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IET Blockchain 2023年第1期3卷 18-34页

作者： Liu, Yang Yang, Weidong Wang, Yanlin Liu, Yang College of Information Science and Engineering Henan University of Technology Henan Zhengzhou China Henan Provincial Key Laboratory of Grain Photoelectric Detection and Control Henan Zhengzhou China Ministry of Education Key Laboratory of Grain Information Processing and Control Henan Zhengzhou China

With the rapid increment of the demand for data sharing among parties, data is considered a cornerstone component to provide value in the big data environment. Concerns regarding sharing data security have impeded the development of cross-domain data interaction. Therefore, an access control model for data security sharing cross-domain is proposed, Fabric-ABAC, that is based on Hyperledger Fabric and Attribute-based Access control (ABAC). In order to solve the data security challenges caused by a trusted central organization implementation, a distributed environment is constructed that consists of stakeholders among parties. The unified attribute model is designed for multi-environment combined with smart contracts. Fabric-ABAC realizes multi-level, fine-grained, and auditable access control, enabling data security through automatic permission verification. Considering the ledger is visible to all participants in consortium blockchain, it is necessary to protect the confidentiality of sensitive data. Thus, Proxy Re-Encryption (PRE), which is implemented by smart contracts, is adopted in the scheme to realize the ciphertext interaction without the third party. The security of PRE and the access control model used in Fabric-ABAC is discussed to show that a secure environment for data sharing is provided. Moreover, the completeness of the implementation and effectiveness of the system performance in the multi-domain environment is demonstrated in the experimental results. © 2023 The Authors. IET Blockchain published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.

关键词： Smart contract

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NeFF: Semantic information Learning In 3D Space Using Neural Feature Field

NeFF: Semantic Information Learning In 3D Space Using Neural...

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2024 China Automation Congress, CAC 2024

作者： Yang, Yimu Chen, Cailian Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368604

Inferring a 3D space with partial observation requires prior knowledge from previous experience, and deep learning offers an intuitive solution. Prior knowledge can be categorized into two extremes Global and Local. Global prior uses input image as a clue to retrieve seen intact 3D objects yielding 3D consistent inference with fewer details. In contrast, Local prior takes advantage of closeby views’ overlapping areas and propagates input image cues to their vicinity via geometry transformation directly, producing realistic inferences around the reference views yet inconsistent inferences away from the reference views. We propose Neural feature field, an implicit 3D neural representation that combines the strength of the Global and Local prior. We represent each 3D scene with a latent embedding, then we perform a global scene-level prior to local view-specific feature prior with the neural feature field and volume rendering technique. Our model learns general scene properties across a category. Given a single input image at test time, the scene latent code is acquired via a two-round optimization process. Experiments on the SRN benchmark show that NeFF generalizes well to unseen objects within the same object category and is capable of producing 3D consistent inferences with sharp details from a single observation. © 2024 IEEE.

关键词： 3D reconstruction

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Dual-type Hyperspectral Microscopic Imaging system based on Fourier Transform Imaging Spectrometer 15

Dual-type Hyperspectral Microscopic Imaging System based on ...

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15th International Conference on information Optics and Photonics, CIOP 2024

作者： Wei, Zhanqi Wu, Kaijie Qin, Yuheng Cheng, Hao Gu, Chaochen Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China

ISBN: (数字)9781510686175

ISBN: (纸本)9781510686168

This article proposes a hyperspectral microscopic imaging system based on Fourier transform interferometer to broaden the spectral range and obtain more types of spectral information under large field of view. Through stage scanning and light sources switching, transmission and fluorescence spectral images can be obtained successively. The system was validated using fibre tissues imaging. The spectral range covers 300-800 nm, and the spectral resolution is approximately 5 nm. It can be effectively applied to pathology and cytogenetics, obtaining morphological and spectral information to study the structure of the object and observe the similarities and differences of components in different positions. © 2024 SPIE.

关键词： Spectral resolution

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Uncertainty-Aware Reactive control for Signal Temporal Logic with Unknown Obstacles 14

Uncertainty-Aware Reactive Control for Signal Temporal Logic...

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14th Asian control Conference, ASCC 2024

作者： Chen, Chen Li, Shaoyuan Yin, Xiang Shanghai Jiao Tong University Department of Automation Shanghai200240 China The Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China

ISBN: (纸本)9789887581598

In this paper, we investigate the challenge of con-trol synthesis for Signal Temporal Logic (STL) specifications within workspaces harboring unknown obstacles. We consider a sensing-based control setting, where robots are equipped with sensors with a limited sensing range to acquire obstacle locations with prior information. The objective is to synthesize a control strategy that maximize the robustness degree of the STL tasks while simultaneously minimizing the probability of collisions with obstacles during its operation. To address this, we present a receding horizon reactive control framework, tackling the problem by solving an uncertainty-aware optimal planning problem at each time instant. A key aspect of our approach is the avoidance of explicit computation of collision probability. Instead, we transform the uncertainty-aware synthesis problem into a non-probabilistic optimization problem, and the results of which still provide probabilistic guarantees. Simulation results are provided to illustrate the effectiveness of our approach. © 2024 Asian control Association.

