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6th International Symposium on System and Software Reliability, ISSSR 2020

作者： Zhang, Yuhong Xiao, Chunjing School of Artificial Intelligence and Big Data Key Laboratory of Grain Information Processing and Control Ministry of Education Zhengzhou China Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng China

ISBN: (纸本)9780738104973

This paper provides a comprehensive observation to examine the reliability of deep learning (DL) models. First, we will briefly introduce the essential background and kernel techniques in deep learning, such as downsampling and nonlinear discontinuity. Each of them may have some relation to the reliability of DL models. Then we discuss the inherent structural flaws of deep learning and the risk of unreliability that can result from it. Subsequently, we discuss various ways of generating adversarial samples that affect the DL model's reliability and corresponding preventive measures. Finally, we complete this observation by identifying current challenges and future trends for research. © 2020 IEEE.

关键词： Reliability

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Model-Based and Data-Driven Contingency Filtering for Real-Time Corrective Security-Constrained Economic Dispatch 5

Model-Based and Data-Driven Contingency Filtering for Real-T...

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5th IEEE Conference on Energy Internet and Energy System Integration, EI2 2021

作者： Han, Donghai Yu, Yaowen He, Dingxin Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781665434256

Security-constrained economic dispatch (SCED) is one of the most important problems in power system operations. Corrective SCED (CSCED) is a type of SCED that considers corrective capabilities of the power system and adjusts base case decisions according to post-contingency states. Because of the large scale of the CSCED problem, it is difficult for purely model-based approaches to meet the time limits in real-time practical operations. To leverage historical operation data, this paper develops a novel hybrid model-based and data-driven framework to accelerate the solution process of CSCED. In the offline stage, our previous model-based contingency filtering approach is utilized to label active statuses of contingencies against historical net load samples. In the online stage, a multi-label classifier based on the K-Nearest Neighbor (KNN) algorithm quickly generates an active contingency set corresponding to the real-time net load. This active contingency set can be used to calculate the economic dispatch decisions in one shot. In addition, the accuracy of our framework can be further improved by adding an optional contingency filtering procedure at the end. Numerical testing results on the IEEE RTS-96 system demonstrate the accuracy and computational efficiency of the hybrid framework as compared to a purely model-based approach. © 2021 IEEE

关键词： Computational efficiency

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Prescribed-Time Stabilization of Singularly Perturbed Systems

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IEEE/CAA Journal of Automatica Sinica 2023年第2期10卷 569-571页

作者： Yan Lei Yan-Wu Wang Xiao-Kang Liu Wu Yang the School of Artificial Intelligence and Automation Huazhong University of Science and Technology(HUST)Wuhan 430074 Key Laboratory of Image Processing and Intelligent Control Ministry of EducationWuhan 430074China the School of Electrical Engineering Guangxi UniversityNanning 530004China

Dear Editor, This letter investigates the prescribed-time stabilization of linear singularly perturbed systems. Due to the numerical issues caused by the small perturbation parameter, the off-the-shelf control design techniques for the prescribed-time stabilization of regular linear systems are typically not suitable here. To solve the problem, the decoupling transformation techniques for time-varying singularly perturbed systems are combined with linear time-varying high gain feedback design techniques.

关键词： prescribed stabilization perturbed

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Protecting Multiple Types of Privacy Simultaneously in EEG-Based Brain-Computer Interfaces

Protecting Multiple Types of Privacy Simultaneously in EEG-B...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Meng, Lubin Jiang, Xue Jia, Tianwang Wu, Dongrui School of Artificial Intelligence and Automation Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control Wuhan China

