of flexible DC distribution equipment are analyzed, and critical state variables are identified. Evaluation criteria for failure degree, importance, and detection rate of these state variables are then developed to achieve quantitative condition assessment of the equipment. Based on the assessment results, differentiated maintenance and operation strategies are formulated. Finally, the method is validated through an analysis of a converter as an example. This approach is also applicable to other flexible DC distribution equipment and can enhance maintenance efficiency and precision.

关键词： Performance evaluation Accuracy Failure analysis Collaboration Distribution networks Maintenance Discrete cosine transforms

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