关键词： Temporal logic

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Safe Deep Learning-Based Offset-Free MPC for Green Hydrogen Injected PEMFC systems

Safe Deep Learning-Based Offset-Free MPC for Green Hydrogen ...

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2023 China Automation Congress, CAC 2023

作者： Wang, Han Li, Longyan Ning, Chao Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Department of Automation Shanghai China

ISBN: (纸本)9798350303759

Safe and stable operation of a proton exchange membrane fuel cell (PEMFC) system requires stringent control of oxygen excess ratio (OER). However, the OER regulation in PEMFC is challenging due to frequent fluctuations of current, various modeling nonlinearities, constrained manipulated variable, and real-time requirements. Offset-free model predictive control (MPC) provides a useful means for controlling systems with disturbances and constraints, but suffers from the heavy computational burden of repeatedly solving an optimization problem in real time. Such computational issue precludes the possibility of meeting the real-time requirements of PEMFC. In this paper, a PEMFC cathode gas supply model is firstly established. Next, we develop a safe deep learning-based offset-free MPC algorithm. Based on the nominal offset-free MPC, the proposed MPC not only reserves the ability of disturbance rejection, but also leverages deep neural networks for approximating the explicit solution to the MPC problem to greatly reduce online computational time. Furthermore, a gauge map is used to guarantee the satisfaction of safe constraints regarding compressor voltage. The simulation results show that the proposed MPC is an order of magnitude faster than the nominal offset-free MPC. © 2023 IEEE.

关键词： Model predictive control

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Provably Safe Deep Learning-Based Offset-Free Model Predictive control and its Application to Safety-Critical Autonomous Driving 6

Provably Safe Deep Learning-Based Offset-Free Model Predicti...

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6th International Conference on Robotics, control and Automation Engineering, RCAE 2023

ISBN: (纸本)9798350315301

Offset-free model predictive control (MPC) provides a useful means for controlling systems with uncertainties and constraints, but suffers from the heavy computational burden of repeatedly solving an optimization problem in real time. Such computational issue precludes the possibility of its application in systems requiring high realtime requirements, such as autonomous driving system. To address this problem, we develop a provably safe deep learning-based offset-free MPC framework. Based on the nominal offset-free MPC, the proposed MPC not only reserves the ability of disturbance rejection, but also leverages deep neural networks for approximating the explicit MPC solution to greatly reduce online computational time. Furthermore, a gauge map is used to guarantee the satisfaction of safe constraints. The proposed MPC is used in trajectory tracking control for smart autonomous driving. The simulation results show that the proposed MPC is an order of magnitude faster than the nominal offset-free MPC in safety-critical systems. © 2023 IEEE.

关键词： Model predictive control

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Review and prospects on the low-voltage Na_(2)Ti_(3)O_(7) anode materials for sodium-ion batteries

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Journal of Energy Chemistry 2024年第1期88卷 446-460,I0011页

作者： Jun Dong Yalong Jiang Ruxing Wang Qiulong Wei Qinyou An Xiaoxing Zhang Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System Hubei University of TechnologyWuhan 430068HubeiChina State Key Laboratory of New Textile Materials and Advanced Processing Technologies Wuhan Textile UniversityWuhan 430200HubeiChina Xiamen Key Laboratory of High-Performance Metals and Materials College of MaterialsXiamen UniversityXiamen 361005FujianChina State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Wuhan University of TechnologyWuhan 430070HubeiChina

Due to its low cost and natural abundance of sodium,Na-ion batteries(NIBs)are promising candidates for large-scale energy storage *** development of ultralow voltage anode materials is of great significance in improving the energy density of ***-voltage anode materials,however,are severely lacking in *** all the reported insertion oxides anodes,the Na_(2)Ti_(3)O_(7) has the lowest operating voltage(an average potential of 0.3 V ***^(+)/Na)and is less likely to deposit sodium,which has excellent potential for achieving NIBs with high energy densities and high *** significant progress has been made,achieving Na_(2)Ti_(3)O_(7) electrodes with excellent performance remains a severe *** paper systematically summarizes and discusses the physicochemical properties and synthesis methods of Na_(2)Ti_(3)O_(7).Then,the sodium storage mechanisms,key issues and challenges,and the optimization strategies for the electrochemical performance of Na_(2)Ti_(3)O_(7) are classified and further ***,remaining challenges and future research directions on the Na_(2)Ti_(3)O_(7) anode are *** review offers insights into the design of high-energy and high-safety NIBs.