ISBN: (纸本)9781665410205

A brain-computer interface (BCI) enables direct communication between the brain and an external device. Electroencephalogram (EEG) is the preferred input signal in non-invasive BCIs, due to its convenience and low cost. EEG-based BCIs have been successfully used in many applications, such as neurological rehabilitation, text input, games, and so on. However, EEG signals inherently carry rich personal information, necessitating privacy protection. This paper demonstrates that multiple types of private information (user identity, gender, and BCI-experience) can be easily inferred from EEG data, imposing a serious privacy threat to BCIs, To address this issue, we design perturbations to convert the original EEG data into privacy-protected EEG data, which conceal the private information while maintaining the primary BCI task performance. Experimental results demonstrated that the privacy-protected EEG data can significantly reduce the classification accuracy of user identity, gender and BCI-experience, but almost do not affect at all the classification accuracy of the primary BCI task, enabling user privacy protection in EEG-based BCIs. © 2024 IEEE.

关键词： Differential privacy

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A Non-Iterative Network Utilization Pricing Mechanism for P2P Energy Trading

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CSEE Journal of Power and Energy Systems 2024年第3期10卷 1301-1306页

作者： Yun Liu Yunqiang Gao Yuanzheng Li Jizhong Zhu Hoay Beng Gooi School of Electric Power Engineering South China University of TechnologyGuangzhou 510641China School of Artificial Intelligence and Automation Ministry of Education Key Laboratory of Image Processing and Intelligence ControlHuazhong University of Science and TechnologyWuhan 430074China School of Electrical and Electronic Engineering Nanyang Technological UniversitySingapore IEEE

To sustain operation and maintenance of an active distribution network(ADN),a network fee should be charged by the distribution network service provider(DNSP)for facilitating the P2P energy trading *** this end,this paper models the interaction among the DNSP and multiple prosumers as a Stackelberg game,and then develops a non-iterative and decentralized transactive mechanism to simultaneously achieve optimal network utilization pricing and peer-to-peer(P2P)*** results in an ADN with four prosumers connected to a common substation bus validate the effectiveness and efficiency of the proposed scheme.

关键词： Distribution network service provider network fee non-iterative peer-to-peer trading prosumer

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Portrait Matting via Semantic and Detail Guidance 1

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7th Asian Conference on Pattern Recognition, ACPR 2023

作者： Wang, Deming Gao, Changxin Sang, Nong Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9783031476341

ISBN: (纸本)9783031476334

Portrait matting is a challenging computer vision task that aims to estimate the per-pixel opacity of the foreground human regions. To produce high-quality alpha mattes, the majority of available methods employ a user-supplied trimap as an auxiliary input. However, obtaining trimap is difficult, which restricts the application of these methods. Recently, trimap-free approaches have been developed, but the alpha quality is significantly lower than that of trimap-based methods due to the lack of guidance. In this paper, we propose a portrait matting framework via semantic and detail guidance. We use the mask obtained from portrait segmentation as semantic guidance to improve semantic understanding of portrait matting, and we present a detail encoder block to capture the low-level feature around the subject as detail guidance, which helps to refine alpha details, such as hair. The proposed approach achieves remarkable results on both composition and real-world benchmarks. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Semantics

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A Robust Recognition and Segmentation Algorithm for Retaining Walls in Mining Scenes

A Robust Recognition and Segmentation Algorithm for Retainin...

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2023 China Automation Congress, CAC 2023

作者： Zeng, Tian Xiao, Li Peng, Gang Wang, Aoze Wang, Zhuo Sun, Zhigang School of Artificial Intelligence and Automation Intelligence and Automation Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control Ministry of Education Wuhan China

ISBN: (纸本)9798350303759

The key for bulldozers to realize automatic operation in mine scenes is whether they can accurately identify and accurately segment the retaining walls, however, because the point cloud dataset of the mine site is too few, resulting in the deep learning-based identification and segmentation algorithm cannot be applied in this scene. At the same time, because of the rugged road surface of the mine scene, the existence of a lot of dust, numerous disturbances, retaining wall features are not obvious and other problems, the algorithms proposed by previous scholars are not perfect enough to solve the problem. We propose a point cloud recognition and segmentation algorithm based on clustering and evaluation function of integrated features. Ours firstly compensates the skew of the point cloud map with RANSAC and down samples the data by gridding the point cloud. Then reduces the influence of dust and truck materials in the scene by normal vector and variance information. Finally, screens out the candidate target class by density clustering, and identifies and segments the retaining wall by integrated feature. Our proposed algorithm is validated in several different real mine scenarios and the results show that ours has high accuracy and strong robustness. © 2023 IEEE.

关键词： Retaining walls

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Resilient control of flexible hypersonic vehicles against unmatched distributed faults

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Chinese Journal of Aeronautics 2024年第5期37卷 60-70页

作者： Dong ZHAO Wenjing REN School of Artificial Intelligence Anhui UniversityHefei 230601China Key Laboratory of System Control and Information Processing Ministry of EducationShanghai Jiao Tong UniversityShanghai 200240China School of Electrical Engineering and Automation Hefei University of TechnologyHefei 230009China

This paper studies a robust fault compensation and vibration suppression problem of flexible hypersonic *** controlled plant is represented by a cascade system composed of a nonlinear Ordinary Differential Equation(ODE)and an Euler-Bernoulli Beam Equation(EBBE),in which the vibration dynamics is coupled with the rigid dynamics and suffers from distributed faults.A state differential transformation is introduced to transfer distributed faults to an EBBE boundary and a longitudinal dynamics is refined by utilizing T-S fuzzy IF-THEN rules.A novel T-S fuzzy based fault-tolerant control algorithm is developed and related stability conditions are *** robust exponential stability and well-posedness are proved by using the modified l_(0)-semigroup based Lyapunov direct approach.A simulation study on the longitudinal dynamics of flexible hypersonic vehicles effectively verifies the validity of the developed theoretical results.

关键词： Flexible hypersonic vehicles ODE-EBBE cascade Robust exponential stability Unmatched distributed fault compensation Vibration suppression

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A Model Reference Adaptive controller with Feedforward Decoupling for Active Magnetic Bearing Rotor System 4

A Model Reference Adaptive Controller with Feedforward Decou...

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4th IEEE Advanced Information Technology, Electronic and Automation control Conference, IAEAC 2019

作者： Yi, Jian Ren, Gui-Ping Zhang, Hai-Tao Wu, Yue Huazhong University of Science and Technology School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control Wuhan430074 China

ISBN: (纸本)9781728119076

Active magnetic bearing (AMB) rotor system is widely applied in the industry for its remarkable advantages. However, it is a typical open-loop unstable mechatronics system suffering from nonlinear and couple characteristic. In this paper, the feedforward decoupling method is used to deal with the couple relationship of different axes. And the model reference adaptive control (MRAC) method is applied to improve the control performance and robustness and overcome the uncertainties. This control method makes the system output reach to the reference model by the designed adaptive law. Simulation results illustrate the effectiveness of the proposed scheme. © 2019 IEEE.

关键词： Model reference adaptive control

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A new approach to extract rectangle building from aerial urban images 6

A new approach to extract rectangle building from aerial urb...

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6th International Conference on Signal processing, ICSP 2002

作者： Tao, Wen-Bing Tian, Jin-Wen Liu, Jian State Key Laboratory for Image Processing and Intelligence Control Hubei Wuhan430074 China Institute for Pattern Recognition and Artificial Intelligence HUST Hubei Wuhan430074 China

ISBN: (纸本)0780374886

In this paper, we proposed a new Primitive-Structure- Based approach for extracting rectangle building from aerial urban images. We obtain all kinds of primitive-structure that compose rectangle by analysing geometrical primitive structure from the straight-line-graph that has been produced by edge- Detection and contour-tracking and straight-line-splitting, then merge these primitive structure to rectangle through the merging arithmetic. The experimental results show that the approach is times computationally faster than the previous methods. The results of performance assessment also support the robustness and precision of the approach developed. © 2002 IEEE.

关键词： Merging

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