关键词： Sodium-ion batteries Low-voltage anode materials Na_(2)Ti_(3)O_(7) Electrochemical performances Electrochemical mechanism

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Spatial confinement of free-standing graphene sponge enables excellent stability of conversion-type Fe_(2)O_(3)anode for sodium storage

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Chinese Chemical Letters 2025年第3期36卷 544-549页

作者： Jun Dong Senyuan Tan Sunbin Yang Yalong Jiang Ruxing Wang Jian Ao Zilun Chen Chaohai Zhang Qinyou An Xiaoxing Zhang Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System Hubei University of TechnologyWuhan 430068China State Key Laboratory of New Textile Materials and Advanced Processing Technologies Wuhan Textile UniversityWuhan 430200China State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Wuhan University of TechnologyWuhan 430070China Nanjing University of Aeronautics and Astronautics Nanjing 210016China

Conversion-type anode materials are highly desirable for Na-ion batteries(NIBs)due to their high theoretical ***,the active materials undergo severe expansion and pulverization during the sodiation,resulting in inferior cycling ***,a self-supporting three-dimensional(3D)graphene sponge decorated with Fe_(2)O_(3)nanocubes(rGO@Fe_(2)O_(3))is ***,the 3D graphene sponge with resilience and high porosity benefits to accommodate the volume expansion of the Fe_(2)O_(3)nanocubes and facilitates the rapid electrons/ions transport,enabling spatial confinement to achieve outstanding ***,the free-standing rGO@Fe_(2)O_(3)can be directly used as an electrode without additional binders and conductive additives,which helps to obtain a higher energy *** on the total mass of the rGO@Fe_(2)O_(3)material,the rGO@Fe_(2)O_(3)anode presents a specific capacity of 859 mAh/g at 0.1 A/*** also delivers an impressive cycling performance(327 mAh/g after 2000 cycles at 1 A/g)and a superior rate capacity(162mAh/g at 20 A/g).The coin-type Na_(3)V_(2)(PO_(4))_(3)@C//rGO@Fe_(2)O_(3)NIB exhibits an energy density of 265.3Wh/*** unique 3D ionic/electronic conductive network may provide new strategies to design advanced conversion-type anode materials for high-performance NIBs.

关键词： Conversion-type anode Spatial confinement Fe_(2)O_(3) Graphene network Self-supporting Sodium-ion batteries

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Multi-Human Pose Estimation by Deep Learning-Based Sequential Approach for Human keypoint Position and Human Body Detection

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Journal of Shanghai Jiaotong University (Science) 2023年 1-11页

作者： Tahir, Rizwan Cai, Yunze Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing of Ministry of Education Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Jiao Tong University Shanghai200240 China

Recent multimedia and computer vision research has focused on analyzing human behavior and activity using images. Skeleton estimation, known as pose estimation, has received a significant attention. For human pose estimation, deep learning approaches primarily emphasize on the keypoint features. Conversely, in the case of occluded or incomplete poses, the keypoint feature is insufficiently substantial, especially when there are multiple humans in a single frame. Other features, such as the body border and visibility conditions, can contribute to pose estimation in addition to the keypoint feature. Our model framework integrates multiple features, namely the human body mask features, which can serve as a constraint to keypoint location estimation, the body keypoint features, and the keypoint visibility via mask region-based convolutional neural network (Mask-RCNN). A sequential multi-feature learning setup is formed to share multi-features across the structure, whereas, in the Mask-RCNN, the only feature that could be shared through the system is the region of interest feature. By two-way up-scaling with the shared weight process to produce the mask, we have addressed the problems of improper segmentation, small intrusion, and object loss when Mask-RCNN is used, for instance, segmentation. Accuracy is indicated by the percentage of correct keypoint, and our model can identify 86.1% of the correct keypoints. © 2023, Shanghai Jiao Tong University.

关键词： Convolutional neural networks

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Digital Twin Enabled Flight control system Testing: A Physical-Virtual Mapping Experiment 22

Digital Twin Enabled Flight Control System Testing: A Physic...

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22nd IEEE International Conference on Industrial Informatics, INDIN 2024

作者： Ren, Cheng Chen, Cailian Zhu, Shanying Ma, Yehan Guan, Xinping Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China

ISBN: (纸本)9798331527471

Flight control system testing (FCST) is one of the most important testing during aircraft final assembly, however, traditional testing method highly rely on manual labor, resulting in low testing quality and efficiency. Targeting at improving the testing quality and efficiency, in this paper, we apply digtial twin (DT) technology in the FCST process for the first time. A virtual experimental platform named DT-FCST is constructed which is identical to a real wing experimental platform, supporting testing elements management and physical-virtual mapping experiments. The development process of the DT-FCST platform is detailed. Several experiments are conducted to demonstrate the effectiveness of DT technology. Based on motion scripts integrating real-time data from the cockpit, the cockpit control sticks and flight control surfaces are driven to achieve consistency between physical and virtual motions. With the help of DT technology, the entire movement process of control sticks and flight control surfaces are mapped with high fidelity in the DT-FCST platform, greatly enhancing the testing efficiency and monitoring quality. © 2024 IEEE.

关键词： Cockpits (aircraft)

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